pylinalg/tests/test_misc.py at 9178b07f9830429113420b38578f9569acbcf7dc · pygfx/pylinalg · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
import numpy as np
from hypothesis import assume, given
from hypothesis.strategies import floats

import pylinalg as la

from . import conftest as ct


@given(
    ct.test_unit_vector,
    ct.test_unit_vector,
    floats(-1e6, 1e6, allow_nan=False, allow_infinity=False),
)
def test_aabb_to_sphere(point, offset, scale):
    assume(abs(scale) > 1e-16)
    assume(np.linalg.norm(point - (0, 0, 1)) > 1e-16)
    assume(np.linalg.norm(point - (0, 1, 0)) > 1e-16)
    assume(np.linalg.norm(point - (1, 0, 0)) > 1e-16)

    candidate = np.stack(
        (
            scale * point + offset,
            -scale * point + offset,
        )
    )

    aabb = np.empty_like(candidate)
    aabb[0, :] = np.min(candidate, axis=0)
    aabb[1, :] = np.max(candidate, axis=0)

    sphere = la.aabb_to_sphere(aabb)

    assert np.allclose(sphere[:3], offset, atol=1e-10)
    assert np.allclose(sphere[-1], abs(scale), rtol=1e-10)


@given(ct.test_unit_vector, ct.test_vector, ct.test_scaling)
def test_aabb_transform(point, translation, scale):
    candidate = np.stack((point, -point))
    aabb = np.empty_like(candidate)
    aabb[0, :] = np.min(candidate, axis=0)
    aabb[1, :] = np.max(candidate, axis=0)

    translation_matrix = la.mat_from_translation(translation)
    result = la.aabb_transform(aabb, translation_matrix)
    assert np.allclose(result, aabb + translation, atol=1e-10)

    scale_matrix = la.mat_from_scale(scale)
    result = la.aabb_transform(aabb, scale_matrix)
    assert np.allclose(result, np.sort(aabb * scale, axis=0), atol=1e-10)


def test_aabb_transform_single():
    """Test single transform."""
    aabb = np.array([[-1, -1, -1], [1, 1, 1]])
    translation = np.array([1, 0, 0])
    translation_matrix = la.mat_from_translation(translation)

    expected = aabb + translation
    result = la.aabb_transform(aabb, translation_matrix)
    assert np.allclose(result, expected, atol=1e-10)


def test_aabb_transform_broadcasting():
    """Test pairwise broadcasting of AABBs and matrices."""
    aabbs = np.array(
        [
            [[-1, -1, -1], [1, 1, 1]],
            [[-2, -2, -2], [2, 2, 2]],
        ]
    )
    translations = np.array(
        [
            [1, 0, 0],
            [0, 1, 0],
        ]
    )
    translation_matrices = la.mat_from_translation(translations)

    expected = aabbs + translations[:, np.newaxis, :]
    result = la.aabb_transform(aabbs, translation_matrices)
    assert np.allclose(result, expected, atol=1e-10)


def test_aabb_transform_broadcasting_2():
    """Test broadcasting many matrices and one AABB."""
    aabb = np.array([[-1, -1, -1], [1, 1, 1]])
    translations = np.array(
        [
            [1, 0, 0],
            [0, 1, 0],
        ]
    )
    translation_matrices = la.mat_from_translation(translations)

    expected = aabb[np.newaxis, ...] + translations[:, np.newaxis, :]
    result = la.aabb_transform(aabb, translation_matrices)
    assert np.allclose(result, expected, atol=1e-10)