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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): 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
l = gudhi.PersistenceLandscapeOnGrid("data/file_with_diagram_1", 100, number)
g = gudhi.PersistenceLandscapeOnGrid("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)
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