diff options
Diffstat (limited to 'src/python/gudhi')
| -rw-r--r-- | src/python/gudhi/representations/vector_methods.py | 14 |
1 files changed, 7 insertions, 7 deletions
diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index 083551a4..cd532275 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -129,19 +129,19 @@ class Landscape(BaseEstimator, TransformerMixin): diagram, num_pts_in_diag = X[i], X[i].shape[0] - ls = np.zeros([self.num_landscapes, self.resolution]) + ls = np.zeros([self.num_landscapes, self.resolution + self.nan_in_range.sum()]) events = [] - for j in range(self.resolution): + for j in range(self.resolution + self.nan_in_range.sum()): events.append([]) for j in range(num_pts_in_diag): [px,py] = diagram[j,:2] - min_idx = np.clip(np.ceil((px - self.sample_range[0]) / step_x).astype(int), 0, self.resolution) - mid_idx = np.clip(np.ceil((0.5*(py+px) - self.sample_range[0]) / step_x).astype(int), 0, self.resolution) - max_idx = np.clip(np.ceil((py - self.sample_range[0]) / step_x).astype(int), 0, self.resolution) + min_idx = np.clip(np.ceil((px - self.sample_range[0]) / step_x).astype(int), 0, self.resolution + self.nan_in_range.sum()) + mid_idx = np.clip(np.ceil((0.5*(py+px) - self.sample_range[0]) / step_x).astype(int), 0, self.resolution + self.nan_in_range.sum()) + max_idx = np.clip(np.ceil((py - self.sample_range[0]) / step_x).astype(int), 0, self.resolution + self.nan_in_range.sum()) - if min_idx < self.resolution and max_idx > 0: + if min_idx < self.resolution + self.nan_in_range.sum() and max_idx > 0: landscape_value = self.sample_range[0] + min_idx * step_x - px for k in range(min_idx, mid_idx): @@ -153,7 +153,7 @@ class Landscape(BaseEstimator, TransformerMixin): events[k].append(landscape_value) landscape_value -= step_x - for j in range(self.resolution): + for j in range(self.resolution + self.nan_in_range.sum()): events[j].sort(reverse=True) for k in range( min(self.num_landscapes, len(events[j])) ): ls[k,j] = events[j][k] |