From 4bacc940e52b82bc76f90fb50ab0055bbf219679 Mon Sep 17 00:00:00 2001 From: "Leaf, Andrew T" Date: Mon, 5 Feb 2024 13:29:28 -0600 Subject: [PATCH 1/2] refactor(notebooks): clean up for docs. Mostly: * Edit header levels for consistency * Add number (01, 02, etc) to Title for thumbnails and html pages * Execute some notebooks to show output; add to notebooks/clear_all_notebooks.py list --- notebooks/clear_all_notebooks.py | 4 +- .../03_useful-std-library-modules.ipynb | 2 +- .../04_files_and_strings.ipynb | 10 +- notebooks/part0_python_intro/05_numpy.ipynb | 18 +- .../part0_python_intro/06_matplotlib.ipynb | 10 +- .../06b_matplotlib_animation.ipynb | 2 +- .../07a_Theis-exercise.ipynb | 2 +- .../part0_python_intro/09_Geopandas.ipynb | 101 +- .../part0_python_intro/10_Rasterio.ipynb | 2 +- .../11_xarray_mt_rainier_precip.ipynb | 14 +- .../01_functions_script__solution.ipynb | 303 +- ...e_objects_modules_packages__solution.ipynb | 2 +- ...useful-std-library-modules-solutions.ipynb | 12 +- .../solutions/04_files_and_strings.ipynb | 2 +- .../solutions/05_numpy__solutions.ipynb | 8 + .../solutions/06_matplotlib__solution.ipynb | 6 +- .../07a_Theis-exercise-solution.ipynb | 2 +- .../solutions/08_pandas.ipynb | 2 +- .../solutions/09_Geopandas__solutions.ipynb | 12 +- .../03_Loading_and_visualizing_models.ipynb | 23984 +- .../04_Modelgrid_and_intersection.ipynb | 1990 +- .../part1_flopy/05-unstructured-grids.ipynb | 210 +- .../part1_flopy/08_Modflow-setup-demo.ipynb | 3 +- .../part1_flopy/09-gwt-voronoi-demo.ipynb | 273104 ++++++++++++++- notebooks/part1_flopy/10_modpath-demo.ipynb | 9 +- ...-Post-Processing-MODFLOW6__solutions.ipynb | 274 +- ...ing_and_visualizing_models-solutions.ipynb | 1461 +- .../04_Modelgrid_and_intersection.ipynb | 1587 - ..._Modelgrid_and_intersection_solution.ipynb | 4 +- .../solutions/06-Project-quadtree.ipynb | 8 + .../06-Project-structured_completed.ipynb | 772 +- .../solutions/06-Project-voronoi.ipynb | 8 + .../solutions/07-stream_capture_voronoi.ipynb | 12688 +- 33 files changed, 288699 insertions(+), 27917 deletions(-) delete mode 100644 notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection.ipynb diff --git a/notebooks/clear_all_notebooks.py b/notebooks/clear_all_notebooks.py index cd548d0..24bba99 100644 --- a/notebooks/clear_all_notebooks.py +++ b/notebooks/clear_all_notebooks.py @@ -8,9 +8,11 @@ '10_Rasterio.ipynb', '11_xarray_mt_rainier_precip.ipynb', '09_Geopandas_ABQ.ipynb', - '03_Loading_and_visualizing_models.ipynb', + #'03_Loading_and_visualizing_models-solutions.ipynb', + '05-unstructured-grids.ipynb', '07-stream_capture_voronoi.ipynb', '08_Modflow-setup-demo.ipynb', + '09-gwt-voronoi-demo.ipynb', '10_modpath-demo.ipynb' ] diff --git a/notebooks/part0_python_intro/03_useful-std-library-modules.ipynb b/notebooks/part0_python_intro/03_useful-std-library-modules.ipynb index b400881..a95e861 100644 --- a/notebooks/part0_python_intro/03_useful-std-library-modules.ipynb +++ b/notebooks/part0_python_intro/03_useful-std-library-modules.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Useful standard library modules\n", + "# 03: Useful standard library modules\n", "(pathlib, shutil, sys, os, subprocess, zipfile, etc.)\n", "\n", "These packages are part of the standard python library and provide very useful functionality for working with your operating system and files. This notebook will provide explore these packages and demonstrate some of their functionality. Online documentation is at https://docs.python.org/3/library/.\n", diff --git a/notebooks/part0_python_intro/04_files_and_strings.ipynb b/notebooks/part0_python_intro/04_files_and_strings.ipynb index 2ef2b36..5c20e43 100644 --- a/notebooks/part0_python_intro/04_files_and_strings.ipynb +++ b/notebooks/part0_python_intro/04_files_and_strings.ipynb @@ -5,7 +5,7 @@ "id": "6264d3bb", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — file input and output\n", + "# 04: File input and output\n", "\n", "In this exercise we will be learning about using python to work with file input and output. We will also learn a little about reading and writing ascii files. \n", "\n", @@ -839,8 +839,14 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "name": "python", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part0_python_intro/05_numpy.ipynb b/notebooks/part0_python_intro/05_numpy.ipynb index d2de263..46a1e35 100644 --- a/notebooks/part0_python_intro/05_numpy.ipynb +++ b/notebooks/part0_python_intro/05_numpy.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — NumPy\n", + "# 05: NumPy\n", "\n", "This notebook demonstrates how to import and use the Numpy module to work with arrays. The NumPy library includes (among other things) ways of storing and manipulating data that are more efficient than standard Python arrays. Using NumPy with numerical data is much faster than using Python lists or tuples.\n", "\n", @@ -78,7 +78,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Numpy Arrays\n", + "## Numpy Arrays\n", "***\n", "\n", "Numpy `array` objects (also called ndarray) are the cental data structure for `numpy`. Let's check out how to make arrays:\n", @@ -354,7 +354,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Array Operations\n", + "## Array Operations\n", "***\n", "It is very easy to perform arithmetic operations on arrays. So we can easily add and subtract arrays and use them in `numpy` functions. \n", ">pro tip: These operations, generally, are _element-wise_ -- so, don't expect matrix maths to be the result. That comes later..." @@ -875,7 +875,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## there are times when it's useful to have a list of indices meeting some condition. [`np.where`](https://numpy.org/doc/stable/reference/generated/numpy.where.html) will hook you up. (also check out [`nonzero`](https://numpy.org/doc/stable/reference/generated/numpy.nonzero.html) and [`argwhere`](https://numpy.org/doc/stable/reference/generated/numpy.argwhere.html) for some nuanced options)" + "### there are times when it's useful to have a list of indices meeting some condition. [`np.where`](https://numpy.org/doc/stable/reference/generated/numpy.where.html) will hook you up. (also check out [`nonzero`](https://numpy.org/doc/stable/reference/generated/numpy.nonzero.html) and [`argwhere`](https://numpy.org/doc/stable/reference/generated/numpy.argwhere.html) for some nuanced options)" ] }, { @@ -991,7 +991,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Views vs. Copies\n", + "## Views vs. Copies\n", "***\n", "**Slice indexing returns a view** That means if you change the slice, you change the original 🤔 " ] @@ -1744,8 +1744,14 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "name": "python", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part0_python_intro/06_matplotlib.ipynb b/notebooks/part0_python_intro/06_matplotlib.ipynb index 12a4c58..48fadcc 100644 --- a/notebooks/part0_python_intro/06_matplotlib.ipynb +++ b/notebooks/part0_python_intro/06_matplotlib.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — `matplotlib` — 2D and 3D plotting\n", + "# 06: `matplotlib` — 2D and 3D plotting\n", "\n", "This IPython Notebook is based on a notebook developed by J.R. Johansson (jrjohansson@gmail.com $-$ http://jrjohansson.github.io)\n", "\n", @@ -1151,8 +1151,14 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "name": "python", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part0_python_intro/06b_matplotlib_animation.ipynb b/notebooks/part0_python_intro/06b_matplotlib_animation.ipynb index 190d2b3..a627ccc 100644 --- a/notebooks/part0_python_intro/06b_matplotlib_animation.ipynb +++ b/notebooks/part0_python_intro/06b_matplotlib_animation.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Using Matplotlib to Create Animation\n", + "# 06a: Using Matplotlib to Create Animation\n", "\n", "This notebooks shows how to create an animation that will run and play inside a notebook. The animation can also be written to a video file." ] diff --git a/notebooks/part0_python_intro/07a_Theis-exercise.ipynb b/notebooks/part0_python_intro/07a_Theis-exercise.ipynb index 8831490..3902d14 100644 --- a/notebooks/part0_python_intro/07a_Theis-exercise.ipynb +++ b/notebooks/part0_python_intro/07a_Theis-exercise.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Using functions to solve an equation-- The Theis example\n", + "# 07: Using functions to solve an equation-- The Theis example\n", "In this exercise we will implement the Theis equation in Python using functions, to evaluate drawdown in hydraulic head from pumping at a well.\n", "\n", "\n", diff --git a/notebooks/part0_python_intro/09_Geopandas.ipynb b/notebooks/part0_python_intro/09_Geopandas.ipynb index a792c1a..e5e2665 100644 --- a/notebooks/part0_python_intro/09_Geopandas.ipynb +++ b/notebooks/part0_python_intro/09_Geopandas.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "aed944c8", + "metadata": {}, + "source": [ + "# 09: GeoPandas - DataFrames with geometry for GIS applications\n" + ] + }, { "cell_type": "code", "execution_count": null, @@ -30,10 +38,9 @@ "id": "0010de6e", "metadata": {}, "source": [ - "# GeoPandas - dataframes with geometry for GIS applications\n", "\n", - "## [Nice overview tutorial](https://geopandas.org/en/stable/getting_started/introduction.html)\n", - "## [Examples Gallery](https://geopandas.org/en/stable/gallery/index.html)" + "**[Nice overview tutorial](https://geopandas.org/en/stable/getting_started/introduction.html)**\n", + "**[Examples Gallery](https://geopandas.org/en/stable/gallery/index.html)**" ] }, { @@ -41,7 +48,7 @@ "id": "2e3cdfc6", "metadata": {}, "source": [ - "# OVERVIEW\n", + "### OVERVIEW\n", "***" ] }, @@ -50,7 +57,7 @@ "id": "25758dd5", "metadata": {}, "source": [ - "### get some data - `read_file` is the ticket for GeoJSON, shapefiles, GDB, etc." + "#### get some data - `read_file` is the ticket for GeoJSON, shapefiles, GDB, etc." ] }, { @@ -68,7 +75,7 @@ "id": "df21682d", "metadata": {}, "source": [ - "## writing back out is veeeery similar with `to_file` but give a few options for formats" + "### writing back out is veeeery similar with `to_file` but give a few options for formats" ] }, { @@ -97,7 +104,7 @@ "id": "c2022bd9", "metadata": {}, "source": [ - "## this now looks like a Pandas DataFrame but there's a special column `geometry`" + "### this now looks like a Pandas DataFrame but there's a special column `geometry`" ] }, { @@ -133,7 +140,7 @@ "id": "2a4d7e19", "metadata": {}, "source": [ - "> ## pro tip: You can have multiple geometry columns but only one is _active_ -- this is important later as we do operations on GeoDataFrames. The column labeled `geometry` is typically the active one but you [you can change it](https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.set_geometry.html)." + "> ### pro tip: You can have multiple geometry columns but only one is _active_ -- this is important later as we do operations on GeoDataFrames. The column labeled `geometry` is typically the active one but you [you can change it](https://geopandas.org/en/stable/docs/reference/api/geopandas.GeoDataFrame.set_geometry.html)." ] }, { @@ -141,10 +148,10 @@ "id": "9d329631", "metadata": {}, "source": [ - "## So what's up with these geometries? They are represented as [`shapely`](https://shapely.readthedocs.io/en/stable/manual.html) objects so can be:\n", - "- ### polygon / multi-polygon\n", - "- ### point / multi-point\n", - "- ### line / multi-line" + "### So what's up with these geometries? They are represented as [`shapely`](https://shapely.readthedocs.io/en/stable/manual.html) objects so can be:\n", + "- #### polygon / multi-polygon\n", + "- #### point / multi-point\n", + "- #### line / multi-line" ] }, { @@ -152,7 +159,7 @@ "id": "a8b12c66", "metadata": {}, "source": [ - "## we can access with pandas `loc` and `iloc` references" + "### we can access with pandas `loc` and `iloc` references" ] }, { @@ -216,7 +223,7 @@ "id": "0a9caf27", "metadata": {}, "source": [ - "## area units in lat/long don't make sense. Let's project to something in meters (but how?) `to_crs` will do it, but importantly, either reassign or set `inplace=True`" + "### area units in lat/long don't make sense. Let's project to something in meters (but how?) `to_crs` will do it, but importantly, either reassign or set `inplace=True`" ] }, { @@ -253,7 +260,7 @@ "id": "cd3b6bde", "metadata": {}, "source": [ - "# VISUALIZATION\n", + "## VISUALIZATION\n", "***" ] }, @@ -262,7 +269,7 @@ "id": "93e92c56", "metadata": {}, "source": [ - "## So back to GeoDataFrames.....we can look at them spatially as well with `plot()`" + "### So back to GeoDataFrames.....we can look at them spatially as well with `plot()`" ] }, { @@ -280,7 +287,7 @@ "id": "a152a006", "metadata": {}, "source": [ - "## easily make a chloropleth map using a selected column as the color (and add a legend) using `plot()`" + "### easily make a chloropleth map using a selected column as the color (and add a legend) using `plot()`" ] }, { @@ -318,7 +325,7 @@ "id": "f87e653b", "metadata": {}, "source": [ - "## also a very cool interactive plot options with a basemap using `explore()`" + "### also a very cool interactive plot options with a basemap using `explore()`" ] }, { @@ -336,7 +343,7 @@ "id": "7cc25673", "metadata": {}, "source": [ - "## we can read in another shapefile" + "### we can read in another shapefile" ] }, { @@ -384,7 +391,7 @@ "id": "64ca1dbe", "metadata": {}, "source": [ - "## WAT! Why so far apart?" + "### WAT! Why so far apart?" ] }, { @@ -402,7 +409,7 @@ "id": "d38d28d3", "metadata": {}, "source": [ - "## we need to reproject. Geopandas uses `to_crs()` for this purpose" + "### we need to reproject. Geopandas uses `to_crs()` for this purpose" ] }, { @@ -433,7 +440,7 @@ "id": "77528630", "metadata": {}, "source": [ - "## or similarly with the interactive maps" + "### or similarly with the interactive maps" ] }, { @@ -452,7 +459,7 @@ "id": "c368f951", "metadata": {}, "source": [ - "## we can make a new geodataframe using shapely properties of the geometry - how about centroids?" + "### we can make a new geodataframe using shapely properties of the geometry - how about centroids?" ] }, { @@ -508,7 +515,7 @@ "id": "44f12aec", "metadata": {}, "source": [ - "# GEOSPATIAL OPERATIONS\n", + "## GEOSPATIAL OPERATIONS\n", "***" ] }, @@ -517,7 +524,7 @@ "id": "fd2e835e", "metadata": {}, "source": [ - "# Operations on and among geodataframes...do I need to use a GIS program?" + "### Operations on and among geodataframes...do I need to use a GIS program?" ] }, { @@ -525,7 +532,7 @@ "id": "59e832e6", "metadata": {}, "source": [ - "## Dissolve" + "### Dissolve" ] }, { @@ -554,7 +561,7 @@ "id": "247414fd", "metadata": {}, "source": [ - "## Convex Hull" + "### Convex Hull" ] }, { @@ -573,7 +580,7 @@ "id": "17eb1ed8", "metadata": {}, "source": [ - "## Bounding Box is a little more tricky" + "### Bounding Box is a little more tricky" ] }, { @@ -602,7 +609,7 @@ "id": "b054106c", "metadata": {}, "source": [ - "## We can make a polygon from these coordinates with `shapely`" + "### We can make a polygon from these coordinates with `shapely`" ] }, { @@ -632,7 +639,7 @@ "id": "4febb485", "metadata": {}, "source": [ - "## to make a GeoDataFrame from scratch, the minimum you need is geometry, but a crs is important, and some data will populate more columns" + "#### to make a GeoDataFrame from scratch, the minimum you need is geometry, but a crs is important, and some data will populate more columns" ] }, { @@ -663,7 +670,7 @@ "id": "50525a00", "metadata": {}, "source": [ - "# How about some spatial joins?" + "### How about some spatial joins?" ] }, { @@ -671,7 +678,7 @@ "id": "e9c23ba8", "metadata": {}, "source": [ - "## we can bring in information based on locational overlap. Let's look at just a couple neighborhoods (Marquette and Tenny-Lapham) on the Isthmus" + "#### we can bring in information based on locational overlap. Let's look at just a couple neighborhoods (Marquette and Tenny-Lapham) on the Isthmus" ] }, { @@ -721,8 +728,8 @@ "id": "752856a0", "metadata": {}, "source": [ - "### so, it matters which direction you join from. The geometry is preserved from the dataframe \"on the left\"\n", - "### equivalently, you can be more explicit in calling `sjoin`" + "#### so, it matters which direction you join from. The geometry is preserved from the dataframe \"on the left\"\n", + "#### equivalently, you can be more explicit in calling `sjoin`" ] }, { @@ -750,7 +757,7 @@ "id": "93be2a56", "metadata": {}, "source": [ - "## we are going to use this `isthmus_parks` geoDataFrame a little later, but we want to trim out some unneeded and distracting columns. We can use `.drop()` just like with a regular Pandas DataFrame" + "#### we are going to use this `isthmus_parks` geoDataFrame a little later, but we want to trim out some unneeded and distracting columns. We can use `.drop()` just like with a regular Pandas DataFrame" ] }, { @@ -779,7 +786,7 @@ "id": "33baed2f", "metadata": {}, "source": [ - "# Let's explore the various predicates with a small intersecting box" + "### Let's explore the various predicates with a small intersecting box" ] }, { @@ -799,7 +806,7 @@ "id": "f18a9bc7", "metadata": {}, "source": [ - "## See [documentation](https://shapely.readthedocs.io/en/latest/manual.html#binary-predicates) for full set of options for predicates. We'll just check out a couple options: `intersects`, `contains`, `within`" + "#### See [documentation](https://shapely.readthedocs.io/en/latest/manual.html#binary-predicates) for full set of options for predicates. We'll just check out a couple options: `intersects`, `contains`, `within`" ] }, { @@ -807,7 +814,7 @@ "id": "a6717770", "metadata": {}, "source": [ - "# TEST YOUR SKILLS #1\n", + "## TEST YOUR SKILLS #1\n", "Using the `bounds` geodataframe you just made, write a function to visualize predicate behaviors.\n", "- your function should accept a left geodataframe, a right geodataframe, and a string for the predicate\n", "- your function should plot:\n", @@ -873,7 +880,7 @@ "id": "e03e0bb2", "metadata": {}, "source": [ - "# Spatial joins are particularly useful with collections of points. A common case is to add a polygon attribute to points falling within each polygon. Let's check out a bigger point dataset with all the trees on streets in Madison" + "#### Spatial joins are particularly useful with collections of points. A common case is to add a polygon attribute to points falling within each polygon. Let's check out a bigger point dataset with all the trees on streets in Madison" ] }, { @@ -892,7 +899,7 @@ "id": "176b8187", "metadata": {}, "source": [ - "## let's put this into the same crs as neighborhoods and join the data together so we can have a neighborhood attribute on the trees geodataframe" + "#### let's put this into the same crs as neighborhoods and join the data together so we can have a neighborhood attribute on the trees geodataframe" ] }, { @@ -920,7 +927,7 @@ "id": "e6dc5f63", "metadata": {}, "source": [ - "## NOTE: if we pass only some columns of the GeoDataFrame, only those columns will be included in the result, which is cool. _But_ - must include the active geometry column as well!" + "#### NOTE: if we pass only some columns of the GeoDataFrame, only those columns will be included in the result, which is cool. _But_ - must include the active geometry column as well!" ] }, { @@ -939,7 +946,7 @@ "id": "64922d2e", "metadata": {}, "source": [ - "## now we can do a `groupby`, for example, to find things like the average or max diameter of trees in each neighborhood" + "#### now we can do a `groupby`, for example, to find things like the average or max diameter of trees in each neighborhood" ] }, { @@ -957,7 +964,7 @@ "id": "33b25331", "metadata": {}, "source": [ - "## We could rearrange that bar chart in various ways, but we can also flip this back to the original neighborhoods GeoDataFrame to make a more useful spatial plot. Note that we used the spatial join to join together the attribute \"Neighborhood Name\" with each tree point. But now, we can aggregate those results and assign them based on an attribute rather than geospatially just like regular Pandas DataFrames" + "#### We could rearrange that bar chart in various ways, but we can also flip this back to the original neighborhoods GeoDataFrame to make a more useful spatial plot. Note that we used the spatial join to join together the attribute \"Neighborhood Name\" with each tree point. But now, we can aggregate those results and assign them based on an attribute rather than geospatially just like regular Pandas DataFrames" ] }, { @@ -978,7 +985,7 @@ "id": "6c2a2109", "metadata": {}, "source": [ - "# TEST YOUR SKILLS _OPTIONAL_\n", + "## TEST YOUR SKILLS _OPTIONAL_\n", "We have an Excel file that contains a crosswalk between SPECIES number as provided and species name. Can we bring that into our dataset and evaluate some conclusions about tree species by neighborhood?\n", "- start with the `trees_with_hoods` GeoDataFrame\n", "- load up and join the data from datapath / 'Madison_Tree_Species_Lookup.xlsx'\n", @@ -996,7 +1003,7 @@ "id": "e63a1ab3", "metadata": {}, "source": [ - "## As we've seen, spatial joins are powerful, but they really only gather data from multiple collections. What if we want to actually calculate the amount of overlap among shapes? Or create new shapes based on instersection or not intersection of shapes? [`overlay`](https://geopandas.org/en/stable/docs/user_guide/set_operations.html?highlight=overlay) does these things." + "#### As we've seen, spatial joins are powerful, but they really only gather data from multiple collections. What if we want to actually calculate the amount of overlap among shapes? Or create new shapes based on instersection or not intersection of shapes? [`overlay`](https://geopandas.org/en/stable/docs/user_guide/set_operations.html?highlight=overlay) does these things." ] }, { @@ -1004,7 +1011,7 @@ "id": "09de3e08", "metadata": {}, "source": [ - "## main options are `intersection`, `difference`, `union`, and `symmetric_difference`" + "#### main options are `intersection`, `difference`, `union`, and `symmetric_difference`" ] }, { @@ -1096,7 +1103,7 @@ "id": "1952cb07", "metadata": {}, "source": [ - "# On your own...\n", + "### On your own...\n", "- what if you switch left and right dataframes?\n", "- how can you evaluate the areas of overlap for the intersection case?" ] diff --git a/notebooks/part0_python_intro/10_Rasterio.ipynb b/notebooks/part0_python_intro/10_Rasterio.ipynb index 899931c..d30c7e7 100644 --- a/notebooks/part0_python_intro/10_Rasterio.ipynb +++ b/notebooks/part0_python_intro/10_Rasterio.ipynb @@ -5,7 +5,7 @@ "id": "57e747dd", "metadata": {}, "source": [ - "# Rasterio: Mt. Rainier glaciers example\n", + "# 10: Using Rasterio and Numpy to examine ice loss on Mt. Rainier\n", "\n", "This exercise focuses on working with [GIS raster data](https://docs.qgis.org/3.4/en/docs/gentle_gis_introduction/raster_data.html). It is based on a [GeoHackWeek tutorial](https://github.com/geohackweek/tutorial_contents/blob/master/raster/notebooks/rainier_dem_example.ipynb). We will use the `rasterio` and `rasterstats` libraries, along with `numpy` and `matplotlib` to look changes in the surface elevations of mapped glaciers since 1970.\n", "\n", diff --git a/notebooks/part0_python_intro/11_xarray_mt_rainier_precip.ipynb b/notebooks/part0_python_intro/11_xarray_mt_rainier_precip.ipynb index 0088aa0..b7df2d6 100644 --- a/notebooks/part0_python_intro/11_xarray_mt_rainier_precip.ipynb +++ b/notebooks/part0_python_intro/11_xarray_mt_rainier_precip.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Mt. Rainier Daymet precipitation example\n", + "# 11: Using Xarray to look at Daymet precipitation around Mt. Rainier\n", "In this example, we'll use [xarray](http://xarray.pydata.org/en/stable/why-xarray.html) to load and process a [NetCDF](https://www.unidata.ucar.edu/software/netcdf/) file of gridded precipitation data from the [Daymet model](https://daymet.ornl.gov/overview). Xarray aims to make working with multi-dimensional data easier, by implementing labeling of indices (e.g., to allow arrays to be indexed or sliced based on x and y coordinates or time, similar to what pandas does for tabular data).\n", "\n", "\"Drawing\"\n", @@ -13,11 +13,11 @@ "\n", "Note that there is also a [UXarray package](https://uxarray.readthedocs.io/en/latest/index.html) in early development that provides xarray-like functionality for unstructured grids.\n", "\n", - "#### Datasets:\n", + "**Datasets:**\n", "* Gridded precipitation output from the [Daymet model](https://daymet.ornl.gov/overview), for 1980-2018, for the area around Mt. Rainier.\n", "* An elevation raster for the area around Mt. Rainier, created in the `gis_raster_mt_rainier_glaciers.ipynb` exercise.\n", "\n", - "#### Xarray operations:\n", + "**Xarray operations:**\n", "* make a `DataArray` from scratch (using the `DataArray()` constructor)\n", "* load a NetCDF dataset into an `xarray.DataSet` instance\n", "* plotting the NetCDF data in projected or geographic coordinates\n", @@ -29,13 +29,13 @@ "* outputting extracted timeseries to pandas DataFrames\n", "* subsetting the xarray dataset and saving to a NetCDF file\n", "\n", - "#### rioxarray operations:\n", + "**rioxarray operations:**\n", "* add coordinate reference information to a dataset\n", "* reproject a dataset\n", "* write one or more (2D) timeslices of a dataset to a raster\n", "* clip a dataset to a polygon feature\n", "\n", - "#### References:\n", + "**References:**\n", "* The [Xarray manual](http://xarray.pydata.org/en/stable/why-xarray.html)\n", "* [Xarray in 45 minutes](https://tutorial.xarray.dev/overview/xarray-in-45-min.html)\n", "* The [GeoHackWeek tutorials](https://github.com/geohackweek/tutorial_contents/tree/master/nDarrays/notebooks)\n", @@ -2398,7 +2398,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Getting data at point locations\n", + "### Getting data at point locations\n", "\n", "Say we want to get data for the mountain summit, and at the Paradise Visitor Center in Mt. Rainier National Park.\n", "We can easily get the lat, lon coordinates for these locations, but to get data from this dataset, we need to work in the [custom coordinate system for Daymet](https://daymet.ornl.gov/overview). Luckly, we found a PROJ string to define that, which we assigned to the variable `daymet_proj_string`. With the PROJ string, we can use `pyproj` to transform the coordinates to the Daymet CRS." @@ -2803,7 +2803,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Groupby\n", + "### Groupby\n", "more in [the xarray manual](http://xarray.pydata.org/en/stable/groupby.html)\n", "\n", "#### getting monthly values" diff --git a/notebooks/part0_python_intro/solutions/01_functions_script__solution.ipynb b/notebooks/part0_python_intro/solutions/01_functions_script__solution.ipynb index 85893a4..670f583 100644 --- a/notebooks/part0_python_intro/solutions/01_functions_script__solution.ipynb +++ b/notebooks/part0_python_intro/solutions/01_functions_script__solution.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — functions and scripts" + "# 01: Functions and scripts" ] }, { @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -43,9 +43,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on function fib in module __main__:\n", + "\n", + "fib(n)\n", + " Print a Fibonacci series up to n.\n", + "\n" + ] + } + ], "source": [ "help(fib)" ] @@ -59,9 +71,34 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "1\n", + "1\n", + "2\n", + "3\n", + "5\n", + "8\n", + "13\n", + "21\n", + "34\n", + "55\n", + "89\n", + "144\n", + "233\n", + "377\n", + "610\n", + "987\n", + "1597\n" + ] + } + ], "source": [ "fib(2000)" ] @@ -110,25 +147,47 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "fib" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[0;31mSignature:\u001b[0m \u001b[0mfib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mDocstring:\u001b[0m Print a Fibonacci series up to n.\n", + "\u001b[0;31mFile:\u001b[0m /var/folders/4x/bmhyjcdn3mgfdvkk_jgz6bsrlnfk3t/T/ipykernel_46966/2487284216.py\n", + "\u001b[0;31mType:\u001b[0m function" + ] + } + ], "source": [ "?fib" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -137,9 +196,29 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0\n", + "1\n", + "1\n", + "2\n", + "3\n", + "5\n", + "8\n", + "13\n", + "21\n", + "34\n", + "55\n", + "89\n", + "144\n" + ] + } + ], "source": [ "f(200)" ] @@ -153,9 +232,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "None\n" + ] + } + ], "source": [ "fib(0)\n", "print(fib(0))" @@ -170,7 +257,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -186,18 +273,40 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "fib2(100)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "f100 = fib2(100) # call it\n", "f100 # write the result" @@ -231,7 +340,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -266,9 +375,38 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on function thiem in module __main__:\n", + "\n", + "thiem(T, r, Q=1000.0, R=10000000000.0, h0=0.0)\n", + " A very simple example function\n", + " with a mixture of argument types.\n", + " Solves the Thiem equation:\n", + " \n", + " h = (Q/2piT)*(ln(R/r)) + h0\n", + " \n", + " Parameters\n", + " ----------\n", + " \n", + " T: transmissivity\n", + " r: distance from pumping to observation\n", + " Q: pumping rate\n", + " R: distance to \"zero\" influence\n", + " h0: initial head\n", + " \n", + " Returns\n", + " -------\n", + " h: head\n", + "\n" + ] + } + ], "source": [ "help(thiem)" ] @@ -284,9 +422,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "27.568951478843925" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "thiem(100.0, 300.0)" ] @@ -300,9 +449,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0.2756895147884393" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "thiem(100.0, 300.0, 10)" ] @@ -316,9 +476,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "13.784475739421962" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "thiem(100.0, 300.0, Q=500.0)" ] @@ -404,7 +575,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -440,9 +611,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[0.029317448718566664, 0.05863489743713333, 0.0879523461557]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "thiem_list(1000, 100, Q=[10, 20, 30])" ] @@ -451,7 +633,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# More on functions: ```lambda``` functions\n", + "## More on functions: ```lambda``` functions\n", "\n", "```lambda``` functions are a special type of function known as an \"in-line\" function. They are present in virtually all modern programming langauges (not Fortran, that's not modern) and are usually high-optimized. They allow you to quickly define a simple-ish function that can only accept a single, *required* argument. The only reason to introduce them is because they appear frequently when using a python library named ```pandas``` that we will cover later." ] @@ -465,9 +647,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(x)>" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "square = lambda x: x * x\n", "square" @@ -475,18 +668,42 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "10000" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "square(100)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "metadata": {}, - "outputs": [], + "outputs": [ + { + "ename": "TypeError", + "evalue": "can't multiply sequence by non-int of type 'str'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43msquare\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mnot gonna work\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n", + "Cell \u001b[0;32mIn[20], line 1\u001b[0m, in \u001b[0;36m\u001b[0;34m(x)\u001b[0m\n\u001b[0;32m----> 1\u001b[0m square \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mlambda\u001b[39;00m x: \u001b[43mx\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mx\u001b[49m\n\u001b[1;32m 2\u001b[0m square\n", + "\u001b[0;31mTypeError\u001b[0m: can't multiply sequence by non-int of type 'str'" + ] + } + ], "source": [ "square(\"not gonna work\")" ] diff --git a/notebooks/part0_python_intro/solutions/02_Namespace_objects_modules_packages__solution.ipynb b/notebooks/part0_python_intro/solutions/02_Namespace_objects_modules_packages__solution.ipynb index 95a899b..ad2a7e8 100644 --- a/notebooks/part0_python_intro/solutions/02_Namespace_objects_modules_packages__solution.ipynb +++ b/notebooks/part0_python_intro/solutions/02_Namespace_objects_modules_packages__solution.ipynb @@ -5,7 +5,7 @@ "id": "00aaaf25", "metadata": {}, "source": [ - "# Python for hydrologists: namespace, modules, packages, and objects\n", + "# 02: Namespace, modules, packages, and objects\n", "\n", "There are a variety of ways to import existing code into a Python script or interactive session.\n", "\n", diff --git a/notebooks/part0_python_intro/solutions/03_useful-std-library-modules-solutions.ipynb b/notebooks/part0_python_intro/solutions/03_useful-std-library-modules-solutions.ipynb index 6d3c0bd..62748d7 100644 --- a/notebooks/part0_python_intro/solutions/03_useful-std-library-modules-solutions.ipynb +++ b/notebooks/part0_python_intro/solutions/03_useful-std-library-modules-solutions.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Useful standard library modules exercise solutions" + "## 03: Solutions to Useful standard library modules exercises" ] }, { @@ -25,7 +25,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Exercise: Make a script with a command line argument using sys.argv\n", + "## Exercise: Make a script with a command line argument using sys.argv\n", "\n", "1) Using a text editor such as VSCode, make a new ``*.py`` file with the following contents:\n", "\n", @@ -106,7 +106,7 @@ "source": [ "## Testing Your Skills with a truly awful example:\n", "\n", - "#### the problem:\n", + "### the problem:\n", "Pretend that the file `data/fileio/netcdf_data.zip` contains some climate data (in the NetCDF format with the ``*.nc`` extension) that we downloaded. If you open `data/fileio/netcdf_data.zip`, you'll see that within a subfolder `zipped` are a bunch of additional subfolders, each for a different year. Within each subfolder is another zipfile. Within each of these zipfiles is yet another subfolder, inside of which is the actual data file we want (`prcp.nc`). " ] }, @@ -142,7 +142,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### the goal:\n", + "### the goal:\n", "To extract all of these `prcp.nc` files into a single folder, after renaming them with their respective years (obtained from their enclosing folders or zip files). e.g. \n", "```\n", "prcp_1980.nc\n", @@ -151,7 +151,7 @@ "```\n", "This will allow us to open them together as a dataset in `xarray` (more on that later). Does this sound awful? I'm not making this up. This is the kind of structure you get when downloading tiles of climate data with the [Daymet Tile Selection Tool](https://daymet.ornl.gov/gridded/)\n", "\n", - "#### hint:\n", + "### hint:\n", "you might find these functions helpful:\n", "```\n", "ZipFile.extractall\n", @@ -180,7 +180,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "#### hint: start by using ``ZipFile.extractall()`` to extract all of the individual zip files from the main zip archive\n", + "### hint: start by using ``ZipFile.extractall()`` to extract all of the individual zip files from the main zip archive\n", "This extracts the entire contents of the zip file to a designated folder" ] }, diff --git a/notebooks/part0_python_intro/solutions/04_files_and_strings.ipynb b/notebooks/part0_python_intro/solutions/04_files_and_strings.ipynb index be583aa..3a7b194 100644 --- a/notebooks/part0_python_intro/solutions/04_files_and_strings.ipynb +++ b/notebooks/part0_python_intro/solutions/04_files_and_strings.ipynb @@ -5,7 +5,7 @@ "id": "6264d3bb", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — file input and output\n", + "# 04: File input and output\n", "\n", "In this exercise we will be learning about using python to work with file input and output. We will also learn a little about reading and writing ascii files. \n", "\n", diff --git a/notebooks/part0_python_intro/solutions/05_numpy__solutions.ipynb b/notebooks/part0_python_intro/solutions/05_numpy__solutions.ipynb index d760b28..83e632f 100644 --- a/notebooks/part0_python_intro/solutions/05_numpy__solutions.ipynb +++ b/notebooks/part0_python_intro/solutions/05_numpy__solutions.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "2067682b", + "metadata": {}, + "source": [ + "# 05: NumPy exercise solutions" + ] + }, { "cell_type": "code", "execution_count": 1, diff --git a/notebooks/part0_python_intro/solutions/06_matplotlib__solution.ipynb b/notebooks/part0_python_intro/solutions/06_matplotlib__solution.ipynb index c2e3093..6d51b65 100644 --- a/notebooks/part0_python_intro/solutions/06_matplotlib__solution.ipynb +++ b/notebooks/part0_python_intro/solutions/06_matplotlib__solution.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — `matplotlib` — 2D and 3D plotting\n", + "# 06: `matplotlib` — 2D and 3D plotting\n", "\n", "This IPython Notebook is based on a notebook developed by J.R. Johansson (jrjohansson@gmail.com $-$ http://jrjohansson.github.io)\n", "\n", @@ -89,7 +89,7 @@ "\n", "\n", "\n", - "# The `matplotlib` object-oriented API\n", + "## The `matplotlib` object-oriented API\n", "\n", "The main idea with object-oriented programming is to have objects that one can apply functions and actions on, and no object or program states should be global (such as the MATLAB-like API). The real advantage of this approach becomes apparent when more than one figure is created, or when a figure contains more than one subplot. \n", "\n", @@ -306,7 +306,7 @@ "ax.legend(loc=4) # lower right corner\n", "```\n", "\n", - "# .. many more options are available\n", + "### .. many more options are available\n", "\n", "Alternatively, location keywords can also be used.\n", "\n", diff --git a/notebooks/part0_python_intro/solutions/07a_Theis-exercise-solution.ipynb b/notebooks/part0_python_intro/solutions/07a_Theis-exercise-solution.ipynb index 4b372f5..a56707d 100755 --- a/notebooks/part0_python_intro/solutions/07a_Theis-exercise-solution.ipynb +++ b/notebooks/part0_python_intro/solutions/07a_Theis-exercise-solution.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Using functions to solve an equation-- The Theis example\n", + "# 07: Using functions to solve an equation-- The Theis example\n", "In this exercise we will implement the Theis equation in Python using functions, to evaluate drawdown in hydraulic head from pumping at a well.\n", "\n", "\n", diff --git a/notebooks/part0_python_intro/solutions/08_pandas.ipynb b/notebooks/part0_python_intro/solutions/08_pandas.ipynb index e6516df..c0abea9 100644 --- a/notebooks/part0_python_intro/solutions/08_pandas.ipynb +++ b/notebooks/part0_python_intro/solutions/08_pandas.ipynb @@ -5,7 +5,7 @@ "id": "8da35269", "metadata": {}, "source": [ - "# Introduction to python for hydrologists — pandas\n", + "# 08: Working with tabular data in Pandas\n", "\n", "" ] diff --git a/notebooks/part0_python_intro/solutions/09_Geopandas__solutions.ipynb b/notebooks/part0_python_intro/solutions/09_Geopandas__solutions.ipynb index 62069a7..8c10201 100644 --- a/notebooks/part0_python_intro/solutions/09_Geopandas__solutions.ipynb +++ b/notebooks/part0_python_intro/solutions/09_Geopandas__solutions.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "b4ae2aec", + "metadata": {}, + "source": [ + "# 09: Geopandas exercise solutions" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -396,7 +404,7 @@ "id": "87c2939a", "metadata": {}, "source": [ - "# TEST YOUR SKILLS #1\n", + "## TEST YOUR SKILLS #1\n", "Using the `bounds` geodataframe you just made, write a function to visualize predicate behaviors.\n", "- your function should accept a left geodataframe, a right geodataframe, and a string for the predicate\n", "- your function should plot:\n", @@ -769,7 +777,7 @@ "id": "fb9476f2", "metadata": {}, "source": [ - "# TEST YOUR SKILLS _OPTIONAL_\n", + "## TEST YOUR SKILLS _OPTIONAL_\n", "We have an Excel file that contains a crosswalk between SPECIES number as provided and species name. Can we bring that into our dataset and evaluate some conclusions about tree species by neighborhood?\n", "- start with the `trees_with_hoods` GeoDataFrame\n", "- load up and join the data from datapath / 'Madison_Tree_Species_Lookup.xlsx'\n", diff --git a/notebooks/part1_flopy/03_Loading_and_visualizing_models.ipynb b/notebooks/part1_flopy/03_Loading_and_visualizing_models.ipynb index 6c7ce7d..b030d5a 100644 --- a/notebooks/part1_flopy/03_Loading_and_visualizing_models.ipynb +++ b/notebooks/part1_flopy/03_Loading_and_visualizing_models.ipynb @@ -37,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -72,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -86,7 +86,7 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -104,54 +104,18 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "xll:552400.0; yll:387200.0; rotation:0.0; units:meters; lenuni:2" - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "m.modelgrid" ] }, { "cell_type": "code", - "execution_count": 49, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['DIS',\n", - " 'IC',\n", - " 'NPF',\n", - " 'STO',\n", - " 'RCHA_0',\n", - " 'OC',\n", - " 'CHD_OBS',\n", - " 'CHD_0',\n", - " 'SFR_OBS',\n", - " 'SFR_0',\n", - " 'LAK_OBS',\n", - " 'LAK_LAKTAB',\n", - " 'LAK_0',\n", - " 'WEL_0',\n", - " 'OBS_3']" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "m.get_package_list()" ] @@ -165,7 +129,7 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -182,30 +146,9 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(6, 6))\n", "pmv = flopy.plot.PlotMapView(m, ax=ax)\n", @@ -218,20 +161,9 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(6, 6))\n", "pmv = flopy.plot.PlotMapView(m, ax=ax)\n", @@ -248,7 +180,7 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -273,20 +205,9 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(14, 5))\n", "xs = flopy.plot.PlotCrossSection(model=m, line={\"row\": 30}, ax=ax)\n", @@ -305,20 +226,9 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ], - "text/plain": [ - " layer row column q boundname per\n", - "0 2 24 2 -396.867 pleasant_2-13-2 0\n", - "1 2 17 2 -409.900 pleasant_2-9-2 0\n", - "2 3 23 44 0.000 pleasant_3-12-23 0\n", - "3 3 25 26 0.000 pleasant_3-13-14 0\n", - "4 3 24 54 -878.654 pleasant_3-13-28 0" - ] - }, - "execution_count": 58, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "dfs = []\n", "for kper, df in m.wel.stress_period_data.get_dataframe().items():\n", @@ -23516,30 +340,9 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Text(0, 0.5, '$m^3$/day')" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "df.groupby('per').sum()['q'].plot()\n", "plt.title('Total pumpage by Stress period')\n", @@ -23572,77 +375,9 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "FloPy is using the following executable to run the model: ../../../../../../software/modflow_exes/mf6\n", - " MODFLOW 6\n", - " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", - " VERSION 6.4.2 06/28/2023\n", - "\n", - " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", - " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", - " Build 20220726_000000\n", - "\n", - "This software has been approved for release by the U.S. Geological \n", - "Survey (USGS). Although the software has been subjected to rigorous \n", - "review, the USGS reserves the right to update the software as needed \n", - "pursuant to further analysis and review. No warranty, expressed or \n", - "implied, is made by the USGS or the U.S. Government as to the \n", - "functionality of the software and related material nor shall the \n", - "fact of release constitute any such warranty. Furthermore, the \n", - "software is released on condition that neither the USGS nor the U.S. \n", - "Government shall be held liable for any damages resulting from its \n", - "authorized or unauthorized use. Also refer to the USGS Water \n", - "Resources Software User Rights Notice for complete use, copyright, \n", - "and distribution information.\n", - "\n", - " \n", - " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/02 14:58:39\n", - " \n", - " Writing simulation list file: mfsim.lst\n", - " Using Simulation name file: mfsim.nam\n", - " \n", - " Solving: Stress period: 1 Time step: 1\n", - " Solving: Stress period: 2 Time step: 1\n", - " Solving: Stress period: 3 Time step: 1\n", - " Solving: Stress period: 4 Time step: 1\n", - " Solving: Stress period: 5 Time step: 1\n", - " Solving: Stress period: 6 Time step: 1\n", - " Solving: Stress period: 7 Time step: 1\n", - " Solving: Stress period: 8 Time step: 1\n", - " Solving: Stress period: 9 Time step: 1\n", - " Solving: Stress period: 10 Time step: 1\n", - " Solving: Stress period: 11 Time step: 1\n", - " Solving: Stress period: 12 Time step: 1\n", - " Solving: Stress period: 13 Time step: 1\n", - " \n", - " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/02 14:58:43\n", - " Elapsed run time: 3.129 Seconds\n", - " \n", - "\n", - "WARNING REPORT:\n", - "\n", - " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'pleasant.sfr' WAS\n", - " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", - " Normal termination of simulation.\n" - ] - }, - { - "data": { - "text/plain": [ - "(True, [])" - ] - }, - "execution_count": 60, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "sim.run_simulation()" ] @@ -23663,7 +398,7 @@ }, { "cell_type": "code", - "execution_count": 61, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -23694,20 +429,9 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "levels=np.arange(280, 315, 1)\n", "new_extent = (554500, 557500, 388500, 392000)\n", @@ -23776,18 +489,9 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pyproj/crs/crs.py:1293: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems\n", - " proj = self._crs.to_proj4(version=version)\n" - ] - } - ], + "outputs": [], "source": [ "from flopy.export.utils import export_array\n", "\n", @@ -23825,20 +529,9 @@ }, { "cell_type": "code", - "execution_count": 65, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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0.000000 0.0 43243.300781 11221.008789 2172.376465 \n", - "2012-02-29 0.000000 0.0 43013.406250 10831.583008 2157.964844 \n", - "2012-03-31 0.000000 0.0 43912.550781 11090.963867 2208.054443 \n", - "2012-04-30 0.000000 0.0 45098.117188 12015.685547 2326.493896 \n", - "\n", - " TOTAL_OUT IN-OUT PERCENT_DISCREPANCY \n", - "2011-12-31 60654.296875 0.396000 0.0 \n", - "2012-01-31 56793.144531 -0.195200 -0.0 \n", - "2012-02-29 56023.539062 -0.094266 -0.0 \n", - "2012-03-31 61473.503906 -0.129200 -0.0 \n", - "2012-04-30 91564.250000 0.044994 0.0 " - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "mfl = Mf6ListBudget(sim_ws / 'pleasant.list')\n", "flux, vol = mfl.get_dataframes(start_datetime='2011-12-30')\n", @@ -24480,24 +659,9 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['STO-SS_IN', 'STO-SY_IN', 'WEL_IN', 'RCHA_IN', 'CHD_IN', 'SFR_IN',\n", - " 'LAK_IN', 'TOTAL_IN', 'STO-SS_OUT', 'STO-SY_OUT', 'WEL_OUT', 'RCHA_OUT',\n", - " 'CHD_OUT', 'SFR_OUT', 'LAK_OUT', 'TOTAL_OUT', 'IN-OUT',\n", - " 'PERCENT_DISCREPANCY'],\n", - " dtype='object')" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "flux.columns" ] @@ -24511,30 +675,9 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(10, 5))\n", "in_cols = ['STO-SS_IN', 'STO-SY_IN', 'WEL_IN', 'RCHA_IN', 'CHD_IN', 'SFR_IN', 'LAK_IN']\n", diff --git a/notebooks/part1_flopy/04_Modelgrid_and_intersection.ipynb b/notebooks/part1_flopy/04_Modelgrid_and_intersection.ipynb index 324522d..094a68f 100644 --- a/notebooks/part1_flopy/04_Modelgrid_and_intersection.ipynb +++ b/notebooks/part1_flopy/04_Modelgrid_and_intersection.ipynb @@ -22,7 +22,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "72833c87", "metadata": {}, "outputs": [], @@ -63,19 +63,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "7154ce13", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "xll:0.0; yll:0.0; rotation:0.0; units:undefined; lenuni:0\n", - "\n" - ] - } - ], + "outputs": [], "source": [ "nrow = 20\n", "ncol = 15\n", @@ -111,21 +102,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "8eabc8cd", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "modelgrid.plot();" ] @@ -142,7 +122,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "bd579167", "metadata": {}, "outputs": [], @@ -157,21 +137,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "075e0165", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(10, 10))\n", "ax = modelgrid.plot(ax=ax)\n", @@ -191,21 +160,10 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "046226a5", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "xc, yc = modelgrid.xcellcenters, modelgrid.ycellcenters\n", "xv, yv = modelgrid.xvertices, modelgrid.yvertices\n", @@ -229,21 +187,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "6392c804", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" [ 0. , 0. , 0. , 0. ,\n", - " 0. , 0. , 0. , 0. ,\n", - " 0. , 0. , 0. , 0. ,\n", - " 0. , 0. , 0. ]]]),\n", - " array([150., 150., 150., 150., 150., 150., 150., 150., 150., 150., 150.,\n", - " 150., 150., 150., 150., 150., 150., 150., 150., 150.]),\n", - " array([250., 250., 250., 250., 250., 250., 250., 250., 250., 250., 250.,\n", - " 250., 250., 250., 250.]))" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "top = modelgrid.top\n", "botm = modelgrid.botm\n", @@ -483,21 +256,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "9b7fd96b", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[(0, 0, 4), (0, 0, 6), (0, 1, 5)]" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "cell = (0, 0, 5)\n", "\n", @@ -517,21 +279,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "6426d2bc", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "'rowcol=(13, 8), layrowcol=(0, 13, 8)'" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "x, y, z = 2348000, 1235000, 25\n", "\n", @@ -561,21 +312,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "50642957", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "modelgrid.set_coord_info(angrot=0)\n", "modelgrid.plot();" @@ -591,25 +331,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "70fc1ed9", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n" - ] - } - ], + "outputs": [], "source": [ "active_shp = data_path / \"active_area.shp\"\n", "refine_shp = data_path / \"refined_area.shp\"\n", @@ -628,31 +353,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "5ed44ddb", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(8, 8))\n", "\n", @@ -673,7 +377,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "d5d43d7e", "metadata": {}, "outputs": [], @@ -693,21 +397,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "a3ed5439", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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a2lrV1NQoOTlZ/fv3V3FxsY4fP66qqipJ55uN6dOn66mnntLo0aN991PExsbK6XRKOn/z5siRI5WZmSmPx6OtW7eqqqpKy5cv98tubm7WypUrlZ+fr+7d/Ut3OBx68MEHVVZWpsGDB2vw4MEqKytTXFycfvaznwU1x4KCAqWkpAT7n+ayNTQ0+OY6Z84cxcXFkd1FsyNxzmTzPiO7a2Z7vV5VVFS0e3zQDccHH3ygnJwc3+P58+dLkvLz87Vq1SqdOHFCR44c8R1/9tlnde7cORUWFvpt0tUyXjp/z8TcuXN17NgxxcbGaujQoVq9erXuvvtuv+w33nhDR44c0axZswLW9sgjj+ibb77R3Llzdfr0aY0aNUrbtm1TYmJiUHOMj49XQkJCUOdcKXFxcWRHSHYkzpls3mdkd51sj8cT1PigG47s7Gxd7LaPliaixY4dOy75mqWlpSotLb3kuPHjx1802+FwqKSkRCUlJZd8LQAAEDr8lgoAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALBc0L8WGwncbrdiYmJCltfQ0BDw32R3vexInDPZoc+OxDmTHfpsr9cb1HiHudjvvUcYl8slp9OpoqKikDYcAADYUWNjo8rLy1VXV6ekpKSLjmVJBQAAWI4llQAKCgqUkpISsryGhgYtX75ckjRnzhzFxcWR3Ymzw3VupGbbte5wZtu17o4iO7TZXq9XFRUV7R5PwxFAfHy8EhISwpIdFxdHto2yw3VupGbbte5wZtu17o4i23oejyeo8SypAAAAy9FwAAAAy9FwAAAAy9FwAAAAy3HTKCJesBvldGSTnY5u0BOJ2XatO5zZnaVuoDUaDkS8lq+T2encSM22a93hzA5n3UBrLKkAAADL8QkHIh4bMnXubLvWHc7szlI30BoNByIeGzLZJ9uudYczO5x1A62xpAIAACxHwwEAACxHwwEAACxHwwEAACzHTaMBuN1uxcTEhCyvo5v0kB3a7K6wIZOdsu1adziz7Vp3R5Ed2myv1xvUeIcxxlhUi+24XC45nU4VFRWFtOEAAMCOGhsbVV5errq6OiUlJV10LEsqAADAciypBFBQUKCUlJSQ5XV0kx6yQ5vdFTZkslO2XesOZ7Zd6+4oskOb7fV6VVFR0e7xNBwBxMfHh22jm3BuskO2fc6N1Gy71h3ObLvW3VFkW8/j8QQ1niUVAABgORoOAABgORoOAABgORoOAABgORoOAABgOb6lgojHDpCdO9uudYczu7PUDbRGw4GI1/L9dTudG6nZdq07nNnhrBtojSUVAABgOT7hQMRjB8jOnW3XusOZ3VnqBlqj4UDEYwdI+2Tbte5wZoezbqA1llQAAIDlaDgAAIDlaDgAAIDlaDgAAIDlgr5pdNeuXfrtb3+rPXv26MSJE9qwYYMmT558wfHr16/X8uXLVVNTo6amJl1//fUqKSnRhAkT/MaUlZXp0KFD8nq9Gjx4sB566CHde++9fq91/Phx/frXv9arr76qb775RkOGDNFzzz2nH/zgB5KkGTNmqLKy0u+cUaNG6Z133glqjm63WzExMUGd0xEd3aSH7NBmd4UNmeyUbde6w5lt17o7iuzQZnu93qDGO4wxJpgTXn31Vb311lv6/ve/rylTplyy4XjwwQeVnp6unJwc9ezZUytXrtSSJUv07rvvKisrS5K0Y8cOnT59WkOHDlWPHj20ZcsWPfTQQ3rllVd8jcnp06eVlZWlnJwczZkzR6mpqfrss880YMAAZWZmSjrfcPzlL3/RypUrffk9evRQcnJyu+bmcrnkdDpVVFQU0oYDAAA7amxsVHl5uerq6pSUlHTRsUF/wpGXl6e8vLx2j1+2bJnf47KyMm3atEmbN2/2NRzZ2dl+Y+bNm6fKykrt3r3b13AsXrxY/fr182smBgwY0CYvOjpaffr0aXd9AADAeiHfh6O5uVlnz5694KcOxhi9+eab2r9/vxYvXux7/uWXX9aECRM0depU7dy5U3379tXcuXN1//33+52/Y8cOpaamqmfPnho3bpx+85vfKDU1NWBWU1OTmpqafI9dLpckqaCgQCkpKR2dart1dJMeskOb3RU2ZLJTtl3rDme2XevuKLJDm+31elVRUdHu8SFvOJYuXSq3261p06b5PV9XV6e+ffuqqalJUVFReuaZZ5Sbm+s7fvjwYS1fvlzz58/Xo48+qvfee0+//OUvFR0drenTp0s6/+nL1KlTlZGRodraWv3zP/+zfvjDH2rPnj2Kjo5uU8uiRYu0cOHCNs/Hx8eHbaObcG6yQ7Z9zo3UbLvWHc5su9bdUWRbz+PxBDU+pA1HdXW1SkpKtGnTpjafOiQmJqqmpkb19fXavn275s+fr0GDBvmWW5qbmzVy5EiVlZVJkrKysvTpp59q+fLlvobj7rvv9r3eDTfcoJEjRyojI0OvvPKK7rrrrjb1FBcXa/78+b7HLpdL/fr1u9LTBgAg4oWs4Vi7dq1mz56tdevW6bbbbmtzvFu3brr22mslSSNGjNC+ffu0aNEiX8ORlpam7373u37nXHfddXrppZcumJmWlqaMjAwdPHgw4PHo6OiAn3wAAIArKyT7cFRXV2vGjBlas2aNJk6c2K5zjDF+91eMHTtW+/fv9xtz4MABZWRkXPA1vv76ax09elRpaWmXVzgAALgigv6Eo76+XocOHfI9rq2tVU1NjZKTk9W/f38VFxfr+PHjqqqqknS+2Zg+fbqeeuopjR49WidPnpQkxcbGyul0Sjp/L8XIkSOVmZkpj8ejrVu3qqqqyu8XB3/1q1/ppptuUllZmaZNm6b33ntPK1as0IoVK3x1lZSUaMqUKUpLS9Pnn3+uRx99VFdffbXuvPPOy/8vBAAAOizohuODDz5QTk6O73HLPRD5+flatWqVTpw4oSNHjviOP/vsszp37pwKCwtVWFjoe75lvHR+o625c+fq2LFjio2N1dChQ7V69Wq/ezJuvPFGbdiwQcXFxXriiSc0cOBALVu2TD//+c8lSVFRUdq7d6+qqqp05swZpaWlKScnR2vXrlViYmKw00QEYUOmzp1t17rDmd1Z6gZaC3rjr66sZeOvv/71r7r66qtDlltfX6+lS5dKkh566KGQ3t1MNgCrROr/pkRKtsfj0eOPP97ujb/4LRUAAGC5kO/DAXQ2bMjUubPtWnc4sztL3UBrNByIeGzIZJ9su9Ydzuxw1g20xpIKAACwHA0HAACwHA0HAACwHA0HAACwHDeNBuB2uxUTExOyvI5u0kN2aLO7woZMdsq2a93hzLZr3R1FdmizvV5vUOPZ+KuVlo2/ioqKQtpwAABgR42NjWz8BQAAOg+WVAIoKChQSkpKyPI6ukkP2aHN7gobMtkp2651hzPbrnV3FNmhzfZ6vaqoqGj3eBqOAOLj48O20U04N9kh2z7nRmq2XesOZ7Zd6+4osq3n8XiCGs+SCgAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBzfUkHEYwfIzp1t17rDmd1Z6gZao+FAxGv5/rqdzo3UbLvWHc7scNYNtMaSCgAAsByfcCDisQNk5862a93hzO4sdQOt0XAg4rEDpH2y7Vp3OLPDWTfQGksqAADAcjQcAADAcjQcAADAcjQcAADActw0GoDb7VZMTEzI8jq6SQ/Zoc3uChsy2SnbrnWHM9uudXcU2aHN9nq9QY13GGOMRbXYjsvlktPpVFFRUUgbDgAA7KixsVHl5eWqq6tTUlLSRceypAIAACzHkkoABQUFSklJCVleRzfpITu02V1hQyY7Zdu17nBm27XujiI7tNler1cVFRXtHk/DEUB8fHzYNroJ5yY7ZNvn3EjNtmvd4cy2a90dRbb1PB5PUONZUgEAAJaj4QAAAJaj4QAAAJaj4QAAAJbjplFEPDZk6tzZdq07nNmdpW6gNRoORLyWr5PZ6dxIzbZr3eHMDmfdQGssqQAAAMvxCQciHhsyde5su9YdzuzOUjfQGg0HIh4bMtkn2651hzM7nHUDrbGkAgAALEfDAQAALEfDAQAALEfDAQAALMdNowG43W7FxMSELK+jm/SQHdrsrrAhk52y7Vp3OLPtWndHkR3abK/XG9R4hzHGWFSL7bhcLjmdThUVFYW04QAAwI4aGxtVXl6uuro6JSUlXXQsSyoAAMByLKkEUFBQoJSUlJDldXSTHrJDm90VNmSyU7Zd6w5ntl3r7iiyQ5vt9XpVUVHR7vE0HAHEx8eHbaObcG6yQ7Z9zo3UbLvWHc5su9bdUWRbz+PxBDWeJRUAAGA5Gg4AAGC5oBuOXbt2adKkSUpPT5fD4dDGjRsvOn79+vXKzc1Vr169lJSUpDFjxui1115rM2bkyJHq2bOn4uPjNWLECD3//PNtXuv48eO65557lJKSori4OI0YMUJ79uzxHTfGqKSkROnp6YqNjVV2drY+/fTTYKcIAACusKAbDrfbreHDh+vpp59u1/hdu3YpNzdXW7du1Z49e5STk6NJkybpo48+8o1JTk7WggUL9Oc//1kff/yxZs6cqZkzZ/o1JqdPn9bYsWN11VVX6dVXX9X//M//aOnSperZs6dvTEVFhZ588kk9/fTTev/999WnTx/l5ubq7NmzwU4TAABcQUHfNJqXl6e8vLx2j1+2bJnf47KyMm3atEmbN29WVlaWJCk7O9tvzLx581RZWandu3drwoQJkqTFixerX79+WrlypW/cgAEDfP82xmjZsmVasGCB7rrrLklSZWWlevfurTVr1ugXv/hFELMEAABXUsi/pdLc3KyzZ88qOTk54HFjjN58803t379fixcv9j3/8ssva8KECZo6dap27typvn37au7cubr//vslSbW1tTp58qTGjx/vOyc6Olrjxo3T22+/HbDhaGpqUlNTk++xy+W6UtOEjbADZOfOtmvd4czuLHUDrYW84Vi6dKncbremTZvm93xdXZ369u2rpqYmRUVF6ZlnnlFubq7v+OHDh7V8+XLNnz9fjz76qN577z398pe/VHR0tKZPn66TJ09Kknr37u33ur1799YXX3wRsJZFixZp4cKFV3iGsJuW76/b6dxIzbZr3eHMDmfdQGshbTiqq6tVUlKiTZs2KTU11e9YYmKiampqVF9fr+3bt2v+/PkaNGiQb7mlublZI0eOVFlZmSQpKytLn376qZYvX67p06f7XsfhcPi9rjGmzXMtiouLNX/+fN9jl8ulfv36XYmpAgCAVkLWcKxdu1azZ8/WunXrdNttt7U53q1bN1177bWSpBEjRmjfvn1atGiRr+FIS0vTd7/7Xb9zrrvuOr300kuSpD59+kiSTp48qbS0NN+YU6dOtfnUo0V0dLSio6M7PDfYGztAdu5su9YdzuzOUjfQWkgajurqas2aNUvV1dWaOHFiu84xxvjdXzF27Fjt37/fb8yBAweUkZEhSRo4cKD69Omj119/3Xczqsfj0c6dO/3uBQH+L3aAtE+2XesOZ3Y46wZaC7rhqK+v16FDh3yPa2trVVNTo+TkZPXv31/FxcU6fvy4qqqqJJ1vNqZPn66nnnpKo0eP9t1rERsbK6fTKen8vRQjR45UZmamPB6Ptm7dqqqqKr8u+Ve/+pVuuukmlZWVadq0aXrvvfe0YsUKrVixQtL5pZQHH3xQZWVlGjx4sAYPHqyysjLFxcXpZz/72eX/FwIAAB0WdMPxwQcfKCcnx/e45R6I/Px8rVq1SidOnNCRI0d8x5999lmdO3dOhYWFKiws9D3fMl46v7fH3LlzdezYMcXGxmro0KFavXq17r77bt/4G2+8URs2bFBxcbGeeOIJDRw4UMuWLdPPf/5z35hHHnlE33zzjebOnavTp09r1KhR2rZtmxITE4OdJgAAuIKCbjiys7NljLng8ZYmosWOHTsu+ZqlpaUqLS295Lgf/ehH+tGPfnTB4w6HQyUlJSopKbnkawEAgNDht1QAAIDl+Hn6ANxut2JiYkKW19FNesgObXZX2JDJTtl2rTuc2Xatu6PIDm221+sNarzDXGx9JMK4XC45nU4VFRWFtOEAAMCOGhsbVV5errq6OiUlJV10LEsqAADAciypBFBQUKCUlJSQ5XV0kx6yQ5vdFTZkslO2XesOZ7Zd6+4oskOb7fV6VVFR0e7xNBwBxMfHh22jm3BuskO2fc6N1Gy71h3ObLvW3VFkW8/j8QQ1niUVAABgORoOAABgORoOAABgORoOAABgOW4aRcRjQ6bOnW3XusOZ3VnqBlqj4UDEa/2rxHY5N1Kz7Vp3OLPDWTfQGksqAADAcnzCgYjHhkydO9uudYczu7PUDbRGw4GIx4ZM9sm2a93hzA5n3UBrLKkAAADL0XAAAADL0XAAAADL0XAAAADLcdNoAG63WzExMSHL6+gmPWSHNrsrbMhkp2y71h3ObLvW3VFkhzbb6/UGNd5hjDEW1WI7LpdLTqdTRUVFIW04AACwo8bGRpWXl6uurk5JSUkXHcuSCgAAsBxLKgEUFBQoJSUlZHkd3aSH7NBmd4UNmeyUbde6w5lt17o7iuzQZnu9XlVUVLR7PA1HAPHx8WHb6Cacm+yQbZ9zIzXbrnWHM9uudXcU2dbzeDxBjWdJBQAAWI6GAwAAWI6GAwAAWI6GAwAAWI6GAwAAWI5vqSDisQNk5862a93hzO4sdQOt0XAg4rV8f91O50Zqtl3rDmd2OOsGWmNJBQAAWI5POBDx2AGyc2fbte5wZneWuoHWaDgQ8dgB0j7Zdq07nNnhrBtojSUVAABgORoOAABgORoOAABgORoOAABgOW4aDcDtdismJiZkeR3dpIfs0GZ3hQ2Z7JRt17rDmW3XujuK7NBme73eoMY7jDHGolpsx+Vyyel0qqioKKQNBwAAdtTY2Kjy8nLV1dUpKSnpomNZUgEAAJZjSSWAgoICpaSkhCyvo5v0kB3a7K6wIZOdsu1adziz7Vp3R5Ed2myv16uKiop2j6fhCCA+Pj5sG92Ec5Mdsu1zbqRm27XucGbbte6OItt6Ho8nqPEsqQAAAMvRcAAAAMvRcAAAAMvRcAAAAMtx0ygiHhsyde5su9YdzuzOUjfQGg0HIl7L18nsdG6kZtu17nBmh7NuoDWWVAAAgOWC/oRj165d+u1vf6s9e/boxIkT2rBhgyZPnnzB8evXr9fy5ctVU1OjpqYmXX/99SopKdGECRP8xpSVlenQoUPyer0aPHiwHnroId17772+MSUlJVq4cKHfa/fu3VsnT570PZ4xY4YqKyv9xowaNUrvvPNOsNNEBGFDps6dbde6w5ndWeoGWgu64XC73Ro+fLhmzpypKVOmXHL8rl27lJubq7KyMvXs2VMrV67UpEmT9O677yorK0uSlJycrAULFmjo0KHq0aOHtmzZopkzZyo1NdWvMbn++uv1xhtv+B5HRUW1ybv99tu1cuVK3+MePXoEO0VEGDZksk+2XesOZ3Y46wZaC7rhyMvLU15eXrvHL1u2zO9xWVmZNm3apM2bN/sajuzsbL8x8+bNU2VlpXbv3u3XcHTv3l19+vS5aF50dPQlxwAAgNAK+T0czc3NOnv2rJKTkwMeN8Zo+/bt2r9/v2699Va/YwcPHlR6eroGDhyof/iHf9Dhw4fbnL9jxw6lpqZqyJAhuv/++3Xq1KkL1tLU1CSXy+X3BwAArryQNxxLly6V2+3WtGnT/J6vq6tTQkKCevTooYkTJ+r3v/+9cnNzfcdHjRqlqqoqvfbaa/rjH/+okydP6qabbtLXX3/tG5OXl6cXXnhBb775ppYuXar3339fP/zhD9XU1BSwlkWLFsnpdPr++vXrZ82kAQCIcCH9Wmx1dbVKSkq0adMmpaam+h1LTExUTU2N6uvrtX37ds2fP1+DBg3yLbe0XsYZNmyYxowZo8zMTFVWVmr+/PmSpLvvvts35oYbbtDIkSOVkZGhV155RXfddVebeoqLi33nSpLL5aLpAADAAiFrONauXavZs2dr3bp1uu2229oc79atm6699lpJ0ogRI7Rv3z4tWrSozf0dLeLj4zVs2DAdPHjwgplpaWnKyMi44Jjo6GhFR0e3ed7tdismJqYds7oyOrpJD9mhze4KGzLZKduudYcz2651dxTZoc32er1BjXcYY8zlhjkcjkt+LVY6/8nGrFmzVF1dfcmxLWbPnq3PPvtMO3bsCHi8qalJmZmZ+sd//Ef9v//3/wKO+frrr9W3b1+tWLFC06dPv2Smy+WS0+lUUVFRSBsOAADsqLGxUeXl5aqrq1NSUtJFxwb9CUd9fb0OHTrke1xbW6uamholJyerf//+Ki4u1vHjx1VVVSXpfLMxffp0PfXUUxo9erRv34zY2Fg5nU5J5++lGDlypDIzM+XxeLR161ZVVVX5fZf74Ycf1qRJk9S/f3+dOnVKpaWlcrlcys/P99VVUlKiKVOmKC0tTZ9//rkeffRRXX311brzzjuDnSYAALiCgm44PvjgA+Xk5Pget9wDkZ+fr1WrVunEiRM6cuSI7/izzz6rc+fOqbCwUIWFhb7nW8ZL55cw5s6dq2PHjik2NlZDhw7V6tWr/e7JOHbsmH7605/qq6++Uq9evTR69Gi98847ysjIkHR+T469e/eqqqpKZ86cUVpamnJycrR27VolJiYGNceCggKlpKQE+5/msnV0kx6yQ5vdFTZkslO2XesOZ7Zd6+4oskOb7fV6VVFR0e7xQTcc2dnZutgqTEsT0eJCSyKtlZaWqrS09KJjXnzxxYsej42N1WuvvXbJrPaIj48P20Y34dxkh2z7nBup2XatO5zZdq27o8i2nsfjCWo8v6UCAAAsR8MBAAAsR8MBAAAsR8MBAAAsF9KdRoHOiA2ZOne2XesOZ3ZnqRtojYYDEa/1fi92OTdSs+1adzizw1k30BpLKgAAwHJ8woGIx4ZMnTvbrnWHM7uz1A20RsOBiMeGTPbJtmvd4cwOZ91AayypAAAAy9FwAAAAy9FwAAAAy9FwAAAAy9FwAAAAy/EtlQDcbrdiYmJCltfRXQHJDm12V9gB0k7Zdq07nNl2rbujyA5tttfrDWq8wxhjLKrFdlwul5xOp4qKikLacAAAYEeNjY0qLy9XXV2dkpKSLjqWJRUAAGA5llQCKCgoUEpKSsjyOrorINn2yY7EOZPN+4zsrpnt9XpVUVHR7vE0HAHEx8eHbWe9cO7qR3Zk5JIdWdmROGeyQ5Pt8XiCGs+SCgAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBwNBwAAsBy/FhuA2+1WTExMyPIaGhoC/pvsrpcdiXMmO/TZkThnskOf7fV6gxrvMMYYi2qxHZfLJafTqaKiopA2HAAA2FFjY6PKy8tVV1enpKSki45lSQUAAFiOJZUACgoKlJKSErK8hoYGLV++XJI0Z84cxcXFkd1FsyNxzmTzPiO7a2Z7vV5VVFS0ezwNRwDx8fFKSEgIS3ZcXBzZEZIdiXMmm/cZ2V0n2+PxBDWeJRUAAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGC5oH+efteuXfrtb3+rPXv26MSJE9qwYYMmT558wfHr16/X8uXLVVNTo6amJl1//fUqKSnRhAkT/MaUlZXp0KFD8nq9Gjx4sB566CHde++9vjElJSVauHCh32v37t1bJ0+e9D02xmjhwoVasWKFTp8+rVGjRunf/u3fdP311wc1R7fbrZiYmKDO6YiGhoaA/ya762VH4pzJDn12JM6Z7NBne73eoMY7jDEmmBNeffVVvfXWW/r+97+vKVOmXLLhePDBB5Wenq6cnBz17NlTK1eu1JIlS/Tuu+8qKytLkrRjxw6dPn1aQ4cOVY8ePbRlyxY99NBDeuWVV3yNSUlJif7zP/9Tb7zxhu+1o6Ki1KtXL9/jxYsX6ze/+Y1WrVqlIUOGqLS0VLt27dL+/fuVmJh4ybm5XC45nU4VFRWFtOEAAMCOGhsbVV5errq6OiUlJV10bNCfcOTl5SkvL6/d45ctW+b3uKysTJs2bdLmzZt9DUd2drbfmHnz5qmyslK7d+/2+ySke/fu6tOnT8AcY4yWLVumBQsW6K677pIkVVZWqnfv3lqzZo1+8YtftLtmAABwZQXdcHRUc3Ozzp49q+Tk5IDHjTF68803tX//fi1evNjv2MGDB5Wenq7o6GiNGjVKZWVlGjRokCSptrZWJ0+e1Pjx433jo6OjNW7cOL399tsBG46mpiY1NTX5HrtcLklSQUGBUlJSOjzX9mpoaNDy5cslSXPmzFFcXBzZXTQ7EudMNu8zsrtmttfrVUVFRbvHh7zhWLp0qdxut6ZNm+b3fF1dnfr27aumpiZFRUXpmWeeUW5uru/4qFGjVFVVpSFDhugvf/mLSktLddNNN+nTTz9VSkqK716O3r17+71u79699cUXXwSsZdGiRW3uC5Gk+Ph4JSQkdHSqlyUuLo7sCMmOxDmTzfuM7K6T7fF4ghof0oajurpaJSUl2rRpk1JTU/2OJSYmqqamRvX19dq+fbvmz5+vQYMG+ZZbWi/jDBs2TGPGjFFmZqYqKys1f/583zGHw+H3usaYNs+1KC4u9jvX5XKpX79+HZ0mAAD4P0LWcKxdu1azZ8/WunXrdNttt7U53q1bN1177bWSpBEjRmjfvn1atGhRm/s7WsTHx2vYsGE6ePCgJPnu7Th58qTS0tJ8406dOtXmU48W0dHRio6O7si0AABAO4RkH47q6mrNmDFDa9as0cSJE9t1jjHG7/6K/6upqUn79u3zNRcDBw5Unz599Prrr/vGeDwe7dy5UzfddFPHJgAAADok6E846uvrdejQId/j2tpa1dTUKDk5Wf3791dxcbGOHz+uqqoqSeebjenTp+upp57S6NGjffdaxMbGyul0Sjp/L8XIkSOVmZkpj8ejrVu3qqqqyncTjCQ9/PDDmjRpkvr3769Tp06ptLRULpdL+fn5ks4vpTz44IMqKyvT4MGDNXjwYJWVlSkuLk4/+9nPLv+/EAAA6LCgG44PPvhAOTk5vsct90Dk5+dr1apVOnHihI4cOeI7/uyzz+rcuXMqLCxUYWGh7/mW8dL5jbbmzp2rY8eOKTY2VkOHDtXq1at19913+8YfO3ZMP/3pT/XVV1+pV69eGj16tN555x1lZGT4xjzyyCP65ptvNHfuXN/GX9u2bWvXHhwAAMA6QTcc2dnZutheYS1NRIsdO3Zc8jVLS0tVWlp60TEvvvjiJV/H4XCopKREJSUllxwLAABCh99SAQAAlqPhAAAAlqPhAAAAlqPhAAAAlqPhAAAAlqPhAAAAlqPhAAAAlgv5r8XagdvtVkxMTMjyGhoaAv6b7K6XHYlzJjv02ZE4Z7JDn+31eoMa7zAX28UrwrhcLjmdThUVFYW04QAAwI4aGxtVXl6uuro6JSUlXXQsSyoAAMByLKkEUFBQoJSUlJDlNTQ0+H6obs6cOYqLiyO7i2ZH4pzJ5n1GdtfM9nq9qqioaPd4Go4A4uPjlZCQEJbsuLg4siMkOxLnTDbvM7K7TrbH4wlqPEsqAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcjQcAADAcvw8fQBut1sxMTEhy2toaAj4b7K7XnYkzpns0GdH4pzJDn221+sNarzDGGMsqsV2XC6XnE6nioqKQtpwAABgR42NjSovL1ddXZ2SkpIuOpYlFQAAYDmWVAIoKChQSkpKyPIaGhq0fPlySdKcOXMUFxdHdhfNjsQ5k837jOyume31elVRUdHu8TQcAcTHxyshISEs2XFxcWRHSHYkzpls3mdkd51sj8cT1HiWVAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOVoOAAAgOX4tdgAPB5P0L+C1xFer9fv32R33exInDPZoc+OxDmTHfrsYHMcxhhjUS22U1dXp549e+pXv/qVoqOjw10OAACdWlNTk373u9/pzJkzcjqdFx1Lw9HKsWPH1K9fv3CXAQCArRw9elTXXHPNRcfQcLTS3NysL7/8UomJiXI4HOEupw2Xy6V+/frp6NGjSkpKCnc5IROJ847EOUvMO5LmHYlzlrrevI0xOnv2rNLT09Wt28VvC+Uejla6det2yQ6tM0hKSuoSb9RgReK8I3HOEvOOJJE4Z6lrzftSSykt+JYKAACwHA0HAACwHA2HjURHR+vxxx+PuG/QROK8I3HOEvOOpHlH4pylyJ23xE2jAAAgBPiEAwAAWI6GAwAAWI6GAwAAWI6GAwAAWI6GwwKLFi3SjTfeqMTERKWmpmry5Mnav3//Rc/ZvXu3xo4dq5SUFMXGxmro0KH63e9+d8HxL774ohwOhyZPntzm2PHjx3XPPfcoJSVFcXFxGjFihPbs2eM7boxRSUmJ0tPTFRsbq+zsbH366aeXPV+p8895xowZcjgcfn+jR4++7Pm2COe8BwwY0GZODodDhYWFvjFWXGup88/biusdzjmfO3dOjz32mAYOHKjY2FgNGjRITzzxhJqbm31juuK1bs+8u9q1Pnv2rB588EFlZGQoNjZWN910k95//32/MVZda8sZXHETJkwwK1euNJ988ompqakxEydONP379zf19fUXPOfDDz80a9asMZ988ompra01zz//vImLizPPPvtsm7Gff/656du3r7nlllvMj3/8Y79jf/vb30xGRoaZMWOGeffdd01tba154403zKFDh3xjysvLTWJionnppZfM3r17zd13323S0tKMy+XqsnPOz883t99+uzlx4oTv7+uvv77s+XaGeZ86dcpvPq+//rqRZP70pz/5xlhxre0wbyuudzjnXFpaalJSUsyWLVtMbW2tWbdunUlISDDLli3zjemK17o98+5q13ratGnmu9/9rtm5c6c5ePCgefzxx01SUpI5duyYb4xV19pqNBwhcOrUKSPJ7Ny5M6jz7rzzTnPPPff4PXfu3DkzduxY8+///u8mPz+/zZv117/+tbn55psv+JrNzc2mT58+pry83PdcY2OjcTqd5g9/+ENQ9V1MZ5qzMSbgeVYI5bz/r3nz5pnMzEzT3NxsjAndtTamc83bmNBc71DOeeLEiWbWrFl+z911112+1+mq1/pS8zama13rhoYGExUVZbZs2eJ3zvDhw82CBQuMMaG91lcaSyohUFdXJ0lKTk5u9zkfffSR3n77bY0bN87v+SeeeEK9evXS7NmzA5738ssva+TIkZo6dapSU1OVlZWlP/7xj77jtbW1OnnypMaPH+97Ljo6WuPGjdPbb78dzLQuqjPNucWOHTuUmpqqIUOG6P7779epU6eCmFH7hHLerXk8Hq1evVqzZs3y/fBgqK611Lnm3cLq6x3KOd98883avn27Dhw4IEn67//+b+3evVt33HGHpK57rS817xZd5VqfO3dO3377rWJiYvyej42N1e7duyWF9lpfceHueLq65uZmM2nSpEv+f+At+vbta3r06GG6detmnnjiCb9ju3fvNn379jV//etfjTGBO/vo6GgTHR1tiouLzYcffmj+8Ic/mJiYGFNZWWmMMeatt94ykszx48f9zrv//vvN+PHjL3OW/jrbnI0x5sUXXzRbtmwxe/fuNS+//LIZPny4uf76601jY2PHJttKqOfd2tq1a01UVJTfdQ3FtTam883bGOuvd6jn3NzcbIqKiozD4TDdu3c3DofDlJWV+Y531Wt9qXkb0/Wu9ZgxY8y4cePM8ePHzblz58zzzz9vHA6HGTJkiDEmdNfaCjQcFps7d67JyMgwR48ebdf4w4cPm48//tisWLHCJCcnmzVr1hhjjHG5XGbAgAFm69atvrGB3qxXXXWVGTNmjN9zDzzwgBk9erQx5v9/s3755Zd+Y+677z4zYcKEYKcXUGebcyBffvmlueqqq8xLL73UzlldWqjn3dr48ePNj370I7/nQnGtjel88w7kSl/vUM+5urraXHPNNaa6utp8/PHHpqqqyiQnJ5tVq1YZY7rutb7UvAOx+7U+dOiQufXWW40kExUVZW688Ubz85//3Fx33XXGmNBdayvQcFjon/7pn8w111xjDh8+fFnn/8u//Iuvq/3oo498b8CWP4fDYRwOh4mKivLdINm/f38ze/Zsv9d55plnTHp6ujHGmM8++8xIMh9++KHfmL//+78306dPv6w6W+uMc76Qa6+91m8dtCPCMe8Wn3/+uenWrZvZuHGj3/NWX2tjOue8L+RKXe9wzPmaa64xTz/9dJvX+c53vmOM6brX+lLzvhA7X+sW9fX1vqZi2rRp5o477jDGhOZaW6V7aBdwIoMxRg888IA2bNigHTt2aODAgZf9Ok1NTZKkoUOHau/evX7HH3vsMZ09e1ZPPfWU+vXrJ0kaO3Zsm69vHThwQBkZGZKkgQMHqk+fPnr99deVlZUl6fw6+M6dO7V48eLLqrOl1s4650C+/vprHT16VGlpaZdVZ+t6wzXvFitXrlRqaqomTpzo97xV17ql3s4670CuxPUO55wbGhrUrZv/LXdRUVG+r4d21Wt9qXkHYvdr3SI+Pl7x8fE6ffq0XnvtNVVUVEiy9lpbLhxdTlc3Z84c43Q6zY4dO/y+qtXQ0OAbU1RUZO69917f46efftq8/PLL5sCBA+bAgQPmP/7jP0xSUpLvzuRAAn0c995775nu3bub3/zmN+bgwYPmhRdeMHFxcWb16tW+MeXl5cbpdJr169ebvXv3mp/+9Kcd/kpVZ57z2bNnzUMPPWTefvttU1tba/70pz+ZMWPGmL59+3b4a2ThnLcxxnz77bemf//+5te//nXA86y41sZ07nlbdb3DOef8/HzTt29f39dD169fb66++mrzyCOP+MZ0xWt9qXl3xWv9X//1X+bVV181hw8fNtu2bTPDhw83f/d3f2c8Ho9vjFXX2mo0HBaQFPBv5cqVvjH5+flm3Lhxvsf/+q//aq6//noTFxdnkpKSTFZWlnnmmWfMt99+e8GcC/2P8ebNm80NN9xgoqOjzdChQ82KFSv8jjc3N5vHH3/c9OnTx0RHR5tbb73V7N27t8vOuaGhwYwfP9706tXLXHXVVaZ///4mPz/fHDlypENz7gzzfu2114wks3///oDnWXGtjenc87bqeodzzi6Xy8ybN8/079/fxMTEmEGDBpkFCxaYpqYm35iueK0vNe+ueK3Xrl1rBg0aZHr06GH69OljCgsLzZkzZ/zGWHWtrcbP0wMAAMuxDwcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAALAcDQcAAF3Yrl27NGnSJKWnp8vhcGjjxo1Bv4YxRkuWLNGQIUMUHR2tfv36qaysLKjX4MfbAADowtxut4YPH66ZM2dqypQpl/Ua8+bN07Zt27RkyRINGzZMdXV1+uqrr4J6DbY2BwAgQjgcDm3YsEGTJ0/2PefxePTYY4/phRde0JkzZ3TDDTdo8eLFys7OliTt27dP3/ve9/TJJ5/oO9/5zmVns6QCAEAEmzlzpt566y29+OKL+vjjjzV16lTdfvvtOnjwoCRp8+bNGjRokLZs2aKBAwdqwIABuu+++/S3v/0tqBwaDgAAItRnn32m6upqrVu3TrfccosyMzP18MMP6+abb9bKlSslSYcPH9YXX3yhdevWqaqqSqtWrdKePXv0k5/8JKgs7uEAACBCffjhhzLGaMiQIX7PNzU1KSUlRZLU3NyspqYmVVVV+cY999xz+sEPfqD9+/e3e5mFhgMAgAjV3NysqKgo7dmzR1FRUX7HEhISJElpaWnq3r27X1Ny3XXXSZKOHDlCwwEAAC4uKytL3377rU6dOqVbbrkl4JixY8fq3Llz+uyzz5SZmSlJOnDggCQpIyOj3Vl8SwUAgC6svr5ehw4dknS+wXjyySeVk5Oj5ORk9e/fX/fcc4/eeustLV26VFlZWfrqq6/05ptvatiwYbrjjjvU3NysG2+8UQkJCVq2bJmam5tVWFiopKQkbdu2rd110HAAANCF7dixQzk5OW2ez8/P16pVq+T1elVaWqqqqiodP35cKSkpGjNmjBYuXKhhw4ZJkr788ks98MAD2rZtm+Lj45WXl6elS5cqOTm53XXQcAAAAMvxtVgAAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGA5Gg4AAGC5/w//lZjj29Ho0AAAAABJRU5ErkJggg==", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "gridprops = g.get_gridprops_vertexgrid()\n", "vertexgrid = flopy.discretization.VertexGrid(**gridprops)\n", @@ -724,21 +417,10 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "7a02615f", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(1, 510)" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "shape = vertexgrid.shape\n", "shape" @@ -776,22 +458,10 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "b6571b07", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(xll:0.0; yll:0.0; rotation:0.0; units:undefined; lenuni:0,\n", - " flopy.discretization.unstructuredgrid.UnstructuredGrid)" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "gridprops = g.get_gridprops_unstructuredgrid()\n", "\n", @@ -801,42 +471,20 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "afe46f93", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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", 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Use public APIs instead.\n", - " warnings.warn(\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "basin.plot()" ] @@ -1091,28 +562,10 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "26693e3c", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " minx miny maxx maxy\n", - "identifier \n", - "10343500 214358.622076 4.366733e+06 221497.557955 4.373287e+06\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n" - ] - } - ], + "outputs": [], "source": [ "cellsize = 90 # 90 m grid\n", "bounds = basin.bounds\n", @@ -1133,7 +586,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": null, "id": "e7de4cad", "metadata": {}, "outputs": [], @@ -1162,19 +615,10 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": null, "id": "c796e3f3", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "xll:214268.62207605224; yll:4366643.474127463; rotation:0.0; crs:EPSG:26911; units:undefined; lenuni:0\n", - "False\n" - ] - } - ], + "outputs": [], "source": [ "modelgrid = flopy.discretization.StructuredGrid(\n", " delc,\n", @@ -1192,41 +636,10 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": null, "id": "f98ef0fd", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", - " warnings.warn(\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(8, 8))\n", "\n", @@ -1256,30 +669,10 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": null, "id": "a8c64285", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n" - ] - }, - { - "data": { - "text/plain": [ - "array([(1, 52), (1, 53), (1, 54), ..., (73, 64), (73, 65), (73, 66)],\n", - " dtype=object)" - ] - }, - "execution_count": 27, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "gx = GridIntersect(modelgrid)\n", "\n", @@ -1297,31 +690,10 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "b9a4efb3", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 28, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ibound = np.zeros((nlay, nrow, ncol))\n", "i, j = zip(*result.cellids)\n", @@ -1347,7 +719,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "id": "9be5182b", "metadata": {}, "outputs": [], @@ -1369,33 +741,10 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "3e6057f8", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[2288.88427734, 2273.79296875, 2263.59692383, ..., 2035.27868652,\n", - " 2020.77258301, 2011.82592773],\n", - " [2308.66918945, 2301.82080078, 2284.20483398, ..., 2037.7668457 ,\n", - " 2022.42944336, 2011.48937988],\n", - " [2326.71118164, 2321.3112793 , 2301.70703125, ..., 2042.32263184,\n", - " 2025.94592285, 2015.38793945],\n", - " ...,\n", - " [2207.31152344, 2229.87426758, 2239.453125 , ..., 2112.20751953,\n", - " 2095.49414062, 2073.16308594],\n", - " [2176.74121094, 2186.13769531, 2201.04858398, ..., 2095.2331543 ,\n", - " 2074.06396484, 2051.18530273],\n", - " [2156.98022461, 2157.87744141, 2164.14770508, ..., 2077.35131836,\n", - " 2053.95043945, 2035.44116211]])" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# let's get the nearest neighbor elevations\n", "dem_data = raster.resample_to_grid(\n", @@ -1408,21 +757,10 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "id": "ec16505d", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Now let's plot it up and see what we have\n", "fig, ax = plt.subplots(figsize=(10, 8)) \n", @@ -1454,7 +792,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "a68ba62a", "metadata": {}, "outputs": [], @@ -1482,35 +820,10 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": null, "id": "0953b65d", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "name = sagehen\n", - "model_type = gwf6\n", - "version = mf6\n", - "model_relative_path = .\n", - "\n", - "###################\n", - "Package dis\n", - "###################\n", - "\n", - "package_name = dis\n", - "filename = sagehen.dis\n", - "package_type = dis\n", - "model_or_simulation_package = model\n", - "model_name = sagehen\n", - "\n" - ] - }, - "execution_count": 33, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "gwf = flopy.mf6.ModflowGwf(\n", " sim,\n", @@ -1544,46 +857,10 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "id": "29159be8", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "name = sagehen\n", - "model_type = gwf6\n", - "version = mf6\n", - "model_relative_path = .\n", - "\n", - "###################\n", - "Package dis\n", - "###################\n", - "\n", - "package_name = dis\n", - "filename = sagehen.dis\n", - "package_type = dis\n", - "model_or_simulation_package = model\n", - "model_name = sagehen\n", - "\n", - "\n", - "###################\n", - "Package ic\n", - "###################\n", - "\n", - "package_name = ic\n", - "filename = sagehen.ic\n", - "package_type = ic\n", - "model_or_simulation_package = model\n", - "model_name = sagehen\n", - "\n" - ] - }, - "execution_count": 34, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "ic = flopy.mf6.ModflowGwfic(gwf, strt=dem_data - 5)\n", "gwf" @@ -1599,7 +876,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "id": "d44c69ce", "metadata": {}, "outputs": [], @@ -1630,7 +907,7 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "id": "4385aa9d", "metadata": {}, "outputs": [], @@ -1667,7 +944,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "id": "e97525f0", "metadata": {}, "outputs": [], @@ -1694,176 +971,10 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "7469763b", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{0: array([[0.89827865, 0.89827865, 0.89827865, ..., 1.00581992, 1.00581992,\n", - " 1.00581992],\n", - " [0.89827865, 0.89827865, 0.89827865, ..., 1.00581992, 1.00581992,\n", - " 1.00581992],\n", - " [0.89827865, 0.89827865, 0.89827865, ..., 1.00581992, 1.00581992,\n", - " 1.00581992],\n", - " ...,\n", - " [0. , 0. , 0. , ..., 1.01081669, 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0.90833336],\n", - " ...,\n", - " [0. , 0. , 0. , ..., 1.10366654, 1.10366654,\n", - " 1.10366654],\n", - " [0. , 0. , 0. , ..., 1.10366654, 1.10366654,\n", - " 1.10366654],\n", - " [0. , 0. , 0. , ..., 1.10366654, 1.10366654,\n", - " 1.10366654]]),\n", - " 11: array([[11.07774162, 11.07774162, 11.07774162, ..., 9.146451 ,\n", - " 9.146451 , 9.146451 ],\n", - " [11.07774162, 11.07774162, 11.07774162, ..., 9.146451 ,\n", - " 9.146451 , 9.146451 ],\n", - " [11.07774162, 11.07774162, 11.07774162, ..., 9.146451 ,\n", - " 9.146451 , 9.146451 ],\n", - " ...,\n", - " [ 0. , 0. , 0. , ..., 10.41838837,\n", - " 10.41838837, 10.41838837],\n", - " [ 0. , 0. , 0. , ..., 10.41838837,\n", - " 10.41838837, 10.41838837],\n", - " [ 0. , 0. , 0. , ..., 10.41838837,\n", - " 10.41838837, 10.41838837]])}" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "rstr = flopy.utils.Raster.load(prcp_raster)\n", "prcp_monthly = {}\n", @@ -2076,7 +1021,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "5556e58f", "metadata": {}, "outputs": [], @@ -2095,21 +1040,10 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "id": "c6310044", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "ksat_raster = data_path / \"ksat.img\"\n", "rstr = flopy.utils.Raster.load(ksat_raster)\n", @@ -2140,7 +1074,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "id": "6283510f", "metadata": {}, "outputs": [], @@ -2174,7 +1108,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": null, "id": "d14f6df9", "metadata": {}, "outputs": [], @@ -2212,45 +1146,10 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "id": "513512bb", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", - " warnings.warn(\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", - " srs = pd.Series(*args, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n", - "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", - " super().__init__(data, index=index, name=name, **kwargs)\n" - ] - }, - { - "data": { - "image/png": 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" - ], - "text/plain": [ - " nhdplus_co geometry\n", - "0 8933522 LINESTRING (221038.128 4369598.916, 221076.482...\n", - "1 8933524 LINESTRING (220540.741 4369697.577, 220691.351...\n", - "2 8933520 LINESTRING (220240.365 4369758.860, 220244.995...\n", - "3 8934344 LINESTRING (219769.843 4369876.335, 219795.329...\n", - "4 8933512 LINESTRING (219321.052 4369977.090, 219357.890...\n", - "5 8933508 LINESTRING (218509.989 4370180.464, 218578.637...\n", - "6 8933496 LINESTRING (217726.838 4370179.373, 217746.044...\n", - "7 8933582 LINESTRING (215175.791 4368533.473, 215195.962..." - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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stage00065_cdsite_no
datetime
2023-01-01 08:00:00+00:000.748752A10343500
2023-01-01 08:15:00+00:000.748752A10343500
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2023-01-01 09:00:00+00:000.748752A10343500
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" - ], - "text/plain": [ - " stage 00065_cd site_no\n", - "datetime \n", - "2023-01-01 08:00:00+00:00 0.748752 A 10343500\n", - "2023-01-01 08:15:00+00:00 0.748752 A 10343500\n", - "2023-01-01 08:30:00+00:00 0.748752 A 10343500\n", - "2023-01-01 08:45:00+00:00 0.748752 A 10343500\n", - "2023-01-01 09:00:00+00:00 0.748752 A 10343500" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "gage = pd.read_csv(data_path / \"sagehen_gage_data.csv\")\n", "gage[\"datetime\"] = pd.to_datetime(gage[\"datetime\"])\n", @@ -2628,21 +1295,10 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": null, "id": "4ed1d203", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "gage[\"month\"] = gage.index.month\n", "gage_mmo = gage.groupby(by=[\"month\"], as_index=False)[\"stage\"].mean()\n", @@ -2660,25 +1316,10 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": null, "id": "d0d82e1f", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "[((0, 42, 75), 1936.8217418655074, 10, 1936.2347412109375),\n", - " ((0, 42, 76), 1935.65633659207, 10, 1935.0693359375),\n", - " ((0, 41, 76), 1932.400721357695, 10, 1931.813720703125),\n", - " ((0, 41, 77), 1930.8251598342574, 10, 1930.2381591796875),\n", - " ((0, 41, 78), 1928.34823112332, 10, 1927.76123046875)]" - ] - }, - "execution_count": 51, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "cond = 10\n", "rbadj = 1\n", @@ -2705,7 +1346,7 @@ }, { "cell_type": "code", - "execution_count": 52, + "execution_count": null, "id": "cadccc45", "metadata": {}, "outputs": [], @@ -2728,429 +1369,10 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "id": "fb26d180", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "writing simulation...\n", - " writing simulation name file...\n", - " writing simulation tdis package...\n", - " writing solution package ims_-1...\n", - " writing model sagehen...\n", - " writing model name file...\n", - " writing package dis...\n", - " writing package ic...\n", - " writing package npf...\n", - " writing package sto...\n", - " writing package oc...\n", - " writing package uzf_0...\n", - "INFORMATION: nuzfcells in ('gwf6', 'uzf', 'dimensions') changed to 3587 based on size of packagedata\n", - " writing package riv_0...\n", - "FloPy is using the following executable to run the model: ../../../../../../software/modflow_exes/mf6\n", - " MODFLOW 6\n", - " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", - " VERSION 6.4.2 06/28/2023\n", - "\n", - " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", - " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", - " Build 20220726_000000\n", - "\n", - "This software has been approved for release by the U.S. Geological \n", - "Survey (USGS). Although the software has been subjected to rigorous \n", - "review, the USGS reserves the right to update the software as needed \n", - "pursuant to further analysis and review. No warranty, expressed or \n", - "implied, is made by the USGS or the U.S. Government as to the \n", - "functionality of the software and related material nor shall the \n", - "fact of release constitute any such warranty. Furthermore, the \n", - "software is released on condition that neither the USGS nor the U.S. \n", - "Government shall be held liable for any damages resulting from its \n", - "authorized or unauthorized use. Also refer to the USGS Water \n", - "Resources Software User Rights Notice for complete use, copyright, \n", - "and distribution information.\n", - "\n", - " \n", - " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/03 10:15:09\n", - " \n", - " Writing simulation list file: mfsim.lst\n", - " Using Simulation name file: mfsim.nam\n", - " \n", - " Solving: Stress period: 1 Time step: 1\n", - " Solving: Stress period: 1 Time step: 2\n", - " Solving: Stress period: 1 Time step: 3\n", - " Solving: Stress period: 1 Time step: 4\n", - " Solving: Stress period: 1 Time step: 5\n", - " Solving: Stress period: 1 Time step: 6\n", - " Solving: Stress period: 1 Time step: 7\n", - " Solving: Stress period: 1 Time step: 8\n", - " Solving: Stress period: 1 Time step: 9\n", - " Solving: Stress period: 1 Time step: 10\n", - " Solving: Stress period: 1 Time step: 11\n", - " Solving: Stress period: 1 Time step: 12\n", - " Solving: Stress period: 1 Time step: 13\n", - " Solving: Stress period: 1 Time step: 14\n", - " Solving: Stress period: 1 Time step: 15\n", - " Solving: Stress period: 1 Time step: 16\n", - " Solving: Stress period: 1 Time step: 17\n", - " Solving: Stress period: 1 Time step: 18\n", - " Solving: Stress period: 1 Time step: 19\n", - " Solving: Stress period: 1 Time step: 20\n", - " Solving: Stress period: 1 Time step: 21\n", - " Solving: Stress period: 1 Time step: 22\n", - " Solving: Stress period: 1 Time step: 23\n", - " Solving: Stress period: 1 Time step: 24\n", - " Solving: Stress period: 1 Time step: 25\n", - " Solving: Stress period: 1 Time step: 26\n", - " Solving: Stress period: 1 Time step: 27\n", - " Solving: Stress period: 1 Time step: 28\n", - " Solving: Stress period: 1 Time step: 29\n", - " Solving: Stress period: 1 Time step: 30\n", - " Solving: Stress period: 1 Time step: 31\n", - " Solving: Stress period: 2 Time step: 1\n", - " Solving: Stress period: 2 Time step: 2\n", - " Solving: Stress period: 2 Time step: 3\n", - " Solving: Stress period: 2 Time step: 4\n", - " Solving: Stress period: 2 Time step: 5\n", - " Solving: Stress period: 2 Time step: 6\n", - " Solving: Stress period: 2 Time step: 7\n", - " Solving: Stress period: 2 Time step: 8\n", - " Solving: Stress period: 2 Time step: 9\n", - " Solving: Stress period: 2 Time step: 10\n", - " Solving: Stress period: 2 Time step: 11\n", - " Solving: Stress period: 2 Time step: 12\n", - " Solving: Stress period: 2 Time step: 13\n", - " Solving: Stress period: 2 Time step: 14\n", - " Solving: Stress period: 2 Time step: 15\n", - " Solving: Stress period: 2 Time step: 16\n", - " Solving: Stress period: 2 Time step: 17\n", - " Solving: Stress period: 2 Time step: 18\n", - " Solving: Stress period: 2 Time step: 19\n", - " Solving: Stress period: 2 Time step: 20\n", - " Solving: Stress period: 2 Time step: 21\n", - " Solving: Stress period: 2 Time step: 22\n", - " Solving: Stress period: 2 Time step: 23\n", - " Solving: Stress period: 2 Time step: 24\n", - " Solving: Stress period: 2 Time step: 25\n", - " Solving: Stress period: 2 Time step: 26\n", - " Solving: Stress period: 2 Time step: 27\n", - " Solving: Stress period: 2 Time step: 28\n", - " Solving: Stress period: 3 Time step: 1\n", - " Solving: Stress period: 3 Time step: 2\n", - " Solving: Stress period: 3 Time step: 3\n", - " Solving: Stress period: 3 Time step: 4\n", - " Solving: Stress period: 3 Time step: 5\n", - " Solving: Stress period: 3 Time step: 6\n", - " Solving: Stress period: 3 Time step: 7\n", - " Solving: Stress period: 3 Time step: 8\n", - " Solving: Stress period: 3 Time step: 9\n", - " Solving: Stress period: 3 Time step: 10\n", - " Solving: Stress period: 3 Time step: 11\n", - " Solving: Stress period: 3 Time step: 12\n", - " Solving: Stress period: 3 Time step: 13\n", - " Solving: Stress period: 3 Time step: 14\n", - " Solving: Stress period: 3 Time step: 15\n", - " Solving: Stress period: 3 Time step: 16\n", - " Solving: Stress period: 3 Time step: 17\n", - " Solving: Stress period: 3 Time step: 18\n", - " Solving: Stress period: 3 Time step: 19\n", - " Solving: Stress period: 3 Time step: 20\n", - " Solving: Stress period: 3 Time step: 21\n", - " Solving: Stress period: 3 Time step: 22\n", - " Solving: Stress period: 3 Time step: 23\n", - " Solving: Stress period: 3 Time step: 24\n", - " Solving: Stress period: 3 Time step: 25\n", - " Solving: Stress period: 3 Time step: 26\n", - " Solving: Stress period: 3 Time step: 27\n", - " Solving: Stress period: 3 Time step: 28\n", - " Solving: Stress period: 3 Time step: 29\n", - " Solving: Stress period: 3 Time step: 30\n", - " Solving: Stress period: 3 Time step: 31\n", - " Solving: Stress period: 4 Time step: 1\n", - " Solving: Stress period: 4 Time step: 2\n", - " Solving: Stress period: 4 Time step: 3\n", - " Solving: Stress period: 4 Time step: 4\n", - " Solving: Stress period: 4 Time step: 5\n", - " Solving: Stress period: 4 Time step: 6\n", - " Solving: Stress period: 4 Time step: 7\n", - " Solving: Stress period: 4 Time step: 8\n", - " Solving: Stress period: 4 Time step: 9\n", - " Solving: Stress period: 4 Time step: 10\n", - " Solving: Stress period: 4 Time step: 11\n", - " Solving: Stress period: 4 Time step: 12\n", - " Solving: Stress period: 4 Time step: 13\n", - " Solving: Stress period: 4 Time step: 14\n", - " Solving: Stress period: 4 Time step: 15\n", - " Solving: Stress period: 4 Time step: 16\n", - " Solving: Stress period: 4 Time step: 17\n", - " Solving: Stress period: 4 Time step: 18\n", - " Solving: Stress period: 4 Time step: 19\n", - " Solving: Stress period: 4 Time step: 20\n", - " Solving: Stress period: 4 Time step: 21\n", - " Solving: Stress period: 4 Time step: 22\n", - " Solving: Stress period: 4 Time step: 23\n", - " Solving: Stress period: 4 Time step: 24\n", - " Solving: Stress period: 4 Time step: 25\n", - " Solving: Stress period: 4 Time step: 26\n", - " Solving: Stress period: 4 Time step: 27\n", - " Solving: Stress period: 4 Time step: 28\n", - " Solving: Stress period: 4 Time step: 29\n", - " Solving: Stress period: 4 Time step: 30\n", - " Solving: Stress period: 5 Time step: 1\n", - " Solving: Stress period: 5 Time step: 2\n", - " Solving: Stress period: 5 Time step: 3\n", - " Solving: Stress period: 5 Time step: 4\n", - " Solving: Stress period: 5 Time step: 5\n", - " Solving: Stress period: 5 Time step: 6\n", - " Solving: Stress period: 5 Time step: 7\n", - " Solving: Stress period: 5 Time step: 8\n", - " Solving: Stress period: 5 Time step: 9\n", - " Solving: Stress period: 5 Time step: 10\n", - " Solving: Stress period: 5 Time step: 11\n", - " Solving: Stress period: 5 Time step: 12\n", - " Solving: Stress period: 5 Time step: 13\n", - " Solving: Stress period: 5 Time step: 14\n", - " Solving: Stress period: 5 Time step: 15\n", - " Solving: Stress period: 5 Time step: 16\n", - " Solving: Stress period: 5 Time step: 17\n", - " Solving: Stress period: 5 Time step: 18\n", - " Solving: Stress period: 5 Time step: 19\n", - " Solving: Stress period: 5 Time step: 20\n", - " Solving: Stress period: 5 Time step: 21\n", - " Solving: Stress period: 5 Time step: 22\n", - " Solving: Stress period: 5 Time step: 23\n", - " Solving: Stress period: 5 Time step: 24\n", - " Solving: Stress period: 5 Time step: 25\n", - " Solving: Stress period: 5 Time step: 26\n", - " Solving: Stress period: 5 Time step: 27\n", - " Solving: Stress period: 5 Time step: 28\n", - " Solving: Stress period: 5 Time step: 29\n", - " Solving: Stress period: 5 Time step: 30\n", - " Solving: Stress period: 5 Time step: 31\n", - " Solving: Stress period: 6 Time step: 1\n", - " Solving: Stress period: 6 Time step: 2\n", - " Solving: Stress period: 6 Time step: 3\n", - " Solving: Stress period: 6 Time step: 4\n", - " Solving: Stress period: 6 Time step: 5\n", - " Solving: Stress period: 6 Time step: 6\n", - " Solving: Stress period: 6 Time step: 7\n", - " Solving: Stress period: 6 Time step: 8\n", - " Solving: Stress period: 6 Time step: 9\n", - " Solving: Stress period: 6 Time step: 10\n", - " Solving: Stress period: 6 Time step: 11\n", - " Solving: Stress period: 6 Time step: 12\n", - " Solving: Stress period: 6 Time step: 13\n", - " Solving: Stress period: 6 Time step: 14\n", - " Solving: Stress period: 6 Time step: 15\n", - " Solving: Stress period: 6 Time step: 16\n", - " Solving: Stress period: 6 Time step: 17\n", - " Solving: Stress period: 6 Time step: 18\n", - " Solving: Stress period: 6 Time step: 19\n", - " Solving: Stress period: 6 Time step: 20\n", - " Solving: Stress period: 6 Time step: 21\n", - " Solving: Stress period: 6 Time step: 22\n", - " Solving: Stress period: 6 Time step: 23\n", - " Solving: Stress period: 6 Time step: 24\n", - " Solving: Stress period: 6 Time step: 25\n", - " Solving: Stress period: 6 Time step: 26\n", - " Solving: Stress period: 6 Time step: 27\n", - " Solving: Stress period: 6 Time step: 28\n", - " Solving: Stress period: 6 Time step: 29\n", - " Solving: Stress period: 6 Time step: 30\n", - " Solving: Stress period: 7 Time step: 1\n", - " Solving: Stress period: 7 Time step: 2\n", - " Solving: Stress period: 7 Time step: 3\n", - " Solving: Stress period: 7 Time step: 4\n", - " Solving: Stress period: 7 Time step: 5\n", - " Solving: Stress period: 7 Time step: 6\n", - " Solving: Stress period: 7 Time step: 7\n", - " Solving: Stress period: 7 Time step: 8\n", - " Solving: Stress period: 7 Time step: 9\n", - " Solving: Stress period: 7 Time step: 10\n", - " Solving: Stress period: 7 Time step: 11\n", - " Solving: Stress period: 7 Time step: 12\n", - " Solving: Stress period: 7 Time step: 13\n", - " Solving: Stress period: 7 Time step: 14\n", - " Solving: Stress period: 7 Time step: 15\n", - " Solving: Stress period: 7 Time step: 16\n", - " Solving: Stress period: 7 Time step: 17\n", - " Solving: Stress period: 7 Time step: 18\n", - " Solving: Stress period: 7 Time step: 19\n", - " Solving: Stress period: 7 Time step: 20\n", - " Solving: Stress period: 7 Time step: 21\n", - " Solving: Stress period: 7 Time step: 22\n", - " Solving: Stress period: 7 Time step: 23\n", - " Solving: Stress period: 7 Time step: 24\n", - " Solving: Stress period: 7 Time step: 25\n", - " Solving: Stress period: 7 Time step: 26\n", - " Solving: Stress period: 7 Time step: 27\n", - " Solving: Stress period: 7 Time step: 28\n", - " Solving: Stress period: 7 Time step: 29\n", - " Solving: Stress period: 7 Time step: 30\n", - " Solving: Stress period: 7 Time step: 31\n", - " Solving: Stress period: 8 Time step: 1\n", - " Solving: Stress period: 8 Time step: 2\n", - " Solving: Stress period: 8 Time step: 3\n", - " Solving: Stress period: 8 Time step: 4\n", - " Solving: Stress period: 8 Time step: 5\n", - " Solving: Stress period: 8 Time step: 6\n", - " Solving: Stress period: 8 Time step: 7\n", - " Solving: Stress period: 8 Time step: 8\n", - " Solving: Stress period: 8 Time step: 9\n", - " Solving: Stress period: 8 Time step: 10\n", - " Solving: Stress period: 8 Time step: 11\n", - " Solving: Stress period: 8 Time step: 12\n", - " Solving: Stress period: 8 Time step: 13\n", - " Solving: Stress period: 8 Time step: 14\n", - " Solving: Stress period: 8 Time step: 15\n", - " Solving: Stress period: 8 Time step: 16\n", - " Solving: Stress period: 8 Time step: 17\n", - " Solving: Stress period: 8 Time step: 18\n", - " Solving: Stress period: 8 Time step: 19\n", - " Solving: Stress period: 8 Time step: 20\n", - " Solving: Stress period: 8 Time step: 21\n", - " Solving: Stress period: 8 Time step: 22\n", - " Solving: Stress period: 8 Time step: 23\n", - " Solving: Stress period: 8 Time step: 24\n", - " Solving: Stress period: 8 Time step: 25\n", - " Solving: Stress period: 8 Time step: 26\n", - " Solving: Stress period: 8 Time step: 27\n", - " Solving: Stress period: 8 Time step: 28\n", - " Solving: Stress period: 8 Time step: 29\n", - " Solving: Stress period: 8 Time step: 30\n", - " Solving: Stress period: 8 Time step: 31\n", - " Solving: Stress period: 9 Time step: 1\n", - " Solving: Stress period: 9 Time step: 2\n", - " Solving: Stress period: 9 Time step: 3\n", - " Solving: Stress period: 9 Time step: 4\n", - " Solving: Stress period: 9 Time step: 5\n", - " Solving: Stress period: 9 Time step: 6\n", - " Solving: Stress period: 9 Time step: 7\n", - " Solving: Stress period: 9 Time step: 8\n", - " Solving: Stress period: 9 Time step: 9\n", - " Solving: Stress period: 9 Time step: 10\n", - " Solving: Stress period: 9 Time step: 11\n", - " Solving: Stress period: 9 Time step: 12\n", - " Solving: Stress period: 9 Time step: 13\n", - " Solving: Stress period: 9 Time step: 14\n", - " Solving: Stress period: 9 Time step: 15\n", - " Solving: Stress period: 9 Time step: 16\n", - " Solving: Stress period: 9 Time step: 17\n", - " Solving: Stress period: 9 Time step: 18\n", - " Solving: Stress period: 9 Time step: 19\n", - " Solving: Stress period: 9 Time step: 20\n", - " Solving: Stress period: 9 Time step: 21\n", - " Solving: Stress period: 9 Time step: 22\n", - " Solving: Stress period: 9 Time step: 23\n", - " Solving: Stress period: 9 Time step: 24\n", - " Solving: Stress period: 9 Time step: 25\n", - " Solving: Stress period: 9 Time step: 26\n", - " Solving: Stress period: 9 Time step: 27\n", - " Solving: Stress period: 9 Time step: 28\n", - " Solving: Stress period: 9 Time step: 29\n", - " Solving: Stress period: 9 Time step: 30\n", - " Solving: Stress period: 10 Time step: 1\n", - " Solving: Stress period: 10 Time step: 2\n", - " Solving: Stress period: 10 Time step: 3\n", - " Solving: Stress period: 10 Time step: 4\n", - " Solving: Stress period: 10 Time step: 5\n", - " Solving: Stress period: 10 Time step: 6\n", - " Solving: Stress period: 10 Time step: 7\n", - " Solving: Stress period: 10 Time step: 8\n", - " Solving: Stress period: 10 Time step: 9\n", - " Solving: Stress period: 10 Time step: 10\n", - " Solving: Stress period: 10 Time step: 11\n", - " Solving: Stress period: 10 Time step: 12\n", - " Solving: Stress period: 10 Time step: 13\n", - " Solving: Stress period: 10 Time step: 14\n", - " Solving: Stress period: 10 Time step: 15\n", - " Solving: Stress period: 10 Time step: 16\n", - " Solving: Stress period: 10 Time step: 17\n", - " Solving: Stress period: 10 Time step: 18\n", - " Solving: Stress period: 10 Time step: 19\n", - " Solving: Stress period: 10 Time step: 20\n", - " Solving: Stress period: 10 Time step: 21\n", - " Solving: Stress period: 10 Time step: 22\n", - " Solving: Stress period: 10 Time step: 23\n", - " Solving: Stress period: 10 Time step: 24\n", - " Solving: Stress period: 10 Time step: 25\n", - " Solving: Stress period: 10 Time step: 26\n", - " Solving: Stress period: 10 Time step: 27\n", - " Solving: Stress period: 10 Time step: 28\n", - " Solving: Stress period: 10 Time step: 29\n", - " Solving: Stress period: 10 Time step: 30\n", - " Solving: Stress period: 10 Time step: 31\n", - " Solving: Stress period: 11 Time step: 1\n", - " Solving: Stress period: 11 Time step: 2\n", - " Solving: Stress period: 11 Time step: 3\n", - " Solving: Stress period: 11 Time step: 4\n", - " Solving: Stress period: 11 Time step: 5\n", - " Solving: Stress period: 11 Time step: 6\n", - " Solving: Stress period: 11 Time step: 7\n", - " Solving: Stress period: 11 Time step: 8\n", - " Solving: Stress period: 11 Time step: 9\n", - " Solving: Stress period: 11 Time step: 10\n", - " Solving: Stress period: 11 Time step: 11\n", - " Solving: Stress period: 11 Time step: 12\n", - " Solving: Stress period: 11 Time step: 13\n", - " Solving: Stress period: 11 Time step: 14\n", - " Solving: Stress period: 11 Time step: 15\n", - " Solving: Stress period: 11 Time step: 16\n", - " Solving: Stress period: 11 Time step: 17\n", - " Solving: Stress period: 11 Time step: 18\n", - " Solving: Stress period: 11 Time step: 19\n", - " Solving: Stress period: 11 Time step: 20\n", - " Solving: Stress period: 11 Time step: 21\n", - " Solving: Stress period: 11 Time step: 22\n", - " Solving: Stress period: 11 Time step: 23\n", - " Solving: Stress period: 11 Time step: 24\n", - " Solving: Stress period: 11 Time step: 25\n", - " Solving: Stress period: 11 Time step: 26\n", - " Solving: Stress period: 11 Time step: 27\n", - " Solving: Stress period: 11 Time step: 28\n", - " Solving: Stress period: 11 Time step: 29\n", - " Solving: Stress period: 11 Time step: 30\n", - " Solving: Stress period: 12 Time step: 1\n", - " Solving: Stress period: 12 Time step: 2\n", - " Solving: Stress period: 12 Time step: 3\n", - " Solving: Stress period: 12 Time step: 4\n", - " Solving: Stress period: 12 Time step: 5\n", - " Solving: Stress period: 12 Time step: 6\n", - " Solving: Stress period: 12 Time step: 7\n", - " Solving: Stress period: 12 Time step: 8\n", - " Solving: Stress period: 12 Time step: 9\n", - " Solving: Stress period: 12 Time step: 10\n", - " Solving: Stress period: 12 Time step: 11\n", - " Solving: Stress period: 12 Time step: 12\n", - " Solving: Stress period: 12 Time step: 13\n", - " Solving: Stress period: 12 Time step: 14\n", - " Solving: Stress period: 12 Time step: 15\n", - " Solving: Stress period: 12 Time step: 16\n", - " Solving: Stress period: 12 Time step: 17\n", - " Solving: Stress period: 12 Time step: 18\n", - " Solving: Stress period: 12 Time step: 19\n", - " Solving: Stress period: 12 Time step: 20\n", - " Solving: Stress period: 12 Time step: 21\n", - " Solving: Stress period: 12 Time step: 22\n", - " Solving: Stress period: 12 Time step: 23\n", - " Solving: Stress period: 12 Time step: 24\n", - " Solving: Stress period: 12 Time step: 25\n", - " Solving: Stress period: 12 Time step: 26\n", - " Solving: Stress period: 12 Time step: 27\n", - " Solving: Stress period: 12 Time step: 28\n", - " Solving: Stress period: 12 Time step: 29\n", - " Solving: Stress period: 12 Time step: 30\n", - " Solving: Stress period: 12 Time step: 31\n", - " \n", - " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/03 10:16:35\n", - " Elapsed run time: 1 Minutes, 25.808 Seconds\n", - " \n", - " Normal termination of simulation.\n" - ] - } - ], + "outputs": [], "source": [ "sim.write_simulation()\n", "sim.run_simulation();" @@ -3158,21 +1380,10 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "id": "81fd5949", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "hds = gwf.output.head()\n", "heads = hds.get_alldata()[-1]\n", @@ -3188,21 +1399,10 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "id": "20c39c28", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fig, ax = plt.subplots(figsize=(12, 8))\n", "ax.set_aspect(\"equal\")\n", diff --git a/notebooks/part1_flopy/05-unstructured-grids.ipynb b/notebooks/part1_flopy/05-unstructured-grids.ipynb index 25230b1..892c4e7 100644 --- a/notebooks/part1_flopy/05-unstructured-grids.ipynb +++ b/notebooks/part1_flopy/05-unstructured-grids.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# FloPy Model Grids" + "# 05: FloPy Model Grids" ] }, { @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -43,7 +43,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -55,14 +55,36 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Basin Example" + "## Basin Example" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "len boundary 55\n", + "Len segment: 38\n", + "Len segment: 14\n", + "Len segment: 12\n", + "Len segment: 13\n" + ] + }, + { + "data": { + "image/png": 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1zWIhxLjmzZuHhQsX4sUXX6y2WCwhRIn+M0itZWdn44UXXkBJSQl69+6NvXv38k4uRwipfydPnsTJkyfh6+uLiRMnYsqUKWjZsqVaGZqGT2ydgPFZJMeGlZSUQCwWQyqVolGjRqaujtkoKirCc889hytXruCpp57CqVOn4ObmZupqEWITUlJSEBYWprfcq6++ikOHDuHevXvctvDwcPzf//0fhg8fjvz8fJqGT6wW3/s3jREiNVZWVobhw4fjypUr8PPzw6FDhygIIsSIVLmLdHFycsJ7772H27dvY+/evRg8eDAEAgESEhIwduxY+Pn54c033+Q9DZ8Qa0UtQnrYaouQtuZyhUKB//3vf4iPj4erqytOnjxJi6cSYgK16dLKzs7Gtm3bsG3bNty6dYv3c0kkEnTu3LnWdSXEFPjevykQ0sMWAyG+K8l/9913GDt2rJFqRQgxFLlcjvj4eMTGxiIhIUFveQqEiCXie/+mwdKkGr4rybdt29YItSGEGJqdnR0GDx4MLy8vXmONCLFmFAgRQgjR6eDBg2jfvj0cHBxolhmxOhQIEUII0WnZsmXYsmULXn31Vaxfvx5lZWVay9IsM2JpKBAihJglOZPjwr8XUFBeAE8HT3Rq2Al2AjtTV8smubu7IycnBzExMXrL0mKvxNIYfPp8RUUF3n77bQQFBcHZ2RktWrTAu+++C4VCwZVhjGHFihXw8/ODs7Mz+vbti8uXL6udp6ysDLNnz4anpydcXFwwdOhQ3L59W61MUVERoqOjIRaLIRaLER0djeLiYrUy2dnZGDJkCFxcXODp6Yk5c+ZAJpMZ+rKtSkVFhamrQGxcQlECItMi8VrGa1h6cyley3gNkWmRSCjSP7CX8Md3Gv6ZM2ewbds2tGjRwkg1I8R4DN4itGbNGmzZsgVff/012rVrhz///BOTJk2CWCzG3LlzAQBr167F+vXrsWPHDrRu3Rrvv/8+BgwYgPT0dLi6ugJQpoY/cOAA9uzZAw8PDyxYsACRkZGQSCSws1N+Khw7dixu376Nw4cPAwCmTZuG6OhoHDhwAIByZkRERASaNGmCU6dOobCwEBMmTABjDJ988omhL90qnDt3Dq+++qqpq0FsWEJRAhZlLqq2Pb88H4syFyEWsQh3CzdBzaxPYGAg0tPTeY35CQ4ORocOHdClSxcj1pAQI2AGFhERwSZPnqy2LSoqio0fP54xxphCoWA+Pj5s9erV3P7S0lImFovZli1bGGOMFRcXMwcHB7Znzx6uTE5ODhMKhezw4cOMMcauXLnCALAzZ85wZZKTkxkAdu3aNcYYYwcPHmRCoZDl5ORwZXbv3s1EIhGTSqUa619aWsqkUin3uHXrFgOgtby1KCoqYjNmzGACgYAB4PWQSCSmrjaxMhWKCjb40mDWWdJZ6+OFSy+wCkWFqatqkyQSCb03EIshlUp53b8N3jX23HPP4dixY7h+/ToA4K+//sKpU6fw4osvAgAyMzORl5eHgQMHcseIRCL06dMHp0+fBqDMWVFeXq5Wxs/PD6GhoVyZ5ORkiMVidO3alSvTrVs3iMVitTKhoaHw8/PjygwaNAhlZWWQSCQa6x8TE8N1tYnFYgQEBBji12K2GGPYs2cPQkJCsHnzZjDGEBUVBZFIpPM4Wkme1IcL/15Afnm+zjJ3y+/iwr8XjFQjUhtLlixBenq6qatBCC8G7xp78803IZVK0bZtW9jZ2UEul+ODDz7AmDFjAAB5eXkAAG9vb7XjvL29kZWVxZVxdHSstmyDt7c3d3xeXh68vLyqPb+Xl5damarP4+bmBkdHR65MVUuWLMH8+fO5n0tKSqw2GLpx4wZmzJiB+Ph4AECbNm3w2WefoV+/fjRFlphEQTm/pRz4liOmceTIETz11FOIjo7GO++8w40tovcVYo4MHgh9//332LlzJ3bt2oV27drh4sWLmDdvHvz8/DBhwgSunEAgUDuOMVZtW1VVy2gqX5sylYlEIr2tIZZA1xuOTCbDDz/8gM2bN6OsrAwikQhLly7F4sWLuWsPDAykNyRidJ4O/FoZ+ZYjptGrVy+cPHkSX3/9Nb777jtMnjwZkyZNQr9+/WiBV2J2DB4ILVq0CG+99RZGjx4NAGjfvj2ysrIQExODCRMmwMfHB4CytcbX15c7Lj8/n2u98fHxgUwmQ1FRkVqrUH5+Pnr06MGVuXv3brXnv3fvntp5zp49q7a/qKgI5eXl1VqKrAnfJTIAYMCAAdi8eTNatWplhJoRolunhp3g5eCls3vM28EbnRp2MmKtiIpqlpm+YGbnzp3Iy8vDO++8g99//x2ff/45tm3bpndGamlpKU6ePImQkBCNz00BEqkPBg+EHj58CKFQfeiRnZ0dN30+KCgIPj4+iI+PR6dOyjczmUyG48ePY82aNQCAsLAwODg4ID4+HiNHjgQA5ObmIi0tDWvXrgUAdO/eHVKpFOfOncOzzz4LADh79iykUikXLHXv3h0ffPABcnNzuaDryJEjEIlEVp1Wnu8SGTExMXjzzTf1tsQRYix2Ajss8l+kcdYYAAggwEL/hZRPyERqMsssMDAQhw8fxqlTp7Bs2TIkJSXxeo7x48dr3O7k5ISEhASdLfYULJFaMfQo7QkTJrCmTZuyX3/9lWVmZrK4uDjm6enJFi9ezJVZvXo1E4vFLC4ujqWmprIxY8YwX19fVlJSwpWZPn068/f3Z0ePHmUpKSksPDycdezYkVVUPJktMnjwYNahQweWnJzMkpOTWfv27VlkZCS3v6KigoWGhrL+/fuzlJQUdvToUebv789mzZrF+3r4jjo3JzSzg1i6Y/ePVZs9FiYJY78V/GbqqpFa+uyzz3jPSNX2cHR01LnfycmJZWVlmfpSiZnge/82eCBUUlLC5s6dywIDA5mTkxNr0aIFW7p0KSsrK+PKKBQKtnz5cubj48NEIhHr3bs3S01NVTvPo0eP2KxZs5i7uztzdnZmkZGRLDs7W61MYWEhGzduHHN1dWWurq5s3LhxrKioSK1MVlYWi4iIYM7Ozszd3Z3NmjWLlZaW8r4eCoQIMY0KRQU7X3Ke/VrwK3vh0guss6Qz+/T2p+x8yXl2qPAQO19ynqbRWxC+70t1fdD7GlHhe/8WMMZYXVqUrF1JSQnEYjGkUikaNWpk6urwkpKSwqvrTyKRoHPnzkaoESF1c6zoGBZnLq623cvBC4v8F1GCRQvA932prjS9r9FsNdvE9/5Na40RQiwWZZsm+vCZPEKz1WwbBUJWiNYKI9ZEzuRYd3udzjLrbq9Dn8Z9aBA1wfjx49G1a1eEhoYiNDQUjDG9k0dooVjbRoGQFdqwYYOpq0CIwdQk23QXV1oHy1zxmXpvCFevXsXVq1fr9TmIdaFAyMp8++232LNnj95ytEQGsRSUbdo66Jp6f/XqVa3T5msqNjYWDx8+RFpaGtLS0pCens6lbyFEEwqErEhKSgqmTZsGAJg7d67OVeRpcCCxFJRt2npoy1jPp7XI0dERMplM73OEh4erDZZOTk7mcssRogkFQlaioKAAw4cPR2lpKSIjI7F+/fpqiS0JsUSUbdr68UnUWFZWhvDwcL2Dnqu2dPNdMumLL75AbGwsGjZsyK/SxGpQIGQFKioqMGrUKGRnZyM4OBjffvstBUHEaujLNg0A3Rp1AwD8+eBPFJQXwNPBE50adqLB0xaEz/qGfLNa18aWLVsQFxeHZcuWYdq0acjLy6Mp9zaC8gjpYQl5hBYuXIgPP/wQLi4uOHv2LNq1a2fqKhFicAlFCYi9HavWMuQidMF/iv8AAI3sGqFEXsLtoxxDBOCfv8jf3x+3b98GAAQEBCAvLw/l5eVay9OUe/PH9/5NzQYWbs+ePfjwww8BAF9//TUFQcRqhbuF49fQX7E1eCs+aP4BtgZvRUKHBPRq1AsA1IIg4EmOoYSiBFNUl5gJ1fgjXZycnJCUlITPPvsMPj4+uHXrls4gCHgy5Z5YPuoas2B//fUXJk+eDAB466238PLLL5u4RoTULzuBndoUeTmTI/1Rus5jKMeQbavJQrEtW7ZEdHQ03nzzTXz66adGrCUxJQqELICm9PBSqRTjx4/Ho0eP0KtXL7z//vsmqh0hpkM5hggffMYfqbi4uGDy5MkUCNkQCoTMHJ/08OfOnUNOTg71VRObQzmGCCF1RWOEzFxBQYHeTKxlZWXUV01sEuUYIoTUFQVChBCLpcoxpAvlGCL1Zc2aNSgrKzN1NUgdUSBECLFYqhxDuiz0X0gDpUm9+OGHH/Dcc88hMzPT1FUhdUCBECHEooW7hSM2KFZjy1DPRj0pjxCpMT5T7h0cHCAWi/Hnn3+iU6dO+Pnnn41TOWJwNFia1Du5HDh5EsjNBXx9gV69ADv6gE4MKNwtHH0a98GFfy+goLwABeUF2JCzAecenEOeLA8+jj6mriKxIHyn3APA6NGjkZycjOHDh+ONN97AjBkzUFJSovM4mthiXiiztB6mzizNNyuqRCJRW2jQXMTFAXPnAo8TtgIA/P2Bjz4CoqJMVy9i/aZdnwbJvxK87Pky/hf4P1NXh1ip8vJyLFmyhEtsKxAIoOu2ShmpjYcySxOTi4sDRoxQD4IAICdHuT0uzjT1Irbhdb/XAQA/F/yMO2V3TFwbYq0cHBywbt06/Pzzz2jYsKHOIAigjNTmiAIhM8c3PXzVFZdNTS5XtgRpek9QbZs3T1mOkPrQqWEndHXtCjnk+DLvS1NXh1i5YcOGYdeuXaauBqkFGiNk5gIDA5GamoqOHTvi4cOH+Oabb6qtJ2aOfc4nT1ZvCaqMMeDWLWW5vn2NVi1iY173ex1n08/iQOEBdGnYBUKBkFamJ/WmadOmpq4CqQUKhCxAVlYWHj58CG9vb4wbNw5Cofk35OXmGrYcIbXR3qU92jq3xbVH17Asaxm3nVamJ4SomP8dleC3334DALzwwgsWEQQBytlhhixHSG0kFCXg2qNr1bbTyvSEEBXLuKvaOFUgFBkZaeKa8Nerl3J2mECgu1xCAqBQKL+Xy4GkJGD3buVXGj9E6kLO5Ii9HauzzLrb6yBn9IdGjOvcuXOmrgKphAIhM5eRkYHr16/DwcEBAwYMMHV1eLOzU06RB6oHQ5V/fu89YPRoZfDTvDnQrx8wdqzya/PmNLOM1F5NVqYnxJhef/11LF68mJbnMBMUCJk5VWtQr169TJLHqC6iooC9e4Gq4wf9/YF9+4AvvwQcHIAff1QGPzTNnhgSrUxPjI3PLF+7x9lkY2Nj0a1bN1y9etUYVSM60GBpM5Odna2WY2L37t0AgI4dOyIlJcUsZ4jpEhUFDBumPbN0ixbA888/6R6rjDFl69G8ecpzAJShmvBHK9MTY+ObkfrChQuYMmUKLl68iM6dO+PDDz/E66+/DoG+sQSkXlBmaT2MmVk6Ozsbbdq0QWlpqdYy1paVNClJ2Q2mz8qVwBdfUIZqwp+cyRGZFqmze8zbwRsHQg/QVHpidLm5uZg4cSKOHDkCAIiIiMBXX30Fb29vE9fMevC9f1MgpIcxAyFLX06jNnbvVnaL1Ybqw9PevfyDIVr3zLYkFCVgUab21eljg2JpCj0xGYVCgU8++QRvvvkmysrK4OXlhTVr1qBDhw5aj7G0XgFT4nv/pq4xYlJ1mT5ftetMX0BD657ZnnC3cMQiFrG3Y6u1DAkhRIAoAH8++BMF5QWUaJEYnVAoxNy5cxEeHo6xY8ciLS0NkyZN0nmMtfUKmANqEdKDWoTql1yunB2Wk6N5OQ6++vYFOnVSDsxu2hTw83vy1dn5ybpnVZ+jNq1KxPLImZxbmd7TwRPf3f0OJ0pOwEHggHJWzpWjRIvEVEpLSzF58mRuXKgu1nQPqE/UIkQsgmqa/YgRyqCkcqBS9WddkpKUD00aNwb+/Vf7umc1aVWqjLrZLIedwA5dXLtwP98svYkTJSfUgiDgSaLFWFCXGTEuJycnLFy4kFcgRAyLps8Tk9M1zX7lSn7nmDkTWLhQOd6oTx+gVStlSxAAFBcDFRXaj1WtezZ8OPDJJ8CxY8rgRlcQFhdHeY8slZzJ8VXeVzrLUKJFQmwHtQgRs6Btmj2gnC2mretMIHgyzqdqawxjgFSqPH7xYv11OHBA+VARi4GnnlJ/hIQA588DI0dWr48q75GubjZqRTK9miRarNyKRAixThQIEbNhZ6d5JXpdXWcAsHGj5mBCIFB2iz3zDL/nHzcO+O8/4MoV4MYNZRCVnKx8VD1vbbrZaLC2eaBEi4SQyigQMpGqiRMB4Ndff9V7nJOTEzw9bSsBnKrrTFMQsXGj/iBCte6Zvlalr79+EryUlQEZGcqgqPLj2jXda6CputmmTQMiI5WtSC1bAr/8onmwNp9WJGJYfBMopj9MR3jjcDgKHeu5RoTUzF9//UWDpQ2IZo3pUR+zxvgkTnR0dERcXBx8q8wvt+UcEnXpVlLNGgM0tyrxDUS+/RZ49dWa1dvBQfmc2sYpqQKxzEzqJjMGPokWVTzsPTDaazRGeI5AI3vLWuKGWB6+M4cdHBywYcMGdO/eXWsZW75XqPC9f9fLYOmcnByMHz8eHh4eaNCgAZ5++mlIJBJuP2MMK1asgJ+fH5ydndG3b19cvnxZ7RxlZWWYPXs2PD094eLigqFDh+J2lcWoioqKEB0dDbFYDLFYjOjoaBQXF6uVyc7OxpAhQ+Di4gJPT0/MmTMHMpmsPi6bt4KCAp1BEADIZDL4+vqic+fOag9b/sNWdZ2NGaP8WpOgQdeA7Jq0xgQE8Cs3cCAQFgY0aACUl/MbrH3ypDLYS0pSJppMStLd+kRqx05gh0X+2pMsAkCkeyS8HbxRWFGIT+98ihfTXkTsrVjcKbtjpFoSW8RnrTKhUIjy8nLMmjULYWFhWh9t2rRBdna2kWpu2QzeNVZUVISePXuiX79+OHToELy8vPD333+jcePGXJm1a9di/fr12LFjB1q3bo33338fAwYMQHp6OlxdXQEA8+bNw4EDB7Bnzx54eHhgwYIFiIyMhEQi4RatGzt2LG7fvo3Dhw8DAKZNm4bo6GgceDziVS6XIyIiAk2aNMGpU6dQWFiICRMmgDGGTz75xNCXTsycvnXP+ODbzXbwoPK8CgWwaZOyW0+f/fuB6GgaQ2QM2hItejt4Y6H/QoS7haOclSP+fjy+zf8W1x9dx557e/DDvR/wvNvzeNX7VYQ0CFE7Z9VcRZSckdQUn7XK3Nzc8Pbbb2PXrl06z1VaWoqCggKb/vDMGzOwN998kz333HNa9ysUCubj48NWr17NbSstLWVisZht2bKFMcZYcXExc3BwYHv27OHK5OTkMKFQyA4fPswYY+zKlSsMADtz5gxXJjk5mQFg165dY4wxdvDgQSYUCllOTg5XZvfu3UwkEjGpVMrreqRSKQPAuzwfEomEAdD7kEgkBntOYjj79jEmECgfynBI+VBt27dPvXxionq5mjy0nZMYRoWigp0vOc8OFR5i50vOswpFRbUyCoWCJUuT2evXX2edJZ25x9T0qexk8UkmV8jZsfvH2OBLg9X2D740mB27f8wEV0WsHd1D+OF7/zZ419gvv/yCLl264JVXXoGXlxc6deqEL774gtufmZmJvLw8DBw4kNsmEonQp08fnD59GoAya2Z5eblaGT8/P4SGhnJlkpOTIRaL0bVrV65Mt27dIBaL1cqEhobCz8+PKzNo0CCUlZWpddVVVlZWhpKSErUHIZXVtJtN1YpUm4WlVa1O8+ZRN1l9UCVaHOw+GF1cu2hswREIBOjWqBs2B2/G7ra7EeEeATvYQfKvBHP/novItEgsylxUbcyRKjljQlGCsS6HEFILBg+E/vnnH3z22WcIDg7G77//junTp2POnDn45ptvAAB5eXkAUG2FXW9vb25fXl4eHB0d4ebmprOMl5dXtef38vJSK1P1edzc3ODo6MiVqSomJoYbcyQWixHAd1AIsSlRUcDNm0BiIrBrl/JrZqbmLixV9mygejDEJziqPIaImFbrBq3xbvN38UvoL4j2ikYDQQPcLb+r8xhKzkiIeTN4IKRQKNC5c2esWrUKnTp1wmuvvYapU6fis88+UysnqHIHYIxV21ZV1TKaytemTGVLliyBVCrlHrdu3dJZJ2K7ajJ4W1cr0rx5/J4vN7eWFSUG5+Pog3n+8/BBiw/0llUlZ6xMzuT488GfOHz/MP588CcFSoSYkMEDIV9fXzz11FNq20JCQrjR6z4+PgBQrUUmPz+fa73x8fGBTCZDUVGRzjJ371b/JHbv3j21MlWfp6ioCOXl5dVailREIhEaNWqk9iDEELS1Ig0bxu/4KpkUiBl4KH/Iq1yu7EkUm1CUgMi0SLyW8RqW3lyK1zJeQ2RaJHWhEYPbu3cvGGXI0cvggVDPnj2Rnp6utu369eto1qwZACAoKAg+Pj6Ij4/n9stkMhw/fhw9evQAAISFhcHBwUGtTG5uLtLS0rgy3bt3h1Qqxblz57gyZ8+ehVQqVSuTlpaG3EofpY8cOQKRSMQrV0N94TNF0hYTJ9oCTa1IfMYQ2dk9GSNEU+zNB9/kjLG3YvHR7Y/w470faTwRMZqYmBhERESo3QNJdQZPqHj+/Hn06NEDK1euxMiRI3Hu3DlMnToVn3/+OcaNGwcAWLNmDWJiYrB9+3YEBwdj1apVSEpKUps+//rrr+PXX3/Fjh074O7ujoULF6KwsFBt+vwLL7yAO3fuYOvWrQCU0+ebNWumNn3+6aefhre3N2JjY3H//n1MnDgRL730Eu/p8/WRUBF4klk6NzcXxcXFmDlzJqRSKVasWIFWrVqhcePG8PX1paRYNkJbwseqIiKAixeV0/dVaIq96fBJziiEEAooeJ3P28EbB0IP6Jx2T9P0CZ+kvPb29hAKhZDJZPDw8MCWLVswQvUmYyP43r/rJbP0r7/+iiVLliAjIwNBQUGYP38+pk6dyu1njGHlypXYunUrioqK0LVrV3z66acIDQ3lypSWlmLRokXYtWsXHj16hP79+2Pz5s1qg5fv37+POXPm4JdffgEADB06FJs2bVLLWZSdnY0ZM2YgISEBzs7OGDt2LNatWweRSMTrWuorEFLVTd8fs5OTE9LT0ykYsgGa1iILCABiYoATJ4DPP9d8XE2zYxPDSihKwKJMzQkaBRBgddBqOAoc8WXel7j88LLGcpVtDd6qdbHXhKKEarmPvBy8sMh/EcLdwmt3AcQiaVqmqTJPT088ePAA0dHRuHBBOUZt/PjxWLx4McrLy3UeZy33G5MGQtakPgMhvunUJRIJrStjI7QtIyKXAz4+gLb3PVqmw7Q0BSiVkzMCwOH7h7H05lK95woSBaGLaxe0cG6BIKcgtHRqCTd7NyQWJ2oNuAAgNihWbzBErUm2RyaT4d1330VMTAwUCv0tk9b04Zvv/ZsWXSXEjKjGEFV18qT2IAhQn2Kv6XhSv8LdwtGncR+dQQbf8USZZZnILMtU29ZI2AiP2COdx627vQ59GvfRGthQa5JtcnR0xPvvv4+IiAiMHDmy2lJVVdliRmoKhAixAHzHOtKYSNNRJWfUplPDTvBy8NI5nsjd3h2z/WbjZtlNZJZm4p/Sf5BTloMShf7ErnfL72LtrbXo3qg7/EX+aCpqCmehMwDt3XeqQdqx0N+aRCxb9+7dsXv3bvTq1cvUVTE7FAgRYgH4Tp2nKfbmS7XYq67xREsCllQLSEoVpdidvxub7mzS+xx7C/Zib8Fe7mdPB080dWiK9EfpOo7S35pErEODBg1MXQWzVC+rzxNCDIvPFPuAAGU5Yr7C3cIRGxQLLwf1rPjeDt5YG7RWY6uMk9AJ7V3a8zp/mEsYQhqEwNVOOfu2oLwAfz38C6VM+4QMQHPSR0JsBbUIEWIBVMt0jBihDIY0TXF45x0aKG0J+IwnqopPt5q3gzc+a/0Zdx5phRS3y27jt8Lf8H3B93rrlfZfmsauPRpgbXuqJjO2dtQiZALZ2dlISUnB1atXTV0VYkG0LdPh6Kj8evCg8etEaofPYq9Vyy/y1z5jTAABFvovVDuP2F6Mdi7teI/9+eTOJxh9dTS+vfst7pXfA0BZsG3ViBEjsHPnTpvJSk3T5/Uw9PR5PrmDKrOmqYzEMKpOsW/cGHjmGaCiAti3j3IJWTM+0/Sr4pP0USQQQc7kqEAFAGUSyFbOrXD90XWtx/CZrk/MC9+ULSoDBw7Eli1bEBQUVI+1qj+UR8hADB0I8f1D3LlzJ0JCQqwquRWpP8uWAe+/r8w1lJoKpKVVz0VErENtuqr0JX1cG7QWYa5hiC+Kx8H7B/HXf3/prQefLNjEvPBN4jtnzhx89NFHKCsrg7OzM959913MmzcPd+7c0ZvE0ZzuVxQIGYipAiFKokhqorQUePppID0dcHEB/vvvyT5agoMANWtNOlh4EMuyluk9p64s2MQ88clIHRgYiIyMDLz22mtITEwEALRr1w4ZGRmQyWRajzW3HgxKqEiIDXFyAsaPV7YMVQ6CAOW6ZCNG0BIctq4mg7SFAn7DRwvKdWT5JGYpMDCQV6ASHByMY8eOYfv27Vi4cCEuX9a/PIylJmOkwdKEWAG5HHi89nA1qjbfefNopXpbx3eQNt8s2HzLEcskEAgwefJkXL16FQMHDjR1deoNBUKEWIGTJ9UXa62q8hIchOijmq6vix3s9JYh1sHb2xsxMTGmrka9oUCIECtAS3AQQ9I3XR8A5JBjyvUpSP0vVfkzk+PPB3/i8P3D+PPBn5Azan4kloHGCBFiBWgJDmJo4W7hiEWsxgHWU32m4seCH5H+KB2vXX8NI5uMxO9Fv9OCrsQiUSBkZJ6ennByctI7fdHTk/reCX+qJThycjRnnQaU++VyYPdumlZP+NE1wHqQ+yAsyVyCUyWn8G3+t9WOpQVdbdOhQ4fQqVMnCHStB2RmaPq8HoaePg88mb4ok8nQvXt3AEBiYiJ3fnPLxUAsQ1yccnYYoDkYatgQ+PffJz/TtHpSVzKFDOGXwvFI8UhrGco3ZB1qkoxxyJAh+Oyzz9C0ahp8I+N7/6YxQiYQGBiIzp07o3nz5gCUI/N79+6Nzp07o3PnzhQEkVrRtgSHSKT8WjkIAp5Mq4+LM079iPW59N8lnUEQQAu6WgtVb4Yu9vb2sLe3x4EDB9CuXTts27bNIpbpoK4xE7p//z4AwM3NDUIhxaSk7qKigGHDnizB4eUFTJigDHqqYky5gOu8ecpjqJuM1BTfPEKUb8jyBQYGIj09XW8yxpKSEkyePBnnz5/HlClTsGfPHnzxxRdo1qyZEWtbMxQImZAqEHJ3dzdxTYg1sbMD+vZVfp+UpDkIUqk8rV51DCF8Ub4h28I3GePp06exceNGLFu2DPHx8QgNDcWaNWswffp0s/zQT4GQCVEgROobTasn9UmVb0jXgq4OAgf4OfoBqN06acTy2NvbY+HChRg6dCimTJmCU6dOYebMmfj+++/x1VdfwdHR0azWLKNAyIRUgZCHh4eJa0KsFU2rJ/VJlW9I24KuAFDOyjH+2ngM9xyOg/cP0hR7G9K6dWscP34cmzdvxltvvYUTJ04gNDQUcrkcFRUVWo8z9ppl5tdGZUMKCwsBUIsQqT+qafW6ZrI2aaLsPktKoiU4SM2Fu4UjNii2WpZpbwdvLPZfjJAGIZDKpdhxd0e1liPVFPuEogRjVpkYkVAoxKxZs5CWlobnn38eZWVlOoMg4MmaZcZCgZAJUdcYqW92dsop8oD2YOjePeWCrf36Ac2b0ywyUnPhbuH4NfRXbA3eig+af4CtwVtxIPQARnmNwpfBX6KBsIHO49fdXkeZqK1c8+bNceTIESxbtszUVamGAiETokCIGIO2afWa0JR6UlvaFnRNe5iGh4qHOo819RR7uVzZIrp7t+aWUX376+tc1kYgEOCll14ydTWqoTFCJkSBEDGWytPqc3KUU+Y1tTzTlHrLJ5c/SZ/AN4N4bY7hy5ym2Gu6zv37gblz1RctrpxsNC5O9/7K9JWtybm01Zf+Jw2PAiETosHSxJhU0+qTkjQHQSo0pd686bo51vRGy+eYut6M+U6dP3j/IEJdQuEv8n9yrUwOSckFnEotQHmBJ55p3Al9etnVKhjQdJ0eHsDjoZpqVC2jCxcC69ZVz9Su2r9375Pfqyqzu7ayNTmXtvpSNvj6QYGQCVGLEDEFmlJvuXTdHAHdN+KqN1rV+fTdvHfv5ncz1hYw6Ztir2qF/KPkD0RdjkKkRyQm+0zG9YfX8W5GLB7Y5wMNAAQCO+964dHoRVg7JrxGwYC269QUBFWu0/r1mperUe2fMQPw8QHKyoDXXtNeFtAcBFU+V+VWWH2vi6bXktQerTWmR32sNabSvHlzZGVl4cyZM+jatatBz02INklJyoHR+mzYAHh7U5N8fapJa4u2m6NqELy7u/Ybu0CgfC0TEp6cXy4HwsOBvLya1Vn1fFVbQ3S1XiQUJWDRP4uUN/1KI1OZAgAEuPPpTPSakoJ/GpwGAAghhIIpwKA+yF9ZHsh8MxZfzeQXDMnlykkAletmriZMAAYNAt54A7h7V3MZgUD5u83MVL6WltZ9xnfNMolEgs6dO9fpufjevykQ0qM+A6FGjRrhwYMHuH79OoKDgw16bkK0Ud0YtK5ULwQEfQDmDSAXwEnA3892m+T53mj4lJMr5DiZfRK5D3KRccEXn7/dCzm3nhTS1dpiTjfzyjfj/ft1B2h79ypbOtqMToDz5Fg4ej9pGZLleeP2uoWQJoXD3x/4JS0VX97diuQHyVqfmymA8nxvSGccwD837FBWBhQVAcXFyq9Vv09Nrd/B/56egL19zQPKukpMBO7ft7zus+zsbLRp0walpaVayxgqjxAFQgZSX4FQeXk5HB0dAQAFBQU0TogYldaV6ocD+AhAQKVttwDMAwQ/WXaTfG0+OfMdp8GnXNzVOMw9PBe3SyoVkvoDhz8CrioLVQ4ehg9XpjbIyAAOHADWrKnDxT/WoAHw+G0HMhnwUPdkLr1atwayswEd9zSIxUBkJPDddwCEcjTsdAEOnsoxP/9e6AQonrwI/fsDDcP+xK1Rr+l97uvTtuLRxS4mn3WVmKj8yqeVVZ8XXgBu3FC+5vpERQE//aQ7ADXEGK/6kJ2dbZTM0hQIGUh9BUL5+fnw9vaGQCBAeXk57Ez9l0lsDnfzvgOgF4ChAOY93lk5scbj7gi8AgScf9Ikr2KOb7RV1XYQsb6WDtVMIH3lEBKHET+MAEOVQuxxoR/2csEQADg4AM7OQElJza5Tn8RE9XXoDHHzNjS3QYcRtGqp3nKZ//sARb8PBqD8e3Nze/Jo3PjJ91KpcpxTTQkEgFCofXp75VYxQHcra03OdfJk3V8X1fk+/BCYP9+yWowMiQIhA6mvQOjatWsICQmBm5sbN2iakPogB3ASyl4uXyhjHlWcslcOzCgH7jnpOYkCwG0AQUDisSc3U2PPbKltqw6fgAZQlnnwQHn+Xr2ULTLauLkpB8AuWqTsonhyYjnQ7CTQMBf41xcN7vcAm90Sj+xvA5qSWjIBUOIPbMwEmPrFCARAQICy+yUlRfd16lJ1XAnAo4uUh5EjgR9+0F+uSxfgzz/1l5s5U9kiFN+RX4vQV4u74MUXARcX7QlDa3OdqnOpZnoB6sdqGyelqZW1pufiU1+RSDlAuzY01d1aUSBkIIYOhFRNgn/99RcmT54Mf39/7N+/n9tv7MXmiOXTFejEAZgLZQyj4g9l7xcAjACqtlHo1hcY7g4sWwb88w/wyiv8Agy1+tayBak2QRefsTVOTsBTTymDnvz82t9gAAAhccDguYC40hP+1wRw0RFRqexIBG725X5cuxaYPVtZP303R4HgyWBpgUD/TVtF181b151BFVht3w48/7z+Szt6FJg4UXf9udYVoRyRaZG4W5avNrBapfIYocy/+U2l13edVafRBwQAGzdqz/1TeX/V59FVlu+59AVVc+cqj6mtqq1Z5t6iW1u879+M6CSVShkAJpVK63yurKws5uTkxKC892h8ODk5saysLAPUnFiDCsZYImNs1+OvFVX272OM+TPGUOnh/3j7PsaYoMo+PN4mYIx5aNin9zGaMeVbM2N2dk++r/oQCBgLCGCsokqF9+1jzN9fvay/v3K7Lvv2Kc+p6XkEAvXj5XLGrl9nbO9exl59VXsddT1EIn7lAgIq/Ryyj2G5gGE5GFZUelT9WdsjdJfauRMTNf8Oqv4eKv8ONP1+AwJ0/361HbNokf7nq6hQHqvptan6d8Cn/irH7h9jnf/szDqd78w6S548Op3vzDqdD2ONw4/p/Zvhe52q60hMZGzXLuXXqn+3+vbXpCzfc+mqb2Ji7f6uqz5WrtT//1iTazc3fO/f1CKkhyFbhIw5bZBYPl2tOVGP92tq0VH1ELgD0DKbutZchwL97YCDB5WDbfU5elQ5ABaoWRdVZXxadRo3Bl5+WTlDKC2t5oOAFy1Stm55eSkXoT13jn+KgTfegLI7bF5zoJGW7i8+HrcIaerGUuHTomDIzNJ8nk9f64W+afbaWlcSihKe5BF6TJbnjUc7FmLt6JrlEdJ3neZKW30N0a2pjdrYNtSu69uQMy3rgrrGDIQCIVKftHVr6QtyfgDwBtSDpHr1eIzQD38Cr0QBO3YAkybpP0woBFq1Uj5OnAD+/VdzOYFAGYTs2aPsmvrvP2Uw8/AhcOkS8OmnNauukxMQGqoMag4d0l++8iBigF9XlL+/coZPy5bAbfskYGItR7hWGiMkeNypqWv8hrFv5nyeryYBTk3qb8jM0tamtt2afFTuatW0D9D+N2rImZZ1RYGQgVAgROqLthafDdAf5LgA+K/+qqbu8ayxReeAtd2U35vjjKOXXgLGjgU6dFAGXnw+OetrfdHV0vH9j3I0CTuJ/Qm52LjzCtDn/ZpXusqsMW3BgyWwtNYWa6AtAF2/XtlSWR8tRoD2/xtDzrQ0xP8ABUIGQoEQqQ+6WnzM7R+ySSmw2QEYUWXKPJ8A48QJ5aDqXbuAr77S/1w+PsqHi4sy502DBspZXAkJ+o+t2qqjUpOuG03HarrRjF4Zh93FVXIC8eDZwBMFD5/kT/FvFICp/hsRXBFFwQOpFV3dmvXVYqQyezbQtatyBqVYrHw+bYklq7WiavnX0fXhpKbMZrD0qlWrGAA2d+5cbptCoWDLly9nvr6+zMnJifXp04elpaWpHVdaWspmzZrFPDw8WIMGDdiQIUPYrVu31Mrcv3+fjR8/njVq1Ig1atSIjR8/nhUVFamVycrKYpGRkaxBgwbMw8ODzZ49m5WVlfGuvyEHS0skEgZoHyitekgkkjo/FzENfYObVWWqDnA29qPyYOmqA6pVP8/TcQ2M1WzwK9/BnVUHCDNWswG52tRmEHHl5688WPTHtH1MsELAbwD044dghYAFrA9gZeVlLDEzke26tIslZiayCrkFjTwlFkfb3/3KlYYZbF2bh4tL7d8Laorv/bteF109f/48Pv/8c3To0EFt+9q1a7F+/Xrs2LEDrVu3xvvvv48BAwYgPT0drq6uAIB58+bhwIED2LNnDzw8PLBgwQJERkZCIpFwyQfHjh2L27dv4/DhwwCAadOmITo6GgcOHAAAyOVyREREoEmTJjh16hQKCwsxYcIEMMbwySef1OelExukb3CzyhEYZmyPJ5SDoTV9uBPgyWDpqq1MqnFGnz/+qqnOG6FeZ02iopStKZr6+at27/TqpdyurwWpV6/q++zslOMGRozQPjV840bdnx6jopTLPNSm68bO7klLk1whR/OP5lZPjKiD4PFvfOPgjXC0d0Tf5n15H0tIXWj7uweAL76oe9dZ797K5J/37wO3bgE6kkVz/uPZp2/URZ/rHnNp9uDBAxYcHMzi4+NZnz59uBYhhULBfHx82OrVq7mypaWlTCwWsy1btjDGGCsuLmYODg5sz549XJmcnBwmFArZ4cOHGWOMXblyhQFgZ86c4cokJyczAOzatWuMMcYOHjzIhEIhy8nJ4crs3r2biUQirRFiaWkpk0ql3OPWrVvUIkT00jdV/S3G2ELGWFfGmFBDuZq25gQwxn6odH5Nz6maQl+19Sng8XYVPq1YutRkOjDfFiRtx9e2VcdQEjMTa9QShBVgAesD2L4rRqwkITzo+3/08KhZKyzfVt/Fi82vRUhDuirDmDlzJiIiIvB8lWxbmZmZyMvLw8CBA7ltIpEIffr0wenTypWHJRIJysvL1cr4+fkhNDSUK5OcnAyxWKy2anu3bt0gFovVyoSGhsLPz48rM2jQIJSVlUEikWisd0xMDMRiMfcICAjQWK42PD094eSkO4Wvo6MjcnNzkZKSguzsbIM9N6kbOYAkALsff5VX2TcXmltmVNHtagDrAJzFkxUr+Kg6E1v180YArwDYC6BplTL+j7dHPX7cBJAIYNfjr5lQb+2xA9AXwJjHX2vaLa9qMRkzRvlVWyuLqgWpaZUK+/vzGxwZFQXcvKkcC7Rrl/JrZqZxBxbnPuD3MfXtXm9jV9QuJE5IRObcTESFWODoZ2LV9P0/fv64ybhqxm5trbCqVl9tGb5VWdLfe49fOU2tw/WlXrrG9uzZg5SUFJw/f77avrzHI6m8vb3Vtnt7eyMrK4sr4+joCDc3t2plVMfn5eXBy8ur2vm9vLzUylR9Hjc3Nzg6OnJlqlqyZAnmz5/P/VxSUmKwYCgwMBDp6ekoKChAbm4uoqKiIKuSjEUmkyEyMhKA4VbgJXWjr8vrJPh1dUUAGAWgJ4A+AHKgvVvLH8CHAOZreN6NeBLIRAEYBu2ZpYEngY45qEsXFaDeTWUKGfd5rIYJoH+L/tQFRsyevv9Hvl3fAP8ubEfHund1G5rBA6Fbt25h7ty5OHLkiM7WD0GVcJAxVm1bVVXLaCpfmzKViUQiiEQinfWoi8DAQAQGBiIlJaVaEFRVaWkpCgoKKBAyIW2zu3IAvAxlEHKO57nGQdnqAiiDqBHQPn5nI5606OgKcgDzCnT4MHUwU1txV+OwImmFzjICCODfyB+9Ao34cZaQOtD1/1jTDy58xw3WZHyhMRg8EJJIJMjPz1ebJi6Xy3HixAls2rQJ6enpAJStNb6+vlwZ1WrsAODj4wOZTIaioiK1VqH8/Hz06NGDK3P37t1qz3/v3j2185w9e1Ztf1FREcrLy6u1FBHbo2uNLtV+XV1eALBfwz5tfCt9HwVl95W+gcqWFuRYK7lCjrmH9Q+SZmDYOHgj7IQ0B55Yh5p+cOEbPNW1ddiQDD5GqH///khNTcXFixe5R5cuXTBu3DhcvHgRLVq0gI+PD+Lj47ljZDIZjh8/zgU5YWFhcHBwUCuTm5uLtLQ0rkz37t0hlUpx7tyTz+Nnz56FVCpVK5OWlobcSsPPjxw5ApFIxCufD7FecQCaA+gHYOzjr80fb1fh2+W1DIAftK+sIAAQAGWgVRmf8TvEPJzMPskrZ9DKvitpPBCxeXzHDfItV98M3iLk6uqK0NBQtW0uLi7w8PDgts+bNw+rVq1CcHAwgoODsWrVKjRo0ABjx44FAIjFYkyZMgULFiyAh4cH3N3dsXDhQrRv354bfB0SEoLBgwdj6tSp2Lp1KwDl9PnIyEi0adMGADBw4EA89dRTiI6ORmxsLO7fv4+FCxdi6tSpBllJnlgmXd1dIwB8CaAcwCae5wsB8An0d3Vp+h+nFh/LwHeQdLB7cD3XhBDLl52djQIdc+09PT2NOiSkXvMIabN48WI8evQIM2bMQFFREbp27YojR45wOYQAYMOGDbC3t8fIkSPx6NEj9O/fHzt27OByCAHAd999hzlz5nCzy4YOHYpNm57cvuzs7PDbb79hxowZ6NmzJ5ydnTF27FisW7fOeBdLzIKqGywHwDzo7u6aUsNz+0IZzPDp6iKWydfVV3+hGpQjxFZlZ2ejTZs2KC0t1VrG2BOFaIkNPQy5xEZltNyG8Wia9aVPawATAXwM4C50z+7KxJPWHn3jjohl+v3G73jhuxe0jhFSDZLOnJtJ44MI0cGY9z6+92+TtAgRYizausH0WQHlDK82qFmXF3V1WT65Qo6T2SeR+yAXvq6+KCktwci9I7kgSACBWkBUOXM0BUGEWB4KhExElVxRV/MgoJzqT/ir3CLjBWAOah4EAU9mePGd3UWsQ9zVOMw9rHkx1eFth2NUu1FYGL9Qbb9/I39sHLyRBkkTYqEoEDKRyskVqyouLsaECRNw+/ZtzJw5E4mJiXB2djZBLS1LbbrAqlJ1d1We4cUnaSGxfHFX4zDihxFau79Gh47GyHYjMeKpEWotRr0Ce1FLECEWjAIhE1IlV9Tk2LFj6N69O86ePYshQ4Zg9erVEAqrZzsw9uh6c1XbLrDKdM3woi4v66YvT5AAAiw8shAvh7wMO6EdZY0mxIpQIGSmWrdujS1btmDkyJE4duwYnnnmGY3laBkO3YkPa4K6u2xD1TFAvQJ76c0TxMBwq+QWTmafpCCIECtDgZAZa9mypd4ytAwH/8SHVQkAeALYAOXCpdTdZf00jQHyb+SPzj78ZqfwzSdECLEcFAgRi6Jpenptbk2qbrAtoBYgW6FtDNDtktu8skYDlCeIkLo6dOiQ3jJOTk7w9PQ0Qm2UKBAiFkPbKvDdanEu6gazLXzWCqs6Lb7qPlpMlRB+tGWO/uOPP7Bs2TIAwIwZMzBliub0tTaRWZqQmtI2GPo2lNPbdRFA2fW1A0A+aNaXLeKzVhjlCSKk7vhkjrazs8PixYvRrFkzI9ZMO4MvukpIXckBJAHY/firDPoHQzd4/LXqwqeqnz8C0B/KJIl9QUGQNZIr5Ei6mYTdqbuRdDMJcoWc23fj/g1e55jXbR6aNmqqts2/kT/2jtxLeYII4aGgoEBvfjy5XI7CwkIj1Ug/ahGyAtevX7eaZTg0dX81AXBPz3EPAawE8AUo8aEt0jYIesPADSh8VIjFRxfzOs+wNsOwbsA6yhNEiA2hQMgKTJgwAY8ePcKkSZNMXZU60db9pS8IUgkGcBOU+NDW6BoE/creV7if7YX2qFBUaDxH5TFAlCeIENtCgZAZ47MMh1AohEwmw+TJk3Hq1Cls2rTJIrNQGyIXkC8o8aGt4TsIesOgDfB19cXovaMBgMYAEVID2gY/q6gGNzPGcPnyZSPWzDAoEDJjupbhUHF3d8d3332Hd955B9u2bYNEIsHevXvRqlUrI9aUH10rs9c2FxCgeVkMYhv4DoLu6NMRfZv3hb3QXmMXGq0VRohmfAY/i0QivPXWW4iLi0NqaqoRa2cYFAiZOV3LcKgsXboU3bp1w5gxY/DXX38hLCwM27dvR1SU+byxa5v6/iEAFwDv1fK8upbFINaPb4JDVbmokCgMazOMxgARwhOfwc9lZWVYuXIlAMDR0REymcwYVTMYmjVmJfr3748LFy6gZ8+eKCkpwcsvv4wFCxagvLzc1FXjxv5U/dx+G8AoAJEAzvI8V9UUW/5QTp83n5CPGEu5vBzn75znVbZyIkTVGKAx7cegb/O+FAQRYgBt2rTBpk2b8Pvvv5u6KjVGgZAVadq0KRITE7FgwQIAwPr169GvXz/k5OSYrE58xv4IAcwC4IXq099VBAACAOQASASw6/HXTFAQZI10TYVXMAV+uPwD2m1uhw1nNug8jwACBDQKoESIhNSzXbt2YebMmWjRogWcnJx0ljV25mh9qGvMyjg4OGDdunXo0aMHJk2ahD/++AOdOnXCxo0b0bZtW63H1VcmTz5jfxQAXgbQD8qWIwHUA6fK3V+OoMHQ1k7bVPiPBn8EV0dXLDm2BJJcCQCgSYMmGNp6KLZd3AaABkETYmp8xrYaO3O0PgLGWF0X7bZqJSUlEIvFkEqlaNSokamrUyM3btzAiBEj8Ndff+ktW1+r2O8GMJZHuV1QJjvUNJYoAJQLyFZomwpfVUPHhljUYxHe6PYGXEWuGoOngEYBNAiakDrIzs7Gq6++iuPHj+stK5FIzC6fHd/7N7UIWbFWrVohOTkZY8aMwf79+3WWra9V7PkuUakqFwVgGCgXkLWRK+R6ByjzmQoPAHOenYO3e7+NJi5NuG00CJoQwykvL8dHH32E5cuX4+HDh6auTr2jQMjKOTs745133tEbCNWXXlAOaM6B5nFCmqa+Uy4g66Krq6tyaw2fqfAAMDxkuFoQpEKJEAmpu9OnT2P69OncNPhOnTrhwoULJq5V/aLB0qRe2UG5zhegfR2wjaAWH2ul6uqqGuDklORgxA8jEHc1DuXycpzKPoVPzn3C65x8p8wTQvi7f/8+pk2bhp49eyI1NRUeHh7Yvn07fvrpJ4sb/FxT1CJE6l0UlFPcNeUR2gga+2OtdHV1qbaNixsHO4Ed/iv/j/d5K0+FJ4TUDWMM3377LRYsWMANcJ4yZQrWrFkDDw8PALC4wc81RYEQ4Rw4cABPP/00hELDNxTS2B/bw6erq7RCmajNs4En+jXvh6P/HEVxabHG4KnyemCEkLq7evUqZsyYgaSkJABAu3btsGXLFjz33HNq5fgk9rVk1DVGOCtWrECXLl2QmJhYL+dXjf0Z8/grBUHWjW8X1qr+q3B34V388MoP+HLolwCeTH1XoanwhBjOo0eP8Pbbb6Njx45ISkqCs7MzVq9ejZSUlGpBkC2gFiHCcXFxwYULFxAeHo6hQ4di7dq1aNOmjamrRSyUgil4levu3x1CgfIzWVRIFPaO3EvrgRFSC3wWR71y5QpmzpyJf/75BwAQERGBTZs2oXnz5kaqpfmhPEJ6WHIeIRU+i+Y5OTnh9OnT+Oqrr7BlyxbI5XLY29vj9ddfxzvvvGPRA+GIYembCn/nwR28d/w9fJHyBeRMrvU8qq6uzLmZGqfS01R4Qvjj8z4vFAqhUCg/oPj7++Pjjz/GSy+9BIFAW05/y8b3/k2BkB7WEAgB/D4pqPqAr169isWLF+PXX38FAIjFYrz99tuYPXs2RCKRUepLzJOuqfB9mvXBmj/W4JNzn3Bjf572eRoX8y5CAIHGrM97R+6lVh5CDCAlJQVhYWF6ywmFQsybNw8rVqyAq6urEWpmOhQIGYi1BEK1kZCQgAULFuDixYsAgKCgIKxZswYjRoyw2k8QRDttWZ9VQY6zvTMeVTwCAPQI6IGY/jHo3aw3ZX0mxAj4BkK7du3CmDFjjFAj06NAyEBsORACALlcjm+++QZLly5Fbq5y8GuPHj2wfv16dO3a1cS1I8YiV8jR/KPmemeBdfDqgFX9V+HF4BfVgmXq6iKkfvENhMxxKYz6wvf+TbPGiE52dnaYNGkSMjIysHz5cjRo0ACnT59Gt27dMGbMGNy8edPUVSRGwDfr84bBGxDROqJai6Eq6/OY9mPQt3lfCoIIMbAbN26YugoWiwIhwouLiwtWrFiB69evY9KkSRAIBNizZw/atm2Lt956C1Kp1NRVJPWI71T4u//ereeaEGLdsrOzkZKSovWRnZ3NlS0oKMDHH3+MsLAwjBo1yoS1tmw0fZ7USNOmTbFt2zbMmTMHCxYsQEJCAtasWYNt27Zh5cqVmDp1Kuzt6c/K2jjZ606xr0JZnwmpPT4zv0QiET7++GMcPHgQv/32GyoqKgAoW+/lcu2zNIl21CJEauXpp5/G0aNHceDAAbRt2xb37t3DjBkz0KFDB/z222+goWeWRa6QI+lmEnan7kbSzSTIFco31HJ5OT468xEm/jxR5/ECCBDQKICyPhNSBwUFBTqDIAAoKyvDa6+9hv3796OiogJhYWH4+OOP8fvvvxupltaHPrqTWhMIBIiMjMSgQYPw+eefY8WKFbh69SoiIyPx/PPPY926dXBzc7PqNWqsgbYp8VM6TcGPV37ElXtXAABBjYOQWZypdSo8ZX0mxDg8PT0xadIkTJgwAe3atQOgbE1ycnLSmy+OcsJVR7PG9LD1WWM1UVxcjFWrVuGjjz6CTCYDoL+51snJCenp6RQMmYi2KfGVeTbwxKrwVZjcaTL2p++nqfCE1BO+M7/Onj2LZ599ttr2muSLswU0fd5AKBCquczMTCxZsgTff/89r/K2NJ3TnPCZEt/QsSEy52TC08VT7TiaCk+IYd24cQMffPABduzYobcsvWfyY7Lp8zExMXjmmWfg6uoKLy8vvPTSS0hPT1crwxjDihUr4OfnB2dnZ/Tt2xeXL19WK1NWVobZs2fD09MTLi4uGDp0KG7fVn/DLioqQnR0NMRiMcRiMaKjo1FcXKxWJjs7G0OGDIGLiws8PT0xZ84crrWC1I+goCDs2bMH27dvN3VViA58psT/K/sXaffS1LbRVHhCtKvJrK9Hjx7hu+++Q79+/RAcHMwrCCKGZ/AxQsePH8fMmTPxzDPPoKKiAkuXLsXAgQNx5coVuLi4AADWrl2L9evXY8eOHWjdujXef/99DBgwAOnp6VzK73nz5uHAgQPYs2cPPDw8sGDBAkRGRkIikcDOTvnGO3bsWNy+fRuHDx8GAEybNg3R0dE4cOAAAGUywIiICDRp0gSnTp1CYWEhJkyYAMYYPvnkE0NfOqmiQ4cOpq4C0SElN4VXOb5T5wmxdXzXdfzpp5/w22+/YefOndyHd6FQiO7du+OPP/4wUm0Jh9Wz/Px8BoAdP36cMcaYQqFgPj4+bPXq1VyZ0tJSJhaL2ZYtWxhjjBUXFzMHBwe2Z88erkxOTg4TCoXs8OHDjDHGrly5wgCwM2fOcGWSk5MZAHbt2jXGGGMHDx5kQqGQ5eTkcGV2797NRCIRk0qlvOovlUoZAN7lyRMSiYQB0PtYsGABu3fvnqmraxUq5BUsMTOR7bq0iyVmJrIKeYXafoVCwRIzE9nQ3UMZVoDXIzEz0TQXQ4iF4fueV/nRrFkz9u6777Ls7Gzex0skElNfqkXge/+u9+nzqkR77u7uAJTjR/Ly8jBw4ECujEgkQp8+fXD69GkAyv7P8vJytTJ+fn4IDQ3lyiQnJ0MsFqst89CtWzeIxWK1MqGhofDz8+PKDBo0CGVlZZBIJBrrW1ZWhpKSErUHqV8ffvghmjZtipEjR+Lw4cOUC6OW4q7GoflHzdHv634YGzcW/b7uh+YfNUfc1TjI5DLsvLQTYZ+Hod/X/fBL+i8AdOcHoinxhNQPe3t7jBw5EkeOHME///yDZcuWISAgAJ6ennBy0p2zi2Z+GV69Tp9njGH+/Pl47rnnEBoaCgDIy8sDAHh7e6uV9fb2RlZWFlfG0dERbm5u1cqojs/Ly4OXl1e15/Ty8lIrU/V53Nzc4OjoyJWpKiYmBitXrqzppZI6CAkJwdWrV/Hjjz/ixx9/REBAACZOnIhJkyYhKChIrSzNitBM2+yvnJIcvPzDy3BzckNRaREAwNneGROfnoi5Xefi8r3LGPHDCACgKfGEGMnhw4fRv3//atsDAwORnp5O73FGVq+B0KxZs3Dp0iWcOnWq2r6qaxExxvSuaF61jKbytSlT2ZIlSzB//nzu55KSEgQEBOisF6mbnTt3ws7ODtu2bcPOnTtx69YtvPfee3jvvfcQHh6OKVOmYPjw4bh37x6v/ndbm44vV8gx9/BcjVPgVduKSovg4+KD2V1n47Ww1+DRwAMA0MazDfaO3KsxjxBNiSekflT9kF9ZYGCgTb1/mYN6C4Rmz56NX375BSdOnIC/vz+33cfHB4CytcbX90k6/vz8fK71xsfHBzKZDEVFRWp/MPn5+ejRowdX5u7d6usa3bt3T+08Z8+eVdtfVFSE8vLyai1FKiKRCCKRqDaXTKpQNfPySfAVGBiIjz76CGvWrMH+/fuxbds2xMfHIyEhAQkJCWjcuDEGDBigN+tqaWkpCgoKbOqNhO+CqN8M/wYDWg6otj0qJArD2gyjKfGE1NH169dNXQVSCwYfI8QYw6xZsxAXF4eEhIRqXRtBQUHw8fFBfHw8t00mk+H48eNckBMWFgYHBwe1Mrm5uUhLS+PKdO/eHVKpFOfOnePKnD17FlKpVK1MWloacnOfzHo5cuQIRCIRr6RVpG5UzbwSiUTro2rrjZOTE0aNGoXff/8dmZmZWLFiBZo1a4bi4mL8+OOPJrwa88V3VlfBQ+3N7TQlnpDak8vlWLt2LaKjo01dFVILBm8RmjlzJnbt2oX9+/fD1dWVG4sjFovh7OwMgUCAefPmYdWqVQgODkZwcDBWrVqFBg0aYOzYsVzZKVOmYMGCBfDw8IC7uzsWLlyI9u3b4/nnnwegHFcyePBgTJ06FVu3bgWgnD4fGRmJNm3aAAAGDhyIp556CtHR0YiNjcX9+/excOFCTJ06lZIjGkldmnmbNWuG5cuXY9myZUhISMC6detoPR0N+C50SguiEmJ4N2/exIQJE3DixAlTV4XUlqGnq0HLdL/t27dzZRQKBVu+fDnz8fFhIpGI9e7dm6Wmpqqd59GjR2zWrFnM3d2dOTs7s8jISJadna1WprCwkI0bN465uroyV1dXNm7cOFZUVKRWJisri0VERDBnZ2fm7u7OZs2axUpLS3lfD02fNx98p5Z++OGHrLi42NTVNZoKeQXzX+/PBCsEGqe/C1YIWMD6gGpT6QkhtadQKNiOHTuYq6srA8AaNmzI1q5dy5ycnHS+Pzk5ObGsrCxTV98m8L1/0xIbetASG+aD7zo8gDI5WZcuXfD888+jf//+6NGjh95pqZZMNWsM0Dz7a+/IvTTwmRADKSgowPTp07Fv3z4AQM+ePfHNN9+gRYsWNLPVjNBaYwZCgZD54BsIBQYGqqWxB5Rjj5577jn0798fzz//PDp16sRlKLcWmlaRpwVRCTGsQ4cOYfLkycjLy4O9vT3effddLF682OreT6wBBUIGQoGQ+eAbCEkkEnh5eeHYsWM4evQojh07pjZgHlBOX+3Xrx8XGAUHB+tM32Apn/JoQVRC6sd///2HxYsXY/PmzQCU41R37txJi5+aMQqEDIQCIfPBdx2fqjPRGGO4evUqjh07hmPHjiExMbFaxnB/f38uKOrfv79aaofaPi8hxDqcO3cO0dHR3PT4uXPnIiYmBs7OziauGdGFAiEDoUDIvBiiZaaiogISiYRrLfrjjz8gk8nUyoSEhHBBUePGjdG3b1+9dZNIJPTpkBArUlFRgVWrVuHdd9+FXC6Hn58fduzYgQEDqufjIuaHAiEDoUDI+j18+BB//PEH12IkkUhQ+d9CIBCAz78JBUKEWI+MjAxER0dzSXlHjRqFzZs3c+tmEvPH9/5dr0tsEGIJGjRogAEDBnCf8u7fv4+kpCSuxYiyxRJiPfS1Knt4eODw4cOYP38+Hj58CLFYjM2bN3N57oj1oUCIkCrc3d0RFRWFqCjlTKuDBw8iIiJC73GZmZno1KmT3jXzCCGmwWe8n1AohEKhAAD069cPX3/9Na03aeUMvsQGIdZGtT6ePiNGjEDbtm3x5ptvIjk5mXszJYSYh4KCAr3rFSoUCjg4OGD9+vU4evQoBUE2gAIhQgzE3t4e169fx9q1a9GjRw/4+fnhtddew6FDh1BWVmbq6hFCeNq5cyfeeOMNCIV0i7QF1DVGiIEkJCQgLy8PP//8M3777TfcvXsXn3/+OT7//HM0bNgQL774Il566SW8+OKLEIvFasdaSp4iQmxBq1atTF0FYkQUCBGih6enJ5ycnPTmEWrWrBl69eqFV155BTKZDMePH8fPP/+Mn3/+GXfu3MEPP/yAH374AQ4ODujXrx9eeuklDB06FHK5nPIUEUKIidD0eT1o+jwB6tZio1AoIJFIuKDoypUravvbtWuHy5cv660DTc8npG4kEgm6dOnCqxz9r1k+mj5PiAEFBgbWujVGKBTimWeewTPPPIMPPvgA169fx/79+/Hzzz8jOTmZVxBUU9TVRoi669ev4/XXXzd1NYgZokCIECNr3bo1Fi1ahEWLFiEvLw+bNm3CBx98oPe4hIQEiMViBAUF6RzESUuCEPJEWVkZ1qxZgw8++KBaBnlCAJo1RohJ+fj4cPmK9Fm0aBFatWoFsViMHj16YPr06fjss8/wxx9/qK2dxmeKcGlpqc4WI0KswfHjx9GxY0csX74cMpkMvXv3hkgk0nmMk5MTPD09jVRDYg6oRYgQCxESEoJ//vkH//77L5KTk5GcnKy2PygoCB06dECTJk1MVENCzENhYSEWLVqE7du3AwC8vb2xceNGjBo1Crdu3aJuY6KGAiFCLMTOnTvRoUMHZGRk4NKlS/jrr7+4r7dv30ZmZiYyMzNNXU1CTIYxhm+//RYLFizggp3p06cjJiYGjRs3BlC38X7EOlEgRIgFsbe3R0hICEJCQjBq1Chu+/3795Gamoq//voLCQkJ2L9/v95zDRo0CE899RSCg4PRqlUrtGrVCsHBwWjZsiUaNmxYn5dBiMFdv34d06dPR2JiIgAgNDQUW7duRY8ePUxcM2LuaPq8HjR9ntQ3Qw9uTklJQVhYWJ3q5OvrqxYcVQ6SXF1d63RuQgyprKwMq1evxqpVqyCTyeDs7Izly5dj/vz5cHBwMHX1iAnR9HlCLERgYCDS09ONPm7hm2++gZ2dHW7cuIGMjAzcuHEDN27cQEFBAXJzc5Gbm4uTJ09WO87b21stOKocJNGHBWJMSUlJmD59OtLT0wEoWzk3b96MFi1amLhmxJJQIESIGTDFuIV27dppTBpXVFSEv//+mwuOKgdJ9+7dw927d3H37l2cOnWq2rFeXl7VgiTV97UNkignEqmqoKAAixYtwo4dOwAog/OPPvoII0eOhEAgMG3liMWhrjE9qGuMWJr6zCNUXFysFiRVDpTy8/N1HtukSZNqwZHqa9W114xxLcTyMMbwzTffYMGCBSgsLARQfTA0ISp8798UCOlBgRCxRKZoRZFKpfj777/VgiPV17t37+o81tPTs1pw1KpVK/z333/o16+f3uemJRGsX3p6OqZPn46kpCQAQPv27bF161Z0797dtBUjZosCIQOhQIiQuispKdEaJOXl5dX5/BQIWTZdgbtMJsP333+PzZs3c4OhV6xYgTfeeIMGQxOdKBAyEAqECKlf//77b7VuNtXX3NxcXucIDw9Hly5d0LJlS7Ro0QItW7ZEQEAA7O3rNgySxifVPz7dnyqDBw/G5s2bERQUZISaEUtHgZCBUCBEiOmcOnUKvXr1qtWx9vb2aN68OVq2bFnt0aJFCzRo0EDn8TQ+yTj4pnuIiYnBm2++SYOhCW80fZ4QYvH0BSsqCxYsgEwmw99//42///4bmZmZkMlkXEuTJr6+vhqDpJYtW8LDw6NGa7bVJRAydqtTfT5ffZ574MCBFASRekGBECHE4o0dO1ZtjJBcLkdOTg4XGFV9SKVSLleSpjQAjRo1gq+vb73X29itTvX5fDU9d3FxMc6fP4+4uLgaPQ8hhkaBECHE6tjZ2XG5marOOmOM4f79+1qDpDt37qCkpAQlJSW8nis6OhoBAQHw8PCAu7s7PDw81L6vvK1Ro0YQCoXcscZqdTLG8/E996xZs5CRkYFr167V6PyE1BcKhAghZsvT0xNOTk56Wxk8PT15n1MgEHCBybPPPltt/6NHj5CZmYkjR47gjTfe0Hu+K1eu4MqVK7ye287ODm5ublyAxHcw99GjR5GVlQU7OzsIhULY2dlxD30/V952+/ZtXs/3zz//wN7eHnK5HHK5HBUVFXq/v379Oq9zHzhwgPu+RYsWaN26NQ4fPszrWELqAw2W1oMGSxNiWqaaucV3EO+GDRvQuHFj3L9/H4WFhSgsLOS+r7zt4cOHBq+jJZoyZQpeeukldO3aFU2aNOH9e6YUCaSmaLA0IcQqmGL5kZro3bs3rxt0aWkp7t+/rxYkpaSk4P3339d7bKdOneDs7AyFQsG1wMjl8mo/a9pW+WeZTMZrmnrjxo0hEolgZ2cHe3t7tdalyj9X/v7Ro0dISUnRe+4ZM2ZQQEPMCgVChBBiBE5OTvDz84Ofnx+3rVmzZrwCoS+//NIgwQPf1pdjx47V+Pn4nruq+uj+JKQmKBAihBAN6AZtHIGBgUhPT6fElcRkKBAihBAN6AZtPObe/UmsGwVChBCiRX3foI3d6lSfz0ctaMRSUSBECCEmYuxWp/p8PmpBI5bKJqbPb968GbGxscjNzUW7du2wceNG3usX0fR5QgghxPLwvX8Lte6xEt9//z3mzZuHpUuX4sKFC+jVqxdeeOEFZGdnm7pqhBBCCDExq28R6tq1Kzp37ozPPvuM2xYSEoKXXnoJMTExeo+nFiFCCCHE8lCLEACZTAaJRIKBAweqbR84cCBOnz6t8ZiysjJunaGarDdECCGEEMtj1YOlCwoKIJfL4e3trbbd29sbeXl5Go+JiYnBypUrq22ngIgQQgixHKr7tr6OL6sOhFQEAoHaz4yxattUlixZgvnz53M/5+Tk4KmnnkJAQEC91pEQQgghhvfgwQOIxWKt+606EPL09ISdnV211p/8/PxqrUQqIpEIIpGI+7lhw4a4desWXF1dtQZPNVVSUoKAgADcunXLJsYd2dr1ArZ3zbZ2vQBdsy1cs61dL2Bd18wYw4MHD9SWtdHEqgMhR0dHhIWFIT4+HsOHD+e2x8fHY9iwYbzOIRQK4e/vXy/1a9SokcX/odWErV0vYHvXbGvXC9A12wJbu17Aeq5ZV0uQilUHQgAwf/58REdHo0uXLujevTs+//xzZGdnY/r06aauGiGEEEJMzOoDoVGjRqGwsBDvvvsucnNzERoaioMHD6JZs2amrhohhBBCTMzqAyEAmDFjBmbMmGHqanBEIhGWL1+uNhbJmtna9QK2d822dr0AXbMtsLXrBWzzmq0+oSIhhBBCiDZWnVCREEIIIUQXCoQIIYQQYrMoECKEEEKIzaJAiBBCCCE2iwIhQgghhNgsCoSMbPPmzQgKCoKTkxPCwsJw8uRJU1epmpiYGDzzzDNwdXWFl5cXXnrpJaSnp6uVmThxIgQCgdqjW7duamXKysowe/ZseHp6wsXFBUOHDsXt27fVyhQVFSE6OhpisRhisRjR0dEoLi5WK5OdnY0hQ4bAxcUFnp6emDNnDmQymUGvecWKFdWux8fHh9vPGMOKFSvg5+cHZ2dn9O3bF5cvX7bY623evHm16xUIBJg5cyYA63h9T5w4gSFDhsDPzw8CgQA///yz2n5ze01TU1PRp08fODs7o2nTpnj33Xf1LhZZk2suLy/Hm2++ifbt28PFxQV+fn549dVXcefOHbVz9O3bt9prP3r0aLO8Zn2vsbn9Hdf3awxA4/+1QCBAbGwsV8aSXmOjYMRo9uzZwxwcHNgXX3zBrly5wubOnctcXFxYVlaWqaumZtCgQWz79u0sLS2NXbx4kUVERLDAwED277//cmUmTJjABg8ezHJzc7lHYWGh2nmmT5/OmjZtyuLj41lKSgrr168f69ixI6uoqODKDB48mIWGhrLTp0+z06dPs9DQUBYZGcntr6ioYKGhoaxfv34sJSWFxcfHMz8/PzZr1iyDXvPy5ctZu3bt1K4nPz+f27969Wrm6urK9u3bx1JTU9moUaOYr68vKykpscjrzc/PV7vW+Ph4BoAlJiYyxqzj9T148CBbunQp27dvHwPAfvrpJ7X95vSaSqVS5u3tzUaPHs1SU1PZvn37mKurK1u3bp3Brrm4uJg9//zz7Pvvv2fXrl1jycnJrGvXriwsLEztHH369GFTp05Ve+2Li4vVypjLNet7jc3p79gYrzFjTO1ac3Nz2bZt25hAIGB///03V8aSXmNjoEDIiJ599lk2ffp0tW1t27Zlb731lolqxE9+fj4DwI4fP85tmzBhAhs2bJjWY4qLi5mDgwPbs2cPty0nJ4cJhUJ2+PBhxhhjV65cYQDYmTNnuDLJyckMALt27RpjTPlPLxQKWU5ODldm9+7dTCQSMalUaqhLZMuXL2cdO3bUuE+hUDAfHx+2evVqbltpaSkTi8Vsy5YtFnm9Vc2dO5e1bNmSKRQKxpj1vb5Vbxjm9ppu3ryZicViVlpaypWJiYlhfn5+3GtS12vW5Ny5cwyA2oexPn36sLlz52o9xlyvWVsgZC5/x6Z6jYcNG8bCw8PVtlnqa1xfqGvMSGQyGSQSCQYOHKi2feDAgTh9+rSJasWPVCoFALi7u6ttT0pKgpeXF1q3bo2pU6ciPz+f2yeRSFBeXq52vX5+fggNDeWuNzk5GWKxGF27duXKdOvWDWKxWK1MaGio2urBgwYNQllZGSQSiUGvMyMjA35+fggKCsLo0aPxzz//AAAyMzORl5endi0ikQh9+vTh6mmJ16sik8mwc+dOTJ48GQKBgNtuba9vZeb2miYnJ6NPnz5q2XwHDRqEO3fu4ObNm4b/BTwmlUohEAjQuHFjte3fffcdPD090a5dOyxcuBAPHjzg9lnaNZvL37EpXuO7d+/it99+w5QpU6rts6bXuK5sYokNc1BQUAC5XA5vb2+17d7e3sjLyzNRrfRjjGH+/Pl47rnnEBoaym1/4YUX8Morr6BZs2bIzMzEsmXLEB4eDolEApFIhLy8PDg6OsLNzU3tfJWvNy8vD15eXtWe08vLS61M1d+Zm5sbHB0dDfp769q1K7755hu0bt0ad+/exfvvv48ePXrg8uXL3PNoeu2ysrK4elrS9Vb2888/o7i4GBMnTuS2WdvrW5W5vaZ5eXlo3rx5tedR7QsKCqrNZepUWlqKt956C2PHjlVbZXzcuHEICgqCj48P0tLSsGTJEvz111+Ij4/n6mMp12xOf8emeI2//vpruLq6IioqSm27Nb3GhkCBkJFV/sQNKAONqtvMyaxZs3Dp0iWcOnVKbfuoUaO470NDQ9GlSxc0a9YMv/32W7V/usqqXq+ma69Nmbp64YUXuO/bt2+P7t27o2XLlvj666+5wZW1ee3M9Xor++qrr/DCCy+ofbKzttdXG3N6TTXVRduxdVVeXo7Ro0dDoVBg8+bNavumTp3KfR8aGorg4GB06dIFKSkp6Ny5s9Y6meM1m9vfsTFfYwDYtm0bxo0bBycnJ7Xt1vQaGwJ1jRmJp6cn7Ozsqn3Kzc/PrxZVm4vZs2fjl19+QWJiIvz9/XWW9fX1RbNmzZCRkQEA8PHxgUwmQ1FRkVq5ytfr4+ODu3fvVjvXvXv31MpU/Z0VFRWhvLy8Xn9vLi4uaN++PTIyMrjZY7peO0u93qysLBw9ehT/93//p7Octb2+5vaaaiqj6sIx9O+hvLwcI0eORGZmJuLj49VagzTp3LkzHBwc1F57S7tmFVP+HRv7ek+ePIn09HS9/9uAdb3GtUGBkJE4OjoiLCyMa3pUiY+PR48ePUxUK80YY5g1axbi4uKQkJDAq/mysLAQt27dgq+vLwAgLCwMDg4Oatebm5uLtLQ07nq7d+8OqVSKc+fOcWXOnj0LqVSqViYtLQ25ublcmSNHjkAkEiEsLMwg16tJWVkZrl69Cl9fX64JufK1yGQyHD9+nKunpV7v9u3b4eXlhYiICJ3lrO31NbfXtHv37jhx4oTa1OMjR47Az8+vWtdCXaiCoIyMDBw9ehQeHh56j7l8+TLKy8u5197SrrkyU/4dG/t6v/rqK4SFhaFjx456y1rTa1wrxhmTTRh7Mn3+q6++YleuXGHz5s1jLi4u7ObNm6aumprXX3+dicVilpSUpDa98uHDh4wxxh48eMAWLFjATp8+zTIzM1liYiLr3r07a9q0abWpx/7+/uzo0aMsJSWFhYeHa5yW2qFDB5acnMySk5NZ+/btNU7R7N+/P0tJSWFHjx5l/v7+Bp9OvmDBApaUlMT++ecfdubMGRYZGclcXV2512b16tVMLBazuLg4lpqaysaMGaNxqrWlXC9jjMnlchYYGMjefPNNte3W8vo+ePCAXbhwgV24cIEBYOvXr2cXLlzgZkiZ02taXFzMvL292ZgxY1hqaiqLi4tjjRo1qvE0Y13XXF5ezoYOHcr8/f3ZxYsX1f63y8rKGGOM3bhxg61cuZKdP3+eZWZmst9++421bduWderUySyvWdf1mtvfsTFeYxWpVMoaNGjAPvvss2rHW9prbAwUCBnZp59+ypo1a8YcHR1Z586d1aakmwsAGh/bt29njDH28OFDNnDgQNakSRPm4ODAAgMD2YQJE1h2drbaeR49esRmzZrF3N3dmbOzM4uMjKxWprCwkI0bN465uroyV1dXNm7cOFZUVKRWJisri0VERDBnZ2fm7u7OZs2apTYd0xBUOWQcHByYn58fi4qKYpcvX+b2KxQKtnz5cubj48NEIhHr3bs3S01NtdjrZYyx33//nQFg6enpatut5fVNTEzU+Hc8YcIExpj5vaaXLl1ivXr1YiKRiPn4+LAVK1bUeIqxrmvOzMzU+r+tyh+VnZ3Nevfuzdzd3ZmjoyNr2bIlmzNnTrXcO+Zyzbqu1xz/juv7NVbZunUrc3Z2rpYbiDHLe42NQcCYuaV4JIQQQggxDhojRAghhBCbRYEQIYQQQmwWBUKEEEIIsVkUCBFCCCHEZlEgRAghhBCbRYEQIYQQQmwWBUKEEEIIsVkUCBFCCCHEZlEgRAghhBCbRYEQIYQQQmwWBUKEEEIIsVn/DxlE7UVQc1q4AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "boundary_polygon = basin.string2geom(basin.boundary)\n", "print(\"len boundary\", len(boundary_polygon))\n", @@ -95,9 +117,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "180000 100000 50 90\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Create a regular MODFLOW grid\n", "Lx = 180000\n", @@ -122,7 +162,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -155,9 +195,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "180000 100000 50 90\n", + "(3194, 2) 2\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Create a regular MODFLOW grid\n", "Lx = 180000\n", @@ -194,9 +253,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1826, 2) 2\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Create an irregular MODFLOW grid\n", "Lx = 180000\n", @@ -240,9 +317,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(548, 2) 2\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# nested grid\n", "from flopy.utils.lgrutil import Lgr\n", @@ -307,6 +402,11 @@ " ax.plot(sa[:, 0], sa[:, 1], \"b-\")" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, { "cell_type": "markdown", "metadata": {}, @@ -318,9 +418,27 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1454, 1) 2\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# quadtree grid\n", "sim = flopy.mf6.MFSimulation()\n", @@ -368,9 +486,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Set maximum cell area\n", "maximum_area = 5000 * 5000\n", @@ -414,9 +543,30 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "maximum_area = 5000 * 5000\n", "\n", @@ -453,8 +603,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part1_flopy/08_Modflow-setup-demo.ipynb b/notebooks/part1_flopy/08_Modflow-setup-demo.ipynb index 0746e66..c735d8e 100644 --- a/notebooks/part1_flopy/08_Modflow-setup-demo.ipynb +++ b/notebooks/part1_flopy/08_Modflow-setup-demo.ipynb @@ -4,7 +4,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Modflow-setup demonstration\n", + "# 08: Modflow-setup demonstration\n", + "\n", "[Modflow-setup](https://github.com/DOI-USGS/modflow-setup) is a python package for rapid, automated construction of MODFLOW models. Often in modeling projects, construction of the basic model structure (discretization, boundary conditions, etc) consumes a lot of time that could be spent on effective history matching, uncertainty quantification and forecast scenario development. Modflow-setup aims to speed up construction of the base model in a way that is robust and repeatable. Grid-independent source data such as shapefiles and rasters are specified in a single configuration file, along with the desired packages and their options. Modflow-setup reads the configuration and the source data, and within a few minutes, produces an external array-based MODFLOW model that is amenable to parameter estimation and uncertainty quantification using PEST (e.g. [White et al, 2021](https://doi.org/10.1016/j.envsoft.2021.105022)). Detailed description of Modflow-setup is provided by [Leaf and Fienen (2022)](https://www.frontiersin.org/articles/10.3389/feart.2022.903965) and in [online documentation](https://doi-usgs.github.io/modflow-setup/latest/).\n", "\n", "#### Example problem\n", diff --git a/notebooks/part1_flopy/09-gwt-voronoi-demo.ipynb b/notebooks/part1_flopy/09-gwt-voronoi-demo.ipynb index b01d523..fde387c 100644 --- a/notebooks/part1_flopy/09-gwt-voronoi-demo.ipynb +++ b/notebooks/part1_flopy/09-gwt-voronoi-demo.ipynb @@ -1,32 +1,32 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "afad5282", + "metadata": {}, + "source": [ + "# 09: Demonstration of MODFLOW 6 Groundwater Transport" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "fc15635f-e887-417c-a9b6-583f1d0c758e", "metadata": {}, "outputs": [], "source": [ - "from IPython.display import clear_output, display\n", - "import pathlib as pl\n", + "import warnings\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import matplotlib.colors as colors\n", - "import geopandas as gpd\n", - "import shapely\n", - "import shapefile\n", "\n", "import flopy\n", - "from flopy.utils.gridgen import Gridgen\n", - "from flopy.discretization import StructuredGrid, VertexGrid\n", - "from flopy.utils.triangle import Triangle as Triangle\n", - "from flopy.utils.voronoi import VoronoiGrid\n", - "from flopy.utils.gridintersect import GridIntersect" + "from flopy.utils.triangle import Triangle as Triangle" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "f55b0c73-ec82-4654-ac95-d840845c6a80", "metadata": {}, "outputs": [], @@ -47,7 +47,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "6e5e72a3-edfd-4595-ba6d-420f210a5d84", "metadata": {}, "outputs": [], @@ -68,11 +68,12 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "20f556d4-fc16-4114-a9d0-5c14181d8ebb", "metadata": {}, "outputs": [], "source": [ + "%%capture\n", "sim = flopy.mf6.MFSimulation.load(sim_ws=model_ws_load, sim_name=name)" ] }, @@ -86,7 +87,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "48b8a191-3230-4e41-b0df-6e00d43a5b04", "metadata": {}, "outputs": [], @@ -104,10 +105,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "dd922664-30cf-4be1-941f-e0d8ce186c3b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2027" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "gwf.modelgrid.intersect(550, 7900)" ] @@ -122,10 +134,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "8d5d5361-3361-4568-b711-3cfa482f2993", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "gwf.modelgrid.plot()\n", "ax = plt.gca()\n", @@ -150,10 +183,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "de99b252-29f7-4da8-b0f4-207ed36a26fd", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(3, 2240)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "nlay, ncpl = gwf.disv.nlay.array, gwf.disv.ncpl.array\n", "nlay, ncpl" @@ -161,10 +205,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "806af036-109a-40dd-bf47-c8e5c9e92dad", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "((2240,), (3, 2240))" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "top, botm = gwf.disv.top.array, gwf.disv.botm.array\n", "top.shape, botm.shape" @@ -172,10 +227,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "8581e8ec-c521-4758-a04b-438c4ef6fd1d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "4908" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "nverts = gwf.disv.nvert.array\n", "nverts" @@ -183,7 +249,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "ab044fde-018d-43f8-a743-1637358d4b0b", "metadata": {}, "outputs": [], @@ -201,7 +267,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "f03b0549-d677-4f23-b01d-b28a164f953b", "metadata": {}, "outputs": [], @@ -222,7 +288,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "845f8a67-c82b-48eb-b151-adc0f8e58b90", "metadata": {}, "outputs": [], @@ -240,10 +306,39 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "0c5fc188-4f1a-4a43-a997-85598d15e9e1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package ims_-1...\n", + " writing model voronoi...\n", + " writing model name file...\n", + " writing package disv...\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " writing package ic...\n", + " writing package adv...\n", + " writing package dsp...\n", + " writing package mst...\n", + " writing package fmi...\n", + " writing package ssm...\n", + " writing package cnc...\n", + "INFORMATION: maxbound in ('gwt6', 'cnc', 'dimensions') changed to 1 based on size of stress_period_data\n", + " writing package oc...\n" + ] + } + ], "source": [ "dis = flopy.mf6.ModflowGwtdisv(\n", " gwt,\n", @@ -283,10 +378,160 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "0a98e64c-cbbb-4f74-9dc6-5f72b23bf13b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FloPy is using the following executable to run the model: ../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:49:07\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " Solving: Stress period: 1 Time step: 2\n", + " Solving: Stress period: 1 Time step: 3\n", + " Solving: Stress period: 1 Time step: 4\n", + " Solving: Stress period: 1 Time step: 5\n", + " Solving: Stress period: 1 Time step: 6\n", + " Solving: Stress period: 1 Time step: 7\n", + " Solving: Stress period: 1 Time step: 8\n", + " Solving: Stress period: 1 Time step: 9\n", + " Solving: Stress period: 1 Time step: 10\n", + " Solving: Stress period: 1 Time step: 11\n", + " Solving: Stress period: 1 Time step: 12\n", + " Solving: Stress period: 1 Time step: 13\n", + " Solving: Stress period: 1 Time 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period: 1 Time step: 56\n", + " Solving: Stress period: 1 Time step: 57\n", + " Solving: Stress period: 1 Time step: 58\n", + " Solving: Stress period: 1 Time step: 59\n", + " Solving: Stress period: 1 Time step: 60\n", + " Solving: Stress period: 1 Time step: 61\n", + " Solving: Stress period: 1 Time step: 62\n", + " Solving: Stress period: 1 Time step: 63\n", + " Solving: Stress period: 1 Time step: 64\n", + " Solving: Stress period: 1 Time step: 65\n", + " Solving: Stress period: 1 Time step: 66\n", + " Solving: Stress period: 1 Time step: 67\n", + " Solving: Stress period: 1 Time step: 68\n", + " Solving: Stress period: 1 Time step: 69\n", + " Solving: Stress period: 1 Time step: 70\n", + " Solving: Stress period: 1 Time step: 71\n", + " Solving: Stress period: 1 Time step: 72\n", + " Solving: Stress period: 1 Time step: 73\n", + " Solving: Stress period: 1 Time step: 74\n", + " Solving: Stress period: 1 Time step: 75\n", + " Solving: Stress period: 1 Time step: 76\n", + " Solving: 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Solving: Stress period: 1 Time step: 98\n", + " Solving: Stress period: 1 Time step: 99\n", + " Solving: Stress period: 1 Time step: 100\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:49:17\n", + " Elapsed run time: 10.273 Seconds\n", + " \n", + " Normal termination of simulation.\n" + ] + }, + { + "data": { + "text/plain": [ + "(True, [])" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sim_gwt.run_simulation()" ] @@ -309,7 +554,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "e0cd47c4-f591-4acd-aeed-7ac399e7447c", "metadata": {}, "outputs": [], @@ -323,7 +568,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "5d872228-ac57-4cba-8873-fb6430dac670", "metadata": {}, "outputs": [], @@ -333,11 +578,272757 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "36492a7c", "metadata": {}, - 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If you're sure you want a larger animation embedded, set the animation.embed_limit rc parameter to a larger value (in MB). This and further frames will be dropped.\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "
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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "line = [(0, 8100), (2000, 8300), (5000, 8100)]\n", "xs = flopy.plot.PlotCrossSection(model=gwt, line={\"line\": line}) \n", @@ -418,8 +273430,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part1_flopy/10_modpath-demo.ipynb b/notebooks/part1_flopy/10_modpath-demo.ipynb index ce6d16b..ed43aa3 100644 --- a/notebooks/part1_flopy/10_modpath-demo.ipynb +++ b/notebooks/part1_flopy/10_modpath-demo.ipynb @@ -1,5 +1,12 @@ { "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 10: MODPATH demonstration" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -18,7 +25,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Groundwater Modeling and Python Programming\n", + "## Groundwater Modeling and Python Programming\n", "\n", "In this exercise, we will use MODPATH to simulate advective transport with the Freyberg flow model. For this exercise, we will use a quadtree version of the Freyberg model.\n", "\n", diff --git a/notebooks/part1_flopy/solutions/02-Building-Post-Processing-MODFLOW6__solutions.ipynb b/notebooks/part1_flopy/solutions/02-Building-Post-Processing-MODFLOW6__solutions.ipynb index 17866c0..f7ea0f5 100644 --- a/notebooks/part1_flopy/solutions/02-Building-Post-Processing-MODFLOW6__solutions.ipynb +++ b/notebooks/part1_flopy/solutions/02-Building-Post-Processing-MODFLOW6__solutions.ipynb @@ -1,17 +1,5 @@ { "cells": [ - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import flopy\n", - "from flopy.plot import styles" - ] - }, { "attachments": { "ex01a.png": { @@ -28,7 +16,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Building and post-processing a MODFLOW 6 model\n", + "# Building and post-processing a MODFLOW 6 model\n", "\n", "A MODFLOW 6 model will be developed of the domain shown above. This model simulation is based on example 1 in [Pollock, D.W., 2016, User guide for MODPATH Version 7—A particle-tracking model for MODFLOW: U.S. Geological Survey Open-File Report 2016–1086, 35 p., http://dx.doi.org/10.3133/ofr20161086](https://doi.org/10.3133/ofr20161086).\n", "\n", @@ -44,6 +32,18 @@ "execution_count": null, "metadata": {}, "outputs": [], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "import flopy\n", + "from flopy.plot import styles" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], "source": [ "ws = \"../temp/ex01b\"\n", "name = \"ex01b\"\n", @@ -52,7 +52,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -75,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -91,7 +91,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -103,7 +103,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -128,9 +128,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "mm = flopy.plot.PlotMapView(model=gwf)\n", "mm.plot_grid()" @@ -138,9 +159,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "xs = flopy.plot.PlotCrossSection(model=gwf, line={\"row\": 10})\n", "xs.plot_grid()" @@ -157,7 +199,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -175,7 +217,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -186,7 +228,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -206,7 +248,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -224,7 +266,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -245,9 +287,40 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{0: [[(0, 0, 19), 320, 100000.0, 318],\n", + " [(0, 1, 19), 320, 100000.0, 318],\n", + " [(0, 2, 19), 320, 100000.0, 318],\n", + " [(0, 3, 19), 320, 100000.0, 318],\n", + " [(0, 4, 19), 320, 100000.0, 318],\n", + " [(0, 5, 19), 320, 100000.0, 318],\n", + " [(0, 6, 19), 320, 100000.0, 318],\n", + " [(0, 7, 19), 320, 100000.0, 318],\n", + " [(0, 8, 19), 320, 100000.0, 318],\n", + " [(0, 9, 19), 320, 100000.0, 318],\n", + " [(0, 10, 19), 320, 100000.0, 318],\n", + " [(0, 11, 19), 320, 100000.0, 318],\n", + " [(0, 12, 19), 320, 100000.0, 318],\n", + " [(0, 13, 19), 320, 100000.0, 318],\n", + " [(0, 14, 19), 320, 100000.0, 318],\n", + " [(0, 15, 19), 320, 100000.0, 318],\n", + " [(0, 16, 19), 320, 100000.0, 318],\n", + " [(0, 17, 19), 320, 100000.0, 318],\n", + " [(0, 18, 19), 320, 100000.0, 318],\n", + " [(0, 19, 19), 320, 100000.0, 318],\n", + " [(0, 20, 19), 320, 100000.0, 318]]}" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "riv_spd = {0: [[(0, i, 19), 320, 1e5, 318] for i in range(nrow)]}\n", "riv_spd" @@ -255,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -273,7 +346,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -289,7 +362,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -305,9 +378,75 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package ims_-1...\n", + " writing model ex01b...\n", + " writing model name file...\n", + " writing package dis...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package wel_0...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + " writing package riv_0...\n", + "INFORMATION: maxbound in ('gwf6', 'riv', 'dimensions') changed to 21 based on size of stress_period_data\n", + " writing package oc...\n", + "FloPy is using the following executable to run the model: ../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:36:33\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:36:33\n", + " Elapsed run time: 0.081 Seconds\n", + " \n", + " Normal termination of simulation.\n" + ] + }, + { + "data": { + "text/plain": [ + "(True, [])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sim.write_simulation()\n", "sim.run_simulation()" @@ -324,7 +463,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -333,7 +472,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -342,7 +481,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -358,9 +497,23 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "RECORD IMETH\n", + "----------------------\n", + "FLOW-JA-FACE 1\n", + "DATA-SPDIS 6\n", + "WEL 6\n", + "RIV 6\n", + "RCHA 6\n" + ] + } + ], "source": [ "cobj.list_unique_records()" ] @@ -374,7 +527,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -392,9 +545,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "with styles.USGSMap():\n", " mm = flopy.plot.PlotMapView(model=gwf, layer=0)\n", @@ -427,8 +591,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part1_flopy/solutions/03_Loading_and_visualizing_models-solutions.ipynb b/notebooks/part1_flopy/solutions/03_Loading_and_visualizing_models-solutions.ipynb index ec658d5..b917b09 100644 --- a/notebooks/part1_flopy/solutions/03_Loading_and_visualizing_models-solutions.ipynb +++ b/notebooks/part1_flopy/solutions/03_Loading_and_visualizing_models-solutions.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Loading and visualizing groundwater models\n", + "# 03: Loading and visualizing groundwater models\n", "\n", "This exercise, we will load an existing model into Flopy, run the model and then use [pandas](https://pandas.pydata.org/), [matplotlib](https://matplotlib.org/) and [numpy](https://www.numpy.org/) to look at the results and compare them to observed data. We will also export model input and output to shapefiles and rasters.\n", "\n", @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -51,7 +51,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -73,10 +73,11 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ + "%%capture\n", "sim_ws = Path('../data/pleasant-lake/')\n", "sim = flopy.mf6.MFSimulation.load('pleasant', sim_ws=str(sim_ws), exe_name='mf6',\n", " #load_only=['dis']\n", @@ -86,7 +87,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -104,18 +105,54 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "xll:552400.0; yll:387200.0; rotation:0.0; units:meters; lenuni:2" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "m.modelgrid" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['DIS',\n", + " 'IC',\n", + " 'NPF',\n", + " 'STO',\n", + " 'RCHA_0',\n", + " 'OC',\n", + " 'CHD_OBS',\n", + " 'CHD_0',\n", + " 'SFR_OBS',\n", + " 'SFR_0',\n", + " 'LAK_OBS',\n", + " 'LAK_LAKTAB',\n", + " 'LAK_0',\n", + " 'WEL_0',\n", + " 'OBS_3']" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "m.get_package_list()" ] @@ -129,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -146,9 +183,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(figsize=(6, 6))\n", "pmv = flopy.plot.PlotMapView(m, ax=ax)\n", @@ -161,9 +219,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(figsize=(6, 6))\n", "pmv = flopy.plot.PlotMapView(m, ax=ax)\n", @@ -180,7 +249,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -206,9 +275,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(figsize=(10, 3))\n", "xs = flopy.plot.PlotCrossSection(model=m, line={\"row\": 30}, ax=ax)\n", @@ -227,9 +317,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(figsize=(10, 3))\n", "xs_line = [(552400, 393000), (552400 + 5000, 393000 - 4000)]\n", @@ -264,9 +375,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ], + "text/plain": [ + " cellid q boundname per\n", + "0 (2, 24, 2) -396.867 pleasant_2-13-2 0\n", + "1 (2, 17, 2) -409.900 pleasant_2-9-2 0\n", + "2 (3, 23, 44) 0.000 pleasant_3-12-23 0\n", + "3 (3, 25, 26) 0.000 pleasant_3-13-14 0\n", + "4 (3, 24, 54) -878.654 pleasant_3-13-28 0" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "dfs = []\n", "for kper, ra in m.wel.stress_period_data.data.items():\n", @@ -317,9 +544,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, '$m^3$/day')" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "df.groupby('per').sum()['q'].plot()\n", "plt.title('Total pumpage by Stress period')\n", @@ -336,9 +584,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
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cellidqboundnameper
0(2, 24, 2)0.0000pleasant_2-13-21
0(2, 24, 2)0.0000pleasant_2-13-24
0(2, 24, 2)-926.7360pleasant_2-13-25
0(2, 24, 2)-4428.3600pleasant_2-13-26
0(2, 24, 2)-5699.1800pleasant_2-13-27
0(2, 24, 2)-1027.5000pleasant_2-13-28
0(2, 24, 2)-99.1399pleasant_2-13-29
0(2, 24, 2)0.0000pleasant_2-13-210
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" + ], + "text/plain": [ + " cellid q boundname per\n", + "0 (2, 24, 2) 0.0000 pleasant_2-13-2 1\n", + "0 (2, 24, 2) 0.0000 pleasant_2-13-2 4\n", + "0 (2, 24, 2) -926.7360 pleasant_2-13-2 5\n", + "0 (2, 24, 2) -4428.3600 pleasant_2-13-2 6\n", + "0 (2, 24, 2) -5699.1800 pleasant_2-13-2 7\n", + "0 (2, 24, 2) -1027.5000 pleasant_2-13-2 8\n", + "0 (2, 24, 2) -99.1399 pleasant_2-13-2 9\n", + "0 (2, 24, 2) 0.0000 pleasant_2-13-2 10" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "rates = df.groupby('boundname').get_group('pleasant_2-13-2')[1:]\n", "rates" @@ -371,7 +745,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -388,18 +762,140 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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cellidqboundnameperdays
0(2, 24, 2)0.0000pleasant_2-13-2131
0(2, 24, 2)0.0000pleasant_2-13-2430
0(2, 24, 2)-926.7360pleasant_2-13-2531
0(2, 24, 2)-4428.3600pleasant_2-13-2630
0(2, 24, 2)-5699.1800pleasant_2-13-2731
0(2, 24, 2)-1027.5000pleasant_2-13-2831
0(2, 24, 2)-99.1399pleasant_2-13-2930
0(2, 24, 2)0.0000pleasant_2-13-21031
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" + ], + "text/plain": [ + " cellid q boundname per days\n", + "0 (2, 24, 2) 0.0000 pleasant_2-13-2 1 31\n", + "0 (2, 24, 2) 0.0000 pleasant_2-13-2 4 30\n", + "0 (2, 24, 2) -926.7360 pleasant_2-13-2 5 31\n", + "0 (2, 24, 2) -4428.3600 pleasant_2-13-2 6 30\n", + "0 (2, 24, 2) -5699.1800 pleasant_2-13-2 7 31\n", + "0 (2, 24, 2) -1027.5000 pleasant_2-13-2 8 31\n", + "0 (2, 24, 2) -99.1399 pleasant_2-13-2 9 30\n", + "0 (2, 24, 2) 0.0000 pleasant_2-13-2 10 31" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "rates" ] }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-98,557,525.66559602\n" + ] + } + ], "source": [ "rates['gallons'] = rates['q'] * rates['days'] * 264.172\n", "print(f\"{rates['gallons'].sum():,}\")" @@ -416,9 +912,77 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FloPy is using the following executable to run the model: ../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:35:34\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " Solving: Stress period: 2 Time step: 1\n", + " Solving: Stress period: 3 Time step: 1\n", + " Solving: Stress period: 4 Time step: 1\n", + " Solving: Stress period: 5 Time step: 1\n", + " Solving: Stress period: 6 Time step: 1\n", + " Solving: Stress period: 7 Time step: 1\n", + " Solving: Stress period: 8 Time step: 1\n", + " Solving: Stress period: 9 Time step: 1\n", + " Solving: Stress period: 10 Time step: 1\n", + " Solving: Stress period: 11 Time step: 1\n", + " Solving: Stress period: 12 Time step: 1\n", + " Solving: Stress period: 13 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:35:37\n", + " Elapsed run time: 3.229 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'pleasant.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n" + ] + }, + { + "data": { + "text/plain": [ + "(True, [])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sim.run_simulation()" ] @@ -439,7 +1003,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "metadata": {}, "outputs": [], "source": [ @@ -471,9 +1035,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "levels=np.arange(280, 315, 1)\n", "\n", @@ -546,9 +1153,18 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pyproj/crs/crs.py:1293: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems\n", + " proj = self._crs.to_proj4(version=version)\n" + ] + } + ], "source": [ "from flopy.export.utils import export_array\n", "\n", @@ -580,9 +1196,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(11.120818299999996, -76.35338698486277)" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "op = wt - m.dis.top.array\n", "op.max(), op.min()" @@ -597,9 +1224,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "plt.imshow(op); plt.colorbar()" ] @@ -613,7 +1261,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "metadata": {}, "outputs": [], "source": [ @@ -631,9 +1279,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(figsize=(10, 3))\n", "xs = flopy.plot.PlotCrossSection(model=m, line={\"row\": 62}, ax=ax)\n", @@ -650,9 +1309,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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U88eIiIiIaKJiEEaUhHhbo6Rwq6CgYNQLZ7ZGEsknloor6Xcu1pUqUxlWJ1LJFi/OHyMiIiKiiYhBGJEMYm2NYrhFlP1ibVNM5e9zPJVs8eL8MSIiIiKayBiEERERZSnODiMiIiIikheDMJrQ4hl0HwkrvCgRzc3NGflcIiIiIiKiiY5BGE0IkQKvRFZwjIYrO44vsYZN0naxbn/48GEAQGNjIxobGxM7uJC+vr6kPp+IiIiIiGgiYhBG495oKzvGsoJjNFzZMfskUzGVaFAV7/YLFy7EjBkzYt7+rbcK4fcrsHx5N1yuo2hsbEROTk7Mn09EREREREQiBmE07kVb2TGeFRyjYWvkyMxmM3bt2iXrPqNVYclZbRVrUNXc3IzGxkYsW7YMkydPjnn7GTNmYMGCBTEfzwUXAC0twKefAkVFATQ2Ng77+tkySURERERENDoGYZQ1kp3XFY0UVg1d2ZEhVupI/49NTU1oampKyWNEC7zirbYaKJGgqrGxEZMnT45r+3j19op/5+YC3d194f1E2hdbJomIiIiIiKJjEEZZobm5GU8++WRKH4NzvCJLpJKot1cBjQZQqwUoFMM/3tHRAQBoaGhAQ0NDsoc4SLQqrESrrYZKtposFQYGYYGA2BIZ7eu32WyyV+GZzWZZ90dERERERJQpDMIoZqmq2AKAY8eOAQBWrlyJmTNnyrpvzvGKzO12A0islfDee38EQIHbb/8FCgp6om5XXFycVCgVTbQqrGwMsZIVDAJSkVduLtDVJf576NcvVYLJ0RoajcfjScl+KTNSWRWr1WpRWlqasv0TERERESWKQRjFZLSB83JRq9WyV22xBTIyvV4PYHhl0WgCAeDee8UysIsuOh/FxYFh20gtkTqdTp6DncBCeSUAMQiLRhqeH+//Zyz4/zm+OJ1OAMDLL7+c0sdZt24dioqKwm8zHCMiIiKibMAgbJyRq2qrt7cXuQOuuqUwaejAebls374djY2NrNrKgHjmWwHAwKKgRYvmwmAYvo3D4UjZbLCJRmqLBIBYFoqM9/8zFvz/HF98Ph+A1FTgAsDRo0exefNmvPDCC8M+duuttzIMIyIiIqKMYhA2jqSjakuj0aRkzlZBQYHs+6TUCF1DAwA0mswdx0QhBWE6HaBSZfZYaHyQ2mj1en1Kns+lGycDgzabzYaNGzemrL2eiIiIiChWDMIyIJ6qraGVWSORq2pLmqk18CKGc7ZIwiAsvQYOyieSgzQf0D2w7zYFiouLhwVtcrSqs8WSiIiIiJLBICzNxkLVlnShMvAihnO2SDIwCFPzGSTlpCAsLy+zxwGIq0fKvSJlIquW0tgj91wytlgSERERUaJ4GRtFpKqteKqzoomnaitSZVYs27Nqi1JJCsLUakChyOyxTAQ9oUU5M1kRJq0WKQ3NTwWpXY/GJ7nmkrHFkoiIiIiSxSAsgmyp2opUmRXL9kSpJAVhbItMj2xojZRWi2xoaEBDQ4Os+25ubkZjY2N41Usa32J9PSMiIiIiSpUxHYSZzWb0SOUSMopUtRVvdVY0rNqisY5BWHplQxAmqaqqkn1FSgBobGwc1iLJlkkiIiIiIkqFMR2EPfnkk9Dr9Snb/8CqrXirs6Jh1RaNdQzC0iubgrBUkFoiGxsb0djYGPXjREREREREchjTQdjatWtRX18v+35ZtUXjkVwVNwzC0mu8B2FSS+SyZcswefLk8PvZMklERERERKkQVxC2fv16rF+/HseOHQMAzJs3Dz/60Y+wZs0a+Hw+/PCHP8Q///lPHDlyBAaDAatWrcKDDz6Impqa8D7OOussbN26ddB+r7jiCmzYsCHug8/JyUnJrBFWbVE2SbZF7PDhwwDkq7hhEJZe4z0Ik0yePHlY22Wkn1ciIPbXaa1Wy9UliYiIiGiQuIKw2tpaPPjgg5gxYwYA4Omnn8bFF1+Mzz77DLW1tdi+fTvuvvtuLFq0CA6HA9/5zndw0UUXDbuYufHGG/HjH/84/Haid/zdbndCn0c0Fkg/39ECrHgtXLgw/LsLJF5xM3DVSEq9iRKERZNsEMxZY+OL0+kEALz88ssxf86tt97KMIyIiIiIwuK6lF27du2gt++//36sX78eH330EW644QZs3rx50McfeeQRnHTSSWhubh7U8pKbm4uqqqokDpto/JPm3w1tGYuXFHjNmDFDloobVoSl10QNwkabHZbo/mhs84WegGJZuMZms2Hjxo3wer3pODQiIiIiGiMSrukIBAJ48cUX0dPTgxUrVkTcxul0QqFQoKioaND7n332WTzzzDOorKzEmjVrcM8996CgoCDqY3k8Hng8nvDbLpcr0cMmGnMitYzFS84WM2l0HoOw9JCCsLy8zB5HukWbHRYvzhobn+JZuCaecQdspSQiIiIa/+IOwnbt2oUVK1bA7XYjPz8fGzduxNy5c4dt53a78f/+3//DVVddhcLCwvD7r776atTX16Oqqgq7d+/GnXfeiR07dgyrJhvogQcewH333RfvoRJRCrAiLL16esS/J1pFmESuIDiWFkm2UY4vibRRAmylJCIiIhrv4g7CZs+ejc8//xydnZ146aWXcO2112Lr1q2DwjCfz4cvf/nLCAaDeOyxxwZ9/o033hj+9/z58zFz5kwsW7YM27dvx5IlSyI+5p133onbbrst/LbL5UJdXV28h05EMmAQll4TtTVSLiO1WD711FcBAJdf/jfk5/cO+xwa2+JpowTYSklEREQ0UcQdhGm12vDA7WXLluHTTz/Fww8/jN///vcAxBPPdevW4ejRo3j77bcHVYNFsmTJEmg0Ghw8eDBqEKbT6aDT6eI9VCJKAQZh6cUgLDnRWiwFAbj33noAwAUXXIjSUn+4jdJms2HXrl2j7psVZGNDPG2URERERDT+Jb3umyAI4fldUgh28OBBbNmyJabWgj179sDn8/EklWiMYBCWXgzC5DG0xXJg0c8JJzTAYEh8QD8ryIiIiIiIxo64grC77roLa9asQV1dHbq6urBhwwa888472LRpE/x+Py6//HJs374dr732GgKBAMxmMwCgpKQEWq0Whw8fxrPPPovzzz8fZWVl2Lt3L26//XaccMIJOPXUU1PyBRKRvBiEpReDsNRwu/v/LRUcxzugn4P4x6d4hutHw6H7RERERNkrriDMYrHgmmuugclkgsFgwMKFC7Fp0yasXr0ax44dwyuvvAIAWLx48aDP27JlC8466yxotVq89dZbePjhh9Hd3Y26ujpccMEFuOeee6BSqWT7oogodRiEpReDsNSIFIRJ4hnQH+sg/mjYXpk9Eh2uHw2H7hMRERFlp7iCsCeeeCLqx6ZOnQpBEEb8/Lq6OmzdujWehySiLMMgLL0YhKVGqKMfOh2gUCS2j0RbKUfaF2VOvMP1o+HQfSIiIqLslvSMMCKaWBiEpReDsNSQKsKSWYcl3lbKSKIN6GelWObINVx/aIsl2yWJiIiIsgODMCKKC4Ow9OrpEf/Oy8vscYw3UhCm1ye/r3haKYcaraqMlWJjz0gtluvWrUNRUVFKHpdBGxEREVFsGIQRUVykIEzNZ4+0kCrCOI9dXnIGYcmIVlUWrVJMDtJCNpQakVosjx49is2bN+OFF15I6WNff/31CVcnEhEREU0UvJQlorj4/eLfrAhLPUHoD8JYESYvaUZYpoMwydCqMjnnj0Xjkb4JlBIDWyylNslk549Fc/DgQWzZsiVcjSa39vb2iDPPWIVGREREYxGDMCKKC1sj08frBYJB8d+cESYvOWaEpZIc88eiaWpqQlNTE3TZ+sWPY3LNHxtKCtocDgdMJpOs+3Y6nXj++eejfpyrYxIREdFYwyCMiOLCICx9pPlgAIMwuWVLa+Rokpk/Fo3D4UBTU5Os+6TM6u7uBgBs2bIFW7ZsScljrF69GvX19eG3uTomERERjVUMwogoLgzC0kdqi9Ro+P2W21gJwuR2yy3A/v1zMH/+55k+FJKRNJds2bJlWLJkiaz7ltouCwoKUlLNFq3tMhq2YxIREVGyGIQRUVwYhKWPFISxGkx+2TYjLF1eeQVoa6vAjBlsixyPUhFWSW2XiX58JKO1XUbDdkwiIiJKBoMwIooLg7D0kVojOShfftk+IyxVpMIblSoIs9ks+4qUgLjiJY1/0mD+l19+Oel9DW27jCbedsx4q82iYRUaERHR+MIgjIjiIgVhWm1mj2MiYEVY6kzU1khp1VelMhAemp8q0sqXND5J7ZjJrISZyrbL9vZ2PProo7Ltj1VoRERE4weDMCIZxFoBIW0Xy/bZWlUh3VxnEJZ6rAhLnYnaGikF2UplEA0NDWhoaJD9MZqbm9HY2AibzRauOMvW5zNKXjIrYSbaVhnL50nbXHLJJSgvL0/ocQAuCkBERDQejekg7KKLZqWkrcXnm4O+vu/ihRfU2LNH/v3T+OEOlZU0NjaisbEx5s+LZ/tsq6qQrgXYGpl6rAhLncmTgS98AVi0KNNHkl5SEKZSBVFVVSX7ipRA/3NWpOe5bHs+o7ElkXZMjUaTkiH/RERENHaN6SDMbk/VlbgGgAb79gmorRXfY7HMQyAwDz/9KVBZmfie49lPvI8p1zEyCIydPlROsmzZMkyePHnU7aVKiVi2l7bNycmR5Vjlwoqw9GEQljqXXy7+mWgGtkamivScNfB5LlKVWCJYWTaxxdOOKbVd+qUf+iRFqkLj7DAiIqKxaUwHYZXlTqg1Stn3azLnIhhUIhhUoK1Neq/4OH4/BrwvEfHsJ97HlOsYUxcERmOxnIZA4LSU7D8dwd7kyZNjrqxobGyMeft4qszShTPC0oetkSQnQQACofxLpQqm/PEGPs+NVCWWCFaWTWyxtGMms5rlQKNVoa1btw5FRUWyPNZADNmIiIhSZ0wHYe/9+zeYPr1O9v2ecMplMJr00KjVUKrEcMlqzUEgqIBKKaCiIvETcIs1B8GgAkqlgMpR9jNw21ge0xrn9tGYzXkpDAKjSeX+hwd7gDzhXiqr9rK1Mo8VYenDijCSkxRiA+KMsHSKVCWWiGytlKXxK1oV2tGjR7F582a88MILKXtsDugnokyKd+Xd3t5e5Mpw0hppP6m+OSDXKsOR8MZGdhrTQViq/Ovv67G3aS8aGhpQUVEBALBarcPelwir1Yo9TXtC+xk5CbFaLdiztynmxxx8jImXVS0/dV0oCNQMCgLlCNmiSeX+Iwd7gDzhWyqr9iIHePGKFr4lGgRKN9nvuAP40Y8ib+P1LofbvRh//asC+/YlfuwTnRSEsSKM5DCwQyyVrZEjiad6NprGxsZwi6TTqcLhwzoUFAQwc6Zn0HZsoyQ5Da1CkyrOklk1MxoO6CeiTJN75V05pOrmQDq+Vt7YyD4MwmiYVzc+gr1NTSMEgfL3Rh5vPo5DR49g6tR6TJkyRdZ9n3bqFTCackIVfqrw+20DqvzKEwzf4t1HPNtbogZ48YoWviUXBDoc4p/IdAB0OHgwuRAvkmgBXrZW0CVDao1kRRjJIRAASkoAj8efltbIVBjaYnngwAw899zVqK424uab/zri5xClQjKrZkbTG7oLIv1NRJRuUhAf68q70lzGZG8ORNpPqm8OxPu1xoM3NrIXgzAa917e+BvsDlfW9ScnVqsFe5v2JVXlZ7VasSuOfVitVuzd24Q5DQ2oHCVQPOe0dTCZB1fmJcI+IHwrGxC+9b8fKCuP/WTb5dLB71Miv8ALrTZyVYnVIleIF0m0AC/5CrpUL1AR7/ah0TR48klAGk8zHgM/So+CAqC9HXj33Q+xZUtmKsKSNbTF8q23CvHcc0BFhQGXXnrpoG3jHdDPCjLKFgzCiChblJeXxxT2S1Wyyd4ckGs/iYj1a6XxgUEYUZZ67uVHsKdpfyg0S7wd12K1oqlpePhmsVqwZ2/y+4/kvNMuhdWSC5VKBZVK3qeZdpsegYACKhVQWt4f7NkskRa5iFeqF6hIrAqvu1v8I0rdzLtoxvpiFjT+SC2W0s9McXHesJbLRAf0s4KMiIiIaHxjEEZEsnv8uV/h4NEWTJ06VfZWV4vVGjHAu/iML8Ji0kGt0UClTKyCrt2Wg0AAw0K2WLYviWH7DltOKMQTYtre1amDu0+D/EIPcvPEgc32qIFfKhecGJuLWQAM2sa76mpg7Vog0tixeAf0cxA/ERER0cTAIIyIxoXH//Y4mpr2JVXhZrFaB8zHGz19sQ6qqht9e8ugdtzRt7/tulV467V6/Pfdn2Ld9U0AgMvPvABWkx4ajRrKAYHf4JDNPeq+49Fu0yEYUEKZin1bclIc7I3eMhsIAMEg0NGR2lbXSBjUJefMM8U/I4lnQP/AQfyJYoslERGR/KS2ybGy39EeQ45VNrkiZeIYhNGEYbfb4Xb3X8R3h3rNbHYb+tyJtcJ09/erEcmur1d8is7J7V/u77EX/4S9EQI/qVIu2ZVtIxEXs2hOyWIWV591HqwmHTQazZBgT49gQJF0+BY9aIskPa2ug6W/1ZWrukaWaCtlNIcOHQr/m+EYERFlg/b29pgGt6cjHIqVMzQ092VpYG6KmEwm2WeEpePYuSJlYhiEZYjNZkdf38gXd1LIYrfb4I4hqOnffnDgE69IAVH/++zoS2Lf0XSGlh/s7OyUfd8ulwuAuGqHzWYb8lEF7DY77LZknuwV8Pl8SXw+UWTdLi0AIL9g/K4086sX/hyx1VWcbZdchR8AXHPWubCZtRCCeng9GqhUwqCPK5UCvB4VFEoBfp9yQPjmGXXfHTZdePviGLaPpN2ih5D2VtfUreoKjN0qt3hbKaM5fPgwduzYgZ07d2Lnzp2DPjYwHJN0dyvhdiuRmxtAbq4w7OOxMJvNCX0eERFNHO3t7Xj00Ufj+pzOzs6MD5CXrrOSXZEymu3bt6OxsTElBQ7Rjl2OVTYTWZEy1iAUGP/VZmM6CGvvsEOjkX8J+EgBVDgIstmSGqQrhTJ2uw12+9BQJjKbzQ5bHEFN5MAnfkMDoiAAq80Gqwz7jqaz04HOTkdK9l1aWorCwsLw293d3bDa7CgrL0N+fn5C++zu7obZ1o7e3l5YrdZRt5fuCrik5QBH4Ipj20T2k+x+KXHOGL/3jg4VAMAvmGG1WuL6XBL94oVnsGfvPuz78Kt47S8n4cpv7oWzQ4eAXwGfVwl9bgAf/HsSFq+w4qt3vBrXAhUWqxW7QlV4sbTGRvJfZ6+E3ayFWq2BasDqsA4ZQrZooodvchle5TaWZr7F00oZzY4dOwYFaiOFY1u3noEtW1Zi6dJtWLv2taQe1+OR92eFiIiyQzwBRjRSldcll1yC8vLyEbeVghq/3z/idumUqpUkCwoKZN/nUEOPXc7VMWOt3nM6nXj++efj2vd4rjYb00GYzW5Hb29qLgoFCMNCHwECbHYbbDEGWCMpKRkcykQiBjU2lMcY1PRvX55wsDNwPwMDou7ublhsNpSXJR4ajcTR2YmOTgeKiopRVFQk676lY6+oqBg0l8lqtcBqs6O8rDzhVrI2YxvMtnYYjUYYjcaYPy/27ZVx7zuSIBRoNZoAo2nIRxRwdHTEvB9BABSK0bebaC2jMQdbocrHWP9PnaEgzGZvQlPTwNYqBTqG/L8xIBtZUVkPLrjqEK765t5hHysweNFh1WfgqID7N2zA3r37QmHa4Iq43U370TCnARVJ9kYKAhDwK6BQAAqlgK+fczo6rHqoU7CqKwB0WHURgrb0zXyTxBu+yR2yDQ3UhoZjktbWSmzZAsyePQWXXnppQo/V1NSEpqYmOBwO7Nq1K6njHurIkRYcOjQNr7/ejWBwF6QOZjnbPWPdVyKPyZlvRDTWJVLJNRKNRjNq+JJNrZEUWaJtl6tXr0Z9ff2I2yRSbTbWjOkgrKysFFWVJbLvNxwElQ0Ogmx2G8rKkg+ZbHYrKisrRh2WLQY14mPGEtRYrdbwcccyiHu0xx0YEFmtVlhsNpSVJx4ajUYMwopkn0FktVpgSVEVm0atAQDU1NTAYDCMur3T6URbmxE1NTUoHGV7l9OJFqM5pm1H349p2DE6OjrQarbBaLHCaIlczWYxVcHcVoOZDfuQm9cLAPB6tNDqYnlSVMLlcsESQ6VcPNJRyRZrqNTRIQZbJqMRppjDSgUqKytRUjL6c5e7T3yuWbCwBpWT8sTHdDhgNltgtYh/BlPC52ebbiTzTmxB0KNEl1ODAoMPwVAxsVIJnHiWCYL8xcVZwWHT4fP3K9B6qAB+nxKFJV5c/6M30I3PUjLzDQC+teo0tJu1UGvUUCnFMLfTrg1XuBnKEj+pckQM2aKJN3yLPWQbSaQATgrZ6urU2LNn8GBc6Z5YXV0ZFiwoS+gxpdZIKRCTU09PDp555nsAgL6++zB0Ud5I7Z6xOnz4MID457LF8piJ7juaZLoBiIiSIYURsVRyjSQbq7wocfG2jEr//wUFBRlvd80GYzoIKy0pw+TJdbLvVwqUyssHB0E2u1idlWzIZLPLGwxQ5hkMhpgDwrY2IwoNhthaqYzm0LZJho9GU8RjbDXbooZ42z6qx+ZXTsLH78/EnHlG3Pjfb+K9txpgKOrFeWt3oKLKFfXhrFYrbO0OdHR0DKtckocS/iiBTzKVUQ5HBwQo0GY0oW1Y9Vw0ClTEGGw5nU60GU0oKSkZ9XnE41bB6xGD1qnTC1BQ2F+xZDZbUD3k/83pdKK1zYzentjadOMxHir8Kmq6UFHRH4gPvJifvVD8GZX525Zxuz8uxWM/WIKiUjdmL+mARheEuTkPL/z2S5hzWg1qvn0gJY9797MvYVeomq0ylARZLBbsCb8v8eez7557CtrNGqg1GqiGJjJDOOMM3+IL2UYSKYAbOWSrqQH+8hfgmWcSe0Sv9wy43ctRXu7H3/8ub7/r9u1i4K5SBXH55f0VayO1e8Zr4cKFmDFjxqjbJfKYse47mubmZjQ2NsJmsw2qtmOlGBGlW3l5eVIBBqu8xqdY2yv5/z/YmA7CiCh5YkA2PJR5962TcdYqK/7w3Dv49g3n4aVnz8G0GZ3YtX0ydm5rwKNPvYGCwsgXl31uN2ztDpSVlaEsiTtXkbicTrS0mdHT0zuo2szhEMOM+KqzIokv2DK2icFWrDOiYg3YpEH5CoWAvPzhoZ9hSEDqD90VkqOVNjKxwk+aVSaXbGjpdHZoodUFMn0Ysnv6wQW49v/twvJVgwepX3jzcdx7zWVoPejAzNkZOrgE/b+//B279u7H7NkNKC2qhkIBKFUCVOrhQ+YtVgv2NO0bFMiN5HvnLUe7RQONWg2lauSQbSSuUACnUAkwlIm/l51WbYrnsokLIPT0CFizRt5Kebd7DgAgGFQMm50Wrd0zVlLINGPGjJjnssX6mInsO5LRVhNlpRgRyW3oPDAGGETyYxBGRBHt21OGG275DADQ1lyIW7/3CVauPg4AuPW6L2DHtkqctrJlxH3k5+cnX802hBT4RA68xLbD4hhCrEicTidajfEFW8a2WCvH4tPlDK0YWegd1ooUiVoTX5tuPKxWKyztDnR0tKOjo13WfYuiV/jJJeBXwONWQqkU52QpFOL7tLogfvG95Vh6uhmnrElFgJg5Kk0QGu3gns9AKO9TqQJQKBJboTDTuuzF+GjfbJgPToZCAZRUuXHieWbUz49epRqL2//8CnaHFz9I/HnLYrVid3jum/g8ctf5y+CwaKBWq6FSqZI6zkhSG7SJzy2CgEHVbFILqEoFVFYmFhyKLaOnxz2XLdYFDeRoiYy2mujASrE77zRi9+4crF3biRUrkq+gZbUZ0cQ10jywbFjBkWi8YBBGRMO4nFpU13RhxmwHgkHgrHOP4axVx8PD8o2tBaif0ZmRY5MCn0itgUajCcUlJUldxLbG3BKZWq5QRViBIb55SvG06caqz90HS7sDZWXlKC9PbIZRNFJL59AKP6lSLNmKMenz/7N5FhyWyTAUe6BUCdBog1Cqgqis6UXrkQKc/oWRQ92x6MSzzfj7H2bCaddhxkIHNNog+nrUePmPZ0Kt9cFQ2gOxkmjsOLyjAm8/fjaKSrXwdBdAowtAEICHbjgRX7juGC7+xuFMH2JE//3U69izV1r8QP45mz9YswSdVm1KgjanVQdBUAAYGrLJsQBCfHPZ0rFqaDRDw7eBlWL/+Ec9mppqEAx+CJMp+fBt6GMQUXaRYwXHaCKt7MjZXulhNptlX3BmrN/YkKMaUavVZuXKkwzCiGiYnFw/7rj7PwDEWUo33ro9vFrk8aOFCAQVmFTXlcEjHN4aCADGLAmx5NDlFAOKaO2nmZCfn5/UjMRIfD7xpC5ahV/yra7ifl5/djH8njzMW2ZHt0uLgF8Bn1cJXU4Ah/cWI6+gvyIt1vAtG9o6oxEE4LKvH0BlbQ9efWoGjv2oMDwsf/ayAzjv5mdRUl0KQP4FZ1LpnQ3z0XDWR7j4BjcqKyrx5D3zsOJCI256cBd+efNSfL61HIvPTM3iKNnspt9txIHDLaifOlX2BRB+sOpE2JsNUCiDMJT3Px+52jWhGWxAYWliz1NOW7yVbKlbNTSaaOHbwEqxt9+uRVMTsHz5IlxySWJtogO1tLTg008/DT8GEWUPuVdwjGbgyo4TsTVyYICU6jBJCjVTseCMZKzd2Eh0Rcpobr311qwLwxiEEdEwGk0Q02Z2ht/W54j9VMEg8P6WyTjx5PHVQpaNpNbIgkJPho8ktTQa8WUoWoXf0PfHS6w4M6FikhXLz27DKecNHxDfYbsc3T0d6HAksgqoEn5f8ndoh4ZqyYZsCoUYhp12YRtOu3BwwnD8+HEcOOICkF0nJLFQaYJQKvvbPbs6tHBY9VCpBag1Ajy98rcdTnQXf/8TPPHN1Siu6cZP3+yvdrJYLeEqt0QXQLj/4kVwWNWhuWyj/9+5bJoUrhoaTeTwbeBKoDU14kqgM2bUYsGCJJYcHeDTTz+Fw+GAyST/DZ5svTtPNBbItYJjNGO9+iuZ0OrZZ0tx6JAW1dUlEecyJrNK8Uikhb0aGhpw4MAKHDyox+rVLixa1Jv0vqU2+rF2YyPeFSmjsdls2LhxY8oqKJPBIIyIYqZUAld/bTd6e/jUkWrhICzO1sixKlqFX6T3x0OaKTdr2Vvo8XrQ1HRs2DbTF7+NvmATLOYOAMq4FktobjOjp7cHlgQXEXB0OEZYqVQBXxInwlIVZyS9rjwEAyNskKVqpjlwYM8MHN1px96OWvi8SlROFk9UfV4l1JrgKHugePm9YqCUiu/tfz2+GXvC89RG/z3/2SUL0SkFZ8qRg7OuDnW4Yq2gJPEZhC57tPCtPyCTrs2+9S3ge99L+KHCvN5ZcLu/i9//vhs33/x48juMIBvvzhONJcmu4BhNtlV/xRpsHT4sjiaItrBILJ5++iaYzbPxla98grPPrg2v+CvnKsUjKS4uht1eh23bgAsuKEcS66wM0tjYOOz7KL2dTHCYjrbLWFekHE2kn+ve3l7k5uYmve+hurpi61ri1SwRDeL1KtFyzICikj4UFHqhHTJsu6Ndj5JSd4aObuLocoVaIydIEJYq0ky5087tQp9rMvp6JmPKLBvcvVrYzQUoLOrDV77ZAaASTqcerUZzaLGE0S/K5VupU4nKIeGbtHCDRp34y7QgIDzXDxD/loblP//j/8Y3/+8N1E9L4rAz4NzrdqD5x/V44vtno6TCj+t/vBvTFjjh8yhx+iWtmDI3uYH5mRIMAFAgpoUx0i2vyIO6pbswabom04eCG37/JvbuEYOzstIKKJTRA1+r1RreNpm5iT+/fL4YvmkGh28DAzLpRneoqEAG4iqgWq0GN910k1w7BZDdd+dp7Gtubo6rotlgMCS86qwk2rwuVj4mx+0Wz/XjDbYWLlwYDrDidfrpnThyZB+OHm3GjBkXDZrLmOwqxSORWiJ1Oh1+/Wt59z3aysPJBIdDHyNWsQRocoVscrdYxkL62R0NgzAiGuT1jTPx6weWY9Wao5hc78T0mQ5UVndj8lQXjh0pwq3Xr8Hmj5/J9GGOe1ptAJU13SitSL4sm4CjexZi019PgfFYAW7+4Wf4z5uT8NGbNejr0eAHj36Asy4Uh+W3Gs0x71OOlTqlxQJKSkqGXay3Gk1wuhJvkfzk39PhcWug1gSgUApQKsVVIgOKMrh7cqFUj83qqeWXb8J1dx9HZUVlOOzT6II4Ze3YmBEoCMCe90rhsOpwwjk2uNq12PavSihVAk6+yITSmuy60VA1oxMrbvoIDQ0NAOSdERgrl10DbU7/z2vb3hJsb5qCnAI/lp5vRX4SFV+juf6xtyMGag+tm49OqwoatQZKlbwJZle7GkJQAadThxNPlLfiJBisQHf3VLz8sh47dsi6a5rg2tvb8eSTT8b9eclUJ442r4uVj4nT6/UAhq+YG43UAjhjxoyYVvWNprzcj7a2yNXwsa4YHC+Hw5Gy2WCjrTycTLg3cPXiWIb8R6va+/zzhXA6DWhoaEJFxeDKrWRnm0VrsZRagJNtvYzk/fffj2k7BmFENMj7WyZj/iIbaie78PH7k7DplRnQ5/gxZ54dRw4Wo2H+xBtEnQlf+fpufOXruzN9GOPGC4+dghv/XxOqJ/fg1otX4/r/2Ym7Hv4Pju4z4Jf/7yQsOCnxn2uxfTPxgKC1bXj45vMnX232x/uuR0mNBbkFPQgEVBCCCkBQQKWpQ68rHwrl2KwI6ekswK536/B5TzUEQQFDmQdzTuxAceXYmKe3dUMtPnqlGj2dGhzeXoR2Yw5Kq93ocWpw8NNiXHHXflRP78n0YWaV5+6egyVfsGLKChNMO2fhk/cXoX6hB61783FsZyEuuu0IiqvS+/9/3aNvo2nvvpSsBPqj1UvQ3Z4rw3yzSFQACmGzBeTeMU1wUlXWypUrUVxcPOr2DocDW7ZsSao6Mdq8rvFa+ZhslU487XjSNvGET8lWNo1nkb6PjY2NSYV7o1WbRTO0au/VV+uxbVs+LrhgOs49V6ysl3u22dAWS6lVUq7Wy4Hy8/Nj2o5BGBENMnVaJ5YsN+HUM1tx/Td2oMulxfZPqnDsSBH+9Nhi/O9jb2b6EIniJgjA3CXtKCjyorDEg1VfPA4AqJ/jhNetglIhICBk+CAH0KgHVJsVJlZtVjfTiav/pxHT5lkHvd9mt+OnX7kF6hiGk2ebY7vLsenhc6HT5qJ+rhsqlQCHRY8n7p6PdbcdwKqrjmOU0VEZt/eDUqy+7jiWnmfF/ZefhFMuMWHl1WJF4mPfWoS2A/kMwoZQKAQUhYKuY/85AWdduxcnny/+wj5+y3zYjuekPQhLpdyiPvj9fqhVaqhk/j0VBAGCx4vycj3EUIxIXjNnzozpwtZkMmHLli2yPGa0eV2pmLfV0iI+X/f0pO95OtE2xWji2c9YW+1wIolWbRZNtKo9KeuaOnXKoLlokWabxSsdc8wSxSCMiAa56dvbodOLd4oFASgo9OLMVc04E83461PzcdIpst+eJko5d58GgdBw+JVrm6HR9ldD+LxKaPVB+LLwXM9QaEBFZWLVZmuvbUNhYSkqKgcPUepzu7HwnA8QQAesFvmrQpJp5xzNi79cgWUXv4YvXIlBVXi9XWr8+MsnY85JHZg8O7YhqZmi1gTh84itdNqcIHIK+tv6lAoBau3YbFlNJbVWQKdZB0M9oM3tg0oTgLQqZDCogEqdRSm2DK78xSYcO9iMqVOnYsqUKbLu+xfXzEOXSQGTSUBlZf/PXkeHSvxeqhRIdKSa1SrOIVSpENM+Ur19PPuQY9/xPmYq9y3XY8azH6u1Cn7/3bj//th+hsQ23e/ihRfUePPNxFrbowVd6ZhLZLVaE56FFa942xSjiacdb6yudjgRJVu199prgMcDFBb2vy/RarNosjFQZRBGRGEejxLvbZmM996ejKuu34XZcwdP/r3+65+jqoaVCjT2nHjW4fCMrBu+17/ikLNDi9x8P7S6AHqy7zU6Ked++Rh6u9XocamRV+iH36dAp10Hd5+AZRdsgasHcO1LZsj/SJQpW/o9p7AbwOCy99wCP1RqAUpF9gci1TN6cODTYliP50GpErDn/TJUT+9Br0sDp12HPEPq5l2NVau+1oxXfz0NljY3Sqa2oXHjIii9XXDZtdDmBGCoGD/VYKnW1a5FV1cOoi2qFQwm344Z7z5SvX08+5Bj3/E+Zir3LddjxrYfBQAFfL5YH1Ns021pceHxx5NbHbWzs3NQRVi0uURy2L59OxobG1P2GicZWEmTSJtiNPG047HVcWKINOY23mqzaEYLVFNRMWaxxLaSe1xB2Pr167F+/XocO3YMADBv3jz86Ec/wpo1awCI5db33XcfHn/8cTgcDixfvhy//e1vMW/evPA+PB4P7rjjDvz1r39FX18fzjnnHDz22GOora2N51CIKAX+975T4PGo4WjX4/WNM7FzuwtP/X4xamq78IP738MVX92b6UMkSshV3/4AhcViBdHAlRR1+gB++qet0IzDKpx920vwu7sXo9upwe0Pf4qX1s/G9q2VUChX4cLv/B6LT+tCeVmZ7I/rdDnR3GZGT29P+GREqhJLtlps8vxj2LX5VFRXWqFdqoFKE4Tfp8SHr9RAqw+MiRBp7TeP4PXf1ePAJ8X48g/2ob01B7/79iL0uDT4yj1NmLG0M9OHmHWmLOzCunsO4JXfVODQp1OhhB6bWkrQcFoHLrvrEAzl42sOkKS7uxvWGE/oY6Uv7IHP54NKpYJS0T/kv8ephRBUQK1WoKIiylKco2BFWHyPmcp9Z6YiTIDfL8T8M+Tz+dDX14eaGkXCq6NKA7ejhVKpmD9UUFAAADCbzTENKI9XtIHmQHZW1cghGMyOVZNT8X86MOjp6wPa2wEp9vD51Ni1KwcWC7BkCTBg8fCsIVf4OjTwGunnPBE2WynKy9sBpGjVyNraWjz44IPhMtCnn34aF198MT777DPMmzcPDz30EP7v//4PTz31FGbNmoWf/vSnWL16Nfbv3x9+0vjOd76DV199FRs2bEBpaSluv/12XHjhhdi2bZvscxCIKD6ffVqNh377JqbPcuDUedfj4nX7cc/Pt+K5J+fj+T/Pwx13/wcqVfZXXBCNRDHg/FyfG4A+d3wOjf7djxbjK7fvgUIJ/Pj6U3H9Xbvwwz/+B/9+OYgXf3sBlq98I+G2y5H4Qhckwwf9K5Ma/g8ACy9oQmDT6Xj+gZV4wpEHtVqA36/AwtNt+Mb/7hgzA/Mv+PpRXPD1owgGgUkze7BwZWwrHE1kFVP6sPb7n0ZcwXG8CfjF5yS73S77jKNTvrEPSh8wY8YMTJo0Kfz+7q5u+D/+D2666SbZgwOaGEwmM77926exdOkSFOQXjLq9xWqB6tAOXHrppaiuTuxCe9UqA1paFuOxx3IQWsgZAODzzUFfn9h2uWdPQruOShrA39TUlLKVBoHBA83Ha5tid7fYkjdwYU8hA5cZQ/9PAwElBAFQy7i6dl9fH3btAp59Fnj4YaC3V4mPPz4Jjz02FRUVYlXWhg1Afb1sDxlVPIslJGu0Fsuhg/sTcfy4Fh6PArNmieeA27Zti+nz4grC1q5dO+jt+++/H+vXr8dHH32EuXPn4te//jV+8IMf4NJLLwUgBmWVlZV47rnncPPNN8PpdOKJJ57AX/7yF6xatQoA8Mwzz6Curg5vvvkmzjvvvIiP6/F44PH0n9y6XK54DpuIYtDaXICgoMD0WQ74fErk5vvwvXs+BADMX2TFlWsvRXeXFoaisXGhORYNrFQiSlbAp8Di061QawTocvw4+zJxgYDZS1vg6T0lZY+rUYunFgMH/TtdTrS2mZMa/i/tp+e0bbjsmw7U1FSgt0sNr1uJfIMPam3ks+dYq9BSOdtsqE6rFsd2G+Aw6REMKFBQ4sWskzpQVJH5yqZgEICArFt0oKdTjUMfV+HoZ3no2V+NSfU6TF/Wifzi1LYnZYJKLX7zy8rKZK/adDqdMDebwgtyEGXKH+8+E932s4eFWPEwmXIQDCoitPpqAGiwb58AuZuOvN7T4XafhPJyP/7+d/l7XaMNNB+PbYrvvw98+9vAddcBV1wBTJ+e/vNgmw04flxc5bShoQH5+YuweXMhurtVOOOMLixe3JvU/geGmMeOAVKR786dOWhpqcP69W9h7twa/OUvpbjjDj3uvTf2n6l4w6pEFl1ItgoxWotltJ/zRJSVAQPv37S2tsb0eQnPCAsEAnjxxRfR09ODFStW4OjRozCbzTj33HPD2+h0Opx55pn48MMPcfPNN2Pbtm3w+XyDtqmpqcH8+fPx4YcfRg3CHnjgAdx3332JHioRxeDIwWLMXySuLmc25uOa/+qfo9Tp0EOnCzAESzGGYCQnn0+JYFABQMCys81QKPuDIiGohDLF1Z2GQgMqB1SctbaZQ+9LvJLnyM4K/POXC7GxqxhX/+hDfPDyLDT9R7zKueGhNzH7pP6Byw6HA0CkyrSRKOH3pba98sgOA569bw6CAQUmzeyGUi2g06zHM/c14NLvHsQZV7RmNISyHc/Ff/5ejaXnWVA2OTvacI7vLMDzP5kFv98HjaEVwc4CHPu0CC/+dCYuuu0Ilq21RG2rkYZmJyrS5wd8g5+sPX1KWI/morDcK2ubZn5+fkqqNs1IbDA5kZy6O/UjzquLjfi7qFAIMJT0/+45O7QQBAWCQUUK5rLpAOig13uSvoCPJpHQy+8HQveh4PeLNzW0WpkPTGYHDojnvs3NwJ13AmecAdTXiwcdaUZaKuZJvfZaEZ5/vgaXXAK43fV44YXZEARg6lTgD3+owB13ABddlNxjSK2B+/YZYLcbsGtXM7ZtCyAnR8C+fR9h3z7g2LEGHDkyEy+//Erc+z906FBM21mt4nVeJhZLiNRiKVe4m2gRc9xB2K5du7BixQq43W7k5+dj48aNmDt3Lj78UKwcqRzygl1ZWYnjx8W70GazGVqtFsXFxcO2MZvNUR/zzjvvxG233RZ+2+Vyoa6uLt5DJ6IRnHFOM045U1wSum6KC1+9sT8I+8eLszFzTke0TyUZ+HwK/P3Z2bCZc9GwsB1nnNccbkPdt6sEU6Y7kTNOW/jS7Td3L8W/XpyGr3x7N668JXVtDZlWP8cJT58KWl0Qtz7wWfj9ro5cqLVeKJRjby7ai79cjqUXvwKNzosn/t+1WP6lN3D9Vx+D+eAUvPyb83HB7e9Dox8YRChQWVmJkuLRB284XU60tJqhTrQ0Yej+BgQo0r+dLieeuXs6Vn1tG2avGBzOubs1ePzW1SiddhiV9fGFN93d3eG/LRZrUsfd1FiLTb+bit3v5WPyfBtqT3DCq9Ohs3PwMSUbMMWzr2fvWYizb9qGkhkH0dZqCrdGdndo8NiNCzF9qROltYNngvijtugmQhEevg0A//ztFMw9N/R/asnBn/97IXxuFVztGlxyxxEsW2tN+bybTX+ow7k3tGTFXB3KTs3NzbL8nhoMhqSGZUeTX+SG3++DWq2BKsEf5EAwCL/fh6LSAH64fl/4/T/9xhx02lVQa2Lft88r3jxSa4IjjgFxdaohBBVwODQJV5sFBpzOKRSD52PF29YZDIqVVe+9B6xZA1RWii12drsY4KxYkdgxpkNHh1gRduONwP33A88/D6jVFSgtnY++vt3IyRkclMg1T2qg7dtPgFpdE/p3HsrKgN/9TvzYk08Cr76aXBA2sDVw504Pduw4HXfcYcShQzNQWtoebg0UhGIAOeHOulgcPnwYO3bswM6dO7Fz587RPyGkvLyciyUggSBs9uzZ+Pzzz9HZ2YmXXnoJ1157LbZu3Rr+uGJISYMgCMPeN9Ro2+h0Ouh0ungPlYjipA4tQT+wRc/rVUKlCuL8i2O720CJ+fNvF2Lbf6qhVgex9V9TYGzJx7rrm6DRBvGT20/Hz//wNmqnJHXblEK6XVq4HDoE/OP7CvL7j30S8f1avQ8XffcJKJWlET+ezQRBhZo5RzB5agXef1rA2ut7odE1oKEB+PRFA2bPng1drhiAOJ1OtBpNKCkuGXaTLpoWmJO+cHQ4xJsG0Wakud19sHbuQ3Df8DIFj+9UHD12GB0eWwKPrILNboctyZlSLS0KTD/zEyy46G1s33ABPvvXShTVzYH1lM9Q2XAYap13QPWqEh2OxG+SRP9eDebuOw021264je0AFOjo6H/MQLAB7R12BLSD21d6esQVjmtqamCItCRWjJxOJ9paTdAMCEiP7SzErDPFsr2tT83HqetMWHGpBU6bFn/+/mzMONGJkhr5Kqg/+FsVgoJY+yIAUKkEfPC3KuQW+qBQAqddbmZFMQ3S3t6O2554TpZ9LVB6cOutt6K0VN7XjP/6yVbs370PDQ1zUFGRWOWj1WpBU5O4D6B/HzfdtxVNe/ahpqY65t//v/76ZBzYUYW1132GJWcej7rdL76zGj3OPPj9qVoFdHhb50jh2LvvAj/+sXje/umnQG4u4HaLA9lvv12stBoy3Sil4qna2r17EpYu7cH+/Z24/HLgwgsV+MMfFNi48Qz85z/n4aGHzFi4sC9cnZTsCoaR6PUG/OMf4r8Vik4Eg1bs2iX2L+7bV4reXi127Uq8itZmE1/Ply1bhkWLZqKqKgilchGKi7sgCEcxY8ZcLFiwAG+/LQ7MX7Agvt+zHTt2xPx9GanKS5rNNvS1JNkqvFRU8UXT2oq4wum4gzCtVhseaLZs2TJ8+umnePjhh/H9738fgFj1NXDIptVqDZ+AVlVVwev1wuFwDKoKs1qtOOWU1M0rIaL4DHwS1GiCuOnbn0XfmGTxxsvT8YeNr6O41IOjBw34/k1nQ5/jx2Vf3Q+FQkBBYeZnB40Xnl7xAlafO/5mC8VCn+tDfrELwNgLwvxeJQRBCYPBgJPOs6OqqhxqjXj2plRoUV1dDo2uv9Kt1Rj7yavcFUSVlZUoCS0B5XT2z0ibu8IF07YvYFLVIZTVdUGlCSDgU2HH5qkwFGswb2EtCkrjmwtls9tgtDhQXlaGsrLypI6873A9vMXFOOHEKTjhxN1ot3+Erc/VYd/r52Hni3qce8vnWLD6OBwOB4wmKywWS8xLlUc2+HsVSfOyHlgbz0fh6Z/DrTiM1r5OHD/YjZZPFiKgcOJYy17oHJHaOBXIzc1NerB+W6tpUEDq8/rgdIpBW6cpD7NPFrsapLZIuYc9/+PhqZix1InC0tDrgALwexVo258PQeB8SRpOGv5dP3Uq9Dn6hPfj7nMDzfvD+8tWQ29gdHRIrfEmGGN8HXB2LgIAWG0taGraF3U7rX45goEAVCoV1Or4LqV7e1QQggqoVAJ8PiWUSjHh9vuUyMv3Qa0RorR1Rp951t0ttkIWFQEuF+DzicPnP/lE/NiVV4ofAxJbRCDWICORVQAPHLgEeXmfw+s9Cp9PBY0mgEmTgFtvBdzur2LRohmYPx/h/cqxguFQdXVAY+NxbNx4MerqWnDoUDGampwoLW3HwYNKzJ27Fy+/vDfpxykvL8dJJ83CF78ovr1rlw0vvrgfPt9cAMB//3fi+47n+9LY2Ai/X/zZAMTXjrw84OWXxUrFdevEKsPRhtzHa2j7ZioCssmTgZ//HOGfmdEkPCNMIggCPB4P6uvrUVVVhc2bN+OEE04AID4Jb926FT//+c8BAEuXLoVGo8HmzZuxbt06AIDJZMLu3bvx0EMPJXsoRMMEAjwzTBZPrtMj4FeiuNSDYBCon+nEI8/+GzdftgZVk3rg9aqQm5/dJ6FjibtPfOnT6dlqOtZMnWdD0C8Gmdf+qP/E1NWuhT7HD1USKzypBw75T7KCqKXNhJKSElRWDJ+Rdu19bfj3k1Pw94dOQ1e7FiqNAL9Pifln2PH1X+1HWW0hgMK4HrPP3QdYHMjPz09qBhsA6DVFMBTrUFlZAZ9XfAGYteo/uPhbnbDsnoeAvyD8dRlNVtRUJ/79EgNC6XsV/bi/+tM2bP5jHd789Xno6VRDpREgBFWYfpIZV9y3E4bKqRH3PbSSKxFSS+TAgLTLeQoaX61GfrkOrnYN7PZ2+FViRZqnL4CODjsC6sTnq0mtrpJbHtuNVx6eihMv6MQJq8Xl4Q9tM2DdXYegSvpMnsazktKSmFZwjKaruwve9BV0xK3/BkbkwKuysmLEkH2gj3Ti92nylCo0NER/LSm//XW0m+2YWj8VU6ZMiflYBQG45+YT8OPH+28uP/aT2bjl7v04diAfL/1pCm5/cA9+8q05cNhV0Gg0UIZ6Jp2O0WeehYpgAQyvVOv/WOyLCFgs8xAIzINCISAvr2fkjQEAUwCcjYqKADZujG1Y+eLFOpSVLUVh4Qnh9zU3N+OTTxpx1VXdMQcaySgqAm66qRn/93/d2L9/BQKBfBiN9SgsdONHP7Jh7tw5AOYkvP+hVVi7d4utrFu21KC5+Vy43aVQqYBFi+T5emKxdWsh/vAHYMoUsXqwtBR48UVArwesVuDEE4Hc3MhD7uM1WvtmrPPNYjF58iw89VQAc+fGdkMwrpfPu+66C2vWrEFdXR26urqwYcMGvPPOO9i0aRMUCgW+853v4Gc/+xlmzpyJmTNn4mc/+xlyc3Nx1VVXARB7zG+44QbcfvvtKC0tRUlJCe644w4sWLAgvIokkZxOP+2rsNl0uO1/7kNDQ6aPZuzg3eX08vkUKK/qxfHDhZgy3QVBACprevCrP2/G1y8/HwG/AhpNBtaTHqc87lBFWM7ErAgby75y93vYtXd4wKDL9eP2xxtlGTJvMBhGDGVi0dI2cgXC6V9qxTnXNEOlFtDXpYLPo0JuYfSVL9OpekYPiqvFtj7NgOMRBGDh2cPbLg2G5BZAaB3leyU58+o2LLhwG/bu2YdpUxagpKgSOYU+qNT5APIjfk5ba/JD4aUgbWBAajujE+2mEnS26lA87QgO7DuGAkc7/F41AsqFOHJsP/QdsVw4jkSJQOgif+qCbnzjt3vwj4fr8fmbZfjSnWLlBV+naaLrv4ExuAXS6XTC2Dr8hsRIlApxDE9paSEqK6LfKHP3udGO+FvQPW4ldDkB9PWqkJMbgM2sg8MuPmbNlF50d4lfy80/3Ir9u5rQ0NAQfi2697sN6GwXZ54ph8w883mV8HrF6rJgqABAqwtCoRTg6VNBrQlCpxeDvVgCtX7i4wgC0NUV+82Znh4Ba9YUj77hAMGg+EehAGy2eQgG1+BnPxPnnQGJVbLFShAAnU7AySd/gjvvzMMZZ5wR+ogeQJEsjyFVVH30EfDgg2Llntmci/b2eiiVuXj+eeC73wW+8x1ZHm5UBw7o8de/AhdfLK646PMBnZ1iZdinn4qrd+bmitvKUYW3Y8cOTJ16GgyGOtTVeeHzKfDKK10wGvfB798T13yzkXg8N+HKK5/CX/5yVUzbxxWEWSwWXHPNNTCZTDAYDFi4cCE2bdqE1atXAwC+973voa+vD7fccgscDgeWL1+Of//73ygo6L8T8atf/QpqtRrr1q1DX18fzjnnHDz11FNQqbJsnW4aF1paCtHVpQvdyUj8jthEs27NZSg0ePHDn72L+unyDUSmyJRK4Ov/sx3+0Mwq6eKmfqYTDz7+Nn5x98kZPLrxxyNVhE2wIOyNZ+vx0b9r0HByHkrnZPEt/gTocoLQ5YyNqslD2w14/mez4bTrcP0De7DluTrsebcUUADf/O3nmHtq5hYmEQRgzgpH+G2fVwGfR4lgQJnR0OXYzgK89MBMuOwKzL+iB00vnohj26ugUgm44eE9mL4s9a9TBoMh3GJ5+f/YYbVa0bR3X6girgKA+LEF/7cTQHIzbGx2G+ymDqgGtF1pdAIu/94RHPjUgMe/PVds8U7w/8Tn1qF5TymcbYWYucSV1LESZQPx93Nw4GWMMwj3+8RzMLUmNQvJqFQC5i114KU/TUF1XR9ajuRh0XLx+b7bpR5xQP837hTDsWgzz/buqMbnjXU45czDyCvw4B8bFsPYWoRzLtiLU846HN73bx44HV1OLZQqFZSKkeekdneJoZlCCRgMo6+m3BlXyDYS8bgGz2CLvZItEb29J6O390T8+tcqfO1rYovdqlXAvHnyPs7jjwOrVwPf/Cawa9ch3HKLE7fcUoXzzy/ANdcAs2YB558v72NG8vWvW1FXVwmzGfiv/wLmzBHDuRkzxMULgkHIGjgePToVzz13Cg4ezMFDDwHvvAN0dHRh9+65uOACC267zQO9PvkbgRs2FGHdugsxbdpW3HTT6NvHFYQ98cQTI35coVDg3nvvxb333ht1G71ej0ceeQSPPPJIPA9NFDenU4uuLvFOS1mZDQzCYmO35WD7J+LqKf/72OYMH83EoFIJWLJi+Mq5ggCcsNyCZ//9jwwc1fjl7hNvvOhyJlZrZPP+Qnz87xoUV7WgNPEqf0rShvvn4Iv/fQgafRDrb12ES+84iFse2YFD24rwt1/MxLTFTujzMvOzKYVdlqO5aN5TAIdFB5ezBB1dOSjL0aKiPDNVSC8/OANrbjkGV3cHXrrvS1h1cxO+8dhhHG404J+/nYqb1++CVp++VVAFAfD2qWA7MBXe43NQUFCIwnIvpi9xQpeb/HH0uftgR+RAdNaJTtyyfjdMh/MSXjHSfrQOrz1zOupmd+P2J+S5E0+UqGQWKJFz9dqAX3xyU6lTU5mr0Qo4e60Zr/21Fnu3F2H2IifOvVRst/b7lDj/iujthCO1gAoCoNDuwwmnAD0eBbrdCpx6bv9MpwMH+rdd/cV9cQ0xVASBmTNnYNKkSaNu+6PvzYWjQxXzKqCCAPT0iAGgQgH4fEooFOLsNABQKAUUhQK4zk65QrZotAAAvz+It98Wq6R++Uvg7rvFFS3l0NzcDLu9Fl1d3di1qxPNzc1wuWpx5IgOBgOQkwM4HKPvRw4KhbiIwmuvAd/4BvC97wHt7cDs2al5vPfeOw133WXCDTdMw9SpwL33AkuXHsPLL7+Mf/7zdqhU+ZBj9FtJCbBgwQKYzbG15nKyAI1bra1iGW9RcQ/0evlWbxrvPn5ffLGbM8+OklL3KFtTKikUYhtfp0OHyure0T+BYuLuFV/6JlprpPR1a3QT6+vONsGAArOXO6DRBaHPC2DFxeJFzYylnfD0qDLe7nZ0RyH+ub4eXR0a1M3phscnwHpsGp7913ScdKEdF377iCxhTzwCfiVmLXegvdMKtc6L+auOAyjH9GVOeHrS31HQvLsAz/xwEfzBHkya4Yc+R4dOiw7P3zcTl915GAvPbpf9MQN+4OjOQnSaxRt8RZUeBANIqB04r1S82rK16jkKgTLG7/NDANBmNKEtjoVNhlIA8PmSf11LdUUYABQW+3DVLUcBhAaSh9okK2rcqKiJfs4drQVUYrPk49jhUlhNhVCpgzAU9WH6bBsqqgavNu50OmFsM8Y0C9PpdMLUaoRaHducxW/e/g727W2KeRVQh0OLh/+3Aff+bAcAoNOhwcsvTMGFl3yAVzdq0NmxFHd8/wgA4O4754khm0YNlRwzEAbo7lbDHwpBFQrg4EHAaBS7Nb71LeCuuwCdLvH9e72z4XZ/F/n53Vi8+CO88EIVdu/eg+7uAvj9alRXi1W5Hg+QH7nLPyV8PuDCC4GVK8VQ7KWXgC99KTWPpVAIyMkRA9jp0wfPQ1OrBdlegz74IL7tGYTRuCUFYTXVaYrXx4n/vCfWHK84vSXDRzJx+HwKdDl1UKuDUKmE8MBvfU4AH22dhCd+vRh/fuOVDB/l+CAIQLtFHABaXDaxAnKXQ7zjmW9IfIh3NnH3qvD1k1ZBpRLw2EdvQpeT3nAmUX6vMjzHZdE5ViiU/XfnAwEllKrMfh2b/zQZc09tx8prxDuqFosVu/fuQ0NDA/5292rsfLscJ16YzCqR8Qv4FBAE8XtWOfcQBnb0BAMKKEdoKUqFF34yE2u+8ym6FB+gYU4DKkIz0jqMOvzh23MxY1kncgvlq+o7urMAz/5oJvJLfCgJzW9zmHVw2rS46p6DmLE0vvbGvOJOQCHA3aNGT6ca+cUMxyn91JqRw51YOJ1OmIwmaDTJX9JKYYg6hTNZ247nYPsHpbCb9BAAVFS7MXlGD+ae0DnscQdWu0n/NhgMqKgcHDId2l+Aza/WwutVosupgVYXRF6+Hx9umYOLrmjGqWfZBm1vbDPGPAvT1Br/CsqxVumZjYUAPLBaxdeTY0dK0dqshtPpRHmFG8ePnBbe9tbvbsG+PWLIFuvMt1g99tvZ2LWrEO4+Hfx+sSVz4MIDnqRPFbUAtOjpKUBjYzl6epTYtWsxBEGAVtuHBx7wYfHiXZg/vwRqdTd27Yp9zIO08mKsKzAO3E6jEc+JtVrgN78BbrkFqKoSP5ZotXE0gqCAJhQwX389MGkSIC027fUqINeErB//GLjhhti3ZxBG41Zri9gKWV3NGVfxCAdhZ8RWVkrJ2/lpJZ54eDGmzXJApRaQk+uDXh9AeVUPPn2/BiXl4yO4yAbdLg36esW7mxU1yQ6zHltcHeItzbxxEoQFfAr0dYn/lyPNVsk2Uxc64fcpoANw5Q/3h9/vsmuhy/GnrC0nVkoVoIpyIajRBpNamTNRNbO74XOLZ+aL1m2CUiWuftPVroE2J5D2ICwYAEomdaFryDViSY0HEOQvr3rxwWm49oH9qGsY/JzVuj8Pz907E//z3Odx3VFXaQIoLO2Dy54LW5se+cXdo38SUYqIoUzi4YYpiWqygSbP6EFhsQ/63NhC7O7ublgtsd8UsLQW4v1NtfD7lVDAC5upAK5OPz7ZWoO6GXqs/crnUCqBjlB/3MCVagFxcpbPPzy03vxaDU4+3YaTzxAH+G94cirOPNcCnT6Av/x+Oiqq3Jg5p2vY58Uq1mDL4eiAIiDA1GKEqWX0AM3r1aKgIB+//vlSFBQ64PPqUF3zCUwtRvR010Or7YbFah10DHK2wkpKSw1QIB86bQ8UShUCAQ30ugDUagFd3Rrodf6kFqzqdGogCEoEgwrYbAOr6xTo68vD4cNBnHXWFAgC8JvfxDvGZwqA05Gf342bb/5DzJ916NAhGI0afPZZHg4e1EGlAmprvVixohtVVWI7aqzhWiwaGpqg188EAHzlK+L7LBagtzcHZWV+FMg0vei558Q2z1gxCKNxS6oIq65hRVisnJ06HDssrvRy0inx3wWixOz+rBwHdpfg1HNaYDXlocOWg55uLQ7vL8ZHW2twytkpGYgwIVnb8gAAhcWemE92x4twRVjR+AjCvKHVPxUKAcoMh0fx+NqDkSfQ6nIDuPV3n8uy8mUy5p3ejl3vlAEApi5woau3D13WEnzSNBO9Lg1KJ6W/Zf6rD+4DAHRZB79fmxPA1369R/a716Opa+jGB39tgKGhFb56JXweBTy9Knz89yoUlHplrygJ+JSonTM8uK+d3ROeaxSv4qoeuOy5sLfmoH4+gzAa2cGDB2G3j7xSoiNdA45S5OYBNyZGEgiI5w52mx12W+yrRx78fAm6e9tx0upNAIAjuxcAUOCEc3bik39/AX9/xoCGEz8GIIZelZWVKCkpASAGQOZmI3p7eoaFbx73FPj89vD7zcYpONDkRsMCM7zeWpjaumAotoT3Eyu/3w+FAJjajDC1xXZNoBhy3KOZNq0dTXu1cHTkorLShcVL+tDeUQmbyYspUz7G/t37wtsqAwLMzW0wQ95z4srSJtRPXYW2tunQatW4/ur9mD/XAb9fgbffrcGSRXaUlSZeFnbXfQvR4VBBo9YgKKjgdqsRCIrzzgAFBEEZ16qckfT0FOCxx+4adbv2dhWCQQAQoFQKEARAEMTZbAqFgGBQCZ3ODY3GDylk27BBhaampA4PJ564DVOnTgEABAaceufm9uGhh1pQX1+U3AMMEIjj1J5BGI1bbW1ivFxT3ZnZAxlDvJ7+C8uCwrGxAtt4UFLeh0u+sh9X3zT8AvmpRxbCZs7NwFGNT1aj+L2caNVgQH9FWL6hD+MhCutxindW8wy+tAchqaDLDUCX4XBWEIAVl5hQUOrFW0/X4fXf1kMQAnD3rcTUhZ1Y98MDqJmZPb87utxg2ueVAcC6Hx3Ey78sx/uPfBXv/UoHlVps0Zx/Vjuu+ukBaGVu0y2v68Omx+tw2pfMKCgR79b3ONX44G9VKK7yJDRfpbiqB8d3l8Peph/0/lgCj5EYDAZMnpzcqpmUPTxuD/YEdNj95ocxf47b7UZB/uASj1f+VIe2o3lY982jKK0a22MJVKE+rrLyMpSXlcX8ee3Ha6BV6dHQIK5WYz1SD3evBg0NXtiOaNHbU4eGBmc49CopKQm3L440LF+lK8XHH+TCYnWhy1kMl6sbjs49aGqyweVaDJP5KATV4Ooev2/0VSBHm0s2lNPphKlFPG6pXXw0vb15EIIlmDuvF0tP9EJafbesfB8mTapCUVHDgH23xTTbLBFFxbvQeqQR8+cbMH1aHQBxdtWqs9qSPr/4769vxr7de9DQ0IAnnz8PK0604MTFVnz/vqVwduUgV++DVgd0dWmRm+uLq8K906kNV5tZrbHNcpMMDIwGrp/gdufCPeB+V0fH6D8roxEEwOFQ4cUXgX37xHZMtboQHo826X0PtHAh8Mc/iqtvxoJBGI1bLa2h1siazsweyBgkpKC1g6I76XQjFi61RvzYvBNsUCrHTrVLtrOFgrDyCbb4gCAMrgjrGwcFIN2hICy/KPmTNBJJgUpVfQ+ue2AvDBVeNB/twI7tzZh/whTUTC3N7AFmCbVWwBnX7UHlir9h5rR5KC6qRDCgQE6hPyWh7JX3HMLrj03Gzy47AUJQAYVS/J1edHY7rr73YEL7LKkWnwTsrWIQ5va4sUetw473Yg88Ilnk9+DWW29FaSl/VsaDQFC8Wo4lDHE6nTC2mhAMDg+CP3uvFLa2HDi+1Dbmg7BE1dY78MmWaXj3nzOhUgmwthViwUniGBJ3nwa5edFvQI8USs2a1YHXX5qEbe9fCqVSwAWX7cSMOaXw+8rhWO7C3IWlKCoRz32kYflqTeyhicFgiGn4PYCYWiIljZ+UYltjKXS6IA4fLsChgwW4YK34/djWuBLt9jxcvq6/gs3U0haakRZbyBarI0fzsenf5TCb9Ni5z4OrvmTB9HqxlfTBXy3G176yH1WV8tw+7OlVY/lSC3TaIH743Vfx7zd9+Hz/xfifb+zGH56dh1u/thPFhtgLEe782QnocKih0aihjKGc3NWlQTCogAAFCvK8UIeq6bt6NMjR+UPtoFrk6H3o7VMjKCjQ0aFCbW3CXzIslnnw++fhvvsUUKsFBAJiyBgM1iEY/B42bPDhyJHE9z/Q+vXApZcChw+fHtP2DMJo3AoPy2cQFjOFgoFLugkCUFndi+0fVeKjrZNw7sVHIAgKHNxbgkKDB8tONXFFLxlZjWJrZMWkiRWE9XapEfCLV+h5hW7YxkMQ1ikFe6xeldPeD0qw+YkpsBzNxRdvP4Ttm+ux9/3zscmjx3UPNWHJF2yj72Sca9mbj7/eNw/dztNR/INd2PSrWTjwcRG0+gBu+PVeTFkgzy/YwBlEZ32tDWd9DXB3ixewggDkFPjQ5wf64li7QGqNKq4WK/tsoSAsGBDDi2QGl/f1uYFD++H18ndyvIk1DDG2RpnXFTq9VGS49VsOgUAAyoCADrMNHeb4ng9Lqqw4sGsufF4dZsz/BAr1fuzbJY4WVGmd2L+7P0jq6OgI/3ukYfkAcM2NNnQ6nCgt90CtVgIQt7noSz1QKgsB9LfeGduMMbVIpmIe10A7Pi/BzFkunL3KjLa2HLy4oR7/fK0WZ51thD+gQUFBetrw//a3esyZ3YRl899Dh/Ns/PHPc3HdVQcwe6YTgYBC1lVE/X4l7O16TKruRTCoQF31QVRX78Dv/rIIVnsO9Nr4qsK/81//QtPu3WhoaIhpzp7FakHTnj04aLwGhkI9Tl1qRIupAP/5rBpXrt2PqvJe/OSR5bjmkr34xR8Ww9mVB78faEuqG7X/7pA04s7n67+wOXpUiepqyDYwHwC6umK7QcogjMalQEABY6g1srqqE/axPbYgfRi4pJ1CAfzzb9Px7r8nw9hSgM4OPTo79Pho6ySYWvNx0+2f4dpv7hxTw8CzmWWCtka6HGJbpC7HD61+fKwQ190ZqggzjN2KsN3vluKT16sw80QHTr88O+YyvvbINJx/y1FUTOnFQ19ehjOv3YmZX3waZTnL8e/fnIppJzhRVJm5oCPgU+Gle1cgv1CDK3+8H2pt+p8bN/58Ok6/ZheOH2vD3+5diwu/3YKv/V8T9n9UhNcfmYqbf7sn6oIDsQj4QzOI7HbY7XY4jRX47MXzAQBLrngNe/+5EvbDk6HJdePk61+EoSZyRXE0SgAF5Z3iY7QObo2Mp/pjqO7uLvgPxddeyVbKiUFaKXc8nMuEWyPLylBeXh7X51ZX5KB+mgPlVV0oKlUCEFv/Zs9WQKUyADCgo6MDVqMFVpP4R6JA5GH5xw7n4bW/1cFi0qO80oO1X2pB/QwxjP/lffNw7TcOo6JKDJV8cc79UgDw+VJzzuDo0GL1eWLl1aRJfbjuhoP43aNzUFZeA7c7F/kF7Sl53KF6e9VYsOAojEfcOOWkvZg1U48nn52F22/dJa6qKOMCMacuN8Ph1GFSdW94RteCua3IyyvG48/OS9vvx3mnf47XtqzE/z6+DGp1EDes242q8l54vUosXWBBscGD/Nxe+GJooR2N25OPoKCCQhFEYZ74c9jdq0cgqID4aqSA2Zz0wwwRW6rGIIzGJbM5D4GAEipVEOUVLgZhCRAEsBIpTV57cSYu/co+rFp7DBeeuA5fvOoANn7wN3R3aXDbtaux/PQ2zDsh8Zkt1M/aFgrCJlhFmKtDrJ4qLB4/lRpSEJY3hlsjj+8pxPt/E3sOsiUICwaB+oVO5BX5kV/sw/xzjuNIK1A+1QW/T2zLyyS/R4v9odWNr/rpvlG2TtEx+BSYtswMb/5B7H8tiGUXikHU7JM78drDU4Ekq6tV6gEX2mVleOap07Hq+oPw9Gjw7p+vxulf2YsFZ+/CgY+qsf31tfjyTz6Ied/i/CETtPk2rLxmN4qremAxWeHqSr76w+32YK9Sh51bY2+vXBhkK+VEEBhHQZgkPz8fFRWxt+nt+awIH7xVAVenBgoFcOo5Vpx0ug1KFbD+57Nx5nlmzF0s/h5ajZZB1ZlOpxOmVhM06uGX7i8/NwUnnWrHCSd14P23K/DU+hm45qbDmDG7C4Hg4IomTbjFcvRZW+JjGqHRpCYuUKsFtLXmYvKUHgSDQFGRD1+59jD+8lQ9WprLUFT0JoDUz8j1+ZVwOcVugWBQgaWL2+H3K/HbP8xFe4ceWq18QdgFqwfPapOus1Yss2Dh3HZZH2skOq0fN125C51dOpQWucPHodUGsebMY1AogO9e/0807dqd9Fw2p9OJv7xyDpYtcOGcU7ux70gp3vl0MmztKnS61HB7C1CQ55VlrICzW4ccnQ9KRRe6YjjNZxBG41J4UP6krnH1optqA1sjGYSlj8+rxIw5YlpbWtGHVWuPAgDyC3xQKARo0vTCOBFIrZGVNRMtCBMrwgpLxs9slvHQGikN/M81ZE+VnrdPFb5oXbrGArVGrE5yOp1w9wbR6TLDLfhkbZuJdV9OpxNBn3jqqlIHocrQWWzArwzP0qxfYh30WhkMyBcW5ufno6KyEkJAj1PXCgC8+OCvKpxzpRdAJSouDuLjv+VGbJWKxuf3Q1AAVkcLDA0tCAJoCo0ZU0CRVPVHMI55UkColfLIfuzZswfFxcUxPYbb7YZerx99wwT2Ice+I+nr68PBgwcxc+ZM5OTkyL7/SMedbSs4Ss8pyjSfk4/23JLIuW53d2Ktz1veqMIJyzuw4iwrdjaW4PUXa8UFSlbaEPArkDNksZShbZCmKG2nPd1qnHyGDWq1gPMuMqK8yo0//246vn1nE4SgApoIrX1i5efoIZ6pNXU3aL505VEoQ/MOlUrxJkxtXS9WnrMPx4+dBJ0uPa+Ly0+ywdGZDw0QrtJavswGv1+JP/55dtp+ZvNy03ceYLQU45lXToDJmofaqm586fwDmFQldkr89NHl+OY1n4e3NRgMqIzjNSaSk+f+HR/u/jr++UERcvV+3Hr1NuRrD+Dzz/bD7r4Ml622QBdnW2gk3394Fbp7tPjCyf/Bi2+Pvj2DMBqXWlvEXvjaWleGj2RsYfCVGV3O/lVTvnjVfpSU9Q/l7HJpkc8VPGUhCIDNJFWETazWSKdUEVYyfn6Wwq2RY7girFda+bIwe76Gxats4RtIa791FG1tHgAKHD3QCb/gxKGje6HSSCesCvj9iR+73+8HBAWMbSYY26LMFhr6Od4SAIAmxpUZkw3sIn1++eQ+ePvEU+gvfPszKBTiBWVXuwbanIDsA/OltjIAmLF08PEEg/G9cIcrQqoH3+V3Op0wtZlkqf6Itb3SbrdjZ5wVZEjlNWkK960QABxsSc3ORzjuSCs4ZkIwzUHYSKssDuXp08Npq4BK44M+txd5htGfM9QQZ4XFo9ulwYKlDihVwOLlHTCUePGXx6ajurYPPp8S+gRXDfb5lOiwa1FR5UEwCCw5qQMBvwKP/3oW2m26tFUZxWvSpMED6KVQbNr0dqy74tcoLJyFgbPNUuWitc04ftyE4wfEt6VroVNPtmDRgnZoZZwRli1eeftEnHWyBYvn2vD2h3V45M+L8fWrdmJqbRcCAQVUKgFynpXk6V349lWvIievFoX54nmoxQJo1R4sm/UOOjvlWQlUrezDDRdtwtOvnxXb9rI8KlGWkQbl107qyvCRjF3i3W5W06XDTXd8htJKsULpkqsPhN/f5dKgoNCLwqLxU8WTSS6HFp7QxetEWzWyy5H+ijCnyxnx33KRVo0sGMPtnr1d4s9jbqE8d4K7u7thscQ3L2qo5V+2otsDdFvEi5KeXjE0rp1cjut++RnyisR1yZ1OJ1qNJqjV8S3ZPtBIK6FF4nQ60dkiXpRodSNfNPr9fghQoM1oQtsoF8KxGDgr5bpfNMFqHX6ZoM0J4LpfyN+uaSj3wt2tgj4/gCt/dCj8fle7BhpdYhdp4l3+wRUhphjDSLnEW0EmrnhnQk114gP9nU4njKbh+3A6nTAaTUktFhCN3WaH3WYPzZQqk3Xf4e9JTeSvJ9IKjpmw6NQOuHtVyMlPT9VLLM8tnfYcbH5hPnpcOhSX94gV+LoAtNMcaFhqjFqNb7fZ4WizhWeFxUoIAua2HBQW+RAIAPUzu/Gl64/hxaemovV4LvIS/N4sW2GH1ZyDiipPOEw68RSxve/p9dPH1MrjUgilVidfHSSH/LzsqdaWU59bi9OWGaFSCbjkvMOoKu/F755diO/d3AgBgFrGuWgA4Owpwx9eOg8dXcWYPbUDV5zfBL/fB4VCgd///QqsWfoYNOrkz+X6+tywW7bj7IWNeCmGiQEMwmhcamkV737V1jIIi8fAijBh7Lxujnlnn388/O+BZfpabRC/ePJN5BdkT7XIWCa1RRaX9UGb4MVjqgytOpF7tSZnhBlhA1ekk1OHw4GgoERrmxmtbeYhH+uI8lmxGRio9UitkWN4WH5/a2RyX0MgEIAgKGC1tcNqS8WAYQUMJVpMmjT4grLVaErqZ3XQSmgxDmj3e8W2pNECoPCFcBKhiXSMxjYTNJrRAz9dbhC6XPmD2Zt+3RTx/Vp9ANc9uF+WxxAEcSGCTIjn/9/YZkq6VcdoirwPozH0/gQXC4jG3eeG3WYPzZSSd99A//dkaIvsaJVQ6XTVd4+kdP/RXkNH+v988dE5mLPYifo5HVAogN5uNWwmPT7YNBdOaw0u+mpLxHMFd58bDsS/eu6qi4zhUEqlElsBGxY64XUr8Yf/mxWxhTEWF32pddDb4blTZ9iwcIkDmgwsKEKj+8emE2CxzEJJmQmVsY+ak4XPr4KzS4uSIrGKcMUSEwJBBR5+8gQ4nHpoZA7CPtxzKU454RhOXrIfmz+oxy/+tBxXny+2b6vUejQ0zIJGhvDz3zt0mDlzNhyOwzFtP6aDMJfLBas1uTufkUhPngOfVFO9hCzJS5oRxtbI+CiSHPBLyRsYRur0Aej02XFXbDyIdVB+PPOKkiVWrQBtRiPajENncSiSDo4kVuMcAIBK2wGXy4WgoExhaAIASlRWVqKkWGxjczg6YDRbYQr9SY4CHR0dcITWj/AprLBYhwd64dfyGKvR5K5ai3QOMfQxXKFvvy9ogzWJSq6+PrHFpKy8DOVl8a1iNhqn04nWNhM0Qyq/fH4fIABGoxHGYT+78VDGNZdKmhGm0HhHPAccdCGc5HyTkdo2U3F+GOsMIn1eEPq85IO3He+U4O+PLkTxlDrMX5ii9j2iFBitBdI/wnNLu0WHMy80DwuKVl5kxk9uWYSzLjSjrFq+KuoTTxv8eitVby06yYFfPPkp9DG2e8cj0SozSr1dTXXodOXB7f1X2h977owWtJoKUFLUX0V42jIjgkEF/vTCPNmrCD2+XJy8cD8qSyvwlYv24M3/TMGTf1+Fs+fvhFqlQkVFhSzh2y1f3oXqsiJ4vfkxbT+mgzCj2QinK/5EPhYCBLQZ29BmbBv0/o6OJO9mRwjZRtuW4heeEVbHirBEsTWSxhupIqyiJvJ8ML/fj4CgQGubCa0xtwgpknpd6OkRj6WmpgaGwv6qlQ6HA21mK4yhP8lqaz4FANDlPg5bewcANUpKS2SvfADE167mNjNKiksGtV4ZzdakVx9yODrQZrLBbLGi0y4OYrJ2HICiqTni9sE0/39KxxipJU+skht8LM6O8wEApvZDCET5GmKnQo4+J65VzEbj8yogdlYN//5JwVgy/6dOpxOtreaY51L5fH74feLj+oM92Ns0WhuiInyhLLfwBbjJCKMpFQOllQik6NiH0miDcJjy0ds1G8EAgzAaO6K1QDqdThhbTVCP8NxSVefGP/9ai1WXmpBXIP6uBQOAu1eFYECBwpLUVxtLNz9TEYKNFS/8dSrM5hyc+wUj5jRk9tr3mRfPRl9fMa67+gBmTEtdMUUwCHR1iwtcGPL7AMQW3MjlwpXbB53/ST+HZ5zUhhPmWqGWeZafP6CF29t/M23ViuPo7nbhX5/cDL+gh0opz8//pIr4FrIY00FYdVU1Jk2S984nID55thnbBp3cdXQ4YDSbYDSbYTSbR9nDyIIQ0NzWBrS1jbqtMo6TcgZn/VpbWRGWCA7Lp/HMIlWERVkxUh3HsuKAGFYZTVaYzeKfxCmQm5s3rK2lTQqOCpOfV/NKUAxHZsw2oLysHEarA4WFhbKGJoO0RX6dFNtUknvMNpMNNTU18PeJJ45zF1ajYkresO2cTida2kwxfw8dofDRZBH/JEcxqCLO6XKipdU87Gfrb27xa2hYUI2KqcO/hljZ7DaYzI64Z9aM5uWfz8TW587CvAu3oGFO5BuPsa4+Fk1ra+znVBqNGgGvGIAWFGnQMGdO1G2dTifa2szh32u5SfvV++fi7/ddgLwiD276w2ZZ9m2z22A3dUAV5djbjTp0tWtQVOlFUUXyFWGzTnRCn+eFuzsfrftKUVWd9C6J0ipSe60xyiqLknVfP4pX/1yHx++fhdx8PyonuZGT58fR/QWYtdCZdSMUxqu9e4rQfDwfp58h/6iGeNnsBnQ48lM+Hqa7R4NAUHy9zs93I91B2EgK8uUPgCuLj+JoayWm1PW/Xq1YuB+mNhP+s++yjF1/jukgLJUn8W3GtmFPqkazKem72eJw2baY9tPh6ECzyYRjZiOOmWO726hXKGWrWhureno06OgQL3gnTeqCd+zOUU67ga2RnBGWGc/+fh5e2TALa684iK98fXemD2dcCVeEjdIaGde8GlNyVU7SwHFNlAteQ2HybV0A4O4WT7LqpuYgPz8fsDqS3mcm5ecVoa9bXABgyvQCFJboI27X0maK63soR/jodImthEMr4lpgHhQaBYOAu0ecc1ZXXwhDeeSvIRZia6T8/6e9TjWEoBIqbfa01wRCFWF5BapR/1/bogSyiYg2gygvrwCebi20eqBCpkEvfe4+2BH9XG7zn2rxyauVOP8bx7HqutFvqo5GrREw8yQzdm2ZjB3vlGPyvMQG/o/180caf0b7mVxxvg3mZgMsrYWwWvKhgICGEw9izhITot0PibV1OVO2fVSK7R+XYN6iTpxyVmo6p+QSDAImYw4AoKY284sYud3ia3JOTmpf8zpDq8XrtT1Qq8Z/4Hr6ghcxu74BwODXyIa6D7D61D4oFKlfHTSSMR2EZUKydz4BoDUcso2+n2ZT7OGbw+GAzWJBq8WMVktyJ3/qIZVo8bR0JkLOFxVpPlhBgQcGgwe27H4NyCoclp95xuYC7NtVhlPObh19Y4qL1ShVhEVujUxUslVOrWkYaJyJVSNTqa9bG/53nkwrLkrE4CzJ1/kYWjHdPWoIQfFJV65VI+UmDfPX5mb+AkUS8Iqnromulhiv/hlEkWahpa71ciTS/Bbp5ycRQ8/nahd0Y9eWyTjwSS32rtwIhTKx/SqgiGvmG5EcC24M5ff7oQwA5hYTzC0jPx97fHoUVwdRMbX/zvn+Ue5DKiEuUpKoLW9UYfe2Yiw/w4aTzrAnvJ9IWo7l4pMPypFf4M/6IMxm1cPnU0GjCaC83J3RYxEEwO0Rzy1yc1I7n7fTJZ6T5eRMnBE+yigvVwV5fQDkCcJe3ToTb31cjwXTYquwZxA2BsRTnWCzWJKfwdLRAbPFgjaLGW0DAjUBAlqNbWg1Jn/3MZpAIPmTp7YBK0ay1Y/Gmp7uULVDCkqTJ7pYh+WPN4LQv2pkQYkX7nGw/kKvUzyJzC30QaUem6l9r1MKdAJpC3Xi1esKBWF5bgDZ8YIqVYRp9en5nkVrmZZWk0xV6+VIlKEO2GAC3wK/3w9BBbRZjWiz9gd76kolNPoz4OnORz5Ow+Q58S+k4XQ6YWo1obe3B9YIC1hE2p4mrtEG3cdKAQwLX6PNDpO4+9R49/VZ2P95NUqruqHT+6HT+1A92Ym5y4zIyY1+Dmaz2dFhtiXVin78UD52by/GjAb5R7gEQwG5UuY5T6nQ1iqel1XX9EGZYPgul0BAjWBQPIjcFFeEOUMVYbn6zAdhf311FgRBgdWnNaO8pC/Th5OUPrcGHc5c9Lpjq7BnEDYOyVG1Zh4SqEWamyYnm80Ou90GlSr5H8kWzgdLwoAXTSE7LnomGikIy2UQBiD5CyXp8x0OF2yhijCV7jis1uEnH+P1oszdq4LfK56wG0o8cGf3DeKY9IbupuYbxm7vuxQy5Rqy93e9p1N8Tdbm9gHIzezBhARCq0Zq0ryibqRzq5FWk5RDd3c3rJbhgZLbLd4c7XL1Rvz4SMILdFQPHy5e1XAQLZ8tQPOO6Vi2Mv6LfJ/fB0EBtJlMaDPF9r2JFGJks/3bCmE36rH4jA7kGcbOcaeT9Fo6sLMg0o3p/sViIodVsT6WyWiKuuBGtGKCZx6dhpy8AK777jEEAwp0uTSwtObg8w9notNWjUuvPw5dlLC9r8+NDiT3QupoF4OQ4jL5q7QDAfGbrRoLQVjoBuWkLGiL9HrF8ESpFKDTpfb1xSHdzMuCIOzdj2vR3avF6ctSV+iSLurQypPBYGyvXwzCKKqhJ32R5qbJpa/PDbvdJp70xXAXcST79y8CAJSUWGG1WsbtxW0qsDUy83p7pIqwsXuBL4fEVnCMLAgl9u/rgd+vgkIRhMn+Gayd0U5yFPBloNUplVwd4gmXRheALsXl/unSEzqJzC/K3hBpNFJFWG5B9v68SWGdJi+LgrDQylOaNFWEZULAHwAUAuztNtjbh19wd7pqAUyHzdaOpv1NCTyCAnl5ecNmrE2avw8tny3AjndK8cVvH4u7QiO8kmh1bMHGaCFGNtrwf9PRbtSjcnIfZizK/EVsNom1wqu9rRolNSYoFGIQmpebl9QKxiajKeoMv2isbTm47IZjmDJj8KiENeva8Ivvz8PR/fmYsyh1N9QddvE1rLhU/nO9YCgIk1qos5kxFITVZEGlfnev+JxVkO9LeUdRZ5ZUhHm8SnT3isdSUpye1lS3R4V7Hj0dELw4d9FeWfetUYvnuH4/gzAaQwIBPwICYLHZYElyqNfevecCAFTqA9i9t/8EcegiAgzIKBv1hGYfTfTWyHhXcIxGHEZvhkYxCwBQVN6LeQtmRd+2Lfrg+rHK5RB/pgpLPOOmXVyqCMsbw0FYT5ZXhAlCf1gnVoRlh3BFWJa2k8pBpRZP4svKylBeNnx1dOP7xTgCoLS4HA1zGuLa90gtnRUzjkKX64PTrsOx3QWYtjCxizSDIfYFKkxpmJEop/xCH9qNevT1jK/XCTlIP1NVlTWwHp0Frc4PbY4fWr0fWl0Auhw/gkFg06Pn4Lu/3SQGoS0mqJMIQv1+PxQBwNRigmnILLCRqg0LS7zY+UnxsCAMALxeJYrLUnczUhAGVISlIAgLBMdQRVirOMtpUhYEYRbbZADAtPrUdxQ5Q+cwuRmeEdbRKS5UoNf5katPz005n18Fo1Xs3lIo5H0d14QqwvwCgzAaQ6SWyPLycpSVlSW1r76+qQCAhYs0aGhogMPhgMlsgdlihTnCEjA+f3ZehGTC4IqwcXLFPMb0sjVyEDmqUFuNZni6qwEA1bXuEQfbJ1t9lo2kirDC4vFTZdhfETZ2v6Y+V6giLEsH5Xt6VAgGxJIgcUZYdpgIFWGS/Pz8iCtR5hWELl5y8hJaqTJaS6dKHcDMZWbsfrcOO94pTTgIG8+kcyOlIvtDhkzx99Xg1ceXYfFpHfD7FFBrg9BoBeTk+eHuVSEnXwhXgA0Nr+IVbRaYNK8uWrXhuhuP4vnf1+Pum05AVW0fyqvdMBR7YTPrUVbpQWlF6haW6e1Ww+sRL9SLS+V/nHBFWJYHYYEAYDaJz2WTauVdxCgRVnsdAGDmtNQXSkgVYTkZrgizO8R20NKivrTdKPX5xfMKpSIo+/OotAKnP8AgjMag/Pz8pC96bdZSAMDcuYrwvkzm4YsIOJ1OGI1G9Pb0wmqNskbyKMZbVZliwBMSWyMzg8PyU6PdLN59Kp+U+ZOtdHN1SBVhYzc0Gqp/RtjY/T2RVmTMLczOr0E6PrU2AJUme46xf1j++GjzTUR41cgUfAvmnNIWDsIuvjX+9shExHoulQ3nXNICBYrE56SPSbF876VtujpyUFTmxZlfNKHLoUFPlxrdnRr4fUq0HsmTfaVfIHTTbEgVoqk1eshWWOTHf33vIJoP52Hv9iL09qhhPJ6LGfNcOGW1FUnMwR+VVA2WX+iDRiv/yfZYaY20WnPg9yuh1QZQmoJZafEQBMBiCwVhM1JfETZ4Rlh+yh8vmo5OMQgrKUrfzS5/eIZd6m5mxZrpMQijcUUQgNZWcQnW2trBKfvQmWc+vw8CgDajEW3DlkSPhwI+X/ZcJNDYFuuw/GjzMFJxodDd3S37PtPNbhZPNCpqMl9+n25SRVhBcWZPNOUUDsLGcGukNH8rWwdu94Yq1vT53qxqqQ1OgNbI0UgXuNLqcHKatsgKXa4fnVYdmvfmY+r81D3/J7pq4NBRF/FI9jVSCH3PFROkIszv9wOCWEUY6+IQutxenHq+BZV1faidPvg1t6zGjca3k+v8SFYgAOz8uARvvDAJp55rxZp1bfh4SxnUM4OYNqc7pSEYMLAtMjWvyWOlNdLY2j8fLNMrRjoc+XB78qFSBVA/JbVVWoIwYNXInMwGYe2hIKw0TfPBgP75XWqV/HdyguHn59jODxiE0bhit+fC41FDoRBQXTPyE1l4qGsSM4icTidajCZoNJqEPj/bsDUy83pHqQjz+/0QoIh44SBAIUOwG40SgUDqLtjjHXQbL6kibCIGYV2hGWGG8VQRFrqbmjeGK8J6w62R2fk19HSKz0U5hdn1c+MPtUZqcyZuECZVI6UiCFNrg5h/qgPbNpfj8y1lKQ3CorW1RdPR4YDFbIHFaoUlwUp+iT/BRVG++I1j6O1WY9L0sfFakuxraTwrO0rz52rqezBnfuR5v5V1fVj1pVSco8Rux0cl+PTdMpx9kQn7dhTh2IF8+H1KmFtzUFDkw7XfOQRDceqel1M5KB8AgqF8IdtbI8MrRmbBfLDmFrFQoqaqHVpNal9bevvU8IXCoBx9Zm80tzvE1tTScVIRFhTiq4ZkEEbjSmtr6GK3sgdabWy/YJGWRI9HS4TVaqLJhrL+kbA1MjHx/v9H2z7gV8DjFp+We/vaYLUOf2GSTkqrI7T6traZkh4uH4nNbofF1h6e5SenkYI9OVdwDAdhE7A10hlqjSwYRzPCertCrSVjeEaYVBGWrTPCpKAupyC7vsf9FWHZ0RqZiZtGqWyNBIBFK9uxbXN5uD0y1RWB8cyCtJgtMQdnkYhjMUzo6emBxWIZ9P5YzF6a+rYpOSRSyRWNAkBuXt6w1sNIjG0mKJRAboH4w2k36aBQiKvj5uQFUD0l8wtvmFpyMWlqL04+246jBwrQ06XGf/3PQQDA849PxUdvleO8y1MX1qVyUD4ABKSgIctbI8MVYbVZEIQ1i4uSTK5NLmCPhaNTDEJz9B6oVZl9/c9Ia2RoRlhKK8LAIIwmoLZQEFZbm54TFakl0mg0whhHFY4jhrJ+V5aHZtkqmbAx3vZCR4cDAGAyGmGK8f9fgBJtRhPaIrSB9Hbnhv99vGUXVKZoLxIK5OXmDhv63tpmkmW4/FB9bjcstnZ0d3fDarWM/glxGC3Yk2sFx4ldERYall/C1shs0hNakTFbV43sdUoVYdn1c5Otw/JjPfGWQypbIwFgzvJO6HIC6O5Uw96mR3lt9iyWACS3iIq0iqDRZILRNPx12B9llcGxJt5qu2icTidMcb4WW829eO2JanRac5Ff7IZW50dOvg+TZ7dj6lwbVGohvO9MsJt1aFgsPrZKJeCEFf3n5CqVgNz81P4MONpDFWEpmoslPS8os3yOXTZVhLWEKsIm19oQ+4SpxHS6QnNbCzL/vNoRbo1MX0DtDy3Co1KmsCIsxtZ1BmE0rrRFmQ+WKlJLZKxVOB0dHTCarTBZxD+jU8CfxlUtB7dGpu1hZSG1OcQTSkWmiHMfClRUVqKkpGTULZ1OJ1qN5mGhj8RqFH9+NVo/5i2YFXUfRqMJ6jS24wb8fgiCAjabHTabPQWPoIwa7MkhEFCiwyYu0V2RBSdc6RYelj+OKsL6XGO/NbIv2yvCQkGdviC7vsfSsPxsC8LSSRFqeZKGYstNqwviG7/ag+ppvdDljq/vs7SKYE318FUGjUYTenp7YJH5ho80ZzMVN5Oi3cCT3jYYDKiMoZJrJKYYX4v9fj8UAeDV3y9DUUUrqmbaAIUAb18OLG1l+PzdOZi+pBczl26DYkC1Urpnvmm0QRSFqrFWXmhCTl7/TUdLWw7mntCZ8PHEIm0VYVncGun3K8IrRma6IqynRw2rrQgAMHmSFYC8N5OHcoZGOxQWZLY6UhAAuxSEpbU1MlQRpk5BRVh4oQjOCKMJqH9QfnpL1+NprzSarTEFZ06nE21GE9TqNM4fG5SgJ3+C3d3dnfQcj6GiVcpJdz+jhUyxEIMqU8z7kOZhlJSUhJcCH02r0SyemEb4eenqKAYA5Bf4In5cEs9QYTmoQt/bsvIylJeVy7pvKRxMZbDX7TBACCqhUgdRXJ75O3Dp5nJIq0ZmV2VPMnpcUmtkdoU08ejJ9hlhUkVYQXb93ARCrZHaCT0sX/xbSOG3IJWzwbLB0IAo0cH9sVIAsNvtsNtTcTMp+nEnOgstEdJ5WE9nFW64ay8USgXEr9wDoA2C0Ibffn8VVl/iRW6BFw6HAxajBVaTFVZT4ueKCiCuMQpX3XI0/O/y6v7nN69HCV1OABU1qT1PSPWw/LGwaqTFokcgoIRO70dpir4PsTp0WOwYKMxvR35+6s8RO0OD8gvzMxuE9fRq4PWKv7MlhvS3RrIijEhm0oywSZPSUxGWqFiDs0jtc2NBMBCaDZGykz5l1Eq5aCFTrFqNptA+Ygu2kp29MVBvjCtGZkp+fn5S8/SiaTWaZd/nQM52MWAsr+7N6jukqSKtGjleKsIEAejrGj8VYdn6NUgzzLJtRli4NTInO2aEZYI0BDtVrZETkVythJHY7XbYrXaUlZWhvFzeFRPDA+prIlS4tZnCX1e6BIMK5Bf6YTzYgCVnDK706ulSQ61WoX5Gcfh9FmPyM9/ibd2MRqUScO1/H4JGm7rzBEEYMCy/LEXD8sOtkdl7vhOeD1bTl/FViY8dE68dy8ta0/J4jlBFWEGGgzBpxciCfE/Mc7XlEK4I46qRRPKSKsImpbkiLJWSnRXmGqVsfiC5WiOVobWny8rKUFYubwWRy+lES5s5vZVyadIzyoqRlBhnu9i2Wj4B54MB/atGjpeKMJ9bh2DoRGosD8sPzwjL1tbIztCw/CxbNTIQHpY/cSvCpNfqVLRGpnPOZjYuIBTPjbBYufvcsMMeupkkf9uVUZoPOqQFUs4bdbFSKgWs/vJuvPf6IrzzSjVqpvaipMIDrT6I5gN5mDZ3+I3qZNs3Y23dHI1KLSDVY7V6e1TwesRHKUrRSs5joTWyrU0cVzEpCwblS7PKSopSPygfGFARluEZYR0ZaIsEAJ9UEZbCVSMVrAijiaitLTQsvy67K8JiIVU8xTuIPzJFlP0oB81m8PuU4X/bbDa4PYk9OfaE5mHk5+cnVZ0VVVtqK4gyJdsrwsYqp128+zwRB+W7e1XhlUjHS0WYp0ecK6LRBaAdo3OivG4l/F7xYihrWyOzvSJsIgdhoQtcQcaKML/fD0EFtFmNaLMmcc6hBNosRrRZYtuHEorwAPuxwNqqR36RD7n5g6sZggHg8K5CzFw8fm7EJmryrA7MWXAAexuLcHRfAYzHcuF1K7HolA4sX5Wa1tCxojM0KD+vwJey9u5wRVgWt0aGK8KyYG6r0SiGckWFtrQ8ntMlzQjL7NfenoEVI4H0VIRxRhhNOB6PChZzPoD0zwhLBaniqaamBoVJlOm7nE60GE3D5pI5OjpgNNtgs1hgCy0h7vf33ws7uP8A8vJ7En5cQAl/YOK2riRCqgjLzcvOC+OxyhWqCKuYlMzP89gkVYOpNUHkpHglrHTxhFZXzc/SlsJY9IbmgymUAvT52fk8KQ3Lzyn0IluiMEHoH5avncitkeFVI+XbZ7g1sDr2OZt+rxLqAS01TqcTxlZjzAsIOZ1OmFtM4QH2Y8HTP5mJa+8+GA7COixaFJV5oVACf/tNPb776C7ox9kCA/Ha11iNpk+m45zLTDjpnKPY+Z9i6PRB1M3Mrtfgo/vzkZPnR0WNOzx3L9U67OJrckmKVowExkpFWGjFyNrM/kz4/QqYzOLNtSKDFUDxyJ8gg/4ZYW54MjiKsd0hft3prgjzp7AiLBBkRRhNUCaTGILp9T6Ulma271pOhUnOvAIAhOZeDZ3vZDTbBgVt0pMTAMyYORuGosS+j3a7DWZbB9Sq1BWZx9LqOdawIiw1pBlhE7EiTJoPVlDsyfgcDrl4esWTt2ydrRWLXqe0YqQva/9fpGPUF2RPEBbwKYFQ68NErgiTLtpT0RopttgNPlcI+AHVkCuGgB94/Pa5uOL/HUbJgIHjxlZjXLM6zS1jaxaqQgnkFfTfVHjhV9NwzZ2HkGfwQ5cTgM+jnNBB2LFd8+F21KB2Rg8+eKMC298thd2ig/l4DuobunHlt48MWqUxk557bBpaj+bh5jv3Y/GKxFeujIcjVBFWlKIVI4EBw/KzNAjz+xWwWsRqpEkZrgizWsWh/VqND/l5TqQ6CBOE/hlhhQV9sGUwCOtvjUzvNXO4IkyZgoowDsuniaq1JTQfbFJX1l5YZKOBQVtgwEl1RXkZiooTu2PldvcBttScVPh94sWvyWiEaVirpyLqEP2xgDPCUkOaETYhg7DwfLBsiTKS5w5VhOWN5flgLikIy94qvf5VI71wZckCgj5P/82VsdoWKwdtrngB4elN9UQjYNe7xSiu9KJ2tli5YW/TQakESqo9KCz14vBnhSipTk9LUTZQqYLo7VYhzxBaZfJILuxGPfIM3QgGFPD0qVBQnL2/16nWaalE/cxOXHhNNx7/8SxodEF88yf7AABP/+8MbH+3FKeuSc8sppF4PUoYm8WbKpNnpO8JziFVhKUwCJOqYlRZ2hppNuUgEFAiJ8eP4gyfm7SF2iLLyp1puXZ0u1XwhsYiFOT3IZPPnOHWyOIMtUaq5X8NFzgsnyYqaT7YpNqxPx8sGwhCdqaJao14cVY9pPXC6XTCaDSN6SH6PawISwmXNCNsArZGujpCQdg4mQ8G9M8IG8utkX0uaVB+dn4NAb8C7u5Qa2SBF8iSIMwfCsIUyiBUmiy5yMvAYeQXiT833Y7Uv97t/aAEpTXucBC2/+MitBv1uOjW45ixxIWD2ww48fyJE4RVTe3DJ/+qwNJz7Di8swCVU/rwwWsV2L6lFDXTeqGbwC27AODuyUNJlVihr88NYPGp/TdF1eog9LnZ8f1pO5aLYECJAoM3Zas3RtJfEZa61shg6FucrRVhxrb++WCZLlwwGsVjqShPT1dJZ2g+WI7eD502s78L7Rkalh9ujUxFRVh4Rlhs26epI5oo9VpbQ4Pyx8F8sEwZ2FOdzKqR6SC1Xkh/5F7uPBN6u8XQghVh8vF5Veh2ij8bE7MiLFSCP05WjAQAT49UETZ2f0+kaqtcQ3ZWjkhBHSC2RmYLnye0YqQ+Oy6mB0njBV1+ifiz39OZ+iBszskOWI7nhN8uqfZg+7/L0GnVQqEQYp7FMl588RvHYT6eg998Zx52/6cY199zAFPndqO3S42zrzBO6GowAAj41dDnij+fZ15kxpRZ/Sm63aJHcXl2vBYdPyRWAk2Z2ZPWMKazXTzPK57ArZH988Eyf04mHUt5eWdaHk+aD1ZkyOzvQTCogMOZoSAsPCw/dTPClKmoCHvggQfw8ssvY9++fcjJycEpp5yCn//855g9e3Z4G0WUZ5OHHnoI//M//wMAOOuss7B169ZBH7/iiiuwYcOGeA6HaJC2VrE1spYVYQnL9J2ZiY6tkfLrsIonuxqdH4YU3oHNVuO5ImxMzwgLBU15WVoRJh2fPs8PlTp7LqakijB1hu+kZ1p/RZgagpDa1+5pi7rw7yfr0GHSoaTag+N787HgjA489YPZ6HWqcf2D+1L34FEkMxM02XmiOXkB3HDfAbg6NOhyaHB4ZyHKqt2YudiJ8kkT7zVmqOVrX8WkaTMAVGDKrP4qbI9biZxcP0oqsuO16PhBca7wlDS2RQJAR3sahuWHWyNT9hBJycYVI9NVESbNBysqzOzvQVePOBtNoRBQVJje563+YfmpmxGWkmH5W7duxTe/+U2ceOKJ8Pv9+MEPfoBzzz0Xe/fuRV6e+INkMg0eevnGG2/ghhtuwGWXXTbo/TfeeCN+/OMfh9/OyckBUTJaW6UZYawIk0O2tkaOZ/3D8rPjRHE8sJvFStHSyok5O7ArPCNs/FygSRVhY7k1sjfLZ4SFK9ayrOpOmhGm0U3wIKxY/H8JBpTo61IhtzB134+CEh9O+aIZT941G8aDeZiz3IEbf7kPvS4VtDlBqNPYour3+yEogTazCW3mxIfsK0L7SoTPq8DbL9Tgw1crEQgokJvvhwAgN9+Phac5sHyNFflZWumZDmqtL2J4rlYLuO57h7Jmtt/xQ6EgbGb6gjBBADo5LL+/IizDQdjAFSPLKzrhSsPoOqdUEVaU2XOyzi4xtyk2uNO+uqg/vKqp/M8F/a2RKQjCNm3aNOjtJ598EhUVFdi2bRvOOOMMAEBVVdWgbf7xj39g5cqVmDZt2qD35+bmDtuWKBlSa+SkOlaEJWpgUJDtrZHjESvC5NcuBWFVE/N5wRleNXL8hKvjoiLMGZoRlqVfQ/j4siyoC1eETfAgTK0VoM/zw92jRrdDi9zC1K76deqlFsxe3oncAj96nBq89UwN9n9cBK9bhRPOsWPuqQ6U16W+vUatFn8ua6qrEx6H4HQ6YWozhfcVrzf/Ogmmozn479/sRkll//Oqw6rFsz+fjqIKD5ae3Z7QvrNZLJV0I22jUgtZU13q7lPC3BoalD89fbND+3pV8LjF57BUtkYGwkFDdny/B/L5FLBaxO99TYZbI6UVI3W6AAyGnrQEYZ1ZUhHW6RKDsHS3RQKAzx96HU9hRZgSaRiWLz3hlZSURPy4xWLB66+/jqeffnrYx5599lk888wzqKysxJo1a3DPPfegoKAg4n48Hg88nv7k1OVixQ8NJgj9FWGcEZYcnd4Pj1sNjyf1q1HRYD1dYhCWn0UzecY6u1l8XiitypJp32kmVYQZxmNF2LhYNTI7gzCpIizbwkZWhPXLL/GFgjA1Kqak/vFy8gN49sczcfizQtQv6MK8Ux2omNKHA58W4fkHpuPWx/YkvO9Y2xWl7QwGAyorKxN+PFNb4tVkXR0azFzsGhSCAUBxhRcVtW502rQJ7zsb+f1+KAKAqcUEU0ts37dEq+3SpeVIHoSgAkWlHhhK0vcc57CLIUhegQ9aXeoq4+KtikknsykHwaACubl+FGX4NVxaMbKmuhfKNHUMOLJkRpgUhJVkIAgLV4QpU7lqZAoqwgY9kCDgtttuw2mnnYb58+dH3Obpp59GQUEBLr300kHvv/rqq1FfX4+qqirs3r0bd955J3bs2IHNmzdH3M8DDzyA++67L9FDpQnA5dShJzRofNKkiVn5IZe8PB88bnV4cDulT09XaFh+QXZdfI5lUkVYWeXEfF5wsSIsK/WvGpmdF4zh1s0sa/HqrwjLruPKhPwiH+wtOWlZOTLgB95+tgaVU/tww0P7Bq3I1bCiE/d/6QR0WuM/Z/D7fAm1OmYyaCkq96J5fz4szU5oc4Lwe5XwupVoO5yLbqcG8091ZOzYUiFchVczehWe0+mEMVRt5+5V4uBOA6qn9qKsKrtuxDSH2yLTu5K0Iw2D8oH+1shsrAiT2iJratO7SEEk0oqRNWlcUdwpVYQZJm5FWCA0I0ytlv+GljQfTxFjyJZwEHbrrbdi586deP/996Nu86c//QlXX3019Hr9oPffeOON4X/Pnz8fM2fOxLJly7B9+3YsWbJk2H7uvPNO3HbbbeG3XS4X6urqEj10GoektsjS0l7k5vIEORk5uT6gPQc9Pak/uabBulziSRIrwuRjt0zs1khXeEbY+PmZcocrwsZuENa/amR2fg29naFh/ll2fD62RoZJc8LSEYSp1MDBxiJcceehYcvSd3VoUDGlD31daqjy49uvWiMeeywhCzA4aMmUs75kwqY/12L99xpQMdkNfa4ffp8SvV1qLD/PhrkndWbs2FLJYDCgIoYqPGOo2q7lcB5+d+8clFS48ZM/f5bqw4tLeMXIdA/KD1WEFadwUD7Q3xqZjTPCpEH5mZ4PBgyYVZbGFcU7XVlSEdYlfu2lxaltq4/EF1o1MhUVYeHWyFRWhH3rW9/CK6+8gnfffRe1tbURt3nvvfewf/9+PP/886Pub8mSJdBoNDh48GDEIEyn00Gn0yVyqDRB9A/Kn5gXu3LKyxNPrnsZhKVduDUyw7MDxpOJPiNMqggrLM6uO/LJ8I6DijCp4iov2yvCsqx10+cRT1s1E3zVSADIS2MQBgAlVW7s/aAYZZPcaDfqYTqci2O7CrDr3RKcdIEV1dN7YbUktm+DwYCKithaHY1JtDUONLQdU3o7ljbN5RebsOwCBUxHiuDzqKDP86F6mvh5lghzhrq7M9ean+wqmYl+vum4eKFdPSX9F9qjCQ/KT3MQ1pmuirAsbo1sawu1I2ZBECatGFmTziAsayrCxN+BjLRGShVhqZgRlsrWSEEQ8K1vfQsbN27EO++8g/r6+qjbPvHEE1i6dCkWLVo06n737NkDn8+H6urqeA6HKCwchHE+WNJyQ0EYK8LSKxBQoLeHrZFyk1aNLKvqAjCx5t553Uq4e8WX+fFSERbwK+DtE4OwsTwjrDfUGpmTZUGTpCc8zD+7gjoOy++XzoowADj3a634cGMlfnLZUtTO7kZRuRdFlV5c/8B+TJk3dmYw+v1+QAEYzSYYh7ZjKgCjyQSjKXrYJgSBgE8DtS70u6sB3F6gfbcKPR3FUOs8yDUMv/GiABAIpO/3ye/3QxEETK0mmFqTCw8VAHxxtqP2B2GZDzwG6u1WwdoWGpQ/I1OtkempCMvG1kijVIWV4UH5A1eMnDSpB71p+FHweFXoc4uvrUWFHnRl8JK10xWqCMvIjLBQRVgqV41UpKA18pvf/Caee+45/OMf/0BBQQHMZjMA8U5OTk5OeDuXy4UXX3wRv/zlL4ft4/Dhw3j22Wdx/vnno6ysDHv37sXtt9+OE044Aaeeemo8h0MU1tYmXuzW1k7Mqg855eWLF5esCEsvacVIgK2RcnH3qtDVKb42icPyE1tlbKyS2iKVqiDysjRwiVffgNmF2VpNFYve8DD67PwaerO0dTPgC91J1qZu0PRYke4grGZGL9Z+8zgu+tZxcR6YAOQV+ZFn8CPgB8xHc6HIUY6+owyLtvKk0+mE0WgadUXKfR9X4/0X5+DS736KskndEIKAQgn4vEps+9c0uHo0WPrlpkGfY7fbYbfaoVKlr6UzntleI3E6nTC1mqCJsx3VdFx87c22irDmw6HZSJVu5Kf5NUQalp/6GWHi39nWGunzKmC1iOOSMt0aabX1rxhZWuJJSxDW1S3+Tuh0fuj1gYwFYYGgCt2hyvrMDMtPfUVYrNWQcT2rrV+/HgBw1llnDXr/k08+ieuuuy789oYNGyAIAq688sph+9BqtXjrrbfw8MMPo7u7G3V1dbjg/7d37+FtlWe68G+dLOtgyedT7BwIAQIJkFAKpBTSUlIoFDrtDFD4KHSYlH1tSMsQvpkybTfQa3bTstvS2enQPZ2PSU9A2e2UgU5bSigESgmUSYBAjk7I2XYcnyTLOkvv98c6SE6cxJal9b6S7t915YJYK9KyrSUt3et5nveaa/DAAw/A4aiuq/VUPIf1GWFd3awImymzIizCIMxKRltkjTtd0tWEqslAn3bFq6Y2Dm9d5bQGTtXYiNEWmZQ+lLZYxvW2glpfEg6nWif5U5VJ2xAfN4blqxU0GcYVDeqy+gm0vQRXksuNv0H73YxbFIQBgNur/dxbZ0/88ORwAm/8ZyvaFsQAr2W7MyOTzbzq7e075YqU4/N8GDwUwB+fugBX3nIY88/NXYAdX2LDhl+0oq1teMK/icfjGBwYLO43MEUzXWETQEEVZapWhB2Q1BYJ5FWElXhGmBEGOBRrjezr80IIG3z+FAKSL7KYLZod0ePmHpZKeEwLn+oDcs/JorEABGxwOTMI+K2/8J5rjcwCRc7CjBlhtlJUhAkxtQPqC1/4Ar7whS9Melt3dzdefvnl6Tws0SlxRljxeM0ZYVw10kqRMNsii21AP9EJNg1XTBA0HaFh7TlVSStGxsa0IMwbKN9gMzaWO/Xy1KkVNBmM1k3VKsKyCg+BhsW75NeP6zELg7DNzzcjPu7Asr/QhoEd2efBeMiJ084bQ1NnAu+/1YbZFd7cYbMLLL50GB/7bC+eeHg+rv2bAzj3Um2lSJc7i3RazpvNiWaeyTAerkFED9PbZ6tVEZYblG9tW6QQwMhQ6SvChAAy5gWDkj1MQfp6tSCoszMq/ZxMxoqRZhAmeVB+JFYPQKsGk/F7yLVGZoofhGUtGJZPpJpDB7UgrIszwmaMw/LliIxxxchiG9BPdALNlbWc/VSNmStGlm9odCyjIqycgzBj/pbbl4bTpWCgAyA6alSEqRWEGcuuq1QRZtOrLgSs/UQhoyIslbRj75Y6MwhLRB34w09n4bTzdmDhJSN4/dfzKj4Iq6nNIhZxYu7ZEfzVPXvxy3+ah773vWidHUPPW0HMP/fE56GRSAQDha4ocALDwyMnnQWWnuZsr2I4elg7J29qj8Ndq86xCgD7e7SKsNkWV4TFog4k4loyVeogzKDajLA+vUq/vUN+OHq4V8aKkdpjNtTLPX8Zj2mt0jLaIoFjKsKKLFcRNrXtGYRR2ctkbOjr097YZnFG2IxxWL4c5oqRDMKKZqA3VxFWjYwVI4MVMigfAKJ6RZinjI+TmH6sexWtBgPyKsIC6WJfsJ0RoWBFmHHCLSz+vG/MCBsPuZDNwpL2ngUXhPD6M63m31u6Y9i+sQEHtvnRv9eDtnkhs321UtV6M2Zb9oLzw7jzm9vxf797Gt56uQndZ4zjI391gjBKAINHBzF4tPgtkjYAbW2taGxsNL8WCoXQe7jPnBVmpaP63F7V2iIjYSeGBrQZVVZXhBnzwXz+VEnHXxiD8gH1Vo3s1yvCOhQIwnoPW79ipFERJj8IqwcANDVICsKMijB7puiF1LkZYSVojSRSUX+/D5mMHU5nBm1t1r6xVSJWhMlhtEb6FZ0ZVI4G9NWJgk3VWREW0oOwSqoIi1ZQRZhqbYeGZNyOlL46o7c+hTGFPsuarZFOdapMjGXaRdbaijBfvfb8yWZsiIWd8NWXPlht7EggnbZj+8Z61PoyePN3LVjx+UN4Zu0cDOz34Lp7/4zoFD+AlKuG1gRuWr3H/HtjWxL/7Vs7TvpvjDCqpbkZzS3NRd0fY5h9Y2Pj8TPPDs9stchC5YIw+YFHvgN6W2TrrBg8Pmsj/tx8sFIPys8LwhS6YAAA/foqjbIrwo5dMdIqoTFjQL0arZFN9XJ+D/kVYcU+C2JrJFWdw/p8sM7OiHJlwOXI69PepFkRZi2jNdJXxpUuqjFaI6s1CAsPG62RlfOciurHiTdQvt+TuWKkoqF3VA/q7I4san0ZpYKwXGukQu/1RkWYxbvkdAl46tKIjTkRGXFZEoQBwF/csxfP/X/dSMYd6D4zgg99uh8f+9whOGsEBo4MYvtWS3ZDGrsDaGyf+PpjVOSdqjLP7/ejrXVmg+snU8gw+1Ia0FsjO2Yr9OIBYF+PAoPym0obgmTyAnmVPhNls0B/n14RZmEV1mSOXTHSKiG2RgIAUnkzwooehJVyWD6Rig7pK0bOmsX5YMXg87MiTAazIozD8ovGGJYfaK7u1siKqggLl39FWHQs13aoImPFSG8gLX2g8bFUHJZvzgiTsEv++pQZhLXNs+bq/mnnjeEL39mOyKgLNbUZeANaZY0Qcn4GKjDCL6tWn1OZECpXhBlBmPXdI1YMygeOqQhTqDVyZNiNZNIBhyOL5hY5AYxBxoqRABAKq9Ua2SwpCMuUckaYHgTbpvjc50s2lT1zxchuzgcrBnNGWISrRlppPKLPCCvjShfVsCJMO4aDDMKUYlSEqdoaGQ0b+6deUGfMn2JrpMbfqD2HIhYOzAcAZ41AfWvSDMEAbVaaasEpWS8R9SIWccNmE2jvVisIM1eMXCChImzQaI0s7XuXEYTZbEKpYLZPrwZrbYvDIXk1SxkrRgphU2ZGmLlqpKQZYfkVYcVmtkZOcfqYQocIUWEO6xVhXDGyODgjTA6jIoytkcUxPubCuN5GV+3D8iuqNdIIwsr4OMmvuFJRdFTdGWZmRZhClQ42Sa2RQG5OmNVBGNGJhI+2AACa2hOoUWjFyNCwC6NDbtjsAl3zKrciLJNV7zUSAPp61WiLBOSsGBlPeJHJOmCzCdQH5Z2/JJJOJFPa70LajDD9fbyUFWF2tkZStTAqwrq4YmRRcNVIOYwZYVw1sjiMQfn+QAw1tdX5Mw2ZM8LKt3rqWGYQFizf7ylmtkaqFzQBeRVhCu5fVm+pcChYEVb05a+mwKwIG+X7tZW2vxnE6NEanLEkjKaO8n0tKoXQoLYYgGorRu7X2yLbu2Ko9Vj/+mF1RZhK88GA3Hyw9nb5VYIyVowcj2lFG4G6JJwSfzej+pyyWncSnlo5a0Ibw/JLUhEm2BpJVeawOSOMQVgxsCJMjvExvTWSM8KKwmiLbGqv3teFyqwI0z5MeOrK98OnWRGmYOshkFvV0qfg/pltPyp9yNPPpKW0RrIiTIr1j8/Ckw+fjv3b/bJ3RTlhZYMwvS1SwqB8ISysCNOzBZXmKAJAf592TtbRWZ0rRkZjWtGG7LbI0bB2HNQHrK+KNKT11khnCVYYnm5FGIMwKnu5ijC2RhaDsWpkNMoTayuZw/I5I6wojuhX/JqrNAiLRx1IxLRAo5JmhI3rFWG+Mq4IM1ZlVHfVSHVnmJkzwkrQUlEooyIsK6MirEGv4JYQhL32dBt+/NUzMHCg1vLHls3p0n7Z6RSHoh0rF4TJr/zJZw7KlzAfLB51IBHXBmOVfFi+qq2RRkVYh9znhawVI8ejigVhdXKCsGwWyGb1IMxZwoowGyvCqAqMj7swMqK9uDIIKw6uGimH0RrJGWHFYVaEtVl/0quCsRHt+eR0ZeHxq1fZU6jYmBaEecr4OInq1Z8eVWeEhdVd1TKT1tt+nOp8yDNnhMmoCNODsDEJQdhbLzTj7T804/23A5Y/tmzOGi2ITSX5MSqfEGq2RgoB7O8xKsKsDwCGB/ULOP4UatylDfEzZmtkSR9mWmIxB0ZHtJ9Be4fc50Wffm7Y0W7tipFmRZjki3hGa6SsijCjGgwAHCWoCDNn5DEIo2pwWF+iuS6QQEDi8MFKYswIi0Vd5hsqlZ5ZEcbWyKIY6NVOequ1NTLXFpmomJXcEnE7UgmjmqoCKsIUrLgCcjPMPHXqBWEqV4RJmRFmVoRZP/J37iLttXXfu3WWP7ZsTpf2/Eun+DEqXyTkRiruUW7FyPCoC2OhGtjsArPmWh/EjAzp88FKXA0G5C0oolBrpDEfLBBMwueTM5fKMDikVbC2tlr7/BzXg7BGVSrCZAVh6dxrprOUq0ZOMWTjKziVNa4YWXzGjDAAiEW5noZVxiP6jDC2RhaFMSy/WlsjK3FQ/rg+ENxmz8DtUzNEmorcMHr1giZA9SBMvQ95NmNGmJBXESZjRtjcxdpr696qDML01shkhVxlKJKj+qiShtZxuGrUOUZ792vnAy0d8ZJXZE1mVA/C6q0IwvQgwKFQa6RKg/KPHtWCsObmuKWPq9yMMEmtkam8irBSXNAyKrPZGklVwZgPxkH5xVPjzphJOtsjrWNUhLE1sjhYEVZ5g/IjIe0YcftiZVvlJkR+66GaYV48onIQpl5FmFEKJiTsklkRFnIha3GhxRy9Imxgv9dcYKFasCJsckf1Lo2WWWpdnO7drwUxnbPltOUN64PyG0u8YiSQa42c6qp5VjDmg3VYuErjiRgVYc0W/C7yGRVhDQ2ygzCjNVLO7yJjrBhpz8JegvM4Y0YYWyOpKhw6yEH5xWaz5arCxhmEWSKVtCMR1z5I1LEibMaEyM0Iq9aKsHAFV4S5vfKvKhcqGXWaYY6Kw+iBXFCnZhDGirB8vnrtdySyNvP3ZhV/fRqterCw773qqgozqp3SnBE2wdHD2jl5i2IXp3sPaOcDnZLmlllaEWbOCFPnNbJfPx+TPSgfAAb1eW3WV4Rpr5EyZ4QJoUBrpLFipLM0V46yrAijamLMCJvVpdabbrnzmgPzayTvSXUw2iKB3M+eChceqTFXTGxqq87XBqMiLFiJFWF++VeVCxWLaN+Dw5VFTa1KVU05MZUrwvSryfYSnUQXIv+EW1j82dPhFPAEZLZHaouR7H/Pb/ljy1Tj0crvEnF+jMo3oJ+TtypXEaYHYbIqwgYtrAjLqnexoL9frwiTHIQJAQwOWt8amUw6kExpPwOZM8Ii4y6k0tr7u7TWSP093Fmiqm7j+T/Viki+glNZO8QZYSXhZUWYpYy2yFpvCk6FVkMrV0ZbZH1THDVuuYNZZTFnhEkuwy+mSEivCPPJv6pcqJi+Oqw3kFK2vZMzwqYn/4RbRntkndQ5Ydq51953q2vlyFojCIsqtDSfZEKoWRGWzQJ9ZkWYnPcOKRVhirRGZrO5IEx2Rdj4uBNxvfuiucm6c6NQWPv+3TUpeDzyzkmHRrUQsNY9VrKKrFMpeUWY2RrJYflUBQ4fMloj1XnTrQRGa2Q0wiDMCpEx7edcx/lgRWG0RbbOknPFSwUVOSPMaI30lXFFmB6E+YLqhUyA9qElrnAQZswXUWlGWH6eaQzqtZKvXv7A/ANb/cio93QpGbeXQdixQkM1SERdsNmyaOqIyN4dU2jIi0TcAaczi9ZOOUFMbtVI62aEqXKxYHDQjXTKDqczi+YWa9sRj98XLQgKBhOoqbHuPSSkz+UK1MkNAof1IMzvGZW2D2YQVqL3cHPVSLZGUqXLZvNaIxW6+lQJWBFmrdygfLZFFoMZhCkwmFWW8IgRhFVORdh4JVSEhbXfi0/R+WCJqMOcdaViECYUbPtBfkWYhIf3N8oLwtrmxlDrTyMZd6B3j8/yx5fFCMLiMQZhhj59IL2/YcRcTEAFA3qVWnt3DA4Jv67ImBNxfVRDg4WrRtoVeWr292nnY21tMdglpw5HB+UMyjcqwmQNqDcMjWjfv88TkrYPaf1ilqtEFWHG+QtbI6niDQ56kUg4YbMJdHQyCCsmn097s+aqkdYY16tE/ByUXxQDh7UPZK2d1VwRpj2nKmpG2KjeQlzOFWFG6F2vZhBmtEU6XVm43Op8mDXkKsLUCcLyW1ylrBypD8yXEYTZ7cDcc7Tzr31bqmdgfi0rwo5zcLf2vhtoHpS8JxMd6dWel7Lmg+3aqgVxHV1RuC2YC2msHqtKa2R/r94WKakaL585KL/J2so0IwgLBOT+DJQIwvSKMEeJZ4SxNZIqnlEN1tYesbTEtRqwIsxaRmukj62RRZFrjSzfwGSmcq2RlVMRZswIqynjirCo4hVhMX3lwdq6tJIzzMz5N6oOy5fRGqk/l6Iha1eNNBjtkdW0cqTboz3/4gzCTO+90QAAaJ27T+6OHMOoCJO1YuSOd+oBAGeda034oFprZG5QvvzzscEhLQhqsbhFMzymnZMG6+T+DJRojTSH5Zfm+ZnN6hfLplifzSCMytahg5wPVirmjDCuGmmJiFERxtbIojCG5bdVaWukEHnD8ispCGNFWMmpPCgfyAVhNkU+5AHHVIRJeHyvPm8uGpZz4coMwt6tniCMFWETjY06sXebXnl1+m7JezOR9CDs3SAA4KxzRy15PKM10qHIa2SffmFS9qB8ABg8qrdGSqoIC0qeEZarCBuVtg9p/T3c5Sz+ogHZvOtjNjsrwqjCHT7E+WClwoowa7E1srgGDlf3sPzYuBPppPYBrZKG5VfCjDCzIkzVICyiB2F+RYMw/WqyUhVhdrkVYUYQNi6pImzOORHYbALDfbUYG66Vsg9WM4flx/gxCgC2/rkBQtjQPmcU3oA65+TZjB2D/X4AQOds6983ho/W4EivBza7wJnnWLO6vVkRpkhrZF+fXhGmQmvkkNwZYUHZM8JGFWiNNN7DSxDUGitGAhyWT1XgkLlipDVvLtXE6+eqkVbKDcuvnNBClmwWONpX3cPyjflg7tq0WblQCSph1choyFg1UtEgzKgICygahCnW9gMc2xpp/eObrZFhOUFYrS+DjvnaMXl4R6OUfbCa8brK1kjNlo3a7/3MpX2S92SisdEGZNIOuD0ZNLRYXx29fUs9AGDu/Ag8Pmvei832cQVeI6PjDoT19zzZFWFC5FaNbG6WVBEmcUZYNguMhLQLcSqsGlmKYfnZvAtRNgZhVOnMFSMZhBVdrjWSQZgVjBlhfgZhMzY6WItU0gGbTaC5vXwDk5nIzQerrOdTJVSExVSvCAur3hppDMtXpyIM+a2REj57egNGa6ScIAwA5ugD8/t66qXtg5XcHi3USCUcyKh5qFgmmbBjxyat/e+MJf2S92ai0GAzAKCjOyplxUKzLfK8Ucse0xwWrkBFmDEfLBhMwuORe1EuEnEikdCC6yYLWyMzGRvGIloAJ3NG2GjYjWzWDrs9C0+tvKrNlDkjrLRBGIflU8XLVYSpU4ZdKbz6qpFsjbSGURHGGWEzZwzKb2qLwemSfyIoQ6gCB+Vns0BEv7Ls9pdvwBkbU7wiTPXWSNUrwoSE1kgjCAvJe7+efXYEANDb0yBtH6zkzqu0TcSquyps51sBJBMONLQk0D5HXsvVZEKDLQDkzAcTAtixRQvCFlo0KB9Q6zUypL9nNzbJPxc5qleD1dcn4LLw3DAUdkEIO2y2DPw+eT8HYz5YwB+dcttgKRgVYc5SVITlt0ZOMQhmEEZly5gRxtbI4mNFmLWMGWFsjZw5Y1B+a2d1zgcDcq2RlVQRFos4zflLbm/5VoQpPyNMb430KtsaqV5FmC3vTFpGa6QxIyw25kRWUtGFEYT176mX8jOwmqtGmHPqqj0Ie/d1rS1y8cUjyq00GxrSg7DZ1gdhfQc9CI/WwFWTwWlnWnfBXqXWyDF9AY86BS7yymqLHBnV3vO9tRGpVXrGipH1kueUpS2qCMMUwz55ddREM3Tf323EwYMBzJ2r1hWoSpAbls9VI61gtkYG5J8slLvcoPzyrRqaKbM1skH+VdhiMVaMdLnTcNaoGdJMhblqpKoVYXp7Xa2irZGZtF7t4JT/Ic8wYdVIiRVhgBaG+eqt/921zY3C5c4gGXMhMthk+ePL4PZmEA3bq3pOWDYLvPeGVgW4+JJhyXtzPKM1snOO9RdPjPlgC84OW1qBpFJrZESvMFah2yEXhFl7XjQ8ogdhHrlFG8ag/IaA3IvEllWEMQijSvfXd7wjexcqFivCrBUxVo1kRdiMHTErwqo5CKu8ijBjPpg3UL7hXiblQDKmfR/KVoQp3xqpXkUYoLVHCmEDJHz2dDgF3L40EuNOjIfkBGEOJ9B11jj2vhPAyKFOAGo+f4qp1pNBNOxCooqDsAO7/AgP16DWm8aCc8MYVigLSyXtiIxqIZ2M1kijLfKsxdZerFepIiw3/1b+64EZhFk4HwzIVYT5vJKDML01MqhKEFaKijD9uW+ziSlXp7I1koiOY6wayRlh1jBaI/2BygkuZDErwqq6NbLyZoQZK0aWcxCWjGqDg212oewwenPVSAX3L5sBINSZf5PPaI+U1RboU2Bg/uyFWnvkyKEOaftgJbdXb42s4iBsy0YtaDr7A6PKzeQ82lcHIezw+hMIWHzhIZMBdm3V5hhbOR9Me2zjNdLSh53UmB6E1fnlX/gxgrCWFkmtkZIrwqqiNdI4P5jGDDQGYUR0HFaEWcsYlu9ToHy83BnD8qu5NTLEijAlJca1IMwXTElZwWwqVJ4RZlztBdSsCAMmtmZYyZgTFg3LHJivzUGqmiBMXwUvXsUzwsz5YJeMSN6T4w3oC2q1do5ZPrvswPt+xGNOeP0pdM2z9qJcVn9pdCjQGmkGYQqM/Rgc1AIp6yvC9PN7j9yF3YyKMFVaI12laI0soC1Y0VMxIpLJWDUyGmEQVmpC5JePV05wIQuH5VdqRZh+MlnOQVhEC2lVnQ8G5IKwWgVbI435YIB6FWHQd01WRVhu5Uj5FWHh/lZkUopNTS8BY+XIRLQ6P0oN9rnRt88Lu13gnAsVDMIO60HYLOsrcXr0arAFC8csv+iRUWjVyIj+fuKXXBEmBDA4JGlYviozwkaMijDJQZheEeYoZUUYgzAimgmfL9caKeS/l1a0ZMKBdEq7oszWyJnJZGwY6teqbtqquCLMmBEWrKCKsIheEeYp42MkOV4+QZiKrZH5QZijBFeTZ8JmnHhLqwjTq7gltkY2zUqgti6JbMaJgf1BafthlVo9CKvWYfnv6m2Rpy8Ow1snabnSkxg4rK0sLyUI26YHYWdb/9hZpYIwNWaEjY25kEw6YLMJNFp8gXDYmBEmMQhLpW0IR7T9kN4aWcKKMHOhCLZGEtFMeLzam1Y2a0cyUZ0neVYx2iJtNmGu1kmFGTriQSZjh8OZRYPFcyBUwoowNRmtkV5FB+UD5dQaKf9DXj67UREmabe8CswIs9mAjtO1yqDengZp+2EVozWyWmeEbdmot0VerNCE/DxGRVibxUFYNgvs3qGFcKfLCML0MICtkTnGfLCG+qSlK3gKkTcsX2IQZswHq3Fl4PXIPYdKlXJGGFsjqRoIIe9ks1rkBzIcmF9axhUzn1/duUHlwhiU39IRVWLFJBmyWSA8YswIK9/Q6FjmjLC68v2eknkzwlSUSduQiKq7amRGP4GGLWsOp1eGIq2RxnEiS8fpowCAvt31UvfDCkZFWKIKZ4SNh53Y854WNKk4Hyw27kB4WD8fmGXtbKa+g15EIy64azOYbfF8MECd1sh02oZYTHs/kT0s/+ignLbIaMyJZFJ7fZDZGmm0RTbWxy2fl3esjLFqZAkqwgRbI6ka2Gzan3TahlE9aaficjgEaj0cmG+F3KD88m35UoU5KL+zetsix8MuZPUTjUBD5TynjNZIb7B8g7CE0RqpaEVYPJL7QK9ia2Q2bXzAU6stEsi1RgpJrZG+oPwZYQDQuUALRfp2V0FFWBW3Rm77r3pkszZ0zI2iuUO91+Te/dpFB48/DI/X2tfbXXpb5GlnjsHhtD6MMipnZV8MjES01yKt20Hu+4kxKL/J6vlgeiW7x5OA0ynvZzCsB2FNDfI7JdL687OkFWHTaI2U+45JNEXvvN2Kt95qR0tLFIFAAvPmjWLDS3MwcNSHe1e/IXv3KpLPl0I85sI4B+aX1PgYV4wsFg7Kz7VFenwp1NSqFxgUKlJBFWF+RYMwoy3SVZuBw8L2kakyZoTZ7Oo9r23SWyPlzwgDgA49CBs8VId41I5ar3q/q2LJDcuvviBs04YmAOq2Rfbt1y461Dcftfyxd0ucDwbkzUmS3BqZ63ZIS+92MFojrV4xclgflB+si1n6uMca0lsjm+rlB2GptPZ66SxBUFvIc59BGJWFH607D88/fxqu/sQejI7UIlgfx+sbu1BfH4fLlcWlHz6AJUuOyN7NiuL1pTA0CETHa2TvSkWL6EEYB+XPnNEa2VrFg/LHzLbIyno+GTPCvMEEyvWjtTEjTNWKsJh+Bd+rYDUYkKt0sKlcEZaVNSxfjYowf0MCnmAYsVAAh3b6cfoSuSullVKtR3seVltF2GC/G1v/rFX8XfQx64OmqejVg7Bg86CljyuE3EH5gDrD8sfC+nwwBS7yGkFYi8WzY435YIGA5CDMaI1UqSLMWfwFNko+I2zNmjW48MILUVdXh9bWVnzqU5/Czp07J2xz++23w2azTfhz8cUXT9gmkUhg1apVaG5uhs/nw3XXXYdDhw5NZ1eoyvy/f78R808bhd+XxJfueQM33rgNNptAe3sEPbsazZ54Kh5v3sqRVDqxcX0mj8Xl+5WIFWFAqAIH5QP5M8LKN+BLRNReNTIWVnfFSCDvA57KFWGyZoQF5Q/LN9R39QIADmz3S96T0nJX6YywV/+zDULYcNbSUbR1y/9gPZlcEGZtUHe0vxahkRo4nVnMPT1i6WMbVGmNHIuoE4TlZoRZe15kBGH1soMwhSrC0uaw/OI/P7Ni+q2R0wrCXn75Zdx11114/fXXsX79eqTTaaxYsQLj4xM/dFx11VXo6+sz//z2t7+dcPs999yDp59+Gj//+c/x6quvIhKJ4Nprr0Umo97yu6SGzs4IfvbE07DZBZ5//jR88KJe1Afj+Or/+CP+9/d/j6VL+2XvYsXx+TgjzAoJfVXO2lq+/s2UWRFWxTPCwsMVXhFWxqtGJs0ZYWoGTUZrZK2iQVgmZVSEqfdaaQZhkh4/t2qk/Pfrhll9ACo/CKutwhlhyYQdrz3XCgC47Dp1z7tlBWFGNdjcBRHUuOWk4rn2MCkPb4ro7yd+yUGYEMDQkBZIWd0amasIk3tOaqwaqcaMMO2J6SrBsPxCKsKmdenoueeem/D3devWobW1FZs2bcJll11mft3tdqO9vX3S+wiFQnjsscfw05/+FB/72McAAD/72c/Q3d2NF154AR//+Mens0tURQLBJD532xY8+fgifGvNMmzb1mKWecp+wa9ErAizRlIPwty1an74LCdHjIqwKm6NDFdgRVg6ZUNcr5z0BhKAnAvtM5ZQfNXIcmmNVLIiTHJrpPGcio05kUkDDomFYQ1dehC2o7KDsGqcEbZpQxOiYy40tsWx6IPqrRYJAGOjTm2mpE0g0DgEwLqFG2S3RQJAVr9OILsizJgRJrsiLBR2IZVywGYTaLT4vGhEH1URlFwRNpy3aqRsRkWYowQjDixfNTIUCgEAGhsbJ3x9w4YNaG1txRlnnIGVK1diYGDAvG3Tpk1IpVJYsWKF+bXOzk4sWrQIr7322qSPk0gkEA6HJ/yh6jRvXggr73wLw8O1WPahgwjWV86HPdX4/FpFCSvCSiuuLy9dw4qwGUkl7Rg5qr3ZV3NrpFERFqygijCjLRIo79bIpOIzwqKKt0aaw/JVnBEmuTUy/3dmBJqy1M/SKoWG+2oRGZHfqlkqbo8RhFXHlVghgFee1YocPnzNEdgVzf+MarDGlnE4Xda+lhlB2OkL5X1OzagyI0wPwvyS30+M+WCNjQk4LV7Fc3hU/rD8WNyBaFz7XVR6RVimgFUjC371FkLg3nvvxaWXXopFixaZX7/66qvx+OOP48UXX8R3vvMdvPnmm/joRz+KREILLPr7+1FTU4OGhokJfVtbG/r7Jy+zXbNmDYLBoPmnu7u70N2mMicE0NISxbf+14v47vfWy96dimZWhHHVyJIyK8LcDMJm4mifB0LYUFObRn1T9QbklTgjzFwxMpCSfnJfqEzahlRcOyFXtSIsPqZ4EJZRedVIvSIMcirCHE6g1mcMzJf7nu2qTaBx1hiAyq4KM1sjq2RG2OE9DTi42w+nK4tLrho49T+QxAjCWmdZG0aNDNZg8EgtbHaB+WeNWfrY+Yz2MIfkVSONIKzOL/f9bvConBUjATWG5RuD8r2eFGoV+JxhBGHOElzQKvmw/Hx33303tmzZgieffHLC12+88UZcc801WLRoET75yU/id7/7HXbt2oXf/OY3J70/IQRstslPIO6//36EQiHzz8GDBwvdbSpz+U+R1tYoRkfdGBz0yNuhCpabEcZVI0vJmBHGirCZMQfld0RxgreSqpCbEVY5Qdh4SPuefMHyrQaLhbUTYptNwBtQMwgzKolUDcKyekuFXcWKMP1sWlZFGKDOypEA0Hm61ja3f1ud5D0pnWprjXzzhdMAABcsH4Q/qOZrBAD07jOCMGvDqJ7tWjVY97xxeLzyzudUqQhTZUbY4JCcQfmplA1j+qrw9RJnhKk0HwwobWtkISFwQe+Wq1atwrPPPotXXnkFXV1dJ922o6MDc+bMQU9PDwCgvb0dyWQSIyMjE6rCBgYGsGzZsknvw+12w+12F7KrVAG2vNOK3l4/WtuiCAQS8HpTcLmyaGmJ4p++90GEw25857svyN7NisMZYdZIxlkRVgxHezkoH8ifEVa+odGxIqN6i4WilVRTEQ1rJ8S1/qSyLUUx1SvCVG6NNGeEydsHbyCN4V41Vo7sOH0U7708GweroCIsk7YjlbTBVVOe1apTER/3YusbswCoPSQfyKsI67K2Imy3AvPBgLxZioq0RtZJvvAzaK4YaW0QNBrSzsVcziy8XnnnY4Mj6qwYCZR4WH4Bq0ZO691SCIFVq1bh6aefxoYNGzBv3rxT/puhoSEcPHgQHR0dAIALLrgALpcL69evxw033AAA6Ovrw3vvvYeHH354OrtDVeLrD30Y27c3Y+HCQdhsQDCYQH1DHGeeOYQXX5iH2z7/juxdrEhcNdIaZkWYW80Pn+ViwAjCZlXvfDAgf0ZYJVWEVUAQpp8UewLqBpQxxWeEZVVujdT/awzrlcGrHx/jClSEdSzQKsIObPdDCFRkla4xIwwAkjEHXDVqHjfFsPft85DN2DH3rDHMOUPd91ghJrZGDo9a99jmoHyJ88EAIJnUgwaX3NdJY1i+3y97RpicFSON+WD19Qmpr39GRZgKg/IBIJUuZWukdt+2UlWE3XXXXXjiiSfwzDPPoK6uzpzpFQwG4fF4EIlE8OCDD+Izn/kMOjo6sG/fPvzDP/wDmpub8Rd/8RfmtnfccQdWr16NpqYmNDY24r777sPixYvNVSSJ8mUydqz55ov44EW92Le3HgcOBLB/Xz0OHQxg69YWnHnmkOxdrEisCLNGMqG9DNd6WBE2E2ZrJCvCAFRaRZgW7vnry/d7iuqtkd6AugGl2Rop+YPLiRgVYWquGqn9V0gswvAZrZEKVIS1zQ3B7sgiMurCcL8bTR3qPu8L5XACrposUkk74lGH+fOvRAe2nQ0A+PC1aleDDR+tQSLmgMOZRWNbxLIgLDLmRO9BLYCTOSgfAGL6Akwy2zOFAMYiaqwaaVaEtVgbBBkrRjZIXtTNmBGmSmtkxpgR5swCRX4rL2RG2LTeLX/wgx8AAJYvXz7h6+vWrcPtt98Oh8OBd999Fz/5yU8wOjqKjo4OfOQjH8FTTz2FurrcnIBHHnkETqcTN9xwA2KxGK644gr86Ec/gsOhaL8ASXXtJ3vQ3BxDe/s42tvHcfElh83bXt4wG7NncxXRUvD6uGqkFYxBuzVsjZyRgcPGVeDqDcIyGWBstPJmhBnD8lUdMj8VMb01UumKMKM1MqDmB/qs2Rqp3mtlrjVSYkVYwAjC5L9nO2uymHV6FAd3+nFwu78igzBAmxOWStqRqOCB+YmYE+HBZgDAwgtCkvfm5Iz5YG2z4pauELh7u/YZt6M7ijrJgWhMn1nnkXhxNZl0IJ3SAg+ZQVg2mz8jzOIgTK8Ia5B8AW9oVJujrUoQll8Rli12EKYf8iVtjTwZj8eD3//+96e8n9raWqxduxZr166dzsNTlbrjb942///YEvs7Vr6NbgZhJeHzszXSClw1sjiOmBVh6rZtlFpktMZszaor4+qpY5kzwurLNwgzKsI8CleERRVvjTRnhClYEWaQWRGm0rB8AOheGMHBnX7s3+7H+R+tzMp9tzeDyKgL8WjBa48pr29vPQAbAo1RBBrVfg3u09siO+dYe0GsZ2sQgPz5YAAQN4Iwr7zX8fGIPh/LlUGNW97rdShUg3TaDrtdoLHB2vdeIwiz+nGPNTyi74cirZH5M8ISRX45KWRYfuW+clNFSCbtePaZM/DBD/w17v/7j2B83IXvPfJBPPzNS/Dulhbc+rl3Ze9ixTJbIyNcNbKUcqtGqvnhs1wMcFi+2RbpDybhdFXO4GZj1ciynhFmtkaqG1DGVV810hwCrV4QZjfOpmUGYfpQahVaIwFg9lkRANqcsEpljDSo5JUje9+vBwDMmj8id0emwJgP1jnX4iBMkflgQK4irFZia+T4uH4uUpeWOh/LqAZraEjA6qazXEWYvCBMCLVWjcxmbebF2pKsGimm3xrJIIyU9tKLc/HE44vwP7/xEmIxF/72Syuwb289/vSnbnz1Hz6CgwcCsnexYnFYvjWSce1DCyvCCpeIORDST3iqOwirvLZIIL8iTN0Q6VRyrZHq/m64amThlGqNVKQibM7ZWhB2aKcf2Qp9e3PrYUO8ooOwBgBA57xRuTtyCtkssG+nFrpaWREWj9lxYK9WkX665IqwdNqGVEp7LnolBmHRce39Tv58MC2MarF4PhiQq8SSGYSFIzVIpR2w2QQag/KDMKMaDCjRqpH6sPzptEYyCCOl9fQ04uxzjuLKFXvR1BxFPO7E9/7383jm1/8XF1zYh5/8ZLHsXaxYHJZvjVxFWIV+UrDAQJ92FdjjTcEfLN+wZKZCFTgoH6iMGWHRMbWH5aeSNqT01yJVg7Cswq2RRtVDVoFh+cYqq7K1zYmixpNBIubAkf0e2btTEkbVTSXPCDODsNPUrgh750+zMdDrgceXxunnWBdIvb+zDiJrQ3NbHI3Nct9743nPQ7fEc8rxqBpB2NGj+nwwi1eMBICRUfnD8o2VKwN1SUtn5p1IJpN7fpZm1UjjHIFBGFWIPbsbMC/vKtQ11/aY/+9wZNGoQKlnpWJFmDWScb2MnUFYwfIH5cssw5ftjPOH8eX/8zpu+tJ22btSXMIGm12UdUVYNKR2a2Qy5kBTVwy++iRqfWoGYRmFWyNhU6giTJHWSLsD6D5Tb4/cUZntkUZFWKW2Ro6NOBEa9AIQSleECQG89MxZAICrbzoEb51151O7jLZIBeaDGW2RNe6M1OAj1xopuSJM0qB8IYDRkPxh+eaKkYrNBwMAh6P4z09j+H7JhuUTWS1YnzCDsL9Z+RY8ntwJ+rb3WnDrbVsk7Vnl87AizBLGsPwat5ofPsvBAAflAwCaO+K47LpDsnej6P7x6VfNE5yjg3L3pVB1TTH4W4bgb1TjhPRYvmAa//iH12TvxknZbICrNg2HU73XSpsKM8KCagVhgDYnbM/bQRzc7sdFnzgqe3eKzu2p7NbI/bu0ALOuaQhuj3rHnWE8FER42AuHM4vLr+239LGN+WCnKzAfzF+Xxt98cRfSablXBD906W5c9Ylx8+KFLCs+dhhnnRlC1yxrzw2zWRtuvakHI6NuNNQnMCRprZChEbVWjMxktddJpyNTkovWWXP+GIMwqhAPPvSK+f8dHbkXsljMCX8giTPOHJaxW1XBqAhLJpxIpexwuRS8Cl8B4saMMFaEFWzuGSHcfPdWzJozJntXqETsZV6/fuP/+BPe27YTCxYuBNAqe3fK0odu6MOC5W9j67adAM6SvTsTGCf1cleN1N6z4xEnMmnAocAZfvdCrSJs//Y6yXtSGrUVXhG2X6/ka+zsk7wnJzdypB2ANhvMVWPdQZhO2bFvl/bcVqEizOPN4KJL5V8tstsBn0/+OW1XVxRdXdbPjXU4BD7yYfnHTJ0/iTNPG8GcWfKfmwCQTmsncs4SVIMBQKaAGWEKvE0STZ/LlcHa7z+HmhqGM6VizAgDgFjUCVcVz14qJaM1sobD8gu2cMkQFi6RdMmNiKqeTYHWSI8/V7ETG3PC3yC/gmeOHoT17vYinbTBaWFIYQW3VzsHjVfojLD9+vD5xg75H+pPZmSgDQAw+3RrK396DzQhnbYjUJ9Ea4caVTdEhmUX9GPZBdZWSJ6MMburVLM0jRlh01k1kkEYlSWt972yTqhUU1OTgdOZQTrtQHTchQCDsJLiqpFEROXpnp+8A9gAe4mudE+FwwnU+tOIR5yIhl1KBGGNHQn4gimMh1w4vNtnriRZKSq5IkyI/CCsF0C91P05mZF+rSKs2+IgbGSwDnZHFgvODlf1fFKiqfB741j5l2/DXaJRMEJvjWRFGBHNmM2mVYWFQw7OCSuhF7Y9LrWdhoiIZkaVSidfMIV4xInxkBqn9zYbMHthBNtfb8CB7f6KC8KMC7KiApsThvrdGA+7YHdkEWw9ClWDMCHyKsLmWxuEnXfR+/j4dQLRcTWONyKVuV1pXHbhwZLdvzksnxVhRFQMnV1jqAskkUmX+YAexfFKIhERzdT1f7sPEEDr7JjsXTGZQVgFrhyZ0Fsia/2VV9FtVIO1zwnB4VT3+wsPe5CI+mCzZzFrnvUL5rhrs3DXsmOCSDZzRhiDMCIqht/98UnZu0BERERTsOgy9RYQmn2WVgV2YHvlBWHxcT0I86obFBXKGJTfedqI5D05ub79QQBAa+eYpYPyiUgtxoywo8NexBNT62RimQcRERERERXdbH1g/sB+D2KRypqlFY9q9QS1Pvnz2Ipt/65yCcLqAQAdc0el7gcRydXcoK0Qun1vC77/y/9nSv+GQRgRERERERVdXWMKzbNiEMKGN37TKnt3isqsCPNU1pCwTAY42OMDAHTOVzsI6zeCsDmjUveDiOT60PkHsermNzCrNYzm+qm9bjEIIyIiIiKikrjsr/oAAFtebpK8J8UV11eLrLSKsP4DXiTjDtR602juUHuBg8/8tzfx0c/+FAuX9sneFSKSyGYDLjynD/9z1Yv4q4/8fkr/hkEYERERERGVxJkfHAUAHNzpQyZdOavDVOqMMGM+2OwzxmFT/JNiTW0GLV2HEWiIy94VIlKA3Q74vFNbMEbxlzciIiIiIipXLV1xePxppBIO9O7xyt6doslVhFVYELbTCMLUrgYjIpoJrhpJREREREQlYbcD888PY2zYhVS8cq7BJ6IVWhG2U5sPNucsBmFEVLkYhBERERERUcncsWYHbJXTFQkgrzWygirCkgk7et/Xg7AzI0gJyTtERFQilXNZhoiIiIiIlFNpIZgQea2RFVQRdmiPF9msDXUNSTS0JGXvDhFRyTAIIyIiIiIimqJkzA4htHSvkirCjEH5c86MVFx4SUSUj0EYERERERHRFBnVYHa7gMudlbw3xXNgVy4IIyKqZAzCiIiIiIiIpih/PlglVU7t28EgjIiqA4MwIiIiIiKiKYrHjPlgacl7UjyJmB3DR9wAgNlnjkveGyKi0uKqkURERERERFPU0JLEX93zPhzOyllW0e3J4n/9x5vo3++BP1A5AR8R0WQYhBEREREREU1RoCmFD3/qiOzdKLoadxazz2A1GBFVPrZGEhERERERERFRVWAQRkREREREREREVYFBGBERERERERERVQUGYUREREREREREVBUYhBERERERERERUVVgEEZERERERERERFWBQRgREREREREREVUFBmFERERERERERFQVGIQREREREREREVFVYBBGRERERERERERVgUEYERERERERERFVBQZhRERERERERERUFRiEERERERERERFRVWAQRkREREREREREVWFaQdiaNWtw4YUXoq6uDq2trfjUpz6FnTt3mrenUin8/d//PRYvXgyfz4fOzk587nOfQ29v74T7Wb58OWw224Q/N910U3G+IyIiIiIiIiIioklMKwh7+eWXcdddd+H111/H+vXrkU6nsWLFCoyPjwMAotEoNm/ejK997WvYvHkzfvWrX2HXrl247rrrjruvlStXoq+vz/zzL//yL8X5joiIiIiIiIiIiCbhnM7Gzz333IS/r1u3Dq2trdi0aRMuu+wyBINBrF+/fsI2a9euxQc/+EEcOHAAs2fPNr/u9XrR3t4+g10nIiIiIiIiIiKauhnNCAuFQgCAxsbGk25js9lQX18/4euPP/44mpubcc455+C+++7D2NjYCe8jkUggHA5P+ENERERERERERDQd06oIyyeEwL333otLL70UixYtmnSbeDyOL3/5y7j55psRCATMr99yyy2YN28e2tvb8d577+H+++/HO++8c1w1mWHNmjV46KGHCt1VIiIiIiIiIiKiwoOwu+++G1u2bMGrr7466e2pVAo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STO-SS_INSTO-SY_INWEL_INRCHA_INCHD_INSFR_INLAK_INTOTAL_INSTO-SS_OUTSTO-SY_OUTWEL_OUTRCHA_OUTCHD_OUTSFR_OUTLAK_OUTTOTAL_OUTIN-OUTPERCENT_DISCREPANCY
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0.000000 0.0 43243.300781 11221.008789 2172.376465 \n", + "2012-02-29 0.000000 0.0 43013.406250 10831.583008 2157.964844 \n", + "2012-03-31 0.000000 0.0 43912.550781 11090.963867 2208.054443 \n", + "2012-04-30 0.000000 0.0 45098.117188 12015.685547 2326.493896 \n", + "\n", + " TOTAL_OUT IN-OUT PERCENT_DISCREPANCY \n", + "2011-12-31 60654.296875 0.396000 0.0 \n", + "2012-01-31 56793.144531 -0.195200 -0.0 \n", + "2012-02-29 56023.539062 -0.094266 -0.0 \n", + "2012-03-31 61473.503906 -0.129200 -0.0 \n", + "2012-04-30 91564.250000 0.044994 0.0 " + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "mfl = Mf6ListBudget(sim_ws / 'pleasant.list')\n", "flux, vol = mfl.get_dataframes(start_datetime='2011-12-30')\n", @@ -780,9 +1964,24 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['STO-SS_IN', 'STO-SY_IN', 'WEL_IN', 'RCHA_IN', 'CHD_IN', 'SFR_IN',\n", + " 'LAK_IN', 'TOTAL_IN', 'STO-SS_OUT', 'STO-SY_OUT', 'WEL_OUT', 'RCHA_OUT',\n", + " 'CHD_OUT', 'SFR_OUT', 'LAK_OUT', 'TOTAL_OUT', 'IN-OUT',\n", + " 'PERCENT_DISCREPANCY'],\n", + " dtype='object')" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "flux.columns" ] @@ -796,9 +1995,30 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(figsize=(10, 5))\n", "in_cols = ['STO-SS_IN', 'STO-SY_IN', 'WEL_IN', 'RCHA_IN', 'CHD_IN', 'SFR_IN', 'LAK_IN']\n", @@ -847,8 +2088,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection.ipynb b/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection.ipynb deleted file mode 100644 index 1471e01..0000000 --- a/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection.ipynb +++ /dev/null @@ -1,1587 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "c3a22877", - "metadata": {}, - "source": [ - "# Modelgrid and intersection\n", - "\n", - "The first part of this notebook is focused on the `flopy.discretization.Grid` (modelgrid) object(s). The modelgrid object(s) are a relatively new addition to FloPy's capabilities and are the backbone of plotting, exporting, and GIS data processing within FloPy. These objects are automatically created when a model is loaded. Alternatively they can also be created as a stand alone object. \n", - "\n", - "There are three types of modelgrids:\n", - "\n", - "* `StructuredGrid`: the StructuredGrid object is created for rectilinear grids. i.e. models that use a DIS file for discretization\n", - "* `VertexGrid`: the VertexGrid object is for discretizations that are defined by vertices (e.g., DISV packages)\n", - "* `UnstructuredGrid`: the UnstructuredGrid object is for unstructured discretizations (e.g., DISU and MODFLOW-USG)\n", - "\n", - "These objects all have a common interface defined by the base `Grid` class. What this means for the user is if they want to get the cell center coordinates from a modelgrid, the function call is identical on all three grids.\n", - "\n", - "The best way to learn about these classes is by checking them out. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "72833c87", - "metadata": {}, - "outputs": [ - { - "ename": "ModuleNotFoundError", - "evalue": "No module named 'pygeohydro'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[1], line 12\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mgeopandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mgpd\u001b[39;00m\n\u001b[1;32m 10\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mshapely\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mgeometry\u001b[39;00m\n\u001b[0;32m---> 12\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpygeohydro\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mgh\u001b[39;00m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpynhd\u001b[39;00m\n\u001b[1;32m 14\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpydaymet\u001b[39;00m\n", - "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'pygeohydro'" - ] - } - ], - "source": [ - "import os\n", - "from pathlib import Path\n", - "import flopy\n", - "from flopy.utils.gridgen import Gridgen\n", - "from flopy.utils import GridIntersect, Raster\n", - "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt\n", - "import geopandas as gpd\n", - "import shapely.geometry\n", - "\n", - "\n", - "# pd.options.mode.chained_assignment = None\n", - "data_path = Path(\"..\", \"data\", \"modelgrid_intersection\")" - ] - }, - { - "cell_type": "markdown", - "id": "b9ea69ac", - "metadata": {}, - "source": [ - "## Grids" - ] - }, - { - "cell_type": "markdown", - "id": "d78299e2", - "metadata": {}, - "source": [ - "## StructuredGrid\n", - "\n", - "Let's start with the most common type of MODFLOW modelgrid, the `StructuredGrid`\n", - "\n", - "#### First we'll build one from scratch " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7154ce13", - "metadata": {}, - "outputs": [], - "source": [ - "nrow = 20\n", - "ncol = 15\n", - "nlay = 1\n", - "\n", - "grad = np.expand_dims(np.linspace(50, 100, nrow), axis=1)[::-1]\n", - "top = np.ones((nrow, ncol)) * grad\n", - "botm = np.zeros((nlay, nrow, ncol))\n", - "botm[0, :, :] = top - 50 \n", - "delr = np.full((ncol,), 250)\n", - "delc = np.full((nrow,), 150)\n", - "ibound = np.ones((nlay, nrow, ncol))\n", - "ibound[0, 4:10, 4:8] = 0\n", - "\n", - "modelgrid = flopy.discretization.StructuredGrid(\n", - " delc,\n", - " delr,\n", - " top,\n", - " botm,\n", - " ibound,\n", - ")\n", - "print(modelgrid)\n", - "print(type(modelgrid))" - ] - }, - { - "cell_type": "markdown", - "id": "f568611b", - "metadata": {}, - "source": [ - "Let's take a look at our modelgrid visually" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8eabc8cd", - "metadata": {}, - "outputs": [], - "source": [ - "modelgrid.plot();" - ] - }, - { - "cell_type": "markdown", - "id": "59337e12", - "metadata": {}, - "source": [ - "This is great, but what if we want to orient it in space and add a coordinate reference system so we can do further processing? \n", - "\n", - "The `set_coord_info()` method allows us to update the coordinate offsets, rotation of the grid, and even add projection information." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bd579167", - "metadata": {}, - "outputs": [], - "source": [ - "xoff = 2345678\n", - "yoff = 1234567\n", - "angrot = -15\n", - "epsg = 32610 # utm zone 10N\n", - "\n", - "modelgrid.set_coord_info(xoff=xoff, yoff=yoff, angrot=angrot, epsg=epsg)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "075e0165", - "metadata": {}, - "outputs": [], - "source": [ - "fig, ax = plt.subplots(figsize=(10, 10))\n", - "ax = modelgrid.plot(ax=ax)\n", - "plt.title(str(modelgrid));" - ] - }, - { - "cell_type": "markdown", - "id": "67c85c8e", - "metadata": {}, - "source": [ - "### Getting cell centers and cell vertices\n", - "\n", - "* Cell centers can be returned to the user through the `.xcellcenters`, `.ycellcenter`, and `.zcellcenter` properties.\n", - "* Cell vertices can be returned to the user through the `.xvertices` and `.yvertices` properties" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "046226a5", - "metadata": {}, - "outputs": [], - "source": [ - "xc, yc = modelgrid.xcellcenters, modelgrid.ycellcenters\n", - "xv, yv = modelgrid.xvertices, modelgrid.yvertices\n", - "\n", - "fig, ax = plt.subplots(figsize=(10, 10))\n", - "modelgrid.plot()\n", - "ax.scatter(xc.ravel(), yc.ravel(), c=\"b\", label=\"cell centers\")\n", - "ax.scatter(xv.ravel(), yv.ravel(), c=\"r\", label=\"cell vertices\")\n", - "plt.legend(loc=0);" - ] - }, - { - "cell_type": "markdown", - "id": "82be3a1c", - "metadata": {}, - "source": [ - "### Getting the ibound/idomain array\n", - "\n", - "The `.idomain` method returns the ibound/idomain array" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6392c804", - "metadata": {}, - "outputs": [], - "source": [ - "ibound = modelgrid.idomain\n", - "\n", - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "pmv = flopy.plot.PlotMapView(modelgrid=modelgrid, ax=ax)\n", - "pmv.plot_grid()\n", - "pmv.plot_array(ibound, masked_values=[0,]);" - ] - }, - { - "cell_type": "markdown", - "id": "9497c9a2", - "metadata": {}, - "source": [ - "### Getting the model top, bottom, delc, and delr\n", - "\n", - "The model top, bottom, delc, and delr can be accessed from the modelgrid using `.top`, `.bottom`, `.delc`, and `.delr`." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "773296c6", - "metadata": {}, - "outputs": [], - "source": [ - "top = modelgrid.top\n", - "botm = modelgrid.botm\n", - "delc = modelgrid.delc\n", - "delr = modelgrid.delr\n", - "top, botm, delc, delr" - ] - }, - { - "cell_type": "markdown", - "id": "2cde8114", - "metadata": {}, - "source": [ - "## Class exercise 1:\n", - "\n", - "Assume that the modelgrid is currently in meters and we want our grid to be in feet. Create a new modelgrid object from the existing one where the discretization is in feet.\n", - "\n", - "make a plot of the new modelgrid after it has been created" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6313fa4b", - "metadata": {}, - "outputs": [], - "source": [ - "conv = 3.28084\n", - "mg2 = flopy.discretization.StructuredGrid(\n", - " modelgrid.delc * conv,\n", - " modelgrid.delr * conv,\n", - " modelgrid.top * conv,\n", - " modelgrid.botm * conv,\n", - " modelgrid.idomain,\n", - " xoff=xoff * conv,\n", - " yoff=yoff * conv,\n", - " angrot=angrot\n", - ")\n", - "print(mg2)\n", - "mg2.plot();" - ] - }, - { - "cell_type": "markdown", - "id": "474d307a", - "metadata": {}, - "source": [ - "### Finding a cell's nearest neighbors\n", - "\n", - "Imagine that we want to find the nearest neighbors of a cell for some reason. The modelgrid has a built in method to 1) internally construct a table of nearest neighbors and 2) return the nearest neighbors for a given cell to the user." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9b7fd96b", - "metadata": {}, - "outputs": [], - "source": [ - "cell = (0, 0, 5)\n", - "\n", - "neighbors = modelgrid.neighbors(*cell)\n", - "neighbors" - ] - }, - { - "cell_type": "markdown", - "id": "5047684b", - "metadata": {}, - "source": [ - "### Finding grid cells by point location\n", - "\n", - "If we want to find a cell number based on x, y coordinate location the model grid has a built in `.intersect()` method that takes `x`, `y`, and an optional `z` coordinate and returns the cell number " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6426d2bc", - "metadata": {}, - "outputs": [], - "source": [ - "x, y, z = 2348000, 1235000, 25\n", - "\n", - "rowcol = modelgrid.intersect(x, y) # without z\n", - "layrowcol = modelgrid.intersect(x, y, z) # with z location\n", - "\n", - "f\"{rowcol=}, {layrowcol=}\"" - ] - }, - { - "cell_type": "markdown", - "id": "8389b845", - "metadata": {}, - "source": [ - "## Vertex model grid\n", - "\n", - "The vertex model grid is produced for MODFLOW model discretizations that are defined by verticies (`DISV`). We can build a quadtree vertex grid from an exiting structured modelgrid using the gridgen utility and the `Gridgen` class." - ] - }, - { - "cell_type": "markdown", - "id": "1791cc4a", - "metadata": {}, - "source": [ - "First let's unrotate the grid coordinates of our structured grid to make this easy" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "50642957", - "metadata": {}, - "outputs": [], - "source": [ - "modelgrid.set_coord_info(angrot=0)\n", - "modelgrid.plot();" - ] - }, - { - "cell_type": "markdown", - "id": "7d4cd2c4", - "metadata": {}, - "source": [ - "Lets load a couple of shapefiles to help with creating the quadtree" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "70fc1ed9", - "metadata": {}, - "outputs": [], - "source": [ - "active_shp = data_path / \"active_area.shp\"\n", - "refine_shp = data_path / \"refined_area.shp\"\n", - "\n", - "active = gpd.read_file(active_shp)\n", - "refined = gpd.read_file(refine_shp)" - ] - }, - { - "cell_type": "markdown", - "id": "1c85d598", - "metadata": {}, - "source": [ - "Now let's plot these areas on the grid to visualize them" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5ed44ddb", - "metadata": {}, - "outputs": [], - "source": [ - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "\n", - "pmv = flopy.plot.PlotMapView(modelgrid=modelgrid)\n", - "pmv.plot_grid()\n", - "# active.geometry.to_list()\n", - "pmv.plot_shapes(active.geometry.to_list(), alpha=0.5, cmap='plasma')\n", - "pmv.plot_shapes(refined.geometry.to_list(), alpha=0.5, cmap='magma');" - ] - }, - { - "cell_type": "markdown", - "id": "c747c5bc", - "metadata": {}, - "source": [ - "### Generate the quadtree grid using `Gridgen`" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d5d43d7e", - "metadata": {}, - "outputs": [], - "source": [ - "g = Gridgen(modelgrid, model_ws=data_path)\n", - "g.add_refinement_features(refined.geometry.to_list(), \"polygon\", 1, [0,])\n", - "g.build(verbose=False)" - ] - }, - { - "cell_type": "markdown", - "id": "b0998989", - "metadata": {}, - "source": [ - "#### Create a vertex model grid from the results" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a3ed5439", - "metadata": {}, - "outputs": [], - "source": [ - "gridprops = g.get_gridprops_vertexgrid()\n", - "vertexgrid = flopy.discretization.VertexGrid(**gridprops)\n", - "vertexgrid.plot();" - ] - }, - { - "cell_type": "markdown", - "id": "8a7cce38", - "metadata": {}, - "source": [ - "### Getting the modelgrid's shape\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7a02615f", - "metadata": {}, - "outputs": [], - "source": [ - "shape = vertexgrid.shape\n", - "shape" - ] - }, - { - "cell_type": "markdown", - "id": "49458e73", - "metadata": {}, - "source": [ - "## Class Exercise 2: \n", - "\n", - "Find and plot all of the nearest neighbors at node 79 on the vertex modelgrid.\n", - "\n", - "**Hint**: Use `flopy.plot.PlotMapView` for your plotting, and plot a boolean (1, 0) array with the cells that are not neighbors masked out.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fad34d11", - "metadata": {}, - "outputs": [], - "source": [ - "neighbors = vertexgrid.neighbors(80)\n", - "arr = np.zeros((vertexgrid.shape[-1]), dtype=int)\n", - "arr[neighbors] = 1\n", - "\n", - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "pmv = flopy.plot.PlotMapView(ax=ax, modelgrid=vertexgrid)\n", - "pmv.plot_grid(zorder=3)\n", - "pmv.plot_array(arr, masked_values=[0,]);" - ] - }, - { - "cell_type": "markdown", - "id": "0426f4ab", - "metadata": {}, - "source": [ - "## UnstructuredGrid\n", - "\n", - "The `UnstructuredGrid` class is used with MODFLOW-USG and MODFLOW-6 DISU type discretizations. We can also create an `UnstructuredGrid` object from the `Gridgen` results" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b6571b07", - "metadata": {}, - "outputs": [], - "source": [ - "gridprops = g.get_gridprops_unstructuredgrid()\n", - "\n", - "ugrid = flopy.discretization.UnstructuredGrid(**gridprops)\n", - "ugrid, type(ugrid)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "afe46f93", - "metadata": {}, - "outputs": [], - "source": [ - "ugrid.plot();" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5575ecf9", - "metadata": {}, - "outputs": [], - "source": [ - "neighbors = ugrid.neighbors(79)\n", - "arr = np.zeros(ugrid.shape, dtype=int)\n", - "arr[neighbors] = 1\n", - "\n", - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "\n", - "pmv = flopy.plot.PlotMapView(ax=ax, modelgrid=ugrid)\n", - "pmv.plot_grid()\n", - "pmv.plot_array(arr, masked_values=[0,]);" - ] - }, - { - "cell_type": "markdown", - "id": "32fb78b6", - "metadata": {}, - "source": [ - "## Intersecting geospatial data\n", - "\n", - "In this part of the lesson we will intersect geospatial data with a modelgrid and begin building a simple adaptation of the Sagehen Creek model, near Truckee, CA. While building this model, we'll work with shapefile and raster data. As we build the model FloPy's intersection capabilities will be presented.\n", - "\n", - "Let's start by getting the basin boundary. For the Sagehen Creek model, we're interested in the contributing area for [USGS gage 10343500](https://waterdata.usgs.gov/ca/nwis/uv/?site_no=10343500&PARAmeter_cd=00065,00060) " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "014f4da6", - "metadata": {}, - "outputs": [], - "source": [ - "import pynhd as nhd\n", - "\n", - "nldi = nhd.NLDI()\n", - "station_id = \"10343500\"\n", - "\n", - "basin = nldi.get_basins(station_id)\n", - "basin" - ] - }, - { - "cell_type": "markdown", - "id": "428b1d96", - "metadata": {}, - "source": [ - "First thing that we notice is that the basin polygon is projected in decimal degrees, which is not good for modeling. An equal area projection would be better suited for this application" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f0c0b47b", - "metadata": {}, - "outputs": [], - "source": [ - "# if pynhd is acting up load shapefile from disk\n", - "# basin = gpd.read_file(data_path / \"sagehen_basin.shp\")\n", - "epsg = 26911 # NAD83 utm zone 11 N, epsg: 26911\n", - "basin = basin.to_crs(epsg=epsg)\n", - "basin" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1a4b2134", - "metadata": {}, - "outputs": [], - "source": [ - "basin.plot()" - ] - }, - { - "cell_type": "markdown", - "id": "30620402", - "metadata": {}, - "source": [ - "We can now get our basin's bounding box using `.bounds`, buffer it, and then begin creating a modelgrid based on the basin boundary." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "26693e3c", - "metadata": {}, - "outputs": [], - "source": [ - "cellsize = 90 # 90 m grid\n", - "bounds = basin.bounds\n", - "xmin = bounds.loc[station_id, \"minx\"] - (cellsize * 1)\n", - "ymin = bounds.loc[station_id, \"miny\"] - (cellsize * 1)\n", - "xmax = bounds.loc[station_id, \"maxx\"] + (cellsize * 1)\n", - "ymax = bounds.loc[station_id, \"maxy\"] + (cellsize * 1)" - ] - }, - { - "cell_type": "markdown", - "id": "88e9ff72", - "metadata": {}, - "source": [ - "Calculate the number of rows and columns the model will have and then create a delc and delr array." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e7de4cad", - "metadata": {}, - "outputs": [], - "source": [ - "dx = xmax - xmin\n", - "dy = ymax - ymin\n", - "\n", - "nlay = 1\n", - "nrow = np.ceil(dy / cellsize).astype(int)\n", - "ncol = np.ceil(dx / cellsize).astype(int)\n", - "delr = np.full((ncol,), cellsize)\n", - "delc = np.full((nrow,), cellsize)\n", - "\n", - "# let's create a fake top and bottom for now\n", - "top = np.full((nrow, ncol), 100)\n", - "botm = np.full((nlay, nrow, ncol), 0)" - ] - }, - { - "cell_type": "markdown", - "id": "3dd72559", - "metadata": {}, - "source": [ - "Now we can create a minimal modelgrid from the information we have" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c796e3f3", - "metadata": {}, - "outputs": [], - "source": [ - "modelgrid = flopy.discretization.StructuredGrid(\n", - " delc,\n", - " delr,\n", - " top=top,\n", - " botm=botm,\n", - " nlay=nlay,\n", - " xoff=xmin,\n", - " yoff=ymin,\n", - " epsg=epsg\n", - ")\n", - "print(modelgrid)\n", - "print(modelgrid.is_complete)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f98ef0fd", - "metadata": {}, - "outputs": [], - "source": [ - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "\n", - "ax = basin.plot(ax=ax)\n", - "modelgrid.plot(ax=ax, lw=0.5);" - ] - }, - { - "cell_type": "markdown", - "id": "0a96c0b8", - "metadata": {}, - "source": [ - "Fantastic! The modelgrid has been created and it completely overlays the contributing area." - ] - }, - { - "cell_type": "markdown", - "id": "12e0691f", - "metadata": {}, - "source": [ - "### Intersecting a polygon with the modelgrid\n", - "\n", - "FloPy has a utility named `GridIntersect` that allows the user to intersect points, polygons, and polylines with modelgrid objects. \n", - "\n", - "In this example, the basin boundary will be intersected with the modelgrid to create the active and inactive extents of the model. The `.intersect()` method returns a numpy recarry with cellids, verticies, cell areas, and shapely polygon objects." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a8c64285", - "metadata": {}, - "outputs": [], - "source": [ - "gx = GridIntersect(modelgrid)\n", - "\n", - "result = gx.intersect(basin.loc[station_id, \"geometry\"])\n", - "result.cellids" - ] - }, - { - "cell_type": "markdown", - "id": "178b1022", - "metadata": {}, - "source": [ - "create the ibound/idomain array (active and incative model cells)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b9a4efb3", - "metadata": {}, - "outputs": [], - "source": [ - "ibound = np.zeros((nlay, nrow, ncol))\n", - "i, j = zip(*result.cellids)\n", - "ibound[:, i, j] = 1\n", - "print(ibound)\n", - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "pmv = flopy.plot.PlotMapView(modelgrid=modelgrid, ax=ax)\n", - "pmv.plot_grid(lw=0.5)\n", - "pmv.plot_array(ibound, masked_values=[0], cmap=\"viridis\")" - ] - }, - { - "cell_type": "markdown", - "id": "71cde52d", - "metadata": {}, - "source": [ - "### Intersecting raster data with a modelgrid\n", - "\n", - "FloPy's `Raster` class allows us to intersect and resample raster data to the model grid. This class is useful for resampling a number of gridded products such as: Digital Elevation Model data, land cover data, and gridded climate data.\n", - "\n", - "The first example of using the `Raster` class will be to resample Digital Elevation Model (DEM) data to define the land surface of the Sagehen model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9be5182b", - "metadata": {}, - "outputs": [], - "source": [ - "dem_file = data_path / \"dem_30m.img\"\n", - "\n", - "raster = Raster.load(dem_file)" - ] - }, - { - "cell_type": "markdown", - "id": "b09c2786", - "metadata": {}, - "source": [ - "#### Now that the raster is loaded we can resample it\n", - "\n", - "The `resample_to_grid()` method performs geostatistics and returns an array in the shape of the modelgrid. Options for resampling include `\"nearest\"`, `\"linear\"` (bilinear), `\"cubic\"` (bicubic), `\"max\"`, `\"min\"`, `\"mean\"`, `\"median\"`, and `\"mode\"` (most common value)." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3e6057f8", - "metadata": {}, - "outputs": [], - "source": [ - "# let's get the nearest neighbor elevations\n", - "dem_data = raster.resample_to_grid(\n", - " modelgrid,\n", - " band=raster.bands[0],\n", - " method=\"nearest\",\n", - " multithread=True,\n", - " thread_pool=12\n", - ")\n", - "dem_data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ec16505d", - "metadata": {}, - "outputs": [], - "source": [ - "# Now let's plot it up and see what we have\n", - "fig, ax = plt.subplots(figsize=(10, 8)) \n", - "pmv = flopy.plot.PlotMapView(ax=ax, modelgrid=modelgrid)\n", - "\n", - "pmv.plot_grid(lw=0.5, zorder=3)\n", - "pc = pmv.plot_array(dem_data, alpha=0.75, zorder=1, cmap=\"viridis\")\n", - "pmv.plot_array(ibound, masked_values=[1], cmap=\"magma\", zorder=2)\n", - "plt.colorbar(pc, shrink=0.7);" - ] - }, - { - "cell_type": "markdown", - "id": "370b8b15", - "metadata": {}, - "source": [ - "### Start creating model files from the data we've gathered so far.\n", - "\n", - "At this point we have almost everything we need to begin creating a model discretization package. The only thing left to calculate is the model bottom. Let's assume bedrock 150 m below land surface throughout the basin and begin creating our model. \n" - ] - }, - { - "cell_type": "markdown", - "id": "dc084602", - "metadata": {}, - "source": [ - "We'll first start by creating our simulation object and adding a solver and the time discretization. This model will be a year long with 12 stress periods and a daily time step" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a68ba62a", - "metadata": {}, - "outputs": [], - "source": [ - "sim = flopy.mf6.MFSimulation(\"sagehen\", sim_ws=data_path)\n", - "ims = flopy.mf6.ModflowIms(sim, complexity=\"COMPLEX\")\n", - "nper = 12\n", - "perlen = (31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31)\n", - "period_data = [(i, i, 1.0) for i in perlen]\n", - "tdis = flopy.mf6.ModflowTdis(\n", - " sim,\n", - " nper=12,\n", - " perioddata=period_data,\n", - " time_units=\"days\"\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "d5c0ba6b", - "metadata": {}, - "source": [ - "Now to create the Groundwater flow model object and add the dis file to it" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0953b65d", - "metadata": {}, - "outputs": [], - "source": [ - "gwf = flopy.mf6.ModflowGwf(\n", - " sim,\n", - " modelname='sagehen',\n", - " save_flows=True,\n", - ")\n", - "\n", - "# add the dis package\n", - "botm = np.expand_dims(dem_data, axis=0) - 200\n", - "dis = flopy.mf6.ModflowGwfdis(\n", - " gwf,\n", - " nrow=modelgrid.nrow,\n", - " ncol=modelgrid.ncol,\n", - " delr=modelgrid.delr,\n", - " delc=modelgrid.delc,\n", - " top=dem_data,\n", - " botm=botm,\n", - " idomain=ibound\n", - ")\n", - "\n", - "gwf" - ] - }, - { - "cell_type": "markdown", - "id": "34d64a8f", - "metadata": {}, - "source": [ - "We can also add an initial conditions file to the model. Let's assume water level begins at 5 meters below land surface" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "29159be8", - "metadata": {}, - "outputs": [], - "source": [ - "ic = flopy.mf6.ModflowGwfic(gwf, strt=dem_data - 35)\n", - "gwf" - ] - }, - { - "cell_type": "markdown", - "id": "35bfb1ca", - "metadata": {}, - "source": [ - "And we can create our NPF and STO packages using values from literature" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d44c69ce", - "metadata": {}, - "outputs": [], - "source": [ - "npf = flopy.mf6.ModflowGwfnpf(\n", - " gwf,\n", - " save_flows=True,\n", - " save_specific_discharge=True,\n", - " k=0.022 # value from Larsen et al, 2022\n", - ")\n", - "\n", - "sto = flopy.mf6.ModflowGwfsto(\n", - " gwf,\n", - " save_flows=True,\n", - " iconvert=1,\n", - " ss=1e-07, # values from Larsen et al, 2022\n", - " sy=0.2\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "eae7944a", - "metadata": {}, - "source": [ - "We can also add a OC package now" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4385aa9d", - "metadata": {}, - "outputs": [], - "source": [ - "# build output control package\n", - "budget_file = \"sagehen.cbc\"\n", - "head_file = \"sagehen.hds\"\n", - "saverecord = {i: [(\"HEAD\", \"ALL\"), (\"BUDGET\", \"ALL\")] for i in range(gwf.nper)}\n", - "oc = flopy.mf6.ModflowGwfoc(\n", - " gwf,\n", - " budget_filerecord=budget_file,\n", - " head_filerecord=head_file,\n", - " saverecord=saverecord,\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "9a9c182a", - "metadata": {}, - "source": [ - "### Getting and processing daymet climate data" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "67db0bc1", - "metadata": {}, - "outputs": [], - "source": [ - "import pydaymet as daymet\n", - "import utm\n", - "\n", - "\n", - "xmin, xmax, ymin, ymax = modelgrid.extent\n", - "\n", - "# convert UTM to decimal lat lon for daymet query\n", - "# ymin, xmin = utm.to_latlon(ext[0], ext[2], 11, \"N\")\n", - "# ymax, xmax = utm.to_latlon(ext[1], ext[3], 11, \"N\")\n", - "geom = shapely.geometry.box(xmin, ymin, xmax, ymax)\n", - "\n", - "dates = (\"2021-01-01\", \"2021-12-31\")\n", - "daily = daymet.get_bygeom(geom, dates, crs=26911, variables=\"prcp\", pet=\"penman_monteith\")\n", - "daily" - ] - }, - { - "cell_type": "markdown", - "id": "1412357b", - "metadata": {}, - "source": [ - "Group Xarray into monthly data and reproject in UTM coordinates" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7d560548", - "metadata": {}, - "outputs": [], - "source": [ - "mm_clim = daily[[\"pet\", \"prcp\"]].resample(time=\"1M\").mean()\n", - "mm_clim = mm_clim.rio.reproject(f\"EPSG:{epsg}\")\n", - "mm_clim.prcp" - ] - }, - { - "cell_type": "markdown", - "id": "f60dafb6", - "metadata": {}, - "source": [ - "Convert the montly mean precipitation and potential evapotranspiration datasets to rasters" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "521b9db1", - "metadata": {}, - "outputs": [], - "source": [ - "pet_raster = data_path / \"pet.tif\"\n", - "prcp_raster = data_path / \"prcp.tif\"\n", - "mm_clim.pet.rio.to_raster(pet_raster)\n", - "mm_clim.prcp.rio.to_raster(prcp_raster)" - ] - }, - { - "cell_type": "markdown", - "id": "3c06684d", - "metadata": {}, - "source": [ - "## Class Exercise: Loading and resampling rasters\n", - "\n", - "Load the potential evapotranspiration raster `pet_raster` using flopy's `Raster` class and create a dictionary of resampled PET that stores all 12 months of values.\n", - "\n", - "**Hints:**\n", - "\n", - " - Rasters contain multiple datasets called bands, the `Raster` class has a `.bands` attribute that returns a list of all of the bands within the raster. Lists can be looped over!\n", - " - Becasue the data is coarse compared to our model discretization, the nearest neighbor method should be appropriate for resampling `method=\"nearest\"`\n", - " - Finally no data values should be converted to 0 value. The `Raster` class has a `.nodatavals` attribute that returns a list of no data values. There is only one in this list; use numpy's boolean indexing or `np.where()` to replace all of the no data entries with 0." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e97525f0", - "metadata": {}, - "outputs": [], - "source": [ - "rstr = flopy.utils.Raster.load(pet_raster)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7ab932b9", - "metadata": {}, - "outputs": [], - "source": [ - "pet_monthly = {}\n", - "for band in rstr.bands:\n", - " t = rstr.resample_to_grid(\n", - " modelgrid,\n", - " band,\n", - " method=\"nearest\"\n", - " )\n", - " t[t == rstr.nodatavals[0]] = 0\n", - " pet_monthly[band - 1] = t\n", - "\n", - "pet_monthly" - ] - }, - { - "cell_type": "markdown", - "id": "a6638822", - "metadata": {}, - "source": [ - "Let's load the saved version of this data, it should be identical to the data that was produced in the exercise." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7469763b", - "metadata": {}, - "outputs": [], - "source": [ - "arr = np.genfromtxt(data_path / \"pet.txt\")\n", - "arr.shape = (12, modelgrid.nrow, modelgrid.ncol)\n", - "pet_monthly = {i: a for i, a in enumerate(arr)}\n", - "pet_monthly" - ] - }, - { - "cell_type": "markdown", - "id": "330ebe43", - "metadata": {}, - "source": [ - "And resample the precipitation raster we saved earlier" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4cb67791", - "metadata": {}, - "outputs": [], - "source": [ - "rstr = flopy.utils.Raster.load(prcp_raster)\n", - "prcp_monthly = {}\n", - "for band in rstr.bands:\n", - " t = rstr.resample_to_grid(\n", - " modelgrid,\n", - " band,\n", - " method=\"nearest\"\n", - " )\n", - " t[t == rstr.nodatavals[0]] = 0\n", - " prcp_monthly[band - 1] = t\n", - " \n", - "prcp_monthly" - ] - }, - { - "cell_type": "markdown", - "id": "9864665e", - "metadata": {}, - "source": [ - "Potetial evapotranspiration and Precipitation data from daymet are in mm/day, however our discretization is meters/day. " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5556e58f", - "metadata": {}, - "outputs": [], - "source": [ - "prcp_monthly = {k: v * 0.001 for k, v in prcp_monthly.items()}\n", - "pet_monthly = {k: v * 0.001 for k, v in pet_monthly.items()}" - ] - }, - { - "cell_type": "markdown", - "id": "bc8ab240", - "metadata": {}, - "source": [ - "Finally we can load a saved soil hydraulic conductivity array, and we have the information we need to create a Unsaturated Zone Flow (UZF) package for this model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c6310044", - "metadata": {}, - "outputs": [], - "source": [ - "ksat_raster = data_path / \"ksat.img\"\n", - "rstr = flopy.utils.Raster.load(ksat_raster)\n", - "vks = rstr.resample_to_grid(\n", - " modelgrid,\n", - " rstr.bands[0],\n", - " method=\"nearest\"\n", - ")\n", - "\n", - "vks[vks == rstr.nodatavals[0]] = np.nan\n", - "vks[np.isnan(vks)] = np.nanmean(vks)\n", - "vks *= 0.0864 \n", - "plt.imshow(vks)\n", - "plt.colorbar(shrink=0.6); # um per sec to m per day" - ] - }, - { - "cell_type": "markdown", - "id": "af094113", - "metadata": {}, - "source": [ - "#### Creating a UZF package \n", - "\n", - "Now that we have some climate and soils data we can create a UZF package from it and add it to the model!\n", - "\n", - "Create the package data and the stress period data info for flopy" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6283510f", - "metadata": {}, - "outputs": [], - "source": [ - "modelgrid = gwf.modelgrid\n", - "modelgrid.set_coord_info(xoff=xmin, yoff=ymin)\n", - "package_data = []\n", - "cnt = 0\n", - "for i in range(modelgrid.nrow):\n", - " for j in range(modelgrid.ncol):\n", - " if modelgrid.idomain[0, i, j] == 0:\n", - " continue\n", - " \n", - " rec = (cnt, (0, i, j), 1, 0, 1.0, vks[i, j], 0.1, 0.38, 0.1, 3.5)\n", - " package_data.append(rec)\n", - " cnt += 1\n", - "\n", - "period_data = {}\n", - "for per in range(gwf.nper):\n", - " spd = []\n", - " cnt = 0\n", - " for i in range(modelgrid.nrow * modelgrid.ncol):\n", - " if modelgrid.idomain.ravel()[i] == 0:\n", - " continue\n", - " rec = (cnt, prcp_monthly[per].ravel()[i], pet_monthly[per].ravel()[i], 0.5, 0.2, -1.1, -75, 1.0)\n", - " spd.append(rec)\n", - " cnt += 1\n", - " \n", - " period_data[per] = spd" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d14f6df9", - "metadata": {}, - "outputs": [], - "source": [ - "uzf = flopy.mf6.ModflowGwfuzf(\n", - " gwf,\n", - " simulate_et=True,\n", - " ntrailwaves=15,\n", - " nwavesets=100,\n", - " packagedata=package_data,\n", - " perioddata=period_data,\n", - " unsat_etwc=True,\n", - " linear_etwc=True,\n", - " simulate_gwseep=True\n", - ")" - ] - }, - { - "cell_type": "markdown", - "id": "6bc25d48", - "metadata": {}, - "source": [ - "### Now to create a simple river package from NHD flowlines \n", - "\n", - "We can use the intersection routines that have been presented thus far to create a river package for the sagehen model. " - ] - }, - { - "cell_type": "markdown", - "id": "44e4060c", - "metadata": {}, - "source": [ - "The first step is to get the NHD flowlines for the basin" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "513512bb", - "metadata": {}, - "outputs": [], - "source": [ - "# get the basin boundary\n", - "nldi = nhd.NLDI()\n", - "basin = nldi.get_basins(station_id)\n", - "\n", - "# get nhd plus medium resolution data\n", - "mr = nhd.WaterData(\"nhdflowline_network\")\n", - "nhdp_mr = mr.bygeom(basin.geometry[0])\n", - "nhdp_mr = nhdp_mr.to_crs(epsg=epsg)\n", - "nhdp_mr.plot()" - ] - }, - { - "cell_type": "markdown", - "id": "30e6d2f5", - "metadata": {}, - "source": [ - "Excellent! Now we have all of the flow lines for the Sagehen watershed. But what if we want to identify the main stem? " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "87b4a83b", - "metadata": {}, - "outputs": [], - "source": [ - "flw_main = nldi.navigate_byid(\n", - " fsource=\"nwissite\",\n", - " fid=f\"USGS-{station_id}\",\n", - " navigation=\"upstreamMain\",\n", - " source=\"flowlines\",\n", - " distance=1000,\n", - ")\n", - "flw_main = flw_main.to_crs(epsg=epsg)\n", - "flw_main.plot()\n", - "flw_main" - ] - }, - { - "cell_type": "markdown", - "id": "fdf6a82e", - "metadata": {}, - "source": [ - "Great! Now we can start processing data to create a river package. We can first identify our main stem cells." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bc236aeb", - "metadata": {}, - "outputs": [], - "source": [ - "main_stem = []\n", - "gx = GridIntersect(modelgrid)\n", - "for iloc, row in flw_main.iterrows():\n", - " results = gx.intersect(row.geometry)\n", - " main_stem += list(results.cellids)\n", - "main_stem[0:5]" - ] - }, - { - "cell_type": "markdown", - "id": "747a7c97", - "metadata": {}, - "source": [ - "## Class Exercise:\n", - "\n", - "Use GridIntersect to create a list of tributary cells from the `nhdp_mr` geodataframe. \n", - "\n", - "**Hint**\n", - "Use the `main_stem` list to filter out cells that are associated with the main stem of the river and only store the cells that are associated with tributaries to the main stem." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4972e581", - "metadata": {}, - "outputs": [], - "source": [ - "tributaries = []\n", - "gx = GridIntersect(modelgrid)\n", - "for iloc, row in nhdp_mr.iterrows():\n", - " results = gx.intersect(row.geometry)\n", - " for res in results.cellids:\n", - " if res in main_stem:\n", - " continue\n", - " else:\n", - " tributaries.append(res)\n", - " \n", - "tributaries[0:5]\n", - "with open(data_path / \"trib_cells.txt\", 'w') as foo:\n", - " for line in tributaries:\n", - " foo.write(f\"{line[0]},{line[1]}\\n\")" - ] - }, - { - "cell_type": "markdown", - "id": "5709f808", - "metadata": {}, - "source": [ - "The cellids for tributaries have been stored previously, so we'll load those up and continue on.\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d85d59db", - "metadata": {}, - "outputs": [], - "source": [ - "tributaries = []\n", - "with open(data_path / \"trib_cells.txt\") as foo:\n", - " for line in foo:\n", - " t = line.strip().split(\",\")\n", - " tributaries.append((int(t[0]), int(t[1])))" - ] - }, - { - "cell_type": "markdown", - "id": "346df19a", - "metadata": {}, - "source": [ - "#### We can also get daily discharge data to help calculate average monthly stages for the RIV package\n", - "\n", - "We'll use the `hydrofunctions` package to get stage information for our model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ff1a57e1", - "metadata": {}, - "outputs": [], - "source": [ - "import hydrofunctions as hf\n", - "\n", - "query = hf.NWIS(station_id, 'iv', \"2021-01-01\", \"2021-12-31\")\n", - "gage = query.df()\n", - "gage = query.df(\"stage\")\n", - "gage.rename(columns={i: \"stage\" for i in list(gage)}, inplace=True)\n", - "# gage.stage *= 0.3284\n", - "# gage.plot();\n", - "gage.stage *= 0.3284\n", - "gage.plot()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "11a7824d", - "metadata": {}, - "source": [ - "Now we can aggregate to a mean monthly state from daily information" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4ed1d203", - "metadata": {}, - "outputs": [], - "source": [ - "gage[\"month\"] = gage.index.month\n", - "gage_mmo = gage.groupby(by=[\"month\"], as_index=False)[\"stage\"].mean()\n", - "gage_mmo.stage.plot();" - ] - }, - { - "cell_type": "markdown", - "id": "994b0757", - "metadata": {}, - "source": [ - "### Now to create the RIV package\n", - "\n", - "Let's give it a higher K to show groundwater mounding along the river" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d0d82e1f", - "metadata": {}, - "outputs": [], - "source": [ - "cond = 1000\n", - "rbadj = 1\n", - "stage_adj = 0.33\n", - "\n", - "perioddata = {}\n", - "for kper, row in gage_mmo.iterrows():\n", - " spd = []\n", - " for (i, j) in main_stem:\n", - " ctop = modelgrid.top[i, j]\n", - " rbed = ctop - rbadj\n", - " rec = ((0, i, j), row.stage + rbed, cond, rbed)\n", - " spd.append(rec)\n", - " \n", - " for (i, j) in tributaries:\n", - " ctop = modelgrid.top[i, j]\n", - " rbed = ctop - (rbadj / 2)\n", - " rec = ((0, i, j), row.stage + rbed, cond, rbed)\n", - " \n", - " perioddata[kper] = spd\n", - "\n", - "perioddata[0][0:5]" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "cadccc45", - "metadata": {}, - "outputs": [], - "source": [ - "riv = flopy.mf6.ModflowGwfriv(\n", - " gwf,\n", - " save_flows=True,\n", - " maxbound=len(perioddata[0]),\n", - " stress_period_data=perioddata\n", - ")\n" - ] - }, - { - "cell_type": "markdown", - "id": "ca7a957f", - "metadata": {}, - "source": [ - "# Testing the model" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "fb26d180", - "metadata": {}, - "outputs": [], - "source": [ - "sim.write_simulation()\n", - "sim.run_simulation();" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "81fd5949", - "metadata": {}, - "outputs": [], - "source": [ - "hds = gwf.output.head()\n", - "heads = hds.get_alldata()[-1]\n", - "\n", - "fig, ax = plt.subplots(figsize=(8, 8))\n", - "pmv = flopy.plot.PlotMapView(modelgrid=modelgrid, ax=ax)\n", - "pc = pmv.plot_array(heads, cmap='viridis', masked_values=[1e30, -1e30])\n", - "pmv.plot_grid(lw=0.5)\n", - "pmv.plot_inactive()\n", - "plt.colorbar(pc, shrink=0.7)\n", - "plt.show();" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "20c39c28", - "metadata": {}, - "outputs": [], - "source": [ - "fig, ax = plt.subplots(figsize=(12, 8))\n", - "ax.set_aspect(\"equal\")\n", - "xc = flopy.plot.PlotCrossSection(modelgrid=modelgrid, ax=ax, line={\"row\": 36}, geographic_coords=True)\n", - "pc = xc.plot_array(heads, cmap='plasma', head=heads, masked_values=[1e+30])\n", - "xc.plot_grid(lw=0.5)\n", - "xc.plot_inactive()\n", - "plt.colorbar(pc, shrink=0.50)\n", - "plt.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f2b7cc47", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "pyclass", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.7" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection_solution.ipynb b/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection_solution.ipynb index 04c5e5f..1edf1b9 100644 --- a/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection_solution.ipynb +++ b/notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection_solution.ipynb @@ -5,7 +5,7 @@ "id": "c3a22877", "metadata": {}, "source": [ - "# Modelgrid and intersection\n", + "# 04: Modelgrid and intersection\n", "\n", "The first part of this notebook is focused on the `flopy.discretization.Grid` (modelgrid) object(s). The modelgrid object(s) are a relatively new addition to FloPy's capabilities and are the backbone of plotting, exporting, and GIS data processing within FloPy. These objects are automatically created when a model is loaded. Alternatively they can also be created as a stand alone object. \n", "\n", @@ -2978,7 +2978,7 @@ "id": "ca7a957f", "metadata": {}, "source": [ - "# Testing the model" + "## Testing the model" ] }, { diff --git a/notebooks/part1_flopy/solutions/06-Project-quadtree.ipynb b/notebooks/part1_flopy/solutions/06-Project-quadtree.ipynb index 40400c1..c820c7c 100644 --- a/notebooks/part1_flopy/solutions/06-Project-quadtree.ipynb +++ b/notebooks/part1_flopy/solutions/06-Project-quadtree.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "1a496643", + "metadata": {}, + "source": [ + "# 06: FloPy class project: Quadtree grid version" + ] + }, { "cell_type": "code", "execution_count": 1, diff --git a/notebooks/part1_flopy/solutions/06-Project-structured_completed.ipynb b/notebooks/part1_flopy/solutions/06-Project-structured_completed.ipynb index 53980b9..74f27b2 100644 --- a/notebooks/part1_flopy/solutions/06-Project-structured_completed.ipynb +++ b/notebooks/part1_flopy/solutions/06-Project-structured_completed.ipynb @@ -1,8 +1,16 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "6a55d07e", + "metadata": {}, + "source": [ + "# 06: FloPy class project: Structured grid version" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "fc15635f-e887-417c-a9b6-583f1d0c758e", "metadata": {}, "outputs": [], @@ -22,7 +30,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "f55b0c73-ec82-4654-ac95-d840845c6a80", "metadata": {}, "outputs": [], @@ -40,7 +48,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "c1f45d54-e585-4b6f-aa44-8db54d57b68c", "metadata": {}, "outputs": [], @@ -60,10 +68,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "a056df43-3d04-41c4-9e6d-641fd118f331", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n" + ] + } + ], "source": [ "river = gpd.read_file(\"../data_project/Flowline_river.shp\")\n", "inactive = gpd.read_file(\"../data_project/inactive_area.shp\")\n", @@ -81,10 +112,83 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "802e1ec8-04c4-42c6-905d-e28ec06d3515", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", + " warnings.warn(\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", + " warnings.warn(\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", + " warnings.warn(\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", + " warnings.warn(\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "ax = river.plot(color=\"cyan\")\n", "active.plot(ax=ax, color=\"blue\")\n", @@ -102,7 +206,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "99fee6a1-dba6-4c47-9239-f0b2c0e81e04", "metadata": {}, "outputs": [], @@ -118,7 +222,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "a44240d6-b0f0-4436-bd2d-fbba92d6dd7e", "metadata": {}, "outputs": [], @@ -140,7 +244,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 8, "id": "9eb9a7bd-02f1-4966-b522-4bdbabeb0d40", "metadata": {}, "outputs": [], @@ -160,10 +264,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 9, "id": "c8e5ef38-e57c-41f7-8c45-a953ae1a5568", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n" + ] + } + ], "source": [ "bedrock = ix.intersect(inactive.geometry[0])\n", "active_cells = ix.intersect(active.geometry[0])" @@ -171,10 +286,26 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "id": "8d5ee1df-925f-4d93-8d06-7adaff89522f", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(rec.array([((0, 0), , 3906.25),\n", + " ((0, 1), , 3906.25),\n", + " ((0, 2), , 3906.25),\n", + " ((0, 3), , 3906.25)],\n", + " dtype=[('cellids', 'O'), ('ixshapes', 'O'), ('areas', ', 62.63873491),\n", + " ((1, 53), , 62.63873491),\n", + " ((2, 53), , 62.63873491),\n", + " ((3, 53), , 62.80215445)],\n", + " dtype=[('cellids', 'O'), ('ixshapes', 'O'), ('lengths', ', 62.5),\n", + " ((159, 21), , 62.5),\n", + " ((159, 22), , 62.5),\n", + " ((159, 23), , 62.5)],\n", + " dtype=[('cellids', 'O'), ('ixshapes', 'O'), ('lengths', '" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "mm = flopy.plot.PlotMapView(modelgrid=base_grid)\n", "mm.plot_array(rtop)\n", @@ -331,10 +534,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "0e344430-3dd6-40f3-99dc-eb3ff4525fd9", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "mm = flopy.plot.PlotMapView(modelgrid=base_grid)\n", "mm.plot_array(rbot)\n", @@ -343,10 +557,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "6025c075-3b2f-4bc4-929c-6ded94d7fb49", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "mm = flopy.plot.PlotMapView(modelgrid=base_grid)\n", "cb = mm.plot_array(rtop - rbot)\n", @@ -356,10 +581,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "fc131289-28c2-4c27-9c28-e2393760ee7a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n" + ] + }, + { + "data": { + "text/plain": [ + "[[2, 33, 61, -708.48],\n", + " [2, 41, 49, -354.24],\n", + " [2, 77, 53, -336.96],\n", + " [2, 101, 37, -71.712],\n", + " [2, 113, 21, -62.208000000000006],\n", + " [2, 133, 45, -371.52]]" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "well_spd = []\n", "for (i, j), q in zip(well_cells, wells[\"Q\"]):\n", @@ -474,7 +834,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "id": "1f0b8a27-6dba-4f62-b11c-f92bdada50a8", "metadata": {}, "outputs": [], @@ -488,10 +848,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 27, "id": "d0013ce6-3c75-4f25-b7a4-17cf7ce7e456", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "12419.290359618695" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "river_length = river_cells[\"lengths\"].sum()\n", "river_length" @@ -499,7 +870,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "a565b394-c57c-45bd-a947-8565c86ed87b", "metadata": {}, "outputs": [], @@ -511,7 +882,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "488d4e1b-6ee5-474e-91a0-6fe1dc764dee", "metadata": {}, "outputs": [], @@ -521,7 +892,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "9f7fca4f-b31a-4679-a06c-9fe79abd4318", "metadata": {}, "outputs": [], @@ -531,7 +902,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "9d5cafa8-be40-4055-a56b-b67878c78e73", "metadata": {}, "outputs": [], @@ -541,10 +912,48 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "d693f849-55a8-450c-934b-2cb7a2ddcc80", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "([[2,\n", + " 0,\n", + " 53,\n", + " 16.597225984480367,\n", + " 2186.8547136345433,\n", + " 16.494956335418845,\n", + " 'upstream'],\n", + " [2,\n", + " 1,\n", + " 53,\n", + " 16.591677953441096,\n", + " 2176.0166873198878,\n", + " 16.484869006256535,\n", + " 'upstream']],\n", + " [[2,\n", + " 158,\n", + " 50,\n", + " 15.508347242017402,\n", + " 1480.5598623536812,\n", + " 14.515176803668005,\n", + " 'downstream'],\n", + " [2,\n", + " 159,\n", + " 50,\n", + " 15.502770376374766,\n", + " 1460.266817949857,\n", + " 14.50503704795412,\n", + " 'downstream']])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "boundname = \"upstream\"\n", "total_length = 0.0\n", @@ -584,7 +993,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "id": "452fa4f3-aac7-422b-b38b-1045e8b4cd1f", "metadata": {}, "outputs": [], @@ -609,10 +1018,22 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "id": "7eb1d1d6-13e3-48a6-ae02-dc82e1878652", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "([(1, 159, 21, 15.5), (2, 159, 21, 15.5)],\n", + " [(1, 159, 59, 15.5), (2, 159, 59, 15.5)])" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "chd_spd = []\n", "for i, j in constant_cells[\"cellids\"]:\n", @@ -634,10 +1055,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "08edb467-a90f-47c9-8465-0b619ea02e83", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "0.00013824" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "recharge_rate = 0.16000000e-08 * 86400.0\n", "recharge_rate" @@ -669,7 +1101,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "id": "b98023a9-21da-4916-a419-4047a423b5df", "metadata": {}, "outputs": [], @@ -679,7 +1111,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "id": "ceeb9cf4-c2a5-4eed-bb6e-058b141739d7", "metadata": {}, "outputs": [], @@ -693,7 +1125,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "id": "9c85c033-c73a-43ec-8682-e866c094fcb9", "metadata": {}, "outputs": [], @@ -708,7 +1140,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "id": "0ce841a8-14ce-408a-844d-49251d91b091", "metadata": {}, "outputs": [], @@ -759,10 +1191,35 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "id": "6a671453-1197-41db-9905-cc6549f705e1", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package ims_-1...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package dis...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package riv_0...\n", + "INFORMATION: maxbound in ('gwf6', 'riv', 'dimensions') changed to 249 based on size of stress_period_data\n", + " writing package obs_0...\n", + " writing package wel_0...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 6 based on size of stress_period_data\n", + " writing package chd_0...\n", + "INFORMATION: maxbound in ('gwf6', 'chd', 'dimensions') changed to 102 based on size of stress_period_data\n", + " writing package oc...\n" + ] + } + ], "source": [ "sim.write_simulation()" ] @@ -777,10 +1234,61 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "id": "8f6a82ba-1005-484e-8a5a-3f59e732eb58", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FloPy is using the following executable to run the model: ../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:14:38\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:14:39\n", + " Elapsed run time: 1.007 Seconds\n", + " \n", + " Normal termination of simulation.\n" + ] + }, + { + "data": { + "text/plain": [ + "(True, [])" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sim.run_simulation()" ] @@ -797,10 +1305,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "id": "6b1b0a5d-b1e6-4824-94c3-c849e176146b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "dtype([('totim', '" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(\n", " ncols=1,\n", @@ -908,10 +1485,41 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "id": "44dbdf83-3b9d-4a8e-9a00-c498647c5155", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/pandas/core/frame.py:706: DeprecationWarning: Passing a BlockManager to GeoDataFrame is deprecated and will raise in a future version. Use public APIs instead.\n", + " warnings.warn(\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geodataframe.py:1645: DeprecationWarning: Passing a SingleBlockManager to Series is deprecated and will raise in a future version. Use public APIs instead.\n", + " srs = pd.Series(*args, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n", + "/Users/aleaf/mambaforge/envs/pyclass/lib/python3.11/site-packages/geopandas/geoseries.py:221: DeprecationWarning: Passing a SingleBlockManager to GeoSeries is deprecated and will raise in a future version. Use public APIs instead.\n", + " super().__init__(data, index=index, name=name, **kwargs)\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(\n", " ncols=1,\n", @@ -955,8 +1563,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" } }, "nbformat": 4, diff --git a/notebooks/part1_flopy/solutions/06-Project-voronoi.ipynb b/notebooks/part1_flopy/solutions/06-Project-voronoi.ipynb index d990b40..f4a3af8 100644 --- a/notebooks/part1_flopy/solutions/06-Project-voronoi.ipynb +++ b/notebooks/part1_flopy/solutions/06-Project-voronoi.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "cdee9a21", + "metadata": {}, + "source": [ + "# 06: FloPy class project: Voronoi grid version" + ] + }, { "cell_type": "code", "execution_count": 1, diff --git a/notebooks/part1_flopy/solutions/07-stream_capture_voronoi.ipynb b/notebooks/part1_flopy/solutions/07-stream_capture_voronoi.ipynb index 7d824e4..a093cff 100644 --- a/notebooks/part1_flopy/solutions/07-stream_capture_voronoi.ipynb +++ b/notebooks/part1_flopy/solutions/07-stream_capture_voronoi.ipynb @@ -1,15 +1,22 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "c9987a92", + "metadata": {}, + "source": [ + "# 07: Evaluating stream capture with a Voronoi grid" + ] + }, { "cell_type": "code", - "execution_count": null, + "execution_count": 1, "id": "ffc212df", "metadata": {}, "outputs": [], "source": [ "import os\n", "import flopy as fp\n", - "import flopy.utils as fu\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", @@ -26,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "id": "27b1afd7", "metadata": {}, "outputs": [], @@ -36,17 +43,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "3e82ace2", "metadata": {}, "outputs": [], "source": [ + "%%capture\n", "base_sim = fp.mf6.MFSimulation.load(sim_ws=str(modelpath))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 4, "id": "fa7fc8fa", "metadata": {}, "outputs": [], @@ -64,7 +72,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "id": "b1866934", "metadata": {}, "outputs": [], @@ -74,7 +82,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "75a6c488", "metadata": {}, "outputs": [], @@ -84,10 +92,61 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "020e9bd3", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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168 rows × 14 columns

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" + ], + "text/plain": [ + " ifno cellid rlen rwid rgrd rtp rbth \\\n", + "0 0 (2, 367) 50.649038 5.010196 0.000161 16.495922 0.502039 \n", + "1 1 (2, 368) 94.011396 5.039316 0.000161 16.484274 0.507863 \n", + "2 2 (2, 369) 116.984410 5.081789 0.000161 16.467284 0.516358 \n", + "3 3 (2, 370) 130.346654 5.131577 0.000161 16.447369 0.526315 \n", + "4 4 (2, 371) 121.584053 5.182290 0.000161 16.427084 0.536458 \n", + ".. ... ... ... ... ... ... ... \n", + "163 163 (2, 1763) 98.589885 9.907079 0.000161 14.537168 1.481416 \n", + "164 164 (2, 1773) 69.061267 9.940827 0.000161 14.523669 1.488165 \n", + "165 165 (2, 1838) 94.392032 9.973731 0.000161 14.510508 1.494746 \n", + "166 166 (2, 1882) 9.370425 9.994618 0.000161 14.502153 1.498924 \n", + "167 167 (2, 1944) 8.683260 9.998252 0.000161 14.500699 1.499650 \n", + "\n", + " rhk man ncon ustrf ndv boundname cell_no_layer \n", + "0 3.5 0.035 1 1.0 0 upstream 367 \n", + "1 3.5 0.035 2 1.0 0 upstream 368 \n", + "2 3.5 0.035 2 1.0 0 upstream 369 \n", + "3 3.5 0.035 2 1.0 0 upstream 370 \n", + "4 3.5 0.035 2 1.0 0 upstream 371 \n", + ".. ... ... ... ... ... ... ... \n", + "163 3.5 0.035 2 1.0 0 downstream 1763 \n", + "164 3.5 0.035 2 1.0 0 downstream 1773 \n", + "165 3.5 0.035 2 1.0 0 downstream 1838 \n", + "166 3.5 0.035 2 1.0 0 downstream 1882 \n", + "167 3.5 0.035 1 1.0 0 downstream 1944 \n", + "\n", + "[168 rows x 14 columns]" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "# make a new columns with just the cellid regardless of layer\n", "sfrcells['cell_no_layer'] = [i[1] for i in sfrcells.cellid]\n", @@ -147,35 +989,68 @@ "id": "6d7dbe70", "metadata": {}, "source": [ - "## now we can find the cells from disv that are _not_ also in SFR using a `set` operation" + "### now we can find the cells from disv that are _not_ also in SFR using a `set` operation" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 11, "id": "8675dba5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(2240, 168)" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "len(set(cells.icell2d)), len(set(sfrcells.cell_no_layer))," ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "id": "df535b68", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2072" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "len(set(cells.icell2d))-len(set(sfrcells.cell_no_layer))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "id": "1158011c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "2072" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "cells_for_wells = list(set(cells.icell2d)-set(sfrcells.cell_no_layer))\n", "len(cells_for_wells)" @@ -191,10 +1066,85 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "id": "625d8db5", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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cellidq
0(2, 1315)-708.480
1(2, 1421)-354.240
2(2, 1435)-336.960
3(2, 1286)-71.712
4(2, 1420)-62.208
5(2, 1434)-371.520
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" + ], + "text/plain": [ + " cellid q\n", + "0 (2, 1315) -708.480\n", + "1 (2, 1421) -354.240\n", + "2 (2, 1435) -336.960\n", + "3 (2, 1286) -71.712\n", + "4 (2, 1420) -62.208\n", + "5 (2, 1434) -371.520" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "wells = pd.DataFrame.from_records(base_m.wel.stress_period_data.array[0])\n", "wells" @@ -202,10 +1152,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 15, "id": "17ecb444", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "-317.52000000000004" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "newq = wells.q.mean()\n", "newq" @@ -216,22 +1177,23 @@ "id": "541f5328", "metadata": {}, "source": [ - "## now let's see about adding a new well - we will reload the model and reset the path to be sure and not stomp on the original model" + "### now let's see about adding a new well - we will reload the model and reset the path to be sure and not stomp on the original model" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "id": "48dd434d", "metadata": {}, "outputs": [], "source": [ + "%%capture\n", "sim = fp.mf6.MFSimulation.load(sim_ws=str(modelpath))" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 17, "id": "281f1bd1", "metadata": {}, "outputs": [], @@ -241,10 +1203,23 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "id": "0bae231a", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "cellid object\n", + "q float64\n", + "dtype: object" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "wells.dtypes" ] @@ -259,7 +1234,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "id": "8eaed08d", "metadata": {}, "outputs": [], @@ -269,7 +1244,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "id": "555ad503", "metadata": {}, "outputs": [], @@ -280,10 +1255,202 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "id": "322b230b", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n" + ] + } + ], "source": [ "sim.exe_name='mf6'\n", "sim.write_simulation()" @@ -291,10 +1458,72 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 22, "id": "3d03aa56", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:02\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:03\n", + " Elapsed run time: 0.464 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n" + ] + }, + { + "data": { + "text/plain": [ + "(True, [])" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sim.run_simulation()" ] @@ -309,7 +1538,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 23, "id": "92af5d55", "metadata": {}, "outputs": [], @@ -319,20 +1548,83 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 24, "id": "cb13f21c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([(1., 5769.24775311, -8741.75640156, -858230.75224689, -866972.50864845)],\n", + " dtype=[('totim', '\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
totimUPSTREAMDOWNSTREAMGAGE1GAGE2
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GAGE1GAGE2
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" + ], + "text/plain": [ + " GAGE1 GAGE2\n", + "time \n", + "1.0 -858469.278905 -867288.493036" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "sfr_base_obs" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "9412afce", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "array([-315.98438773])" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "(sfr_base_obs.GAGE2.values-sfr_test.GAGE2.values)" ] @@ -383,7 +1782,7 @@ "id": "2bc098f2", "metadata": {}, "source": [ - "# Cool! We can see a difference in flow pretty close to the new pumping rate. Now we are ready to systematically work with the entire model!" + "### Cool! We can see a difference in flow pretty close to the new pumping rate. Now we are ready to systematically work with the entire model!" ] }, { @@ -391,12 +1790,12 @@ "id": "2dcab79b", "metadata": {}, "source": [ - "## now let's make a dataframe to hold the depletion calculation results" + "### now let's make a dataframe to hold the depletion calculation results" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "46d80de2", "metadata": {}, "outputs": [], @@ -409,7 +1808,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "4d675fb7", "metadata": {}, "outputs": [], @@ -419,10 +1818,122 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "6354f39c", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/html": [ + "
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" + ], + "text/plain": [ + " Gage1 Gage2\n", + "0 0 NaN NaN\n", + " 1 NaN NaN\n", + " 2 NaN NaN\n", + " 3 NaN NaN\n", + " 4 NaN NaN\n", + "... ... ...\n", + "2 2235 NaN NaN\n", + " 2236 NaN NaN\n", + " 2237 NaN NaN\n", + " 2238 NaN NaN\n", + " 2239 NaN NaN\n", + "\n", + "[6720 rows x 2 columns]" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "depletion_results = pd.DataFrame(index=pd.MultiIndex.from_tuples(cells_with_layers), data = {'Gage1':np.nan, 'Gage2':np.nan})\n", "depletion_results" @@ -433,14 +1944,14 @@ "id": "09d73dac", "metadata": {}, "source": [ - "# now make a function to run ... the slow way\n", + "### now make a function to run ... the slow way\n", "\n", - "## we know how to read in the model with flopy, make a change, run it, etc. all using flopy" + "#### we know how to read in the model with flopy, make a change, run it, etc. all using flopy" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 33, "id": "b2a0d8f3", "metadata": {}, "outputs": [], @@ -466,10 +1977,10356 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 34, "id": "5484122e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:04\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:04\n", + " Elapsed run time: 0.337 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:05\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:05\n", + " Elapsed run time: 0.334 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:06\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:06\n", + " Elapsed run time: 0.308 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:07\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:07\n", + " Elapsed run time: 0.318 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:08\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:08\n", + " Elapsed run time: 0.337 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:09\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:09\n", + " Elapsed run time: 0.315 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:10\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:10\n", + " Elapsed run time: 0.309 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:11\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:11\n", + " Elapsed run time: 0.375 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:12\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:12\n", + " Elapsed run time: 0.305 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:12\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:13\n", + " Elapsed run time: 0.358 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:13\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:14\n", + " Elapsed run time: 0.360 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:14\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:15\n", + " Elapsed run time: 0.329 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:15\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:16\n", + " Elapsed run time: 0.316 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:16\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:16\n", + " Elapsed run time: 0.309 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:17\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:17\n", + " Elapsed run time: 0.294 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:18\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:18\n", + " Elapsed run time: 0.310 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:19\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:19\n", + " Elapsed run time: 0.321 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n", + "FloPy is using the following executable to run the model: ../../../../../../../software/modflow_exes/mf6\n", + " MODFLOW 6\n", + " U.S. GEOLOGICAL SURVEY MODULAR HYDROLOGIC MODEL\n", + " VERSION 6.4.2 06/28/2023\n", + "\n", + " MODFLOW 6 compiled Jun 28 2023 18:34:54 with Intel(R) Fortran Intel(R) 64\n", + " Compiler Classic for applications running on Intel(R) 64, Version 2021.7.0\n", + " Build 20220726_000000\n", + "\n", + "This software has been approved for release by the U.S. Geological \n", + "Survey (USGS). Although the software has been subjected to rigorous \n", + "review, the USGS reserves the right to update the software as needed \n", + "pursuant to further analysis and review. No warranty, expressed or \n", + "implied, is made by the USGS or the U.S. Government as to the \n", + "functionality of the software and related material nor shall the \n", + "fact of release constitute any such warranty. Furthermore, the \n", + "software is released on condition that neither the USGS nor the U.S. \n", + "Government shall be held liable for any damages resulting from its \n", + "authorized or unauthorized use. Also refer to the USGS Water \n", + "Resources Software User Rights Notice for complete use, copyright, \n", + "and distribution information.\n", + "\n", + " \n", + " Run start date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:20\n", + " \n", + " Writing simulation list file: mfsim.lst\n", + " Using Simulation name file: mfsim.nam\n", + " \n", + " Solving: Stress period: 1 Time step: 1\n", + " \n", + " Run end date and time (yyyy/mm/dd hh:mm:ss): 2024/02/05 11:55:20\n", + " Elapsed run time: 0.324 Seconds\n", + " \n", + "\n", + "WARNING REPORT:\n", + "\n", + " 1. OPTIONS BLOCK VARIABLE 'UNIT_CONVERSION' IN FILE 'project.sfr' WAS\n", + " DEPRECATED IN VERSION 6.4.2. SETTING UNIT_CONVERSION DIRECTLY.\n", + " Normal termination of simulation.\n", + "2.83 s ± 71 ms per loop (mean ± std. dev. of 5 runs, 1 loop each)\n" + ] + } + ], "source": [ "%%timeit -r 5 # the timeit special function will run the folling code a few times and indicate how long \n", " # the mean runtime and variance are\n", @@ -483,8 +12340,8 @@ "id": "a2dd8128", "metadata": {}, "source": [ - "# now make a function to run ... the FAST way\n", - "### we will use flopy only to make the initial model and then manipulate and run only with MF6 files directly" + "#### now make a function to run ... the FAST way\n", + "#### we will use flopy only to make the initial model and then manipulate and run only with MF6 files directly" ] }, { @@ -497,10 +12354,552 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "2599a667", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "loading simulation...\n", + " loading simulation name file...\n", + " loading tdis package...\n", + " loading model gwf6...\n", + " loading package disv...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'disv', 'cell2d', 'cell2d', 'icvert') based on shape \"ncvert\".\n", + " loading package ic...\n", + " loading package npf...\n", + " loading package rch...\n", + " loading package sfr...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " loading package wel...\n", + " loading package chd...\n", + " loading package oc...\n", + " loading solution package project...\n", + "writing simulation...\n", + " writing simulation name file...\n", + " writing simulation tdis package...\n", + " writing solution package project...\n", + " writing model project...\n", + " writing model name file...\n", + " writing package disv...\n", + " writing package ic...\n", + " writing package npf...\n", + " writing package rcha_0...\n", + " writing package sfr_obs...\n", + " writing package sfr_0...\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + "WARNING: Unable to resolve dimension of ('gwf6', 'sfr', 'connectiondata', 'connectiondata', 'ic') based on shape \"nconifno\".\n", + " writing package wel_0...\n", + " writing package chd_0...\n", + " writing package oc...\n", + " writing package wel_1...\n", + "INFORMATION: maxbound in ('gwf6', 'wel', 'dimensions') changed to 1 based on size of stress_period_data\n" + ] + } + ], "source": [ "sim = fp.mf6.MFSimulation.load(sim_ws=str(modelpath))\n", "# get the model\n", @@ -515,10 +12914,44 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "id": "3aadfec0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "package_name = sfr_obs\n", + "filename = project.sfr.obs\n", + "package_type = obs\n", + "model_or_simulation_package = model\n", + "model_name = project\n", + "parent_file = sfr_0\n", + "\n", + "Block options\n", + "--------------------\n", + "print_input\n", + "{internal}\n", + "(True)\n", + "\n", + "\n", + "Block continuous\n", + "--------------------\n", + "continuous\n", + "{internal}\n", + "(rec.array([('upstream', 'sfr', 'upstream', None),\n", + " ('downstream', 'sfr', 'downstream', None),\n", + " ('gage1', 'downstream-flow', '47', None),\n", + " ('gage2', 'ext-outflow', '168', None)],\n", + " dtype=[('obsname', 'O'), ('obstype', 'O'), ('id', 'O'), ('id2', 'O')]))\n", + "\n" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "testmod.sf" ] @@ -533,10 +12966,33 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "id": "576bcc85", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "['# File generated by Flopy version 3.5.0 on 02/05/2024 at 11:55:21.\\n',\n", + " 'BEGIN options\\n',\n", + " ' SAVE_FLOWS\\n',\n", + " 'END options\\n',\n", + " '\\n',\n", + " 'BEGIN dimensions\\n',\n", + " ' MAXBOUND 1\\n',\n", + " 'END dimensions\\n',\n", + " '\\n',\n", + " 'BEGIN period 1\\n',\n", + " ' 1 1 -3.17520000E+02\\n',\n", + " 'END period 1\\n',\n", + " '\\n']" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "inwell = open(runpath / 'project_0.wel', 'r').readlines()\n", "inwell" @@ -544,7 +13000,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "id": "b8b279ad", "metadata": {}, "outputs": [], @@ -559,10 +13015,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "id": "87065dc0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'# File generated by Flopy version 3.5.0 on 02/05/2024 at 11:55:21.\\n BEGIN options\\n SAVE_FLOWS\\n END options\\n \\n BEGIN dimensions\\n MAXBOUND 1\\n END dimensions\\n \\n BEGIN period 1\\n 1 1 -3.17520000E+02\\n END period 1\\n \\n'" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "well_template = ' '.join(well_template)\n", "well_template" @@ -570,10 +13037,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "id": "b38bda7d", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "'# File generated by Flopy version 3.5.0 on 02/05/2024 at 11:55:21.\\n BEGIN options\\n SAVE_FLOWS\\n END options\\n \\n BEGIN dimensions\\n MAXBOUND 1\\n END dimensions\\n \\n BEGIN period 1\\n 1 1 -3.17520000E+02\\n END period 1\\n \\n'" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "well_template.replace('',f'1 1 {newq:0.4f}')" ] @@ -588,7 +13066,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "id": "a0d70087", "metadata": {}, "outputs": [], @@ -599,7 +13077,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "id": "867ace37", "metadata": {}, "outputs": [], @@ -619,7 +13097,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 43, "id": "1f7de900", "metadata": {}, "outputs": [], @@ -630,10 +13108,25 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "id": "6a73c9b0", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "running layer = 0, cellid = 0\r" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "5.74 s ± 300 ms per loop (mean ± std. dev. of 5 runs, 1 loop each)\n" + ] + } + ], "source": [ "%%timeit -r 5\n", "for lay in range(3):\n", @@ -643,7 +13136,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 45, "id": "f180d062", "metadata": {}, "outputs": [], @@ -655,7 +13148,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 46, "id": "ea56fe6c", "metadata": {}, "outputs": [], @@ -665,10 +13158,21 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "id": "fd8e62ba", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fig, ax = plt.subplots(2,3, figsize=(9,8))\n", "ax = ax.ravel()\n", @@ -717,8 +13221,22 @@ } ], "metadata": { + "kernelspec": { + "display_name": "pyclass", + "language": "python", + "name": "python3" + }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.7" } }, "nbformat": 4, From e7c0ecb523c397ee898b48d487512da4bfce2b08 Mon Sep 17 00:00:00 2001 From: "Leaf, Andrew T" Date: Mon, 5 Feb 2024 13:34:49 -0600 Subject: [PATCH 2/2] feat(HTML docs): add sphinx configuration; build workflow and source files --- .github/workflows/build_docs.yaml | 81 +++++ docs/Makefile | 20 ++ docs/docs-environment.yml | 53 +++ docs/source/SOME_HELPFUL_LINKS.md | 48 +++ docs/source/bonus_examples.rst | 6 + docs/source/conf.py | 306 ++++++++++++++++++ docs/source/contributing.md | 53 +++ docs/source/glossary_of_jargon.md | 65 ++++ docs/source/index.rst | 28 ++ docs/source/part0.rst | 21 ++ docs/source/part1.rst | 16 + .../07a_Theis-exercise.ipynb | 2 +- notebooks/part0_python_intro/07b_VSCode.md | 2 +- 13 files changed, 699 insertions(+), 2 deletions(-) create mode 100644 .github/workflows/build_docs.yaml create mode 100644 docs/Makefile create mode 100644 docs/docs-environment.yml create mode 100644 docs/source/SOME_HELPFUL_LINKS.md create mode 100644 docs/source/bonus_examples.rst create mode 100644 docs/source/conf.py create mode 100644 docs/source/contributing.md create mode 100644 docs/source/glossary_of_jargon.md create mode 100644 docs/source/index.rst create mode 100644 docs/source/part0.rst create mode 100644 docs/source/part1.rst diff --git a/.github/workflows/build_docs.yaml b/.github/workflows/build_docs.yaml new file mode 100644 index 0000000..47d8e5d --- /dev/null +++ b/.github/workflows/build_docs.yaml @@ -0,0 +1,81 @@ +# from pyproj: https://github.com/pyproj4/pyproj/blob/master/.github/workflows/build_docs.yaml +name: Publish Docs + +on: + push: + branches: + - main + - '*docs*' + release: + types: [ created ] + workflow_dispatch: + +jobs: + docs: + name: Publish Docs + runs-on: ubuntu-latest + + steps: + - name: Checkout source + uses: actions/checkout@v3 + with: + persist-credentials: false + + - name: Fetch all Git tags + run: git fetch --prune --unshallow --tags + + - name: Setup Micromamba + uses: mamba-org/setup-micromamba@v1 + with: + environment-file: docs/docs-environment.yml + cache-environment: false + cache-downloads: false + + - name: Conda info + shell: bash -l {0} + run: micromamba info + - name: Install Modflow executables + uses: modflowpy/install-modflow-action@v1 + with: + path: ~/.local/bin + github_token: ${{ secrets.GITHUB_TOKEN }} + - name: Modflow version + shell: bash -l {0} + run: mf6 --version + - name: Install ipykernel + shell: bash -l {0} + run: | + python -m ipykernel install --user --name pyclass --display-name "pyclass" + - name: Conda list + shell: bash -l {0} + run: micromamba list + - name: Run tests + shell: bash -l {0} + run: | + pytest tests/test_notebook_output.py + + - name: Build docs + shell: bash -l {0} + run: | + set -e + make -C docs html + + - name: Deploy 🚀 + uses: JamesIves/github-pages-deploy-action@3.7.1 + if: ${{ github.event_name == 'release' }} + with: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + BRANCH: gh-pages + FOLDER: docs/build/html + CLEAN: false + TARGET_FOLDER: ${{ github.ref }} + + - name: Deploy 🚀 + uses: JamesIves/github-pages-deploy-action@3.7.1 + if: ${{ github.event_name == 'push' }} + with: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + BRANCH: gh-pages + FOLDER: docs/build/html + CLEAN: false + TARGET_FOLDER: latest diff --git a/docs/Makefile b/docs/Makefile new file mode 100644 index 0000000..a0b6c97 --- /dev/null +++ b/docs/Makefile @@ -0,0 +1,20 @@ +# Minimal makefile for Sphinx documentation +# + +# You can set these variables from the command line. +#SPHINXOPTS = "-W" # This flag turns warnings into errors. +SPHINXBUILD = sphinx-build +SPHINXPROJ = PackagingScientificPython +SOURCEDIR = source +BUILDDIR = build + +# Put it first so that "make" without argument is like "make help". +help: + @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) + +.PHONY: help Makefile + +# Catch-all target: route all unknown targets to Sphinx using the new +# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). +%: Makefile + @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/docs-environment.yml b/docs/docs-environment.yml new file mode 100644 index 0000000..b7f9144 --- /dev/null +++ b/docs/docs-environment.yml @@ -0,0 +1,53 @@ +name: pyclass-docs +channels: + - conda-forge +dependencies: + # required + - python=3.11 + - pip + + - numpy + - matplotlib + + - jupyter + - jupytext + - jupyterlab + - git + - python-dateutil + - affine + - scipy + - openpyxl + - xlrd + - pandas + - netcdf4 + - pyshp + - rasterio + - rasterstats + - fiona + - descartes + - pyproj + - shapely + - geos + - geojson + - geopandas + - vtk + - xarray + - rioxarray + - uxarray + - pyyaml + - rtree + - requests + - pytest + - statsmodels + - dataretrieval + - flopy + - gis-utils + - sfrmaker + - modflow-export + - modflow-setup + - sphinx + - numpydoc + - nbsphinx # for rendering notebooks in sphinx-generated docs + - sphinx-copybutton + - sphinx_rtd_theme + - myst-parser # for including markdown source diff --git a/docs/source/SOME_HELPFUL_LINKS.md b/docs/source/SOME_HELPFUL_LINKS.md new file mode 100644 index 0000000..7199b90 --- /dev/null +++ b/docs/source/SOME_HELPFUL_LINKS.md @@ -0,0 +1,48 @@ +# Here are some links you might find helpful moving forward with python + +### conda +* [Getting started with conda](https://conda.io/projects/conda/en/latest/user-guide/getting-started.html) +* [General information on conda environments](https://docs.conda.io/projects/conda/en/latest/user-guide/concepts/environments.html) +* [Managing Conda Environments](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) +* [Tutorial introduction to conda enviroments](https://towardsdatascience.com/getting-started-with-python-environments-using-conda-32e9f2779307) +* [Conda-pack](https://conda.github.io/conda-pack/) + +### cheat sheets +* [conda](https://conda.io/projects/conda/en/latest/user-guide/cheatsheet.html) +* [pandas](https://pandas.pydata.org/Pandas_Cheat_Sheet.pdf) +* [numpy](http://datacamp-community-prod.s3.amazonaws.com/ba1fe95a-8b70-4d2f-95b0-bc954e9071b0) +* [data science packages](https://www.utc.fr/~jlaforet/Suppl/python-cheatsheets.pdf) +* [Jupyter Notebook/Lab keyboard shortcuts](https://towardsdatascience.com/jypyter-notebook-shortcuts-bf0101a98330) +* [Numpy for MATLAB Users](https://numpy.org/doc/stable/user/numpy-for-matlab-users.html) + +### general python +* [Tutorial on General Python Programming](https://cscircles.cemc.uwaterloo.ca/) +* [Installing packages dynamically into an environment](https://packaging.python.org/en/latest/guides/distributing-packages-using-setuptools/#working-in-development-mode) + +### Flopy and MODFLOW +* [Flopy code](https://github.com/modflowpy/flopy.git) +* [Flopy official documentation](https://flopy.readthedocs.io/en/3.3.5/) +* [MODFLOW 6 -- online documentation](https://modflow6.readthedocs.io/en/latest/) +* [MODFLOW 6 Example Problems -- overview](https://modflow6-examples.readthedocs.io/en/master/introduction.html) +* [MODFLOW 6 Example Problems](https://modflow6-examples.readthedocs.io/en/master/examples.html) +* [Flopy Tutorial Notebooks](https://github.com/modflowpy/flopy/blob/develop/docs/notebook_examples.md) +* [Groundwater Paper](https://ngwa.onlinelibrary.wiley.com/doi/abs/10.1111/gwat.12413) +* [Another Groundwater Paper](https://ngwa.onlinelibrary.wiley.com/doi/10.1111/gwat.13259) + +### Modflow-setup and SFRmaker +* [Modflow-setup code and docs](https://github.com/doi-usgs/modflow-setup) +* [Modflow-setup paper](https://www.frontiersin.org/articles/10.3389/feart.2022.903965/full) +* [SFRmaker code and docs](https://github.com/DOI-USGS/sfrmaker) +* [SFRmaker paper](https://ngwa.onlinelibrary.wiley.com/doi/10.1111/gwat.13095) +* [A worked example/workflow using Modflow-setup, SFRmaker, and PEST++](https://github.com/DOI-USGS/neversink_workflow) +* [A worked example/workflow Groundwater paper](https://ngwa.onlinelibrary.wiley.com/doi/full/10.1111/gwat.13129) + +### some galleries +* [matplotlib gallery](https://matplotlib.org/stable/gallery/index.html) +* [geopandas gallery](https://geopandas.org/en/stable/gallery/index.html) +* [a hydrologic "data story" using pandas](https://code.usgs.gov/cdi/cdi-fy20/jupyter-data-stories/-/tree/main/examples/hydrologic_data_analysis) + +### more general references +* [numpy for matlab users](https://numpy.org/doc/stable/user/numpy-for-matlab-users.html) +* [datetime formats](https://docs.python.org/3/library/datetime.html) (jump to the bottom of the page where it says "Format Codes") +* [Jupyter Lab Getting Started](https://jupyterlab.readthedocs.io/en/stable/getting_started/overview.html) \ No newline at end of file diff --git a/docs/source/bonus_examples.rst b/docs/source/bonus_examples.rst new file mode 100644 index 0000000..8503e20 --- /dev/null +++ b/docs/source/bonus_examples.rst @@ -0,0 +1,6 @@ +Bonus examples +======================================= + +.. nbgallery:: + + notebooks/part0_python_intro/09_Geopandas_ABQ.ipynb \ No newline at end of file diff --git a/docs/source/conf.py b/docs/source/conf.py new file mode 100644 index 0000000..a957b27 --- /dev/null +++ b/docs/source/conf.py @@ -0,0 +1,306 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +# +# Python for Hydrology documentation build configuration file, created by +# sphinx-quickstart on Thu Jun 28 12:35:56 2018. +# +# This file is execfile()d with the current directory set to its +# containing dir. +# +# Note that not all possible configuration values are present in this +# autogenerated file. +# +# All configuration values have a default; values that are commented out +# serve to show the default. + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +# +import os +from pathlib import Path +import shutil + +# import sys +# sys.path.insert(0, os.path.abspath('.')) + + +# -- General configuration ------------------------------------------------ + +# If your documentation needs a minimal Sphinx version, state it here. +# +# needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + 'sphinx.ext.autodoc', + #'sphinx.ext.autosectionlabel', + 'sphinx.ext.autosummary', + 'sphinx.ext.githubpages', + #'sphinx.ext.intersphinx', + 'sphinx.ext.mathjax', + 'sphinx.ext.viewcode', + 'IPython.sphinxext.ipython_directive', + 'IPython.sphinxext.ipython_console_highlighting', + 'matplotlib.sphinxext.plot_directive', + 'nbsphinx', + 'numpydoc', + 'sphinx_copybutton', + 'myst_parser' +] + +# copy notebooks to docs folder for use with nbsphinx +#if not os.path.isdir('notebooks'): +# os.makedirs('notebooks') +#shutil.copy('../../examples/Pleasant_lake_lgr_example.ipynb', 'notebooks') + +# settings for sphinx_nbexamples (couldn't get this to work) +#example_gallery_config = { +# 'examples_dirs': ['../../examples/'], +# 'pattern': '.ipynb', +# 'urls': 'https://github.com/aleaf/modflow-setup/tree/develop/examples', +# 'binder_url': 'https://mybinder.org/v2/gh/aleaf/modflow-setup/develop?filepath=examples' +#} +# +#process_examples = not os.path.exists(os.path.join(os.path.dirname(__file__), 'examples')) + + +# Configuration options for plot_directive. See: +# https://github.com/matplotlib/matplotlib/blob/f3ed922d935751e08494e5fb5311d3050a3b637b/lib/matplotlib/sphinxext/plot_directive.py#L81 +plot_html_show_source_link = False +plot_html_show_formats = False + +# Generate the API documentation when building +autosummary_generate = True +numpydoc_show_class_members = False + +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix(es) of source filenames. +# You can specify multiple suffix as a list of string: +# +#source_suffix = ['.rst', '.md'] +source_suffix = '.rst' + +# The master toctree document. +master_doc = 'index' + +# General information about the project. +import datetime + +now = datetime.datetime.now() + +project = 'Python for Hydrology' +copyright = f"2022-{now.year}, USGS Python for Hydrology instructors" +author = 'USGS Python for Hydrology instructors' + +# The version info for the project you're documenting, acts as replacement for +# |version| and |release|, also used in various other places throughout the +# built documents. +# +#import mfsetup + +# The short X.Y version. +version = '1.0'#mfsetup.__version__ +# The full version, including alpha/beta/rc tags. +release = '1.0a'#mfsetup.__version__ + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +# +# This is also used if you do content translation via gettext catalogs. +# Usually you set "language" from the command line for these cases. +language = 'en' + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +# This patterns also effect to html_static_path and html_extra_path +exclude_patterns = ['_build', 'pleasant-example.rst', "Thumbs.db", ".DS_Store", "**.ipynb_checkpoints"] + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = 'sphinx' + +# If true, `todo` and `todoList` produce output, else they produce nothing. +todo_include_todos = True + + +# -- Options for HTML output ---------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +# +html_theme = 'sphinx_rtd_theme' +import sphinx_rtd_theme + +html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +# +# html_theme_options = {} + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +#html_static_path = ['_static'] + +# Custom sidebar templates, must be a dictionary that maps document names +# to template names. +# +# This is required for the alabaster theme +# refs: http://alabaster.readthedocs.io/en/latest/installation.html#sidebars +html_sidebars = { + '**': [ + 'relations.html', # needs 'show_related': True theme option to display + 'searchbox.html', + ] +} + +# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. +html_show_copyright = True + +# If not '', a 'Last updated on:' timestamp is inserted at every page bottom, +# using the given strftime format. +html_last_updated_fmt = '%b %d, %Y' + +# -- Options for HTMLHelp output ------------------------------------------ + +# Output file base name for HTML help builder. +htmlhelp_basename = 'modflow-setup' + + +# -- Options for LaTeX output --------------------------------------------- + +latex_elements = { + # The paper size ('letterpaper' or 'a4paper'). + # + # 'papersize': 'letterpaper', + + # The font size ('10pt', '11pt' or '12pt'). + # + # 'pointsize': '10pt', + + # Additional stuff for the LaTeX preamble. + # + # 'preamble': '', + + # Latex figure (float) alignment + # + # 'figure_align': 'htbp', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, +# author, documentclass [howto, manual, or own class]). +latex_documents = [ + (master_doc, 'modflow-setup.tex', 'Modflow-setup Documentation', + 'Contributors', 'manual'), +] + + +# -- Options for manual page output --------------------------------------- + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + (master_doc, 'modflow-setup', 'Modflow-setup Documentation', + [author], 1) +] + + +# -- Options for Texinfo output ------------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + (master_doc, 'modflow-setup', 'Modflow-setup Documentation', + author, 'modflow-setup', 'Package to facilitate setup of a MODFLOW-6 groundwater flow model with the SFR package.', + 'Miscellaneous'), +] + + + + +# Example configuration for intersphinx: refer to the Python standard library. +intersphinx_mapping = { + 'flopy': ('https://flopy.readthedocs.io/en/latest/', None), + 'python': ('https://docs.python.org/3/', None), + 'numpy': ('https://numpy.org/doc/stable/', None), + 'scipy': ('https://docs.scipy.org/doc/scipy/', None), + 'pandas': ('https://pandas.pydata.org/pandas-docs/stable', None), + 'pyproj': ('https://pyproj4.github.io/pyproj/stable/', None), + 'matplotlib': ('https://matplotlib.org/stable/', None), + 'rasterio': ('https://rasterio.readthedocs.io/en/latest/', None) +} +tls_verify = False + +# settings for sphinxcontrib.collections +#collections = { +# 'notebooks': { +# 'driver': 'copy_folder', +# 'source': '../notebooks/', +# #'target': 'my_data/', +# 'ignore': ['*.py', '.exe', '__pycache__', '*output'], +# +# } +#} +# copy notebooks to docs folder +dest_path = Path('notebooks') +shutil.rmtree(dest_path, ignore_errors=True) +dest_path.mkdir() +source_path = Path('../../notebooks') +copy_notebooks = [ + source_path / 'part0_python_intro/solutions/01_functions_script__solution.ipynb', + source_path / 'part0_python_intro/solutions/02_Namespace_objects_modules_packages__solution.ipynb', + source_path / 'part0_python_intro/03_useful-std-library-modules.ipynb', + source_path / 'part0_python_intro/solutions/03_useful-std-library-modules-solutions.ipynb', + source_path / 'part0_python_intro/solutions/04_files_and_strings.ipynb', + source_path / 'part0_python_intro/05_numpy.ipynb', + source_path / 'part0_python_intro/solutions/05_numpy__solutions.ipynb', + source_path / 'part0_python_intro/solutions/06_matplotlib__solution.ipynb', + source_path / 'part0_python_intro/06b_matplotlib_animation.ipynb', + source_path / 'part0_python_intro/solutions/07a_Theis-exercise-solution.ipynb', + source_path / 'part0_python_intro/07b_VSCode.md', + source_path / 'part0_python_intro/solutions/08_pandas.ipynb', + source_path / 'part0_python_intro/data/pandas', + source_path / 'part0_python_intro/09_Geopandas.ipynb', + source_path / 'part0_python_intro/data/geopandas', + source_path / 'part0_python_intro/solutions/09_Geopandas__solutions.ipynb', + source_path / 'part0_python_intro/10_Rasterio.ipynb', + source_path / 'part0_python_intro/11_xarray_mt_rainier_precip.ipynb', + source_path / 'part1_flopy/solutions/02-Building-Post-Processing-MODFLOW6__solutions.ipynb', + source_path / 'part1_flopy/solutions/03_Loading_and_visualizing_models-solutions.ipynb', + source_path / 'part1_flopy/solutions/04_Modelgrid_and_intersection_solution.ipynb', + source_path / 'part1_flopy/05-unstructured-grids.ipynb', + source_path / 'part1_flopy/solutions/06-Project-quadtree.ipynb', + source_path / 'part1_flopy/solutions/06-Project-structured_completed.ipynb', + source_path / 'part1_flopy/solutions/06-Project-voronoi.ipynb', + source_path / 'part1_flopy/solutions/07-stream_capture_voronoi.ipynb', + source_path / 'part1_flopy/08_Modflow-setup-demo.ipynb', + source_path / 'part1_flopy/09-gwt-voronoi-demo.ipynb', + source_path / 'part1_flopy/10_modpath-demo.ipynb', + # "bonus" notebooks + source_path / 'part0_python_intro/09_Geopandas_ABQ.ipynb' +] +# copy the notebooks +for f in copy_notebooks: + dest_f = dest_path / f.relative_to(source_path) + dest_f.parent.mkdir(exist_ok=True, parents=True) + if f.is_dir(): + shutil.copytree(f, dest_f) + else: + shutil.copy(f, dest_f) + print(f"copied {f} to {dest_f}") + +shutil.copy('../../more_resources/glossary_of_jargon.md', '.') +shutil.copy('../../SOME_HELPFUL_LINKS.md', '.') + +#nbsphinx settings +nbsphinx_allow_errors = True +# disable automatic notebook execution (nbs are built in CI for now) +# nbsphinx_execute = "never" diff --git a/docs/source/contributing.md b/docs/source/contributing.md new file mode 100644 index 0000000..e7a6012 --- /dev/null +++ b/docs/source/contributing.md @@ -0,0 +1,53 @@ +Contributing +======================================= + +Contributions are welcome from the community. Questions can be asked on the +[issues page][1]. Before creating a new issue, please take a moment to search +and make sure a similar issue does not already exist. If one does exist, you +can comment (most simply even with just a `:+1:`) to show your support for that +issue. + +If you have direct contributions you would like considered for incorporation +into the project you can [fork this repository][2] and +[submit a pull request][3] for review. + + +[1]: https://github.com/DOI-USGS/python-for-hyrology/issues +[2]: https://help.github.com/articles/fork-a-repo/ +[3]: https://help.github.com/articles/about-pull-requests/ + + +Adding a Notebook +-------------------- +1) Fork the repository +2) Install the `docs/docs-environment.yml` python environment, which has a few extra packages for building the HTML documentation. +3) See the existing `notebooks/` for examples. +4) When developing the notebook, pay attention to the markdown header levels: + * `#` for the title, which will appear in the Table of Contents tree on the left, and as the caption for the thumbnail. + * `##` for subheaders, which will also appear in the Table of Contents tree. + * `###` and `####` between subheaders, as needed. +5) For now, each notebook title begins with the number (e.g. "01: Title"). +6) Including output or not: + + * Currently, output in the exercise notebooks (not in the `solutions/` subfolders) should be cleared prior to submitting a PR, unless the notebook is listed as excepted in `notebooks/clear_all_notebooks.py`. The `.github/workflows/notebook-output.yaml` workflow will check for output in non-solution notebooks. + +7) Notebook execution + + * Notebooks that don't have saved output will be executed by `nbsphinx`, so that the output is rendered in the HTML docs. + * Excessive errors can be quieted by importing `warnings` at the top, and then including `warnings.filterwarnings("ignore")` within the offending cell. + * Alternatively, screen output for a given cell can be turned off by including `%%capture` at the top. + +8) Testing + + * The `.github/workflows/test.yaml` workflow will check for successfull notebook execution. + * If your notebook has intentional errors, consider just showing the error in a markdown block (wrapped in python`````` so that the syntax gets highlighted). + * Otherwise, include the notebook in the `xfail_notebooks` list in `tests/test_notebooks.py`, so that the notebook gets marked as expected to fail (and doesn't fail the test workflow). + + +9) Adding the notebook to the example gallery + + * Edit the `copy_notebooks` list in `docs/conf.py` to add the notebook. This will copy the notebook to the `docs/notebooks` folder so that it can be rendered in the documentation. + * Edit `part0.rst`, `part1.rst` or `bonus_examples.rst` to add the notebook to the appropriate example gallery. + * At the command line run `make -C docs html` + * Check the results by entering `file:///` into a web browser + * By default, the thumbnail icon is made from the last plot (if one exists). Otherwise, see the [nbsphinx instructions on thumbnails](https://nbsphinx.readthedocs.io/en/0.9.3/subdir/gallery.html#) to use another plot or include a static thumbnail. \ No newline at end of file diff --git a/docs/source/glossary_of_jargon.md b/docs/source/glossary_of_jargon.md new file mode 100644 index 0000000..cba3076 --- /dev/null +++ b/docs/source/glossary_of_jargon.md @@ -0,0 +1,65 @@ +# Glossary of coding coding and software jargon + + +#### Athens test +When a code runs from start to finish (compiled or script) without throwing an error, it passes the Athens test. This has no bearing on whether the code is performing the actual function it was designed for - it just means it is capable of executing without failure. For etymology, consult Steve Westenbroek :) + +#### Boat anchor +Something obsolete, useless, and cumbersome – so-called because metaphorically its only productive use is to be thrown into the water as a boat mooring. + +#### Code smell +In computer programming, a code smell is any characteristic in the source code of a program that possibly indicates a deeper problem. Determining what is and is not a code smell is subjective, and varies by language, developer, and development methodology. ... It is also a term used by agile programmers. + +#### Continuous integration (CI) +A development practice where developers integrate code into a shared repository frequently, preferably several times a day. Each integration can then be verified by an automated build and automated tests. + +#### Cruft +A jargon word for anything that is left over, redundant and getting in the way. It is used particularly for defective, superseded, useless, superfluous, or dysfunctional elements in computer software. + +#### Dogfooding +Eating your own dog food, also called dogfooding, occurs when an organization uses its own product. This can be a way for an organization to test its products in real-world usage. Hence dogfooding can act as quality control, and eventually a kind of testimonial advertising. Once in the market, dogfooding demonstrates confidence in the developers' own products. In software development, this means using the code from a user's point of view. + +**DRY** don't don't repeat yourself. + +#### God object +In object-oriented programming, a God object is an object that knows too much or does too much. The God object is an example of an anti-pattern. + +#### Kludge +A kludge or kluge (/klʌdʒ, kluːdʒ/) is a workaround or quick-and-dirty solution that is clumsy, inelegant, inefficient, difficult to extend and hard to maintain. + +#### Lint +Lint, or a linter, is a tool that analyzes source code to flag programming errors, bugs, stylistic errors, and suspicious constructs. The term originates from a Unix utility that examined C language source code. + +#### lmgtfy +Let me Google that for you. https://lmgtfy.com/ + +#### Minimum viable product +A minimum viable product (MVP) is a version of a product with just enough features to satisfy early customers and provide feedback for future product development. Gathering insights from an MVP is often less expensive than developing a product with more features, which increases costs and risk if the product fails, for example, due to incorrect assumptions. + +#### Munging +Verb (used with or without object), munged, mung·ing. Computer Slang. To manipulate (raw data), especially to convert (data) from one format to another: the munging of HTML content. + +#### PEBKAC +Problem exists between keyboard and computer. see also RTFM + +#### REPL +Read-Eval-Print Loop + +#### RTFM +Read the f---ing manual. + +#### Software regression +A bug that makes a feature stop functioning as intended after a certain event (for example, when features or code are added or refactored). One goal of testing is to prevent software regression. + +#### Stranded development +When code development branches in different directions that are further developed by not re-integrated with the main branch. Can lead to duplication of effort and makes maintenance difficult. + +#### Technical debt +Technical debt (also known as design debt or code debt, but can be also related to other technical endeavors) is a concept in software development that reflects the implied cost of additional rework caused by choosing an easy (limited) solution now instead of using a better approach that would take longer. [JRR: Seems like there should be a corresponding inverse, say, Technical Surplus: implied cost of over-engineering the solution from the start.] + +#### Test-driven development (TDD) +A software development process that relies on the repetition of a very short development cycle: requirements are turned into very specific test cases, then the code is improved so that the tests pass. This is opposed to software development that allows code to be added that is not proven to meet requirements. In the context of scientific programming, the idea is to start new code development with a test function that describes what needs to be done, and a small piece of test data that mimics the (large) real dataset that needs to be processed. The new code (usually a function) can then be written and tested rapidly against the test data set (via the test function). When the test finally passes, the new code can be run with the real dataset. This can greatly speed development (faster runtimes) and when the code is developed, a test is already in place to prevent future regressions to the code when new features are added. + +#### "You aren't gonna need it" (YAGNI) +A principle of extreme programming (XP) that states a programmer should not add functionality until deemed necessary. XP co-founder Ron Jeffries has written: "Always implement things when you actually need them, never when you just foresee that you need them." + \ No newline at end of file diff --git a/docs/source/index.rst b/docs/source/index.rst new file mode 100644 index 0000000..3662380 --- /dev/null +++ b/docs/source/index.rst @@ -0,0 +1,28 @@ +================================== +USGS Python for Hydrology Course +================================== + +Welcome to the USGS python for hydrology and flopy course. This is organized into two parts: part 0 focusing on general python for data analysis in hydrologic contexts, and part 1 focusing on flopy - the python interface into MODFLOW for groundwater modeling. + +We encourage students to explore these materials for their own study or to reach out to USGS to attend an in-person course. + +.. toctree:: + :maxdepth: 2 + :caption: Main Curriculum + + Part 0: Introduction to Python + Part 1: Flopy + +.. toctree:: + :maxdepth: 2 + :caption: Bonus Examples + + General Python + +.. toctree:: + :maxdepth: 1 + :caption: Reference + + Additional links + Contributing + Glossary of jargon diff --git a/docs/source/part0.rst b/docs/source/part0.rst new file mode 100644 index 0000000..2df9b6f --- /dev/null +++ b/docs/source/part0.rst @@ -0,0 +1,21 @@ +Part 0: General Python Exercises +======================================= + +.. nbgallery:: + + notebooks/part0_python_intro/solutions/01_functions_script__solution.ipynb + notebooks/part0_python_intro/solutions/02_Namespace_objects_modules_packages__solution.ipynb + notebooks/part0_python_intro/03_useful-std-library-modules.ipynb + notebooks/part0_python_intro/solutions/03_useful-std-library-modules-solutions.ipynb + notebooks/part0_python_intro/solutions/04_files_and_strings.ipynb + notebooks/part0_python_intro/05_numpy.ipynb + notebooks/part0_python_intro/solutions/05_numpy__solutions.ipynb + notebooks/part0_python_intro/solutions/06_matplotlib__solution.ipynb + notebooks/part0_python_intro/06b_matplotlib_animation.ipynb + notebooks/part0_python_intro/solutions/07a_Theis-exercise-solution.ipynb + notebooks/part0_python_intro/07b_VSCode.md + notebooks/part0_python_intro/solutions/08_pandas.ipynb + notebooks/part0_python_intro/09_Geopandas.ipynb + notebooks/part0_python_intro/solutions/09_Geopandas__solutions.ipynb + notebooks/part0_python_intro/10_Rasterio.ipynb + notebooks/part0_python_intro/11_xarray_mt_rainier_precip.ipynb \ No newline at end of file diff --git a/docs/source/part1.rst b/docs/source/part1.rst new file mode 100644 index 0000000..821f687 --- /dev/null +++ b/docs/source/part1.rst @@ -0,0 +1,16 @@ +Part 1 flopy +======================================= + +.. nbgallery:: + + notebooks/part1_flopy/solutions/02-Building-Post-Processing-MODFLOW6__solutions.ipynb + notebooks/part1_flopy/solutions/03_Loading_and_visualizing_models-solutions.ipynb + notebooks/part1_flopy/solutions/04_Modelgrid_and_intersection_solution.ipynb + notebooks/part1_flopy/05-unstructured-grids.ipynb + notebooks/part1_flopy/solutions/06-Project-structured_completed.ipynb + notebooks/part1_flopy/solutions/06-Project-quadtree.ipynb + notebooks/part1_flopy/solutions/06-Project-voronoi.ipynb + notebooks/part1_flopy/solutions/07-stream_capture_voronoi.ipynb + notebooks/part1_flopy/08_Modflow-setup-demo.ipynb + notebooks/part1_flopy/09-gwt-voronoi-demo.ipynb + notebooks/part1_flopy/10_modpath-demo.ipynb \ No newline at end of file diff --git a/notebooks/part0_python_intro/07a_Theis-exercise.ipynb b/notebooks/part0_python_intro/07a_Theis-exercise.ipynb index 3902d14..b476497 100644 --- a/notebooks/part0_python_intro/07a_Theis-exercise.ipynb +++ b/notebooks/part0_python_intro/07a_Theis-exercise.ipynb @@ -4,7 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# 07: Using functions to solve an equation-- The Theis example\n", + "# 07a: Using functions to solve an equation-- The Theis example\n", "In this exercise we will implement the Theis equation in Python using functions, to evaluate drawdown in hydraulic head from pumping at a well.\n", "\n", "\n", diff --git a/notebooks/part0_python_intro/07b_VSCode.md b/notebooks/part0_python_intro/07b_VSCode.md index 246e4f5..3295f01 100644 --- a/notebooks/part0_python_intro/07b_VSCode.md +++ b/notebooks/part0_python_intro/07b_VSCode.md @@ -1,4 +1,4 @@ -# VSCode Tutorial +# 07b: VSCode Tutorial In this tutorial we will explore using an integrated development environment (IDE) for python programming. IDEs offer many advantages over Jupyter Notebooks, particularly for developing production code that will be reused many times and shared with others. The advantages of IDEs include: * *Linting* to catch errors, dead code, and other code quality issues * automatic docstring generation and other auto completion