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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): Hind Montassif
Copyright (C) 2021 Inria
Modification(s):
- YYYY/MM Author: Description of the modification
"""
from gudhi.datasets.generators import points
import pytest
def test_sphere():
assert points.sphere(n_samples = 10, ambient_dim = 2, radius = 1., sample = 'random').shape == (10, 2)
with pytest.raises(ValueError):
points.sphere(n_samples = 10, ambient_dim = 2, radius = 1., sample = 'other')
def _basic_torus(impl):
assert impl(n_samples = 64, dim = 3, sample = 'random').shape == (64, 6)
assert impl(n_samples = 64, dim = 3, sample = 'grid').shape == (64, 6)
assert impl(n_samples = 10, dim = 4, sample = 'random').shape == (10, 8)
# Here 1**dim < n_samples < 2**dim, the output shape is therefore (1, 2*dim) = (1, 8), where shape[0] is rounded down to the closest perfect 'dim'th power
assert impl(n_samples = 10, dim = 4, sample = 'grid').shape == (1, 8)
with pytest.raises(ValueError):
impl(n_samples = 10, dim = 4, sample = 'other')
def test_torus():
for torus_impl in [points.torus, points.ctorus]:
_basic_torus(torus_impl)
# Check that the two versions (torus and ctorus) generate the same output
assert points.ctorus(n_samples = 64, dim = 3, sample = 'random').all() == points.torus(n_samples = 64, dim = 3, sample = 'random').all()
assert points.ctorus(n_samples = 64, dim = 3, sample = 'grid').all() == points.torus(n_samples = 64, dim = 3, sample = 'grid').all()
assert points.ctorus(n_samples = 10, dim = 3, sample = 'grid').all() == points.torus(n_samples = 10, dim = 3, sample = 'grid').all()
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