8000 Revert "[MRG] set blockwise diagonals to zero for euclidean distance … · xhluca/scikit-learn@aa7f911 · GitHub
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Revert "[MRG] set blockwise diagonals to zero for euclidean distance (scikit-learn#12612)"
This reverts commit 5a3ea57.
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‎doc/whats_new/v0.20.rst

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@@ -120,10 +120,6 @@ Changelog
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set to "euclidean". :issue:`12481` by
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:user:`Jérémie du Boisberranger <jeremiedbb>`.
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- |Fix| Fixed a bug in :func:`metrics.pairwise.pairwise_distances_chunked`
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which didn't ensure the diagonal is zero for euclidean distances.
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:issue:`12612` by :user:`Andreas Müller <amueller>`.
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- |API| The :func:`metrics.calinski_harabaz_score` has been renamed to
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:func:`metrics.calinski_harabasz_score` and will be removed in version 0.23.
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:issue:`12211` by :user:`Lisa Thomas <LisaThomas9>`,

‎sklearn/metrics/pairwise.py

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@@ -1271,12 +1271,6 @@ def pairwise_distances_chunked(X, Y=None, reduce_func=None,
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X_chunk = X[sl]
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D_chunk = pairwise_distances(X_chunk, Y, metric=metric,
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n_jobs=n_jobs, **kwds)
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if ((X is Y or Y is None)
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and PAIRWISE_DISTANCE_FUNCTIONS.get(metric, None)
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is euclidean_distances):
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# zeroing diagonal, taking care of aliases of "euclidean",
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# i.e. "l2"
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D_chunk.flat[sl.start::_num_samples(X) + 1] = 0
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if reduce_func is not None:
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chunk_size = D_chunk.shape[0]
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D_chunk = reduce_func(D_chunk, sl.start)

‎sklearn/metrics/tests/test_pairwise.py

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@@ -473,7 +473,7 @@ def check_pairwise_distances_chunked(X, Y, working_memory, metric='euclidean'):
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metric=metric)
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assert isinstance(gen, GeneratorType)
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blockwise_distances = list(gen)
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Y = X if Y is None else Y
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Y = np.array(X if Y is None else Y)
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min_block_mib = len(Y) * 8 * 2 ** -20
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for block in blockwise_distances:
@@ -485,18 +485,6 @@ def check_pairwise_distances_chunked(X, Y, working_memory, metric='euclidean'):
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assert_array_almost_equal(blockwise_distances, S)
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@pytest.mark.parametrize(
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'metric',
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('euclidean', 'l2', 'sqeuclidean'))
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def test_pairwise_distances_chunked_diagonal(metric):
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rng = np.random.RandomState(0)
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X = rng.normal(size=(1000, 10), scale=1e10)
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chunks = list(pairwise_distances_chunked(X, working_memory=1,
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metric=metric))
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assert len(chunks) > 1
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assert_array_almost_equal(np.diag(np.vstack(chunks)), 0, decimal=10)
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@ignore_warnings
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def test_pairwise_distances_chunked():
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# Test the pairwise_distance helper function.

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