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| author | Marc Glisse <marc.glisse@inria.fr> | 2020-05-19 20:16:32 +0200 |
|---|---|---|
| committer | Marc Glisse <marc.glisse@inria.fr> | 2020-05-19 20:16:32 +0200 |
| commit | bee990ed74dec6d3257b89e1fcceb24b089d5c00 (patch) | |
| tree | e2b01279ff738b67e5c21f38a044d143e36e719f /src/python/gudhi | |
| parent | fe8c35e2716eca9d88e33133c64f5c2121535539 (diff) | |
long line
Diffstat (limited to 'src/python/gudhi')
| -rw-r--r-- | src/python/gudhi/point_cloud/dtm.py | 5 |
1 files changed, 3 insertions, 2 deletions
diff --git a/src/python/gudhi/point_cloud/dtm.py b/src/python/gudhi/point_cloud/dtm.py index d836c28d..55ac58e6 100644 --- a/src/python/gudhi/point_cloud/dtm.py +++ b/src/python/gudhi/point_cloud/dtm.py @@ -95,8 +95,9 @@ class DTMDensity: Only available for the Euclidean metric, defaults to False. n_samples (int): number of sample points used for fitting. Only needed if `normalize` is True and metric is "neighbors". - kwargs: same parameters as :class:`~gudhi.point_cloud.knn.KNearestNeighbors`, except that metric="neighbors" means that - :func:`transform` expects an array with the distances to the k nearest neighbors. + kwargs: same parameters as :class:`~gudhi.point_cloud.knn.KNearestNeighbors`, except that + metric="neighbors" means that :func:`transform` expects an array with the distances to + the k nearest neighbors. """ if weights is None: self.k = k |