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
|
from ase.io import read, write
import numpy as np
from ase import Atoms
# Check that saving/loading pdb files correctly reproduces the atoms object.
#
# Loading will restore the cell from lengths/angles, so the best we can do
# is to recreate the scaled positions, not the absolute positions.
images = [
Atoms(symbols='C8O8Ru64',
pbc=np.array([True, True, True], dtype=bool),
cell=np.array([[9.46101634e+00, 5.46231901e+00, -7.62683750e-07],
[0.00000000e+00, 1.09246400e+01, -7.62683750e-07],
[0.00000000e+00, 0.00000000e+00, 2.14654300e+01]]),
positions=np.array(
[[7.80131882e-01, 6.83747136e+00, 8.38204657e+00],
[5.51092271e+00, 9.56854231e+00, 8.38223568e+00],
[3.07270715e+00, 2.87955302e+00, 8.37140640e+00],
[7.80350536e+00, 5.61092571e+00, 8.37131213e+00],
[4.27438360e+00, 6.25264571e+00, 7.97264597e+00],
[9.00498640e+00, 8.98355980e+00, 7.97286435e+00],
[6.37288973e+00, 1.35474697e+01, 7.83982205e+00],
[1.64255024e+00, 1.08160090e+01, 7.83994023e+00],
[7.71235875e-01, 6.84831577e+00, 9.54503003e+00],
[5.50223518e+00, 9.57934418e+00, 9.54476437e+00],
[3.03497100e+00, 2.94960249e+00, 9.52997683e+00],
[7.76620880e+00, 5.68120179e+00, 9.52999700e+00],
[4.23008702e+00, 6.32508468e+00, 9.15933250e+00],
[8.96060688e+00, 9.05590199e+00, 9.15923442e+00],
[6.34874076e+00, 1.35969943e+01, 9.03839912e+00],
[1.61820848e+00, 1.08649253e+01, 9.01849841e+00],
[1.57683637e+00, 2.73116147e+00, -2.54228044e-07],
[1.56720630e+00, 2.72722886e+00, 4.28570884e+00],
[7.88417713e-01, 1.36558046e+00, 2.15514407e+00],
[8.02210750e-01, 1.34385101e+00, 6.43536380e+00],
[3.94209046e+00, 4.09674123e+00, -4.44898981e-07],
[3.95116212e+00, 4.10376637e+00, 4.28640956e+00],
[3.15367180e+00, 2.73116022e+00, 2.15514388e+00],
[3.15302826e+00, 2.73391087e+00, 6.47587998e+00],
[6.30734454e+00, 5.46232098e+00, -6.35569919e-07],
[6.29772257e+00, 5.45840160e+00, 4.28564811e+00],
[5.51892683e+00, 4.09674051e+00, 2.15514369e+00],
[5.53267073e+00, 4.07509705e+00, 6.43527963e+00],
[8.67259863e+00, 6.82790073e+00, -8.26240856e-07],
[8.68166544e+00, 6.83494012e+00, 4.28642358e+00],
[7.88417997e+00, 5.46231972e+00, 2.15514350e+00],
[7.88362942e+00, 5.46507502e+00, 6.47590212e+00],
[1.57683637e+00, 5.46232147e+00, -4.44898981e-07],
[1.58727500e+00, 5.44486645e+00, 4.24854361e+00],
[7.88417713e-01, 4.09674046e+00, 2.15514388e+00],
[8.01608482e-01, 4.07705367e+00, 6.44578990e+00],
[3.94209046e+00, 6.82790123e+00, -6.35569919e-07],
[3.95243122e+00, 6.81073405e+00, 4.32065689e+00],
[3.15367180e+00, 5.46232022e+00, 2.15514369e+00],
[3.16456215e+00, 5.44150374e+00, 6.44566316e+00],
[6.30734454e+00, 8.19348098e+00, -8.26240856e-07],
[6.31780039e+00, 8.17600912e+00, 4.24852811e+00],
[5.51892588e+00, 6.82789997e+00, 2.15514350e+00],
[5.53216899e+00, 6.80824683e+00, 6.44574538e+00],
[8.67259863e+00, 9.55906073e+00, -1.01691179e-06],
[8.68296348e+00, 9.54187626e+00, 4.32068356e+00],
[7.88417997e+00, 8.19347972e+00, 2.15514331e+00],
[7.89512792e+00, 8.17267187e+00, 6.44565547e+00],
[1.57683637e+00, 8.19348147e+00, -6.35569919e-07],
[1.58115689e+00, 8.20071292e+00, 4.29055653e+00],
[7.88417713e-01, 6.82790046e+00, 2.15514369e+00],
[7.91948666e-01, 6.82222698e+00, 6.48549188e+00],
[3.94209046e+00, 9.55906123e+00, -8.26240856e-07],
[3.93358820e+00, 9.55894698e+00, 4.29187459e+00],
[3.15367180e+00, 8.19348022e+00, 2.15514350e+00],
[3.15825664e+00, 8.18574447e+00, 6.38108109e+00],
[6.30734454e+00, 1.09246410e+01, -1.01691179e-06],
[6.31166355e+00, 1.09318806e+01, 4.29057142e+00],
[5.51892588e+00, 9.55905997e+00, 2.15514331e+00],
[5.52249944e+00, 9.55339051e+00, 6.48545486e+00],
[8.67259863e+00, 1.22902207e+01, -1.20758273e-06],
[8.66410508e+00, 1.22901152e+01, 4.29183559e+00],
[7.88418091e+00, 1.09246403e+01, 2.15514312e+00],
[7.88880125e+00, 1.09169018e+01, 6.38105940e+00],
[1.57683637e+00, 1.09246415e+01, -8.26240856e-07],
[1.58687157e+00, 1.09077863e+01, 4.32193338e+00],
[7.88417713e-01, 9.55906046e+00, 2.15514350e+00],
[7.78394031e-01, 9.52397919e+00, 6.44162756e+00],
[3.94209046e+00, 1.22902212e+01, -1.01691179e-06],
[3.95166143e+00, 1.22749617e+01, 4.26568019e+00],
[3.15367180e+00, 1.09246402e+01, 2.15514331e+00],
[3.19235336e+00, 1.09175437e+01, 6.44091634e+00],
[6.30734454e+00, 1.36558010e+01, -1.20758273e-06],
[6.31737307e+00, 1.36389093e+01, 4.32189961e+00],
[5.51892588e+00, 1.22902200e+01, 2.15514312e+00],
[5.50895045e+00, 1.22551312e+01, 6.44172685e+00],
[8.67259863e+00, 1.50213807e+01, -1.39825367e-06],
[8.68213569e+00, 1.50061426e+01, 4.26566744e+00],
[7.88418091e+00, 1.36558003e+01, 2.15514293e+00],
[7.92283529e+00, 1.36487476e+01, 6.44087611e+00]])),
]
def test_pdb_cell_io():
atoms1 = images[0]
write('grumbles.pdb', atoms1)
atoms2 = read('grumbles.pdb')
spos1 = (atoms1.get_scaled_positions() + 0.5) % 1.0
spos2 = (atoms2.get_scaled_positions() + 0.5) % 1.0
for a, b in zip(spos1, spos2):
print(a, b)
err = np.abs(spos1 - spos2).max()
print(err)
assert err < 2e-4
|
