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author | Hind-M <hind.montassif@gmail.com> | 2021-11-09 16:08:10 +0100 |
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committer | Hind-M <hind.montassif@gmail.com> | 2021-11-09 16:08:10 +0100 |
commit | fe75d33d715d038e348b7e48512b14c7488ee4f4 (patch) | |
tree | e4609c839f4ad17f083c4a48370b74297735d64a /src/python/gudhi/datasets/generators/points.py | |
parent | cfb60a50a7c3aea08abc41118fbfdf31061a44a4 (diff) |
Remove sphinx warnings for torus
Diffstat (limited to 'src/python/gudhi/datasets/generators/points.py')
-rw-r--r-- | src/python/gudhi/datasets/generators/points.py | 5 |
1 files changed, 1 insertions, 4 deletions
diff --git a/src/python/gudhi/datasets/generators/points.py b/src/python/gudhi/datasets/generators/points.py index cf97777d..481f3f71 100644 --- a/src/python/gudhi/datasets/generators/points.py +++ b/src/python/gudhi/datasets/generators/points.py @@ -41,10 +41,7 @@ def torus(n_samples, dim, sample='random'): :param n_samples: The number of points to be generated. :param dim: The dimension of the torus on which points would be generated in R^2*dim. :param sample: The sample type of the generated points. Can be 'random' or 'grid'. - :returns: numpy array containing the generated points on a torus. - The shape of returned numpy array is: - if sample is 'random' : (n_samples, 2*dim). - if sample is 'grid' : (⌊n_samples**(1./dim)⌋**dim, 2*dim), where shape[0] is rounded down to the closest perfect 'dim'th power. + :returns: numpy array containing the generated points on a torus. The shape of returned numpy array is: If sample is 'random': (n_samples, 2*dim). If sample is 'grid': (⌊n_samples**(1./dim)⌋**dim, 2*dim), where shape[0] is rounded down to the closest perfect 'dim'th power. """ if sample == 'random': # Generate points randomly |