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| author | wreise <wojciech.reise@epfl.ch> | 2022-10-15 18:45:42 +0200 |
|---|---|---|
| committer | wreise <wojciech.reise@epfl.ch> | 2022-10-15 18:45:42 +0200 |
| commit | cd7dea8627f4b1c624e88d5ff28b32d1602f5e39 (patch) | |
| tree | f7602049d89cfec1f3511f4875823a7d85a20e93 | |
| parent | 74617f0673aa13bce47833c366321a8838a7d123 (diff) | |
Treat the case when there are less points than landscape layers
| -rw-r--r-- | src/python/gudhi/representations/vector_methods.py | 13 |
1 files changed, 7 insertions, 6 deletions
diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index 6267e077..a169aee8 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -179,14 +179,15 @@ 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] - 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: - landscapes = np.concatenate([ - landscapes, np.zeros((self.num_landscapes-n_points, *landscapes.shape[1:])) - ], axis=0) + tent_functions = np.concatenate( + [tent_functions, np.zeros((tent_functions.shape[0], self.num_landscapes-n_points))], + axis=1 + ) + tent_functions.partition(tent_functions.shape[1]-self.num_landscapes, axis=1) + landscapes = np.sort(tent_functions[:, -self.num_landscapes:], axis=1)[:, ::-1].T + landscapes = np.sqrt(2) * np.ravel(landscapes) Xfit.append(landscapes) |