wehub-resource-sync
104 lines
3.1 KiB
Python
104 lines
3.1 KiB
Python
import matplotlib.pyplot as plt
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import numpy as np
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import pytest
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import shap
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from shap.utils._exceptions import DimensionError
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def test_violin_with_invalid_plot_type():
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with pytest.raises(ValueError, match="plot_type: Expected one of "):
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shap.plots.violin(np.random.randn(20, 5), plot_type="nonsense")
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def test_violin_wrong_features_shape():
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"""Checks that DimensionError is raised if the features data matrix
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has an incompatible shape with the shap_values matrix.
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"""
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rs = np.random.RandomState(42)
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emsg = (
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"The shape of the shap_values matrix does not match the shape of "
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"the provided data matrix. Perhaps the extra column"
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)
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with pytest.raises(DimensionError, match=emsg):
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expln = shap.Explanation(
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values=rs.randn(20, 5),
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data=rs.randn(20, 4),
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)
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shap.plots.violin(expln, show=False)
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# legacy API
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with pytest.raises(DimensionError, match=emsg):
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shap.plots.violin(
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shap_values=rs.randn(20, 5),
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features=rs.randn(20, 4),
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show=False,
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)
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emsg = "The shape of the shap_values matrix does not match the shape of the provided data matrix."
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with pytest.raises(DimensionError, match=emsg):
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expln = shap.Explanation(
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values=rs.randn(20, 5),
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data=rs.randn(20, 1),
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)
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shap.plots.violin(expln, show=False)
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# legacy API
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with pytest.raises(DimensionError, match=emsg):
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shap.plots.violin(
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shap_values=rs.randn(20, 5),
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features=rs.randn(20, 1),
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show=False,
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)
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@pytest.mark.mpl_image_compare
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def test_violin(explainer):
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"""Make sure the violin plot is unchanged."""
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fig = plt.figure()
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shap_values = explainer.shap_values(explainer.data)
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shap.plots.violin(shap_values, show=False)
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plt.tight_layout()
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return fig
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# FIXME: remove once we migrate violin completely to the Explanation object
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# ------ "legacy" violin plots -------
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# Currently using the same files as the `test_summary.py` violin tests for comparison
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@pytest.mark.mpl_image_compare(
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filename="test_summary_violin_with_data.png",
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tolerance=5,
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)
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def test_summary_violin_with_data2():
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"""Check a violin chart with shap_values as a np.array."""
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rs = np.random.RandomState(0)
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fig = plt.figure()
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shap.plots.violin(
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rs.standard_normal(size=(20, 5)),
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rs.standard_normal(size=(20, 5)),
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plot_type="violin",
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show=False,
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)
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fig.set_layout_engine("tight")
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return fig
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# Currently using the same files as the `test_summary.py` violin tests for comparison
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@pytest.mark.mpl_image_compare(
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filename="test_summary_layered_violin_with_data.png",
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tolerance=5,
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)
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def test_summary_layered_violin_with_data2():
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"""Check a layered violin chart with shap_values as a np.array."""
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rs = np.random.RandomState(0)
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fig = plt.figure()
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shap_values = rs.randn(200, 5)
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feats = rs.randn(200, 5)
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shap.plots.violin(
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shap_values,
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feats,
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plot_type="layered_violin",
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show=False,
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)
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fig.set_layout_engine("tight")
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return fig
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