49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
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import pytest
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import numpy as np
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from sklearn.impute._base import _BaseImputer
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@pytest.fixture
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def data():
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X = np.random.randn(10, 2)
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X[::2] = np.nan
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return X
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class NoFitIndicatorImputer(_BaseImputer):
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def fit(self, X, y=None):
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return self
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def transform(self, X, y=None):
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return self._concatenate_indicator(X, self._transform_indicator(X))
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class NoTransformIndicatorImputer(_BaseImputer):
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def fit(self, X, y=None):
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super()._fit_indicator(X)
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return self
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def transform(self, X, y=None):
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return self._concatenate_indicator(X, None)
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def test_base_imputer_not_fit(data):
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imputer = NoFitIndicatorImputer(add_indicator=True)
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err_msg = "Make sure to call _fit_indicator before _transform_indicator"
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with pytest.raises(ValueError, match=err_msg):
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imputer.fit(data).transform(data)
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with pytest.raises(ValueError, match=err_msg):
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imputer.fit_transform(data)
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def test_base_imputer_not_transform(data):
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imputer = NoTransformIndicatorImputer(add_indicator=True)
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err_msg = ("Call _fit_indicator and _transform_indicator in the "
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"imputer implementation")
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with pytest.raises(ValueError, match=err_msg):
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imputer.fit(data).transform(data)
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with pytest.raises(ValueError, match=err_msg):
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imputer.fit_transform(data)
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