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import gudhi
"""This file is part of the Gudhi Library. The Gudhi library
(Geometric Understanding in Higher Dimensions) is a generic C++
library for computational topology.
Author(s): Vincent Rouvreau
Copyright (C) 2016 INRIA
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 INRIA"
__license__ = "GPL v3"
def test_write_off_file_for_tests():
file = open("subsample.off", "w")
file.write("nOFF\n")
file.write("2 7 0 0\n")
file.write("1.0 1.0\n")
file.write("7.0 0.0\n")
file.write("4.0 6.0\n")
file.write("9.0 6.0\n")
file.write("0.0 14.0\n")
file.write("2.0 19.0\n")
file.write("9.0 17.0\n")
file.close()
def test_simple_choose_n_farthest_points_with_a_starting_point():
point_set = [[0,1], [0,0], [1,0], [1,1]]
i = 0
for point in point_set:
# The iteration starts with the given starting point
sub_set = gudhi.choose_n_farthest_points(points = point_set, nb_points = 1, starting_point = i)
assert sub_set[0] == point_set[i]
i = i + 1
# The iteration finds then the farthest
sub_set = gudhi.choose_n_farthest_points(points = point_set, nb_points = 2, starting_point = 1)
assert sub_set[1] == point_set[3]
sub_set = gudhi.choose_n_farthest_points(points = point_set, nb_points = 2, starting_point = 3)
assert sub_set[1] == point_set[1]
sub_set = gudhi.choose_n_farthest_points(points = point_set, nb_points = 2, starting_point = 0)
assert sub_set[1] == point_set[2]
sub_set = gudhi.choose_n_farthest_points(points = point_set, nb_points = 2, starting_point = 2)
assert sub_set[1] == point_set[0]
# Test the limits
assert gudhi.choose_n_farthest_points(points = [], nb_points = 0, starting_point = 0) == []
assert gudhi.choose_n_farthest_points(points = [], nb_points = 1, starting_point = 0) == []
assert gudhi.choose_n_farthest_points(points = [], nb_points = 0, starting_point = 1) == []
assert gudhi.choose_n_farthest_points(points = [], nb_points = 1, starting_point = 1) == []
# From off file test
for i in range (0, 7):
assert len(gudhi.choose_n_farthest_points(off_file = 'subsample.off', nb_points = i, starting_point = i)) == i
def test_simple_choose_n_farthest_points_randomed():
point_set = [[0,1], [0,0], [1,0], [1,1]]
# Test the limits
assert gudhi.choose_n_farthest_points(points = [], nb_points = 0) == []
assert gudhi.choose_n_farthest_points(points = [], nb_points = 1) == []
assert gudhi.choose_n_farthest_points(points = point_set, nb_points = 0) == []
# Go furter than point set on purpose
for iter in range(1,10):
sub_set = gudhi.choose_n_farthest_points(points = point_set, nb_points = iter)
for sub in sub_set:
found = False
for point in point_set:
if point == sub:
found = True
# Check each sub set point is existing in the point set
assert found == True
# From off file test
for i in range (0, 7):
assert len(gudhi.choose_n_farthest_points(off_file = 'subsample.off', nb_points = i)) == i
def test_simple_pick_n_random_points():
point_set = [[0,1], [0,0], [1,0], [1,1]]
# Test the limits
assert gudhi.pick_n_random_points(points = [], nb_points = 0) == []
assert gudhi.pick_n_random_points(points = [], nb_points = 1) == []
assert gudhi.pick_n_random_points(points = point_set, nb_points = 0) == []
# Go furter than point set on purpose
for iter in range(1,10):
sub_set = gudhi.pick_n_random_points(points = point_set, nb_points = iter)
print(5)
for sub in sub_set:
found = False
for point in point_set:
if point == sub:
found = True
# Check each sub set point is existing in the point set
assert found == True
# From off file test
for i in range (0, 7):
assert len(gudhi.pick_n_random_points(off_file = 'subsample.off', nb_points = i)) == i
def test_simple_sparsify_points():
point_set = [[0,1], [0,0], [1,0], [1,1]]
# Test the limits
# assert gudhi.sparsify_point_set(points = [], min_squared_dist = 0.0) == []
# assert gudhi.sparsify_point_set(points = [], min_squared_dist = 10.0) == []
assert gudhi.sparsify_point_set(points = point_set, min_squared_dist = 0.0) == point_set
assert gudhi.sparsify_point_set(points = point_set, min_squared_dist = 1.0) == point_set
assert gudhi.sparsify_point_set(points = point_set, min_squared_dist = 2.0) == [[0,1], [1,0]]
assert gudhi.sparsify_point_set(points = point_set, min_squared_dist = 2.01) == [[0,1]]
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 0.0)) == 7
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 30.0)) == 5
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 40.0)) == 4
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 90.0)) == 3
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 100.0)) == 2
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 325.0)) == 2
assert len(gudhi.sparsify_point_set(off_file = 'subsample.off', min_squared_dist = 325.01)) == 1
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