61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
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"""Test kddcup99 loader, if the data is available,
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or if specifically requested via environment variable
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(e.g. for travis cron job).
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Only 'percent10' mode is tested, as the full data
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is too big to use in unit-testing.
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"""
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from functools import partial
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import pytest
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from sklearn.datasets.tests.test_common import check_as_frame
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from sklearn.datasets.tests.test_common import check_pandas_dependency_message
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from sklearn.datasets.tests.test_common import check_return_X_y
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@pytest.mark.parametrize("as_frame", [True, False])
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@pytest.mark.parametrize(
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"subset, n_samples, n_features",
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[(None, 494021, 41),
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("SA", 100655, 41),
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("SF", 73237, 4),
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("http", 58725, 3),
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("smtp", 9571, 3)]
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)
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def test_fetch_kddcup99_percent10(
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fetch_kddcup99_fxt, as_frame, subset, n_samples, n_features
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):
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data = fetch_kddcup99_fxt(subset=subset, as_frame=as_frame)
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assert data.data.shape == (n_samples, n_features)
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assert data.target.shape == (n_samples,)
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if as_frame:
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assert data.frame.shape == (n_samples, n_features + 1)
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def test_fetch_kddcup99_return_X_y(fetch_kddcup99_fxt):
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fetch_func = partial(fetch_kddcup99_fxt, subset='smtp')
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data = fetch_func()
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check_return_X_y(data, fetch_func)
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def test_fetch_kddcup99_as_frame(fetch_kddcup99_fxt):
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bunch = fetch_kddcup99_fxt()
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check_as_frame(bunch, fetch_kddcup99_fxt)
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def test_fetch_kddcup99_shuffle(fetch_kddcup99_fxt):
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dataset = fetch_kddcup99_fxt(
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random_state=0, subset='SA', percent10=True,
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)
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dataset_shuffled = fetch_kddcup99_fxt(
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random_state=0, subset='SA', shuffle=True, percent10=True,
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)
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assert set(dataset['target']) == set(dataset_shuffled['target'])
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assert dataset_shuffled.data.shape == dataset.data.shape
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assert dataset_shuffled.target.shape == dataset.target.shape
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def test_pandas_dependency_message(fetch_kddcup99_fxt, hide_available_pandas):
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check_pandas_dependency_message(fetch_kddcup99_fxt)
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