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Added ROMS ocean model example notebook #3116

Merged
merged 10 commits into from
Aug 16, 2019
6 changes: 3 additions & 3 deletions azure-pipelines.yml
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Expand Up @@ -64,7 +64,7 @@ jobs:
steps:
- template: ci/azure/install.yml
- bash: |
source activate test_env
source activate xarray-tests
mypy . || exit 0
displayName: mypy type checks

Expand All @@ -76,7 +76,7 @@ jobs:
parameters:
env_file: doc/environment.yml
- bash: |
source activate test_env
source activate xarray-tests
cd doc
sphinx-build -n -j auto -b html -d _build/doctrees . _build/html
displayName: Build HTML docs
Expand All @@ -89,6 +89,6 @@ jobs:
steps:
- template: ci/azure/install.yml
- bash: |
source activate test_env
source activate xarray-tests
pytest properties
displayName: Property based tests
8 changes: 4 additions & 4 deletions ci/azure/install.yml
Original file line number Diff line number Diff line change
Expand Up @@ -6,11 +6,11 @@ steps:
- template: add-conda-to-path.yml

- bash: |
conda env create -n test_env --file ${{ parameters.env_file }}
conda env create -n xarray-tests --file ${{ parameters.env_file }}
displayName: Install conda dependencies

- bash: |
source activate test_env
source activate xarray-tests
pip install -f https://7933911d6844c6c53a7d-47bd50c35cd79bd838daf386af554a83.ssl.cf2.rackcdn.com \
--no-deps \
--pre \
Expand All @@ -29,12 +29,12 @@ steps:
displayName: Install upstream dev dependencies

- bash: |
source activate test_env
source activate xarray-tests
pip install --no-deps -e .
displayName: Install xarray

- bash: |
source activate test_env
source activate xarray-tests
conda info -a
conda list
python xarray/util/print_versions.py
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4 changes: 2 additions & 2 deletions ci/azure/unit-tests.yml
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Expand Up @@ -3,14 +3,14 @@ steps:
- template: install.yml

- bash: |
source activate test_env
source activate xarray-tests
python -OO -c "import xarray"
displayName: Import xarray

# Work around for allowed test failures:
# https://github.com/microsoft/azure-pipelines-tasks/issues/9302
- bash: |
source activate test_env
source activate xarray-tests
pytest xarray \
--junitxml=junit/test-results.xml \
--cov=xarray \
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2 changes: 1 addition & 1 deletion ci/requirements/py35-min.yml
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@@ -1,4 +1,4 @@
name: test_env
name: xarray-tests
dependencies:
- python=3.5.0
- pytest
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2 changes: 1 addition & 1 deletion ci/requirements/py36-hypothesis.yml
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
name: test_env
name: xarray-tests
channels:
- conda-forge
dependencies:
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2 changes: 1 addition & 1 deletion ci/requirements/py36.yml
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
name: test_env
name: xarray-tests
channels:
- conda-forge
dependencies:
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2 changes: 1 addition & 1 deletion ci/requirements/py37-windows.yml
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
name: test_env
name: xarray-tests
channels:
- conda-forge
dependencies:
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2 changes: 1 addition & 1 deletion ci/requirements/py37.yml
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
name: test_env
name: xarray-tests
channels:
- conda-forge
dependencies:
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4 changes: 2 additions & 2 deletions doc/contributing.rst
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Expand Up @@ -152,10 +152,10 @@ We'll now kick off a two-step process:

# Create and activate the build environment
conda env create -f ci/requirements/py36.yml
conda activate test_env
conda activate xarray-tests

# or with older versions of Anaconda:
source activate test_env
source activate xarray-tests

# Build and install xarray
pip install -e .
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1 change: 1 addition & 0 deletions doc/examples.rst
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Expand Up @@ -8,3 +8,4 @@ Examples
examples/monthly-means
examples/multidimensional-coords
examples/visualization_gallery
examples/ROMS_ocean_model
223 changes: 223 additions & 0 deletions doc/examples/ROMS_ocean_model.ipynb
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@@ -0,0 +1,223 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# ROMS Ocean Model Example"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import cartopy.crs as ccrs\n",
"import cartopy.feature as cfeature\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"# import cmocean # TODO: Add this dependency to the docs\n",
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Let's keep cmocean out since it isn't strictly necessary for the example.

"\n",
"import xarray as xr"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Load a sample ROMS file. This is a subset of a full model available at \n",
"\n",
" http://barataria.tamu.edu/thredds/catalog.html?dataset=txla_hindcast_agg\n",
" \n",
"The subsetting was done using the following command on one of the output files:\n",
"\n",
" #open dataset\n",
" ds = xr.open_dataset('/d2/shared/TXLA_ROMS/output_20yr_obc/2001/ocean_his_0015.nc')\n",
" \n",
" # Turn on chunking to activate dask and parallelize read/write.\n",
" ds = ds.chunk({'ocean_time': 1})\n",
" \n",
" # Pick out some of the variables that will be included as coordinates\n",
" ds = ds.set_coords(['Cs_r', 'Cs_w', 'hc', 'h', 'Vtransform'])\n",
" \n",
" # Select a a subset of variables. Salt will be visualized, zeta is used to \n",
" # calculate the vertical coordinate\n",
" variables = ['salt', 'zeta']\n",
" ds[variables].isel(ocean_time=slice(47, None, 7*24), \n",
" xi_rho=slice(300, None)).to_netcdf('ROMS_example.nc', mode='w')\n",
"\n",
"So, the `ROMS_example.nc` file contains a subset of the grid, one 3D variable, and two time steps."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load in ROMS dataset as an xarray object"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# load in the file\n",
"ds = xr.tutorial.open_dataset('ROMS_example.nc', chunks={'ocean_time': 1})\n",
"\n",
"# This is a way to turn on chunking and lazy evaluation. Opening with mfdataset, or \n",
"# setting the chunking in the open_dataset would also achive this.\n",
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Suggested change
"# setting the chunking in the open_dataset would also achive this.\n",
"# setting the chunking in the open_dataset would also achieve this.\n",

"ds"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Add a lazilly calculated vertical coordinates\n",
"\n",
"Write equations to calculate the vertical coordinate. These will be only evaluated when data is requested. Information about the ROMS vertical coordinate can be found (here)[https://www.myroms.org/wiki/Vertical_S-coordinate]\n",
"\n",
"In short, for `Vtransform==2` as used in this example, \n",
"\n",
"$Z_0 = (h_c \\, S + h \\,C) / (h_c + h)$\n",
"\n",
"$z = Z_0 (\\zeta + h) + \\zeta$\n",
"\n",
"where the variables are defined as in the link above."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"if ds.Vtransform == 1:\n",
" Zo_rho = ds.hc * (ds.s_rho - ds.Cs_r) + ds.Cs_r * ds.h\n",
" z_rho = Zo_rho + ds.zeta * (1 + Zo_rho/ds.h)\n",
"# Zo_w = ds.hc * (ds.s_w - ds.Cs_w) + ds.Cs_w * ds.h\n",
"# z_w = Zo_w + ds.zeta * (1 + Zo_w/ds.h)\n",
"elif ds.Vtransform == 2:\n",
" Zo_rho = (ds.hc * ds.s_rho + ds.Cs_r * ds.h) / (ds.hc + ds.h)\n",
" z_rho = ds.zeta + (ds.zeta + ds.h) * Zo_rho\n",
"# Zo_w = (ds.hc * ds.s_w + ds.Cs_w * ds.h) / (ds.hc + ds.h)\n",
"# z_w = ds.zeta + (ds.zeta + ds.h) * Zo_w\n",
"\n",
"ds.coords['z_rho'] = z_rho.transpose() # needing transpose seems to be an xarray bug\n",
"# ds.coords['z_w'] = z_w.transpose()\n",
"ds.salt"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### A naive vertical slice\n",
"\n",
"Create a slice using the s-coordinate as the vertical dimension is typically not very informative."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"scrolled": false
},
"outputs": [],
"source": [
"ds.salt.isel(xi_rho=50, ocean_time=0).plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can feed coordinate information to the plot method to give a more informative cross-section that uses the depths. Note that we did not need to slice the depth or longitude information separately, this was done automatically as the variable was sliced."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"section = ds.salt.isel(xi_rho=50, eta_rho=slice(0, 167), ocean_time=0)\n",
"section.plot(x='lon_rho', y='z_rho', figsize=(15, 6), cmap=cmocean.cm.haline, clim=(25, 35))\n",
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Lets just use a standard matplotlib colormap

"plt.ylim([-100, 1]);"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### A plan view\n",
"\n",
"Now make a naive plan view, without any projection information, just using lon/lat as x/y. This looks OK, but will appear compressed because lon and lat do not have an aspect constrained by the projection."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"ds.salt.isel(s_rho=-1, ocean_time=0).plot(x='lon_rho', y='lat_rho')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And let's use a projection to make it nicer, and add a coast."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"proj = ccrs.LambertConformal(central_longitude=-92, central_latitude=29)\n",
"fig = plt.figure(figsize=(15, 5))\n",
"ax = plt.axes(projection=proj)\n",
"ds.salt.isel(s_rho=-1, ocean_time=0).plot(x='lon_rho', y='lat_rho', \n",
" cmap=cmocean.cm.haline, transform=ccrs.PlateCarree())\n",
"\n",
"coast_10m = cfeature.NaturalEarthFeature('physical', 'land', '10m',\n",
" edgecolor='k', facecolor='0.8')\n",
"ax.add_feature(coast_10m)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.6.7"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
12 changes: 8 additions & 4 deletions xarray/tutorial.py
Original file line number Diff line number Diff line change
Expand Up @@ -33,8 +33,9 @@ def open_dataset(name, cache=True, cache_dir=_default_cache_dir,
Parameters
----------
name : str
Name of the netcdf file containing the dataset
ie. 'air_temperature'
Name of the file containing the dataset. If no suffix is given, assumed
to be netCDF ('.nc' is appended)
e.g. 'air_temperature'
cache_dir : string, optional
The directory in which to search for and write cached data.
cache : boolean, optional
Expand All @@ -51,10 +52,13 @@ def open_dataset(name, cache=True, cache_dir=_default_cache_dir,
xarray.open_dataset

"""
root, ext = _os.path.splitext(name)
if not ext:
ext = '.nc'
fullname = root + ext
longdir = _os.path.expanduser(cache_dir)
fullname = name + '.nc'
localfile = _os.sep.join((longdir, fullname))
md5name = name + '.md5'
md5name = fullname + '.md5'
md5file = _os.sep.join((longdir, md5name))

if not _os.path.exists(localfile):
Expand Down