From 9ea9ae8f72c26dbe37319168cfce64afa01d0fd9 Mon Sep 17 00:00:00 2001 From: Marc Glisse Date: Thu, 5 Nov 2020 01:00:56 +0100 Subject: More numpy in BettiCurve suggested by @raphaeltinarrage --- src/python/gudhi/representations/vector_methods.py | 17 +++++------------ 1 file changed, 5 insertions(+), 12 deletions(-) diff --git a/src/python/gudhi/representations/vector_methods.py b/src/python/gudhi/representations/vector_methods.py index 5ca127f6..6a1f61ef 100644 --- a/src/python/gudhi/representations/vector_methods.py +++ b/src/python/gudhi/representations/vector_methods.py @@ -323,22 +323,15 @@ class BettiCurve(BaseEstimator, TransformerMixin): Returns: numpy array with shape (number of diagrams) x (**resolution**): output Betti curves. """ - num_diag, Xfit = len(X), [] + Xfit = [] x_values = np.linspace(self.sample_range[0], self.sample_range[1], self.resolution) step_x = x_values[1] - x_values[0] - for i in range(num_diag): - - diagram, num_pts_in_diag = X[i], X[i].shape[0] - + for diagram in X: + diagram_int = np.clip(np.ceil((diagram[:,:2] - self.sample_range[0]) / step_x).astype(int), 0, self.resolution) bc = np.zeros(self.resolution) - 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) - max_idx = np.clip(np.ceil((py - self.sample_range[0]) / step_x).astype(int), 0, self.resolution) - for k in range(min_idx, max_idx): - bc[k] += 1 - + for interval in diagram_int: + bc[interval[0]:interval[1]] += 1 Xfit.append(np.reshape(bc,[1,-1])) Xfit = np.concatenate(Xfit, 0) -- cgit v1.2.3