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| author | wreise <wojciech.reise@epfl.ch> | 2022-10-15 17:00:25 +0200 |
|---|---|---|
| committer | wreise <wojciech.reise@epfl.ch> | 2022-10-15 17:00:25 +0200 |
| commit | 74617f0673aa13bce47833c366321a8838a7d123 (patch) | |
| tree | ad04bc8a575d6aeeeae1eaa83f3da0d6c2dbb2ad | |
| parent | 80edbbaccc344abfa18ebc48a8493f747a775476 (diff) | |
Remove old lines
| -rw-r--r-- | src/python/gudhi/representations/vector_methods.py | 6 |
1 files changed, 2 insertions, 4 deletions
diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index 3a91eccd..6267e077 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -179,10 +179,8 @@ class Landscape(BaseEstimator, TransformerMixin): midpoints, heights = (diag[:, 0] + diag[:, 1]) / 2., (diag[:, 1] - diag[:, 0]) / 2. tent_functions = np.maximum(heights[None, :] - np.abs(x_values[:, None] - midpoints[None, :]), 0) n_points = diag.shape[0] - # Get indices of largest elements: can't take more than n_points - 1 (the last ones are in the right position) - argpartition = np.argpartition(-tent_functions, min(self.num_landscapes, n_points-1), axis=1) - landscapes = np.take_along_axis(tent_functions, argpartition, axis=1) - landscapes = landscapes[:, :min(self.num_landscapes, n_points)].T + tent_functions.partition(n_points-self.num_landscapes, axis=1) + landscapes = np.sort(tent_functions[:, -self.num_landscapes:], axis=1)[:, ::-1].T # Complete the array with zeros to get the right number of landscapes if self.num_landscapes > n_points: |