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| Current File : //proc/thread-self/root/usr/local/lib/python3.8/dist-packages/sklearn/impute/tests/test_base.py |
import pytest
import numpy as np
from sklearn.impute._base import _BaseImputer
from sklearn.utils._mask import _get_mask
@pytest.fixture
def data():
X = np.random.randn(10, 2)
X[::2] = np.nan
return X
class NoFitIndicatorImputer(_BaseImputer):
def fit(self, X, y=None):
return self
def transform(self, X, y=None):
return self._concatenate_indicator(X, self._transform_indicator(X))
class NoTransformIndicatorImputer(_BaseImputer):
def fit(self, X, y=None):
mask = _get_mask(X, value_to_mask=np.nan)
super()._fit_indicator(mask)
return self
def transform(self, X, y=None):
return self._concatenate_indicator(X, None)
class NoPrecomputedMaskFit(_BaseImputer):
def fit(self, X, y=None):
self._fit_indicator(X)
return self
def transform(self, X):
return self._concatenate_indicator(X, self._transform_indicator(X))
class NoPrecomputedMaskTransform(_BaseImputer):
def fit(self, X, y=None):
mask = _get_mask(X, value_to_mask=np.nan)
self._fit_indicator(mask)
return self
def transform(self, X):
return self._concatenate_indicator(X, self._transform_indicator(X))
def test_base_imputer_not_fit(data):
imputer = NoFitIndicatorImputer(add_indicator=True)
err_msg = "Make sure to call _fit_indicator before _transform_indicator"
with pytest.raises(ValueError, match=err_msg):
imputer.fit(data).transform(data)
with pytest.raises(ValueError, match=err_msg):
imputer.fit_transform(data)
def test_base_imputer_not_transform(data):
imputer = NoTransformIndicatorImputer(add_indicator=True)
err_msg = ("Call _fit_indicator and _transform_indicator in the "
"imputer implementation")
with pytest.raises(ValueError, match=err_msg):
imputer.fit(data).transform(data)
with pytest.raises(ValueError, match=err_msg):
imputer.fit_transform(data)
def test_base_no_precomputed_mask_fit(data):
imputer = NoPrecomputedMaskFit(add_indicator=True)
err_msg = "precomputed is True but the input data is not a mask"
with pytest.raises(ValueError, match=err_msg):
imputer.fit(data)
with pytest.raises(ValueError, match=err_msg):
imputer.fit_transform(data)
def test_base_no_precomputed_mask_transform(data):
imputer = NoPrecomputedMaskTransform(add_indicator=True)
err_msg = "precomputed is True but the input data is not a mask"
imputer.fit(data)
with pytest.raises(ValueError, match=err_msg):
imputer.transform(data)
with pytest.raises(ValueError, match=err_msg):
imputer.fit_transform(data)