From 83a1bc1fb6124a35d515f4836d2e830f3dbdf0e7 Mon Sep 17 00:00:00 2001 From: Marc Glisse Date: Sun, 12 Apr 2020 21:57:51 +0200 Subject: Parallelize the "precomputed" case of knn It is supposed to be possible to compile numpy with openmp, but it looks like it isn't done in any of the usual packages. It may be possible to refactor that code so there is less redundancy. --- src/python/test/test_knn.py | 8 ++++++++ 1 file changed, 8 insertions(+) (limited to 'src/python/test/test_knn.py') diff --git a/src/python/test/test_knn.py b/src/python/test/test_knn.py index 6aac2006..6269df54 100755 --- a/src/python/test/test_knn.py +++ b/src/python/test/test_knn.py @@ -52,6 +52,14 @@ def test_knn_explicit(): r = knn.fit_transform(dist) assert np.array_equal(r[0], [[0, 1], [1, 0], [2, 0]]) assert np.array_equal(r[1], [[0, 3], [0, 1], [0, 1]]) + # Second time in parallel + knn = KNearestNeighbors(2, metric="precomputed", return_index=True, return_distance=False, n_jobs=2) + r = knn.fit_transform(dist) + assert np.array_equal(r, [[0, 1], [1, 0], [2, 0]]) + knn = KNearestNeighbors(2, metric="precomputed", return_index=True, return_distance=True, n_jobs=2) + r = knn.fit_transform(dist) + assert np.array_equal(r[0], [[0, 1], [1, 0], [2, 0]]) + assert np.array_equal(r[1], [[0, 3], [0, 1], [0, 1]]) def test_knn_compare(): -- cgit v1.2.3