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# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
# Author(s): Hind Montassif
#
# Copyright (C) 2021 Inria
#
# Modification(s):
# - YYYY/MM Author: Description of the modification
import numpy as np
import math
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)
# 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)
return array_points
def generate_grid_points(num_points, dim):
num_points_grid = (int(num_points**(1./dim)))**dim
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)
return array_points
def generate_points(num_points, dim, sample='random'):
if sample == 'random':
print("Sample is random")
npoints = num_points
elif sample == 'grid':
print("Sample is grid")
npoints = (int(num_points**(1./dim)))**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
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