From 3b5578bfa2b9b1b0865f99bce92901cd6d771573 Mon Sep 17 00:00:00 2001 From: ssolson Date: Fri, 9 Aug 2024 09:03:20 -0400 Subject: [PATCH 1/7] matplotlib >=3.8 --- environment.yml | 2 +- mhkit/wave/contours.py | 8 +------- requirements.txt | 2 +- setup.py | 2 +- 4 files changed, 4 insertions(+), 10 deletions(-) diff --git a/environment.yml b/environment.yml index ac679176d..ee1b37bf0 100644 --- a/environment.yml +++ b/environment.yml @@ -8,7 +8,7 @@ dependencies: - pandas>=1.0.0 - numpy>=1.21.0, <2.0.0 - scipy<=1.13.1 - - matplotlib + - matplotlib>=3.8.0 - requests - lxml - scikit-learn diff --git a/mhkit/wave/contours.py b/mhkit/wave/contours.py index 905c560b8..b2a054c4c 100644 --- a/mhkit/wave/contours.py +++ b/mhkit/wave/contours.py @@ -8,11 +8,8 @@ import numpy as np import warnings from mhkit.utils import to_numeric_array - import matplotlib -mpl_version = tuple(map(int, matplotlib.__version__.split("."))) - # Contours def environmental_contours(x1, x2, sea_state_duration, return_period, method, **kwargs): @@ -1696,10 +1693,7 @@ def _bivariate_KDE(x1, x2, bw, fit, nb_steps, Ndata_bivariate_KDE, kwargs): x1_bivariate_KDE = [] x2_bivariate_KDE = [] - if mpl_version < (3, 8): # For versions before 3.8 - segments = vals.allsegs[0] - else: - segments = [path.vertices for path in vals.get_paths()] + segments = [path.vertices for path in vals.get_paths()] for seg in segments: x1_bivariate_KDE.append(seg[:, 1]) diff --git a/requirements.txt b/requirements.txt index 381f1068f..1f68d7614 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,7 +1,7 @@ pandas>=1.0.0 numpy>=1.21.0, <2.0.0 scipy<=1.13.1 -matplotlib +matplotlib>=3.8.0 requests pecos>=0.3.0 fatpack diff --git a/setup.py b/setup.py index c30ff2e9f..8d2825b3b 100644 --- a/setup.py +++ b/setup.py @@ -21,7 +21,7 @@ "pandas>=1.0.0", "numpy>=1.21.0, <2.0.0", "scipy<=1.13.1", - "matplotlib", + "matplotlib>=3.8.0", "requests", "pecos>=0.3.0", "fatpack", From 8303aaf4d10237ef980435894b77d474df3787e2 Mon Sep 17 00:00:00 2001 From: akeeste Date: Thu, 15 Aug 2024 15:39:55 -0500 Subject: [PATCH 2/7] fix issue 339 - bug in wave performance MAEP matrix --- mhkit/utils/type_handling.py | 50 +++++++++++++++++++----------------- 1 file changed, 26 insertions(+), 24 deletions(-) diff --git a/mhkit/utils/type_handling.py b/mhkit/utils/type_handling.py index 2b6c5b920..31ad35f18 100644 --- a/mhkit/utils/type_handling.py +++ b/mhkit/utils/type_handling.py @@ -97,10 +97,12 @@ def convert_to_dataarray(data, name="data"): """ Converts the given data to an xarray.DataArray. - This function is designed to handle inputs that can be either a numpy ndarray, pandas Series, - or an xarray DataArray. For convenience, pandas DataFrame and xarray Dataset can also be input - but may only contain a single variable. The function ensures that the output is consistently - an xarray.DataArray. + This function takes in a numpy ndarray, pandas Series, pandas Dataframe, or xarray Dataset + and outputs an equivalent xarray DataArray. DataArrays can be passed through with no changes. + + Multivariate pandas Dataframes become 2D DataArrays, which is especially useful when IO + functions return Dataframes with an extremely large number of variable. Use the function + convert_to_dataset to change a multivariate Dataframe into a multivariate Dataset. Parameters ---------- @@ -138,7 +140,7 @@ def convert_to_dataarray(data, name="data"): data, (np.ndarray, pd.DataFrame, pd.Series, xr.DataArray, xr.Dataset) ): raise TypeError( - "Input data must be of type np.ndarray, pandas.DataFrame, pandas.Series, " + "Input data must be of type np.ndarray, pandas.Series, pandas.DataFrame, " f"xarray.DataArray, or xarray.Dataset. Got {type(data)}" ) @@ -147,40 +149,40 @@ def convert_to_dataarray(data, name="data"): # Checks pd.DataFrame input and converts to pd.Series if possible if isinstance(data, pd.DataFrame): - if data.shape[1] > 1: - raise ValueError( - "If the input data is a pd.DataFrame or xr.Dataset, it must contain one variable. Got {data.shape[1]}" - ) - else: - # use iloc instead of squeeze. For DataFrames/Series with only a - # single value, squeeze returns a scalar, which is unexpected. - # iloc will return a Series as expected + if data.shape[1] == 1: + # Convert the 1D, univariate case to a Series, which will be caught by the Series conversion below. + # This eliminates an unnecessary variable dimension and names the DataArray with the DataFrame variable name. + # + # Use iloc instead of squeeze. For DataFrames/Series with only a + # single value, squeeze returns a scalar which is unexpected. + # iloc returns a Series with one value as expected. data = data.iloc[:, 0] + else: + index = data.index.values + columns = data.columns.values + data = xr.DataArray(data = data.T, dims=("variable","index"), coords={"variable": columns, "index": index}) # Checks xr.Dataset input and converts to xr.DataArray if possible if isinstance(data, xr.Dataset): keys = list(data.keys()) - if len(keys) > 1: - raise ValueError( - "If the input data is a pd.DataFrame or xr.Dataset, it must contain one variable. Got {len(data.keys())}" - ) - else: - data = data.to_array() - data = data.sel( - variable=keys[0] - ) # removes the variable dimension, further simplifying the dataarray + data = data.to_array() + if len(data.variable) == 1: + # if only one variable, remove that dimension and rename the DataArray to simplify + data = data.sel(variable=keys[0]) + data.name = keys[0] + data.drop('variable') # Converts pd.Series to xr.DataArray if isinstance(data, pd.Series): data = data.to_xarray() - # Converts np.ndarray to xr.DataArray. Assigns a simple 0-based dimension named index + # Converts np.ndarray to xr.DataArray. Assigns a simple 0-based dimension named index to match how pandas converts to xarray if isinstance(data, np.ndarray): data = xr.DataArray( data=data, dims="index", coords={"index": np.arange(len(data))} ) - # If there's no data name, add one to prevent issues calling or converting the dataArray later one + # If there's no data name, add one to prevent issues calling or converting to a Dataset later on if data.name == None: data.name = name From 8de205528f42b3a1adeca639d3b5edc0d9a8acf5 Mon Sep 17 00:00:00 2001 From: akeeste Date: Thu, 15 Aug 2024 15:40:53 -0500 Subject: [PATCH 3/7] restore MAEP matrix calc to wave_example.ipynb --- examples/wave_example.ipynb | 24 ++++++++++-------------- 1 file changed, 10 insertions(+), 14 deletions(-) diff --git a/examples/wave_example.ipynb b/examples/wave_example.ipynb index d3c2ba897..4f705ceb9 100644 --- a/examples/wave_example.ipynb +++ b/examples/wave_example.ipynb @@ -39,7 +39,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "c:\\users\\sterl\\codes\\mhkit-python\\mhkit\\wave\\io\\ndbc.py:99: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n", + "c:\\users\\akeeste\\documents\\software\\github\\mhkit-python\\mhkit\\wave\\io\\ndbc.py:99: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n", " data = pd.read_csv(\n" ] }, @@ -2761,18 +2761,14 @@ } ], "source": [ - "# Calcaulte maep from timeseries\n", + "# Calculate maep from timeseries\n", "maep_timeseries = wave.performance.mean_annual_energy_production_timeseries(L, J)\n", "print(\"MAEP from timeseries = \", maep_timeseries)\n", "\n", - "# Calcaulte maep from matrix \n", - "# See Issue #339\n", - "# maep_matrix = wave.performance.mean_annual_energy_production_matrix(\n", - "# LM_mean, JM, LM_freq\n", - "# )\n", - "\n", - "T = 8766 # Average length of a year (h)\n", - "maep_matrix = T * np.nansum(LM_mean * JM * LM_freq)\n", + "# Calculate maep from matrix \n", + "maep_matrix = wave.performance.mean_annual_energy_production_matrix(\n", + " LM_mean, JM, LM_freq\n", + ")\n", "\n", "print(\"MAEP from matrices = \", maep_matrix)" ] @@ -2792,7 +2788,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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", 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", 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" ] @@ -2861,7 +2857,7 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 3", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -2875,7 +2871,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.7" + "version": "3.11.9" } }, "nbformat": 4, From 6e0077ddd26eca5d06dbf54ccd15055188b503ab Mon Sep 17 00:00:00 2001 From: akeeste Date: Thu, 15 Aug 2024 16:08:22 -0500 Subject: [PATCH 4/7] type_handling - special dataset to dataarray case and tests --- mhkit/tests/utils/test_utils.py | 65 +++++++++++++++++++++------------ mhkit/utils/type_handling.py | 14 +++++-- 2 files changed, 51 insertions(+), 28 deletions(-) diff --git a/mhkit/tests/utils/test_utils.py b/mhkit/tests/utils/test_utils.py index 315d0de19..b1b558807 100644 --- a/mhkit/tests/utils/test_utils.py +++ b/mhkit/tests/utils/test_utils.py @@ -171,20 +171,27 @@ def test_convert_to_dataarray(self): # test data formats test_n = d1 test_s = pd.Series(d1, t) - test_df = pd.DataFrame({"d1": d1}, index=t) - test_df2 = pd.DataFrame({"d1": d1, "d1_duplicate": d1}, index=t) + test_df_1d = pd.DataFrame({"d1": d1}, index=t) + test_df_2d = pd.DataFrame({"d1": d1, "d1_duplicate": d1}, index=t) test_da = xr.DataArray( data=d1, dims="time", coords=dict(time=t), ) - test_ds = xr.Dataset( + test_ds_1d_1v = xr.Dataset( data_vars={"d1": (["time"], d1)}, coords={"time": t, "index": i} ) - test_ds2 = xr.Dataset( + test_ds_2d_1v = xr.Dataset( data_vars={ "d1": (["time"], d1), - "d2": (["ind"], d2), + "d1_duplicate": (["time"], d1), + }, + coords={"time": t}, + ) + test_ds_2d_2v = xr.Dataset( + data_vars={ + "d1": (["time"], d1), + "d2": (["index"], d2), }, coords={"time": t, "index": i}, ) @@ -205,15 +212,33 @@ def test_convert_to_dataarray(self): self.assertIsInstance(da, xr.DataArray) self.assertTrue(all(da.data == d1)) - # Dataframe - df = utils.convert_to_dataarray(test_df) - self.assertIsInstance(df, xr.DataArray) - self.assertTrue(all(df.data == d1)) - - # Dataset - ds = utils.convert_to_dataarray(test_ds) - self.assertIsInstance(ds, xr.DataArray) - self.assertTrue(all(ds.data == d1)) + # 1D Dataframe + df_1d = utils.convert_to_dataarray(test_df_1d) + self.assertIsInstance(df_1d, xr.DataArray) + self.assertTrue(all(df_1d.data == d1)) + self.assertTrue('variable' not in df_1d.dims) + + # Multivariate Dataframe + df_2d = utils.convert_to_dataarray(test_df_2d) + self.assertIsInstance(df_2d, xr.DataArray) + self.assertTrue(all(df_2d.sel(variable='d1').data == d1)) + self.assertTrue(all(df_2d.sel(variable='d1_duplicate').data == d1)) + + # 1D Dataset + ds_1d_1v = utils.convert_to_dataarray(test_ds_1d_1v) + self.assertIsInstance(ds_1d_1v, xr.DataArray) + self.assertTrue(all(ds_1d_1v.data == d1)) + self.assertTrue('variable' not in ds_1d_1v.dims) + + # Multivariate 1D Dataset + ds_2d_1v = utils.convert_to_dataarray(test_ds_2d_1v) + self.assertIsInstance(ds_2d_1v, xr.DataArray) + self.assertTrue(all(ds_2d_1v.sel(variable='d1').data == d1)) + self.assertTrue(all(ds_2d_1v.sel(variable='d1_duplicate').data == d1)) + + # Multivariate 2D Dataset (error) + with self.assertRaises(ValueError): + utils.convert_to_dataarray(test_ds_2d_2v) # int (error) with self.assertRaises(TypeError): @@ -223,14 +248,6 @@ def test_convert_to_dataarray(self): with self.assertRaises(TypeError): utils.convert_to_dataarray(test_n, 5) - # Multivariate Dataframe (error) - with self.assertRaises(ValueError): - utils.convert_to_dataarray(test_df2) - - # Multivariate Dataset (error) - with self.assertRaises(ValueError): - utils.convert_to_dataarray(test_ds2) - def test_convert_to_dataset(self): # test data a = 5 @@ -242,7 +259,7 @@ def test_convert_to_dataset(self): # test data formats test_n = d1 test_s = pd.Series(d1, t) - test_df2 = pd.DataFrame({"d1": d1, "d2": d2}, index=t) + test_df_2d = pd.DataFrame({"d1": d1, "d2": d2}, index=t) test_da = xr.DataArray( data=d1, dims="time", @@ -267,7 +284,7 @@ def test_convert_to_dataset(self): self.assertTrue(all(da["test_name"].data == d1)) # Dataframe - df = utils.convert_to_dataset(test_df2) + df = utils.convert_to_dataset(test_df_2d) self.assertIsInstance(df, xr.Dataset) self.assertTrue(all(df["d1"].data == d1)) self.assertTrue(all(df["d2"].data == d2)) diff --git a/mhkit/utils/type_handling.py b/mhkit/utils/type_handling.py index 31ad35f18..45f1626f9 100644 --- a/mhkit/utils/type_handling.py +++ b/mhkit/utils/type_handling.py @@ -165,12 +165,18 @@ def convert_to_dataarray(data, name="data"): # Checks xr.Dataset input and converts to xr.DataArray if possible if isinstance(data, xr.Dataset): keys = list(data.keys()) - data = data.to_array() - if len(data.variable) == 1: - # if only one variable, remove that dimension and rename the DataArray to simplify + if len(keys) == 1: + # if only one variable, remove the "variable" dimension and rename the DataArray to simplify + data = data.to_array() data = data.sel(variable=keys[0]) data.name = keys[0] - data.drop('variable') + data.drop_vars('variable') + else: + # Allow multiple variables if they have the same dimensions + if all([data[keys[0]].dims == data[key].dims for key in keys]): + data = data.to_array() + else: + raise ValueError('Multivariate Datasets can only be input if all variables have the same dimensions.') # Converts pd.Series to xr.DataArray if isinstance(data, pd.Series): From 49296c37ff545220e9edc1d680beedd419cb3cbf Mon Sep 17 00:00:00 2001 From: ssolson Date: Mon, 19 Aug 2024 10:27:25 -0400 Subject: [PATCH 5/7] black --- mhkit/tests/utils/test_utils.py | 12 ++++++------ mhkit/utils/type_handling.py | 16 +++++++++++----- 2 files changed, 17 insertions(+), 11 deletions(-) diff --git a/mhkit/tests/utils/test_utils.py b/mhkit/tests/utils/test_utils.py index b1b558807..ba2b9cb03 100644 --- a/mhkit/tests/utils/test_utils.py +++ b/mhkit/tests/utils/test_utils.py @@ -216,25 +216,25 @@ def test_convert_to_dataarray(self): df_1d = utils.convert_to_dataarray(test_df_1d) self.assertIsInstance(df_1d, xr.DataArray) self.assertTrue(all(df_1d.data == d1)) - self.assertTrue('variable' not in df_1d.dims) + self.assertTrue("variable" not in df_1d.dims) # Multivariate Dataframe df_2d = utils.convert_to_dataarray(test_df_2d) self.assertIsInstance(df_2d, xr.DataArray) - self.assertTrue(all(df_2d.sel(variable='d1').data == d1)) - self.assertTrue(all(df_2d.sel(variable='d1_duplicate').data == d1)) + self.assertTrue(all(df_2d.sel(variable="d1").data == d1)) + self.assertTrue(all(df_2d.sel(variable="d1_duplicate").data == d1)) # 1D Dataset ds_1d_1v = utils.convert_to_dataarray(test_ds_1d_1v) self.assertIsInstance(ds_1d_1v, xr.DataArray) self.assertTrue(all(ds_1d_1v.data == d1)) - self.assertTrue('variable' not in ds_1d_1v.dims) + self.assertTrue("variable" not in ds_1d_1v.dims) # Multivariate 1D Dataset ds_2d_1v = utils.convert_to_dataarray(test_ds_2d_1v) self.assertIsInstance(ds_2d_1v, xr.DataArray) - self.assertTrue(all(ds_2d_1v.sel(variable='d1').data == d1)) - self.assertTrue(all(ds_2d_1v.sel(variable='d1_duplicate').data == d1)) + self.assertTrue(all(ds_2d_1v.sel(variable="d1").data == d1)) + self.assertTrue(all(ds_2d_1v.sel(variable="d1_duplicate").data == d1)) # Multivariate 2D Dataset (error) with self.assertRaises(ValueError): diff --git a/mhkit/utils/type_handling.py b/mhkit/utils/type_handling.py index 45f1626f9..a1cd6692a 100644 --- a/mhkit/utils/type_handling.py +++ b/mhkit/utils/type_handling.py @@ -100,7 +100,7 @@ def convert_to_dataarray(data, name="data"): This function takes in a numpy ndarray, pandas Series, pandas Dataframe, or xarray Dataset and outputs an equivalent xarray DataArray. DataArrays can be passed through with no changes. - Multivariate pandas Dataframes become 2D DataArrays, which is especially useful when IO + Multivariate pandas Dataframes become 2D DataArrays, which is especially useful when IO functions return Dataframes with an extremely large number of variable. Use the function convert_to_dataset to change a multivariate Dataframe into a multivariate Dataset. @@ -152,7 +152,7 @@ def convert_to_dataarray(data, name="data"): if data.shape[1] == 1: # Convert the 1D, univariate case to a Series, which will be caught by the Series conversion below. # This eliminates an unnecessary variable dimension and names the DataArray with the DataFrame variable name. - # + # # Use iloc instead of squeeze. For DataFrames/Series with only a # single value, squeeze returns a scalar which is unexpected. # iloc returns a Series with one value as expected. @@ -160,7 +160,11 @@ def convert_to_dataarray(data, name="data"): else: index = data.index.values columns = data.columns.values - data = xr.DataArray(data = data.T, dims=("variable","index"), coords={"variable": columns, "index": index}) + data = xr.DataArray( + data=data.T, + dims=("variable", "index"), + coords={"variable": columns, "index": index}, + ) # Checks xr.Dataset input and converts to xr.DataArray if possible if isinstance(data, xr.Dataset): @@ -170,13 +174,15 @@ def convert_to_dataarray(data, name="data"): data = data.to_array() data = data.sel(variable=keys[0]) data.name = keys[0] - data.drop_vars('variable') + data.drop_vars("variable") else: # Allow multiple variables if they have the same dimensions if all([data[keys[0]].dims == data[key].dims for key in keys]): data = data.to_array() else: - raise ValueError('Multivariate Datasets can only be input if all variables have the same dimensions.') + raise ValueError( + "Multivariate Datasets can only be input if all variables have the same dimensions." + ) # Converts pd.Series to xr.DataArray if isinstance(data, pd.Series): From 1d554f3711cfa05dea74f219c0a7e40a553de65b Mon Sep 17 00:00:00 2001 From: akeeste Date: Tue, 27 Aug 2024 10:25:17 -0500 Subject: [PATCH 6/7] add requirement on datasets to the docstring --- mhkit/utils/type_handling.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/mhkit/utils/type_handling.py b/mhkit/utils/type_handling.py index a1cd6692a..1e8f0a304 100644 --- a/mhkit/utils/type_handling.py +++ b/mhkit/utils/type_handling.py @@ -100,6 +100,8 @@ def convert_to_dataarray(data, name="data"): This function takes in a numpy ndarray, pandas Series, pandas Dataframe, or xarray Dataset and outputs an equivalent xarray DataArray. DataArrays can be passed through with no changes. + Xarray datasets can only be input when all variable have the same dimensions. + Multivariate pandas Dataframes become 2D DataArrays, which is especially useful when IO functions return Dataframes with an extremely large number of variable. Use the function convert_to_dataset to change a multivariate Dataframe into a multivariate Dataset. From d062154fb9313d3965a6e8f3715586925b43a10e Mon Sep 17 00:00:00 2001 From: akeeste Date: Tue, 27 Aug 2024 10:25:47 -0500 Subject: [PATCH 7/7] black --- mhkit/utils/type_handling.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/mhkit/utils/type_handling.py b/mhkit/utils/type_handling.py index 1e8f0a304..1b06c7d12 100644 --- a/mhkit/utils/type_handling.py +++ b/mhkit/utils/type_handling.py @@ -100,7 +100,7 @@ def convert_to_dataarray(data, name="data"): This function takes in a numpy ndarray, pandas Series, pandas Dataframe, or xarray Dataset and outputs an equivalent xarray DataArray. DataArrays can be passed through with no changes. - Xarray datasets can only be input when all variable have the same dimensions. + Xarray datasets can only be input when all variable have the same dimensions. Multivariate pandas Dataframes become 2D DataArrays, which is especially useful when IO functions return Dataframes with an extremely large number of variable. Use the function