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Diffstat (limited to 'src/cython/test/test_persistence_representations_landscapes_on_grid.py')
| -rwxr-xr-x | src/cython/test/test_persistence_representations_landscapes_on_grid.py | 120 |
1 files changed, 120 insertions, 0 deletions
diff --git a/src/cython/test/test_persistence_representations_landscapes_on_grid.py b/src/cython/test/test_persistence_representations_landscapes_on_grid.py new file mode 100755 index 00000000..c03b8312 --- /dev/null +++ b/src/cython/test/test_persistence_representations_landscapes_on_grid.py @@ -0,0 +1,120 @@ +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): Pawel Dlotko + + Copyright (C) 2017 Swansea University + + 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__ = "Pawel Dlotko" +__copyright__ = "Copyright (C) 2017 Swansea University" +__license__ = "GPL v3" + +epsilon = 0.0000005; + + + +def test_check_construction_of_landscape: + l = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100,sys.maxsize) + l.print_to_file("landscape_from_file_with_diagram_1") + g = gudhi.PersistenceLandscapeOnGrid + g.load_landscape_from_file("landscape_from_file_with_diagram_1") + assert l == g + + +def test_check_construction_of_landscape_using_only_ten_levels: + number = 10 + gudhi.PersistenceLandscapeOnGrid l("data/file_with_diagram_1", 100, number) + gudhi.PersistenceLandscapeOnGrid g("data/file_with_diagram_1", 100, sys.maxsize) + for level in range(0,number): + v1 = l.vectorize(level) + v2 = g.vectorize(level) + assert v1 == v2 + +def test_check_computations_of_integrals: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, sys.maxsize) + integral = p.compute_integral_of_landscape() + assert fabs(integral - 27.343) <= 0.00005 + +def test_check_computations_of_integrals_for_each_level_separatelly: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, sys.maxsize) + integrals_fir_different_levels = [0.241168,0.239276,0.237882,0.235193,0.230115,0.227626,0.226132.0.223643,0.221651,0.220556,0.21727,0.215976,0.213685,0.211993,0.2102,0.208707,0.207014,0.205122,0.204226,0.202633] + for level in range(0,len(integrals_fir_different_levels)) + integral = p.compute_integral_of_landscape(level); + assert fabs(integral - integrals_fir_different_levels[level]) <= 0.00005 + +def test_check_computations_of_integrals_of_powers_of_landscape: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, sys.maxsize) + integrals_fir_different_powers = [0.241168,0.239276,0.237882,0.235193,0.23011] + for power in range(0:5): + integral = p.compute_integral_of_landscape(power) + assert fabs(integral - integrals_fir_different_powers[power]) <= 0.00001 + +def test_check_computations_of_values_on_different_points: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, sys.maxsize) + results_level_0 = [0.00997867,0.0521921,0.104312,0.156432,0.208552,0.260672,0.312792,0.364912,0.417032,0.429237] + results_level_10 = [7.21433e-05,0.0422135,0.0943335,0.146453,0.198573,0.240715,0.272877,0.324997,0.359232,0.379344] + double x = 0.0012321; + double dx = 0.05212; + for i in range(0,10): + assert almost_equal(p.compute_value_at_a_given_point(0, x), results_level_0[i])); + assert almost_equal(p.compute_value_at_a_given_point(10, x), results_level_10[i])); + x += dx; + +def test_check_computations_of_maxima_and_norms: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 0., 1., 100) + second = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_2", 0., 1., 100) + assert fabs(p.compute_maximum() - 0.46) <= 0.00001 + assert fabs(p.compute_norm_of_landscape(1) - 27.3373) <= 0.00001 + assert fabs(p.compute_norm_of_landscape(2) - 1.84143) <= 0.00001 + assert fabs(p.compute_norm_of_landscape(3) - 0.927067) <= 0.00001 + +def test_check_default_parameters_of_distances: + diag = read_persistence_intervals_in_dimension("data/file_with_diagram") + p = gudhi.PersistenceLandscapeOnGrid(diag, 0., 1., 100) + diag1 = read_persistence_intervals_in_dimension("data/file_with_diagram_1") + q = gudhi.PersistenceLandscapeOnGrid(diag1, 0., 1., 100) + dist_numeric_limit_max = p.distance(q, sys.maxsize); + dist_infinity = p.distance(q, sys.maxsize); + assert dist_numeric_limit_max == dist_infinity + +def test_check_computations_of_averages: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram", 0., 1., 100) + q = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 0., 1., 100) + av = gudhi.PersistenceLandscapeOnGrid + av.compute_average({&p, &q) + + template_average = gudhi.PersistenceLandscapeOnGrid + template_average.load_landscape_from_file("data/average_on_a_grid") + assert template_average == av + + +def test_check_computations_of_distances: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram", 0., 1., 10000) + q = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 0., 1., 10000) + assert fabs(p.distance(q) - 25.5779) <= 0.00005 + assert fabs(p.distance(q, 2) - 2.04891) <= 0.00001 + assert fabs(p.distance(q, sys.maxsize) - 0.359) <= 0.00001 + + +def test_check_computations_of_scalar_product: + p = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram", 0., 1., 10000) + q = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 0., 1., 10000) + assert almost_equal(p.compute_scalar_product(q), 0.754367) |