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Diffstat (limited to 'cython/test/test_subsampling.py')
| -rwxr-xr-x | cython/test/test_subsampling.py | 133 |
1 files changed, 0 insertions, 133 deletions
diff --git a/cython/test/test_subsampling.py b/cython/test/test_subsampling.py deleted file mode 100755 index 96906a6f..00000000 --- a/cython/test/test_subsampling.py +++ /dev/null @@ -1,133 +0,0 @@ -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 |