TEST-#5903: Add third party unit tests for interoperability

.github/workflows/ci.yml

@@ -821,8 +821,9 @@ jobs:
  if: matrix.engine == 'python' || matrix.test_task == 'group_4'
  - run: python -m pytest modin/test/interchange/dataframe_protocol/test_general.py
  if: matrix.engine == 'python' || matrix.test_task == 'group_4'
- - run: python -m pytest modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
+ - run: python -m pytest modin/pandas/test/interoperability
  if: matrix.engine == 'python' || matrix.test_task == 'group_4'
+ - run: python -m pytest modin/test/interchange/dataframe_protocol/pandas/test_protocol.py
  - uses: ./.github/workflows/upload-coverage
 
  test-experimental:

.github/workflows/push-to-master.yml

@@ -86,6 +86,7 @@ jobs:
  python -m pytest modin/pandas/test/test_general.py
  python -m pytest modin/pandas/test/test_io.py
  python -m pytest modin/experimental/pandas/test/test_io_exp.py
+ python -m pytest modin/pandas/test/interoperability
 
  test-docs:
  runs-on: ubuntu-latest

modin/pandas/test/interoperability/matplotlib/test_axes.py

@@ -0,0 +1,154 @@
+# Licensed to Modin Development Team under one or more contributor license agreements.
+# See the NOTICE file distributed with this work for additional information regarding
+# copyright ownership. The Modin Development Team licenses this file to you under the
+# Apache License, Version 2.0 (the "License"); you may not use this file except in
+# compliance with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software distributed under
+# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific language
+# governing permissions and limitations under the License.
+
+import numpy as np
+import matplotlib.pyplot as plt
+import modin.pandas as pd
+from matplotlib.testing.decorators import (
+ check_figures_equal,
+)
+
+# Note: Some test cases are run twice: once normally and once with labeled data
+# These two must be defined in the same test function or need to have
+# different baseline images to prevent race conditions when pytest runs
+# the tests with multiple threads.
+
+
+@check_figures_equal(extensions=["png"])
+def test_invisible_axes(fig_test, fig_ref):
+ ax = fig_test.subplots()
+ ax.set_visible(False)
+
+
+def test_boxplot_dates_pandas():
+ # import modin.pandas as pd
+
+ # smoke test for boxplot and dates in pandas
+ data = np.random.rand(5, 2)
+ years = pd.date_range("1/1/2000", periods=2, freq=pd.DateOffset(years=1)).year
+ plt.figure()
+ plt.boxplot(data, positions=years)
+
+
+def test_bar_pandas():
+ # Smoke test for pandas
+ df = pd.DataFrame(
+ {
+ "year": [2018, 2018, 2018],
+ "month": [1, 1, 1],
+ "day": [1, 2, 3],
+ "value": [1, 2, 3],
+ }
+ )
+ df["date"] = pd.to_datetime(df[["year", "month", "day"]])
+
+ monthly = df[["date", "value"]].groupby(["date"]).sum()
+ dates = monthly.index
+ forecast = monthly["value"]
+ baseline = monthly["value"]
+
+ fig, ax = plt.subplots()
+ ax.bar(dates, forecast, width=10, align="center")
+ ax.plot(dates, baseline, color="orange", lw=4)
+
+
+def test_bar_pandas_indexed():
+ # Smoke test for indexed pandas
+ df = pd.DataFrame({"x": [1.0, 2.0, 3.0], "width": [0.2, 0.4, 0.6]}, index=[1, 2, 3])
+ fig, ax = plt.subplots()
+ ax.bar(df.x, 1.0, width=df.width)
+
+
+def test_pandas_minimal_plot():
+ # smoke test that series and index objects do not warn
+ for x in [pd.Series([1, 2], dtype="float64"), pd.Series([1, 2], dtype="Float64")]:
+ plt.plot(x, x)
+ plt.plot(x.index, x)
+ plt.plot(x)
+ plt.plot(x.index)
+ df = pd.DataFrame({"col": [1, 2, 3]})
+ plt.plot(df)
+ plt.plot(df, df)
+
+
+@check_figures_equal(extensions=["png"])
+def test_violinplot_pandas_series(fig_test, fig_ref):
+ np.random.seed(110433579)
+ s1 = pd.Series(np.random.normal(size=7), index=[9, 8, 7, 6, 5, 4, 3])
+ s2 = pd.Series(np.random.normal(size=9), index=list("ABCDEFGHI"))
+ s3 = pd.Series(np.random.normal(size=11))
+ fig_test.subplots().violinplot([s1, s2, s3])
+ fig_ref.subplots().violinplot([s1.values, s2.values, s3.values])
+
+
+def test_pandas_pcolormesh():
+ time = pd.date_range("2000-01-01", periods=10)
+ depth = np.arange(20)
+ data = np.random.rand(19, 9)
+
+ fig, ax = plt.subplots()
+ ax.pcolormesh(time, depth, data)
+
+
+def test_pandas_indexing_dates():
+ dates = np.arange("2005-02", "2005-03", dtype="datetime64[D]")
+ values = np.sin(range(len(dates)))
+ df = pd.DataFrame({"dates": dates, "values": values})
+
+ ax = plt.gca()
+
+ without_zero_index = df[np.array(df.index) % 2 == 1].copy()
+ ax.plot("dates", "values", data=without_zero_index)
+
+
+def test_pandas_errorbar_indexing():
+ df = pd.DataFrame(
+ np.random.uniform(size=(5, 4)),
+ columns=["x", "y", "xe", "ye"],
+ index=[1, 2, 3, 4, 5],
+ )
+ fig, ax = plt.subplots()
+ ax.errorbar("x", "y", xerr="xe", yerr="ye", data=df)
+
+
+def test_pandas_index_shape():
+ df = pd.DataFrame({"XX": [4, 5, 6], "YY": [7, 1, 2]})
+ fig, ax = plt.subplots()
+ ax.plot(df.index, df["YY"])
+
+
+def test_pandas_indexing_hist():
+ ser_1 = pd.Series(data=[1, 2, 2, 3, 3, 4, 4, 4, 4, 5])
+ ser_2 = ser_1.iloc[1:]
+ fig, ax = plt.subplots()
+ ax.hist(ser_2)
+
+
+def test_pandas_bar_align_center():
+ # Tests fix for issue 8767
+ df = pd.DataFrame({"a": range(2), "b": range(2)})
+
+ fig, ax = plt.subplots(1)
+
+ ax.bar(df.loc[df["a"] == 1, "b"], df.loc[df["a"] == 1, "b"], align="center")
+
+ fig.canvas.draw()
+
+
+def test_scatter_series_non_zero_index():
+ # create non-zero index
+ ids = range(10, 18)
+ x = pd.Series(np.random.uniform(size=8), index=ids)
+ y = pd.Series(np.random.uniform(size=8), index=ids)
+ c = pd.Series([1, 1, 1, 1, 1, 0, 0, 0], index=ids)
+ plt.scatter(x, y, c)

modin/pandas/test/interoperability/matplotlib/test_cbook.py

@@ -0,0 +1,43 @@
+# Licensed to Modin Development Team under one or more contributor license agreements.
+# See the NOTICE file distributed with this work for additional information regarding
+# copyright ownership. The Modin Development Team licenses this file to you under the
+# Apache License, Version 2.0 (the "License"); you may not use this file except in
+# compliance with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software distributed under
+# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific language
+# governing permissions and limitations under the License.
+
+import numpy as np
+import modin.pandas as pd
+from matplotlib import cbook
+
+
+def test_reshape2d_pandas():
+ # separate to allow the rest of the tests to run if no pandas...
+ X = np.arange(30).reshape(10, 3)
+ x = pd.DataFrame(X, columns=["a", "b", "c"])
+ Xnew = cbook._reshape_2D(x, "x")
+ # Need to check each row because _reshape_2D returns a list of arrays:
+ for x, xnew in zip(X.T, Xnew):
+ np.testing.assert_array_equal(x, xnew)
+
+
+def test_index_of_pandas():
+ # separate to allow the rest of the tests to run if no pandas...
+ X = np.arange(30).reshape(10, 3)
+ x = pd.DataFrame(X, columns=["a", "b", "c"])
+ Idx, Xnew = cbook.index_of(x)
+ np.testing.assert_array_equal(X, Xnew)
+ IdxRef = np.arange(10)
+ np.testing.assert_array_equal(Idx, IdxRef)
+
+
+def test_safe_first_element_pandas_series():
+ # deliberately create a pandas series with index not starting from 0
+ s = pd.Series(range(5), index=range(10, 15))
+ actual = cbook._safe_first_finite(s)
+ assert actual == 0

modin/pandas/test/interoperability/matplotlib/test_collections.py

@@ -0,0 +1,31 @@
+# Licensed to Modin Development Team under one or more contributor license agreements.
+# See the NOTICE file distributed with this work for additional information regarding
+# copyright ownership. The Modin Development Team licenses this file to you under the
+# Apache License, Version 2.0 (the "License"); you may not use this file except in
+# compliance with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software distributed under
+# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific language
+# governing permissions and limitations under the License.
+
+import modin.pandas as pd
+from matplotlib.collections import Collection
+
+
+def test_pandas_indexing():
+ # Should not fail break when faced with a
+ # non-zero indexed series
+ index = [11, 12, 13]
+ ec = fc = pd.Series(["red", "blue", "green"], index=index)
+ lw = pd.Series([1, 2, 3], index=index)
+ ls = pd.Series(["solid", "dashed", "dashdot"], index=index)
+ aa = pd.Series([True, False, True], index=index)
+
+ Collection(edgecolors=ec)
+ Collection(facecolors=fc)
+ Collection(linewidths=lw)
+ Collection(linestyles=ls)
+ Collection(antialiaseds=aa)

modin/pandas/test/interoperability/matplotlib/test_colors.py

@@ -0,0 +1,27 @@
+# Licensed to Modin Development Team under one or more contributor license agreements.
+# See the NOTICE file distributed with this work for additional information regarding
+# copyright ownership. The Modin Development Team licenses this file to you under the
+# Apache License, Version 2.0 (the "License"); you may not use this file except in
+# compliance with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software distributed under
+# the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
+# ANY KIND, either express or implied. See the License for the specific language
+# governing permissions and limitations under the License.
+
+from numpy.testing import assert_array_equal
+import matplotlib.colors as mcolors
+import modin.pandas as pd
+
+
+def test_pandas_iterable():
+ # Using a list or series yields equivalent
+ # colormaps, i.e the series isn't seen as
+ # a single color
+ lst = ["red", "blue", "green"]
+ s = pd.Series(lst)
+ cm1 = mcolors.ListedColormap(lst, N=5)
+ cm2 = mcolors.ListedColormap(s, N=5)
+ assert_array_equal(cm1.colors, cm2.colors)