Use PI constant from numpy instead of math

Modify grid points generation incorrect formula

1 files changed, 10 insertions, 20 deletions

diff --git a/src/python/gudhi/datasets/generators/points/torus.py b/src/python/gudhi/datasets/generators/points/torus.py
index 2de696b2..5a2b9016 100644
--- a/src/python/gudhi/datasets/generators/points/torus.py
+++ b/src/python/gudhi/datasets/generators/points/torus.py
@@ -8,45 +8,35 @@
 #   - YYYY/MM Author: Description of the modification
 
 import numpy as np
-import math
-
+import itertools
 
 def generate_random_points(num_points, dim):
 
     # Generate random angles of size num_points*dim
-    alpha = 2*math.pi*np.random.rand(num_points*dim)
+    alpha = 2*np.pi*np.random.rand(num_points*dim)
 
-    # Based on angles, construct points of size num_points*dim on a circle and reshape the result in a num_points*2*dim array
-    array_points = np.asarray([[np.cos(a), np.sin(a)] for a in alpha]).ravel().reshape(num_points, 2*dim)
+    # Based on angles, construct points of size num_points*dim on a circle and reshape the result in a num_points*2*dim array    
+    array_points = np.column_stack([np.cos(alpha), np.sin(alpha)]).reshape(-1, 2*dim)
     
     return array_points
 
-
 def generate_grid_points(num_points, dim):
     
-    num_points_grid = (int(num_points**(1./dim)))**dim
+    num_points_grid = int(num_points**(1./dim))
+    alpha = np.linspace(0, 2*np.pi, num_points_grid, endpoint=False)
     
-    alpha = 2*math.pi*np.random.rand(num_points_grid*dim)
-    
-    array_points = np.asarray([[np.cos(a), np.sin(a)] for a in alpha]).ravel().reshape(num_points_grid, 2*dim)
+    array_points_inter = np.column_stack([np.cos(alpha), np.sin(alpha)])
+    array_points = np.array(list(itertools.product(array_points_inter, repeat=dim))).reshape(-1, 2*dim)
     
     return array_points
 
 def generate_points(num_points, dim, sample='random'):
     if sample == 'random':
         print("Sample is random")
-        npoints = num_points
+        generate_random_points(num_points, dim)
     elif sample == 'grid':
         print("Sample is grid")
-        npoints = (int(num_points**(1./dim)))**dim
+        generate_grid_points(num_points, dim)
     else:
         print("Sample type '{}' is not supported".format(sample))
         return
-    
-    # Generate random angles of size num_points*dim
-    alpha = 2*math.pi*np.random.rand(npoints*dim)
-    
-    # Based on angles, construct points of size num_points*dim on a circle and reshape the result in a num_points*2*dim array
-    array_points = np.asarray([[np.cos(a), np.sin(a)] for a in alpha]).ravel().reshape(npoints, 2*dim)
-    
-    return array_points