44 lines
1.7 KiB
Python
44 lines
1.7 KiB
Python
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"""Test loaders for common functionality.
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"""
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import pytest
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import numpy as np
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def check_pandas_dependency_message(fetch_func):
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try:
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import pandas # noqa
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pytest.skip("This test requires pandas to be not installed")
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except ImportError:
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# Check that pandas is imported lazily and that an informative error
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# message is raised when pandas is missing:
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expected_msg = ('{} with as_frame=True requires pandas'
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.format(fetch_func.__name__))
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with pytest.raises(ImportError, match=expected_msg):
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fetch_func(as_frame=True)
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def check_return_X_y(bunch, fetch_func_partial):
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X_y_tuple = fetch_func_partial(return_X_y=True)
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assert isinstance(X_y_tuple, tuple)
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assert X_y_tuple[0].shape == bunch.data.shape
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assert X_y_tuple[1].shape == bunch.target.shape
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def check_as_frame(bunch, fetch_func_partial,
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expected_data_dtype=None, expected_target_dtype=None):
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pd = pytest.importorskip('pandas')
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frame_bunch = fetch_func_partial(as_frame=True)
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assert hasattr(frame_bunch, 'frame')
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assert isinstance(frame_bunch.frame, pd.DataFrame)
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assert isinstance(frame_bunch.data, pd.DataFrame)
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assert frame_bunch.data.shape == bunch.data.shape
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if frame_bunch.target.ndim > 1:
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assert isinstance(frame_bunch.target, pd.DataFrame)
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else:
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assert isinstance(frame_bunch.target, pd.Series)
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assert frame_bunch.target.shape[0] == bunch.target.shape[0]
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if expected_data_dtype is not None:
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assert np.all(frame_bunch.data.dtypes == expected_data_dtype)
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if expected_target_dtype is not None:
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assert np.all(frame_bunch.target.dtypes == expected_target_dtype)
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