diff options
Diffstat (limited to 'src/cython/test/test_subsampling.py')
| -rwxr-xr-x | src/cython/test/test_subsampling.py | 166 |
1 files changed, 106 insertions, 60 deletions
diff --git a/src/cython/test/test_subsampling.py b/src/cython/test/test_subsampling.py index 96906a6f..c816e203 100755 --- a/src/cython/test/test_subsampling.py +++ b/src/cython/test/test_subsampling.py @@ -1,30 +1,18 @@ 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. +""" 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): Vincent Rouvreau - Author(s): Vincent Rouvreau + Copyright (C) 2016 Inria - 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/>. + Modification(s): + - YYYY/MM Author: Description of the modification """ __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" -__license__ = "GPL v3" +__license__ = "MIT" def test_write_off_file_for_tests(): @@ -40,45 +28,72 @@ def test_write_off_file_for_tests(): 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]] + 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) + 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) + 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) + 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) + 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) + 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) == [] + 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 + 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]] + 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) == [] + 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 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: @@ -88,19 +103,23 @@ def test_simple_choose_n_farthest_points_randomed(): 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 + 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]] + 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) == [] + 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) + 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 @@ -111,23 +130,50 @@ def test_simple_pick_n_random_points(): 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 + 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]] + 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 + 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 + ) |