File: test_augment.py

package info (click to toggle)
mdanalysis 2.10.0-1
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 116,696 kB
  • sloc: python: 92,135; ansic: 8,156; makefile: 215; sh: 138
file content (148 lines) | stat: -rw-r--r-- 4,521 bytes parent folder | download | duplicates (2)
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
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
# -*- Mode: python; tab-width: 4; indent-tabs-mode:nil; coding:utf-8 -*-
# vim: tabstop=4 expandtab shiftwidth=4 softtabstop=4 fileencoding=utf-8
#
# MDAnalysis --- https://www.mdanalysis.org
# Copyright (c) 2006-2017 The MDAnalysis Development Team and contributors
# (see the file AUTHORS for the full list of names)
#
# Released under the Lesser GNU Public Licence, v2.1 or any higher version
#
# Please cite your use of MDAnalysis in published work:
#
# R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler,
# D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein.
# MDAnalysis: A Python package for the rapid analysis of molecular dynamics
# simulations. In S. Benthall and S. Rostrup editors, Proceedings of the 15th
# Python in Science Conference, pages 102-109, Austin, TX, 2016. SciPy.
# doi: 10.25080/majora-629e541a-00e
#
# N. Michaud-Agrawal, E. J. Denning, T. B. Woolf, and O. Beckstein.
# MDAnalysis: A Toolkit for the Analysis of Molecular Dynamics Simulations.
# J. Comput. Chem. 32 (2011), 2319--2327, doi:10.1002/jcc.21787

import os

import numpy as np
import pytest
from MDAnalysis.lib._augment import augment_coordinates, undo_augment
from MDAnalysis.lib.distances import apply_PBC, transform_StoR
from numpy.testing import assert_almost_equal, assert_equal

# Find images for several query points,
# here in fractional coordinates
# Every element of qres tuple is (query, images)
qres = (
    ([0.1, 0.5, 0.5], [[1.1, 0.5, 0.5]]),  # box face
    ([0.5, 0.5, 0.5], []),  # box center
    ([0.5, -0.1, 0.5], [[0.5, -0.1, 0.5]]),  # box face
    (
        [0.1, 0.1, 0.5],
        [
            [1.1, 0.1, 0.5],
            [0.1, 1.1, 0.5],
            [1.1, 1.1, 0.5],
        ],
    ),  # box edge
    (
        [0.5, -0.1, 1.1],
        [
            [0.5, -0.1, 0.1],
            [0.5, 0.9, 1.1],
            [0.5, -0.1, 1.1],
        ],
    ),  # box edge
    (
        [0.1, 0.1, 0.1],
        [
            [1.1, 0.1, 0.1],
            [0.1, 1.1, 0.1],
            [0.1, 0.1, 1.1],
            [0.1, 1.1, 1.1],
            [1.1, 1.1, 0.1],
            [1.1, 0.1, 1.1],
            [1.1, 1.1, 1.1],
        ],
    ),  # box vertex
    (
        [0.1, -0.1, 1.1],
        [
            [1.1, 0.9, 0.1],
            [0.1, -0.1, 0.1],
            [0.1, 0.9, 1.1],
            [0.1, -0.1, 1.1],
            [1.1, -0.1, 0.1],
            [1.1, 0.9, 1.1],
            [1.1, -0.1, 1.1],
        ],
    ),  # box vertex
    (
        [2.1, -3.1, 0.1],
        [
            [1.1, 0.9, 0.1],
            [0.1, -0.1, 0.1],
            [0.1, 0.9, 1.1],
            [0.1, -0.1, 1.1],
            [1.1, -0.1, 0.1],
            [1.1, 0.9, 1.1],
            [1.1, -0.1, 1.1],
        ],
    ),  # box vertex
    (
        [
            [0.1, 0.5, 0.5],
            [0.5, -0.1, 0.5],
        ],
        [
            [1.1, 0.5, 0.5],
            [0.5, -0.1, 0.5],
        ],
    ),  # multiple queries
)


@pytest.mark.xfail(os.name == "nt", reason="see gh-3248")
@pytest.mark.parametrize(
    "b",
    (
        np.array([10, 10, 10, 90, 90, 90], dtype=np.float32),
        np.array([10, 10, 10, 45, 60, 90], dtype=np.float32),
    ),
)
@pytest.mark.parametrize("q, res", qres)
def test_augment(b, q, res):
    radius = 1.5
    q = transform_StoR(np.array(q, dtype=np.float32), b)
    if q.shape == (3,):
        q = q.reshape((1, 3))
    q = apply_PBC(q, b)
    aug, mapping = augment_coordinates(q, b, radius)
    if aug.size > 0:
        aug = np.sort(aug, axis=0)
    else:
        aug = list()
    if len(res) > 0:
        cs = transform_StoR(np.array(res, dtype=np.float32), b)
        cs = np.sort(cs, axis=0)
    else:
        cs = list()
    assert_almost_equal(aug, cs, decimal=5)


@pytest.mark.parametrize(
    "b",
    (
        np.array([10, 10, 10, 90, 90, 90], dtype=np.float32),
        np.array([10, 10, 10, 45, 60, 90], dtype=np.float32),
    ),
)
@pytest.mark.parametrize("qres", qres)
def test_undoaugment(b, qres):
    radius = 1.5
    q = transform_StoR(np.array(qres[0], dtype=np.float32), b)
    if q.shape == (3,):
        q = q.reshape((1, 3))
    q = apply_PBC(q, b)
    aug, mapping = augment_coordinates(q, b, radius)
    for idx, val in enumerate(aug):
        imageid = np.asarray([len(q) + idx], dtype=np.intp)
        assert_equal(mapping[idx], undo_augment(imageid, mapping, len(q))[0])