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| author | Marc Glisse <marc.glisse@inria.fr> | 2020-03-27 13:43:58 +0100 |
|---|---|---|
| committer | Marc Glisse <marc.glisse@inria.fr> | 2020-03-27 13:43:58 +0100 |
| commit | f74c71ca8e474ff927cae029ea63329d30293582 (patch) | |
| tree | 4696a751c330e2c5a4bc710c28ba72bcee0579f6 /src/python/gudhi/point_cloud | |
| parent | af35ea5b4ce631ae826f1db1940798f254aba658 (diff) | |
Improve coverage
Diffstat (limited to 'src/python/gudhi/point_cloud')
| -rw-r--r-- | src/python/gudhi/point_cloud/dtm.py | 2 |
1 files changed, 2 insertions, 0 deletions
diff --git a/src/python/gudhi/point_cloud/dtm.py b/src/python/gudhi/point_cloud/dtm.py index 839e7452..541b74a6 100644 --- a/src/python/gudhi/point_cloud/dtm.py +++ b/src/python/gudhi/point_cloud/dtm.py @@ -30,6 +30,8 @@ class DTM: X (numpy.array): coordinates for mass points """ if self.params.setdefault("metric", "euclidean") != "neighbors": + # KNN gives sorted distances, which is unnecessary here. + # Maybe add a parameter to say we don't need sorting? self.knn = KNN(self.k, return_index=False, return_distance=True, **self.params) self.knn.fit(X) return self |