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| author | MathieuCarriere <mathieu.carriere3@gmail.com> | 2020-04-29 19:16:50 -0400 |
|---|---|---|
| committer | MathieuCarriere <mathieu.carriere3@gmail.com> | 2020-04-29 19:16:50 -0400 |
| commit | b2177e897b575e0c8d17b8ae5ed3259541a06bea (patch) | |
| tree | e51227c643de04061a27043fab86fe93b7a31e4a /src/python/gudhi/representations/kernel_methods.py | |
| parent | e7e885f707acde12bfbf632e4275048534a2023f (diff) | |
small modifs
Diffstat (limited to 'src/python/gudhi/representations/kernel_methods.py')
| -rw-r--r-- | src/python/gudhi/representations/kernel_methods.py | 3 |
1 files changed, 2 insertions, 1 deletions
diff --git a/src/python/gudhi/representations/kernel_methods.py b/src/python/gudhi/representations/kernel_methods.py index edd1382a..596f4f07 100644 --- a/src/python/gudhi/representations/kernel_methods.py +++ b/src/python/gudhi/representations/kernel_methods.py @@ -67,7 +67,8 @@ def pairwise_persistence_diagram_kernels(X, Y=None, kernel="sliced_wasserstein", Parameters: X (list of n numpy arrays of shape (numx2)): first list of persistence diagrams. Y (list of m numpy arrays of shape (numx2)): second list of persistence diagrams (optional). If None, pairwise kernel values are computed from the first list only. - kernel: kernel to use. It can be either a string ("sliced_wasserstein", "persistence_scale_space", "persistence_weighted_gaussian", "persistence_fisher") or a function taking two numpy arrays of shape (nx2) and (mx2) as inputs. + kernel: kernel to use. It can be either a string ("sliced_wasserstein", "persistence_scale_space", "persistence_weighted_gaussian", "persistence_fisher") or a function taking two numpy arrays of shape (nx2) and (mx2) as inputs. If it is a function, make sure that it is symmetric. + **kwargs: optional keyword parameters. Any further parameters are passed directly to the kernel function. See the docs of the various kernel classes in this module. Returns: numpy array of shape (nxm): kernel matrix. |