wehub-resource-sync
75 lines
2.7 KiB
Python
75 lines
2.7 KiB
Python
from typing import Any
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import numpy as np
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import pandas as pd
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import shap
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def test_dependence_one_string_feature():
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"""Test the dependence plot with a string feature."""
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X = _create_sample_dataset(string_features={"Sex"})
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shap.dependence_plot("Sex", np.random.randn(*X.values.shape), X, interaction_index="Age", show=False)
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def test_dependence_two_string_features():
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"""Test the dependence plot with two string features."""
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X = _create_sample_dataset(string_features={"Sex", "Blood group"})
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shap.dependence_plot("Sex", np.random.randn(*X.values.shape), X, interaction_index="Blood group", show=False)
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def test_dependence_one_string_feature_no_interaction():
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"""Test the dependence plot with no interactions."""
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X = _create_sample_dataset(string_features={"Sex"})
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shap.dependence_plot("Sex", np.random.randn(*X.values.shape), X, interaction_index=None, show=False)
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def test_dependence_one_string_feature_auto_interaction():
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"""Test the dependence plot with auto interaction detection."""
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X = _create_sample_dataset(string_features={"Sex"})
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shap.dependence_plot("Sex", np.random.randn(*X.values.shape), X, interaction_index="auto", show=False)
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def test_approximate_interactions():
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"""Test the approximate interaction detector."""
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X_no_string_features = _create_sample_dataset(string_features={})
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X_one_string_feature = _create_sample_dataset(string_features={"Sex"})
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X_two_string_features = _create_sample_dataset(string_features={"Sex", "Blood group"})
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shap_values = np.random.randn(*X_one_string_feature.values.shape)
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interactions_no_features = shap.approximate_interactions(0, shap_values, X_no_string_features)
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interactions_one_string_feature = shap.approximate_interactions(0, shap_values, X_one_string_feature)
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interactions_two_string_feature = shap.approximate_interactions(0, shap_values, X_two_string_features)
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assert (interactions_no_features == interactions_one_string_feature).all()
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assert (interactions_no_features == interactions_two_string_feature).all()
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def _create_sample_dataset(string_features):
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sex_values: list[Any]
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if "Sex" in string_features:
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sex_values = ["Male", "Female", "Male", "Male", "Female", "Female"]
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else:
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sex_values = [0, 1, 0, 0, 1, 1]
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blood_values: list[Any]
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if "Blood group" in string_features:
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blood_values = ["A", "B", "A", "O", "O", "O"]
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else:
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blood_values = [1, 2, 1, 3, 3, 3]
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X = pd.DataFrame(
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{
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"Sex": sex_values,
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"Blood group": blood_values,
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"Age": [10, 15, 28, 3, 84, 56],
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"Height": [130, 170, 185, 40, 150, 164],
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}
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)
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return X
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