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Merged
merged 2 commits into from
Apr 25, 2019
Merged

new tests for mean_shift algo #13179

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dea8840
new tests for mean_shift algo
rajdeepd Feb 17, 2019
aa17ea1
Merge remote-tracking branch 'upstream/master' into test_mean_shift
rajdeepd Apr 1, 2019
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4 changes: 2 additions & 2 deletions sklearn/cluster/mean_shift_.py
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Original file line number Diff line number Diff line change
Expand Up @@ -183,8 +183,8 @@ def mean_shift(X, bandwidth=None, seeds=None, bin_seeding=False,
if bandwidth is None:
bandwidth = estimate_bandwidth(X, n_jobs=n_jobs)
elif bandwidth <= 0:
raise ValueError("bandwidth needs to be greater than zero or None,\
got %f" % bandwidth)
raise ValueError("bandwidth needs to be greater than zero or None,"
" got %f" % bandwidth)
if seeds is None:
if bin_seeding:
seeds = get_bin_seeds(X, bandwidth, min_bin_freq)
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34 changes: 23 additions & 11 deletions sklearn/cluster/tests/test_mean_shift.py
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Expand Up @@ -5,10 +5,10 @@

import numpy as np
import warnings
import pytest

from scipy import sparse

from sklearn.utils.testing import assert_equal
from sklearn.utils.testing import assert_array_equal
from sklearn.utils.testing import assert_array_almost_equal
from sklearn.utils.testing import assert_raise_message
Expand Down Expand Up @@ -36,23 +36,35 @@ def test_estimate_bandwidth_1sample():
# Test estimate_bandwidth when n_samples=1 and quantile<1, so that
# n_neighbors is set to 1.
bandwidth = estimate_bandwidth(X, n_samples=1, quantile=0.3)
assert_array_almost_equal(bandwidth, 0., decimal=5)
assert bandwidth == 0.


def test_mean_shift():
@pytest.mark.parametrize("bandwidth, cluster_all, expected, "
"first_cluster_label",
[(1.2, True, 3, 0), (1.2, False, 4, -1)])
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Much clearer, thanks!

def test_mean_shift(bandwidth, cluster_all, expected, first_cluster_label):
# Test MeanShift algorithm
bandwidth = 1.2

ms = MeanShift(bandwidth=bandwidth)
ms = MeanShift(bandwidth=bandwidth, cluster_all=cluster_all)
labels = ms.fit(X).labels_
labels_unique = np.unique(labels)
n_clusters_ = len(labels_unique)
assert_equal(n_clusters_, n_clusters)
assert n_clusters_ == expected
assert labels_unique[0] == first_cluster_label

cluster_centers, labels = mean_shift(X, bandwidth=bandwidth)
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Removing this means we are not testing the mean_shift function directly anymore.

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we are testing using
ms = MeanShift(bandwidth=bandwidth, cluster_all=cluster_all)
labels = ms.fit(X).labels_

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The testing of mean_shift should be independent of ms.fit. At the moment, ms.fit calls mean_shift, but we do not know how the code base will change.

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@thomasjpfan do we need another test for mean_shift?

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Leaving the original test here will sufficiently test mean_shift.

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@thomasjpfan added test for mean_shift as well

labels_unique = np.unique(labels)
n_clusters_ = len(labels_unique)
assert_equal(n_clusters_, n_clusters)
cluster_centers, labels_mean_shift = mean_shift(X, cluster_all=cluster_all)
labels_mean_shift_unique = np.unique(labels_mean_shift)
n_clusters_mean_shift = len(labels_mean_shift_unique)
assert n_clusters_mean_shift == expected
assert labels_mean_shift_unique[0] == first_cluster_label


def test_mean_shift_negative_bandwidth():
bandwidth = -1
ms = MeanShift(bandwidth=bandwidth)
msg = (r"bandwidth needs to be greater than zero or None,"
r" got -1\.000000")
with pytest.raises(ValueError, match=msg):
ms.fit(X)


def test_estimate_bandwidth_with_sparse_matrix():
Expand Down