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author | Marc Glisse <marc.glisse@inria.fr> | 2019-11-14 13:37:08 +0100 |
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committer | Marc Glisse <marc.glisse@inria.fr> | 2019-11-14 13:37:08 +0100 |
commit | 8427713bc748bc040dd696a64d81b3fe6f648a07 (patch) | |
tree | 655d53f6efe979a5b62ecaf9e0320a54e9adb9ff /src/python/gudhi | |
parent | 0fa77a12509ea6d51043569b592bad855f276a45 (diff) |
Remove mentions of the exact sliced Wasserstein (not implemented)
Diffstat (limited to 'src/python/gudhi')
-rw-r--r-- | src/python/gudhi/sktda/kernel_methods.py | 2 | ||||
-rw-r--r-- | src/python/gudhi/sktda/metrics.py | 2 |
2 files changed, 2 insertions, 2 deletions
diff --git a/src/python/gudhi/sktda/kernel_methods.py b/src/python/gudhi/sktda/kernel_methods.py index 24067718..d409accd 100644 --- a/src/python/gudhi/sktda/kernel_methods.py +++ b/src/python/gudhi/sktda/kernel_methods.py @@ -26,7 +26,7 @@ class SlicedWassersteinKernel(BaseEstimator, TransformerMixin): Attributes: bandwidth (double): bandwidth of the Gaussian kernel applied to the sliced Wasserstein distance (default 1.). - num_directions (int): number of lines evenly sampled from [-pi/2,pi/2] in order to approximate and speed up the kernel computation (default 10). If -1, the exact kernel is computed. + num_directions (int): number of lines evenly sampled from [-pi/2,pi/2] in order to approximate and speed up the kernel computation (default 10). """ self.bandwidth = bandwidth self.sw_ = SlicedWassersteinDistance(num_directions=num_directions) diff --git a/src/python/gudhi/sktda/metrics.py b/src/python/gudhi/sktda/metrics.py index b8acf261..f55f553b 100644 --- a/src/python/gudhi/sktda/metrics.py +++ b/src/python/gudhi/sktda/metrics.py @@ -15,7 +15,7 @@ try: USE_GUDHI = True except ImportError: USE_GUDHI = False - print("Gudhi not found: BottleneckDistance will return null matrix, and exact SlicedWassersteinDistance not available") + print("Gudhi built without CGAL: BottleneckDistance will return a null matrix") ############################################# # Metrics ################################### |