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# fmt: off
import io
import numpy as np
from ase import Atoms
# from ase.io import read
from ase.calculators.openmx.reader import read_eigenvalues, read_openmx
from ase.units import Bohr, Ha
openmx_out_sample = """
System.CurrentDirectory ./
System.Name ch4
Atoms.SpeciesAndCoordinates.Unit Ang
<Definition.of.Atomic.Species
C C5.0-s1p1 C_PBE19
H H5.0-s1 H_PBE19
Definition.of.Atomic.Species>
Atoms.SpeciesAndCoordinates.Unit Ang
<Atoms.SpeciesAndCoordinates
1 C 0.0 0.0 0.1 2.0 2.0
2 H 0.682793 0.682793 0.682793 0.5 0.5
3 H -0.682793 -0.682793 0.68279 0.5 0.5
4 H -0.682793 0.682793 -0.682793 0.5 0.5
5 H 0.682793 -0.682793 -0.682793 0.5 0.5
Atoms.SpeciesAndCoordinates>
<Atoms.UnitVectors
10.0 0.0 0.0
0.0 10.0 0.0
0.0 0.0 10.0
Atoms.UnitVectors>
scf.EigenvalueSolver Band
...
Utot. -8.055096450113
...
Chemical potential (Hartree) -0.156250000000
...
*************************************************************************
*************************************************************************
Decomposed energies in Hartree unit
Utot = Utot(up) + Utot(dn)
= Ukin(up) + Ukin(dn) + Uv(up) + Uv(dn)
+ Ucon(up)+ Ucon(dn) + Ucore+UH0 + Uvdw
Uele = Ukin(up) + Ukin(dn) + Uv(up) + Uv(dn)
Ucon arizes from a constant potential added in the formalism
up: up spin state, dn: down spin state
*************************************************************************
*************************************************************************
Total energy (Hartree) = -8.055096425922011
Decomposed.energies.(Hartree).with.respect.to.atom
Utot
1 C -6.261242355014 ...
2 H -0.445956460556 ...
3 H -0.445956145906 ...
4 H -0.450970732231 ...
5 H -0.450970732215 ...
...
<coordinates.forces
5
1 C 0.00 0.00 0.10 0.00000 0.00000 -0.091659
2 H 0.68 0.68 0.68 0.02700 0.02700 0.029454
3 H -0.68 -0.68 0.68 -0.02700 -0.02700 0.029455
4 H -0.68 0.68 -0.68 0.00894 -0.00894 0.016362
5 H 0.68 -0.68 -0.68 -0.00894 0.00894 0.016362
coordinates.forces>
...
***********************************************************
***********************************************************
Fractional coordinates of the final structure
***********************************************************
***********************************************************
1 C 0.00000 0.00000 0.01000
2 H 0.06827 0.06827 0.06827
3 H 0.93172 0.93172 0.06827
4 H 0.93172 0.06827 0.93172
5 H 0.06827 0.93172 0.93172
...
"""
def test_openmx_out(config_file):
with open('openmx_fio_test.out', 'w') as fd:
fd.write(openmx_out_sample)
atoms = read_openmx('openmx_fio_test')
tol = 1e-2
# Expected values
energy = -8.0551
energies = np.array([-6.2612, -0.4459, -0.4459, -0.4509, -0.4509])
forces = np.array([[0.00000, 0.00000, -0.091659],
[0.02700, 0.02700, 0.029454],
[-0.02700, -0.02700, 0.029455],
[0.00894, -0.00894, 0.016362],
[-0.00894, 0.00894, 0.016362]])
assert isinstance(atoms, Atoms)
assert np.isclose(atoms.calc.results['energy'], energy * Ha, atol=tol)
assert np.all(np.isclose(atoms.calc.results['energies'],
energies * Ha, atol=tol))
assert np.all(np.isclose(atoms.calc.results['forces'],
forces * Ha / Bohr, atol=tol))
openmx_eigenvalues_gamma_sample = """
...
***********************************************************
***********************************************************
Eigenvalues (Hartree) for SCF KS-eq.
***********************************************************
***********************************************************
Chemical Potential (Hartree) = -0.12277513509616
Number of States = 58.00000000000000
HOMO = 29
Eigenvalues
Up-spin Down-spin
1 -0.96233478518931 -0.96233478518931
2 -0.94189339856450 -0.94189339856450
3 -0.86350555424836 -0.86350555424836
4 -0.83918201748919 -0.83918201748919
5 -0.72288697309928 -0.72288697309928
6 -0.67210805969879 -0.67210805969879
7 -0.64903406048465 -0.64903406048465
8 -0.58249976216367 -0.58249976216367
9 -0.55161386332358 -0.55161386332358
***********************************************************
***********************************************************
History of cell optimization
***********************************************************
***********************************************************
...
"""
openmx_eigenvalues_bulk_sample = """
...
scf.Kgrid = 2 1 1
...
***********************************************************
***********************************************************
Eigenvalues (Hartree) of SCF KS-eq.
***********************************************************
***********************************************************
Chemical Potential (Hatree) = -0.19810093996855
Number of States = 156.00000000000000
Eigenvalues
Up-spin Down-spin
kloop=0
k1= -0.44444 k2= -0.44445 k3= 0.00000
1 -2.33424746491277 -2.33424746917880
2 -2.33424055817432 -2.33424056243807
3 -2.33419668076232 -2.33419668261398
4 -1.46440634271635 -1.46440634435648
5 -1.46439286017722 -1.46439286180118
6 -1.46436086583111 -1.46436086399066
7 -1.46397017044962 -1.46397017874325
8 -1.46394407220255 -1.46394408049882
9 -1.46389030794971 -1.46389031384386
kloop=1
k1= -0.44444 k2= -0.33333 k3= 0.00000
1 -2.33424705259020 -2.33424705685571
2 -2.33424133604313 -2.33424134030309
3 -2.33419651862703 -2.33419652048304
4 -1.46440529840756 -1.46440530004421
5 -1.46439446518585 -1.46439446677862
6 -1.46436032862668 -1.46436032682027
7 -1.46396740984959 -1.46396741813205
8 -1.46394638210900 -1.46394639039694
9 -1.46389029838585 -1.46389030429995
***********************************************************
***********************************************************
History of geometry optimization
***********************************************************
***********************************************************
...
"""
def test_openmx_read_eigenvalues():
tol = 1e-2
# reader.py -> `def read_file(filename...)` -> patterns
eigenvalues_pattern = "Eigenvalues (Hartree)"
with io.StringIO(openmx_eigenvalues_gamma_sample) as fd:
while True:
line = fd.readline()
if eigenvalues_pattern in line:
break
eigenvalues = read_eigenvalues(line, fd)
gamma_eigenvalues = np.array([[[-0.96233478518931, -0.96233478518931],
[-0.94189339856450, -0.94189339856450],
[-0.86350555424836, -0.86350555424836],
[-0.83918201748919, -0.83918201748919],
[-0.72288697309928, -0.72288697309928],
[-0.67210805969879, -0.67210805969879],
[-0.64903406048465, -0.64903406048465],
[-0.58249976216367, -0.58249976216367],
[-0.55161386332358, -0.55161386332358]]])
gamma_eigenvalues = np.swapaxes(gamma_eigenvalues.T, 1, 2)
assert np.all(np.isclose(eigenvalues, gamma_eigenvalues, atol=tol))
with io.StringIO(openmx_eigenvalues_bulk_sample) as fd:
while True:
line = fd.readline()
if eigenvalues_pattern in line:
break
eigenvalues = read_eigenvalues(line, fd)
bulk_eigenvalues = np.array([[[-2.33424746491277, -2.33424746917880],
[-2.33424055817432, -2.33424056243807],
[-2.33419668076232, -2.33419668261398],
[-1.46440634271635, -1.46440634435648],
[-1.46439286017722, -1.46439286180118],
[-1.46436086583111, -1.46436086399066],
[-1.46397017044962, -1.46397017874325],
[-1.46394407220255, -1.46394408049882],
[-1.46389030794971, -1.46389031384386]],
[[-2.33424705259020, -2.33424705685571],
[-2.33424133604313, -2.33424134030309],
[-2.33419651862703, -2.33419652048304],
[-1.46440529840756, -1.46440530004421],
[-1.46439446518585, -1.46439446677862],
[-1.46436032862668, -1.46436032682027],
[-1.46396740984959, -1.46396741813205],
[-1.46394638210900, -1.46394639039694],
[-1.46389029838585, -1.46389030429995]]])
bulk_eigenvalues = np.swapaxes(bulk_eigenvalues.T, 1, 2)
assert np.all(np.isclose(eigenvalues[:, :2, :], bulk_eigenvalues, atol=tol))
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