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""" 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
Copyright (C) 2016 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
import gudhi
__author__ = "Vincent Rouvreau"
__copyright__ = "Copyright (C) 2016 Inria"
__license__ = "MIT"
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)
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=0.999) == point_set
assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=1.001) == [
[0, 1],
[1, 0],
]
assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=1.999) == [
[0, 1],
[1, 0],
]
assert gudhi.sparsify_point_set(points=point_set, min_squared_dist=2.001) == [[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=40.1))
== 4
)
assert (
len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=89.9))
== 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=324.9))
== 2
)
assert (
len(gudhi.sparsify_point_set(off_file="subsample.off", min_squared_dist=325.01))
== 1
)
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