wehub-resource-sync
96 lines
2.8 KiB
Python
96 lines
2.8 KiB
Python
"""Unit tests for the ActionOptimizer."""
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import numpy as np
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import pandas as pd
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import pytest
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import shap
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from shap.utils._exceptions import ConvergenceError, InvalidAction
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def create_basic_scenario():
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X = pd.DataFrame({"feature1": np.ones(5), "feature2": np.ones(5), "feature3": np.ones(5)})
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class IncreaseFeature1(shap.actions.Action):
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"""Sample action."""
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def __init__(self, amount):
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self.amount = amount
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self.cost = 5 * amount
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def __call__(self, X):
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X["feature1"] += self.amount
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def __str__(self):
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return f"Improve feature1 by {self.amount}."
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class IncreaseFeature2(shap.actions.Action):
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"""Sample action."""
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def __init__(self, amount):
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self.amount = amount
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self.cost = 3 * amount
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def __call__(self, X):
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X["feature2"] += self.amount
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def __str__(self):
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return f"Improve feature2 by {self.amount}."
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class IncreaseFeature3(shap.actions.Action):
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"""Sample action."""
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def __init__(self, amount):
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self.amount = amount
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self.cost = 4 * amount
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def __call__(self, X):
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X["feature3"] += self.amount
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def __str__(self):
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return f"Improve feature3 by {self.amount}."
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def passed(x):
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return np.sum(x) > 10
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return X, IncreaseFeature1, IncreaseFeature2, IncreaseFeature3, passed
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def test_basic_run():
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X, IncreaseFeature1, IncreaseFeature2, IncreaseFeature3, passed = create_basic_scenario()
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possible_actions = [
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[IncreaseFeature1(i) for i in range(1, 10)],
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IncreaseFeature2(5),
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[IncreaseFeature3(i) for i in range(1, 20)],
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]
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optimizer = shap.ActionOptimizer(passed, possible_actions)
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actions = optimizer(X.iloc[0])
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assert len(actions) == 2
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assert sum(a.cost for a in actions) == 27 # ensure we got the optimal answer
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def test_too_few_evals():
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X, IncreaseFeature1, IncreaseFeature2, IncreaseFeature3, passed = create_basic_scenario()
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possible_actions = [
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[IncreaseFeature1(i) for i in range(1, 10)],
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IncreaseFeature2(5),
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[IncreaseFeature3(i) for i in range(1, 20)],
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]
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optimizer = shap.ActionOptimizer(passed, possible_actions)
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with pytest.raises(ConvergenceError):
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optimizer(X.iloc[0], max_evals=3)
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def test_run_out_of_group():
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X, IncreaseFeature1, IncreaseFeature2, IncreaseFeature3, passed = create_basic_scenario()
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possible_actions = [[IncreaseFeature1(i) for i in range(1, 10)], IncreaseFeature2(5), [IncreaseFeature3(1)]]
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optimizer = shap.ActionOptimizer(passed, possible_actions)
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actions = optimizer(X.iloc[0])
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print(actions)
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assert len(actions) == 3
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def test_bad_action():
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with pytest.raises(InvalidAction):
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shap.ActionOptimizer(None, [None]) # type: ignore
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