From 5c140bbdae08561ce69f0cc05841eb1467aa8eab Mon Sep 17 00:00:00 2001 From: Hind Montassif Date: Fri, 7 May 2021 15:11:24 +0200 Subject: Use PI constant from numpy instead of math Modify grid points generation incorrect formula --- .../gudhi/datasets/generators/points/torus.py | 30 ++++++++-------------- 1 file 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 -- cgit v1.2.3