def read_dynmat_ir_raman(filename='dynmat.out', natoms=None,
cols={1: 'freqs', 3:'ir', 4: 'raman', 5: 'depol'}):
"""Read ``dynmat.x`` text output file and extract IR and Raman
intensities.
Parameters
----------
filename : str
dynmat.x text output file (e.g. from ``dynmat.x < dynmat.in >
dynmat.out``)
natoms : int
number of atoms in the cell
cols : dict
column numbers of the text block
Returns
-------
cols = None
Return the parsed array as found in the file
cols = dict
Return dict with keys from `cols` and 1d arrays ``{'freqs': <array>,
'ir': <array>, 'raman': <array>, 'depol': <array>}``. If a column is
not present, the array is None.
Notes
-----
The parsed textblock looks like this::
# mode [cm-1] [THz] IR Raman depol.fact
1 0.00 0.0000 0.0000 0.0005 0.7414
2 0.00 0.0000 0.0000 0.0005 0.7465
3 0.00 0.0000 0.0000 0.0018 0.2647
4 252.27 7.5627 0.0000 0.0073 0.7500
5 252.27 7.5627 0.0000 0.0073 0.7500
6 548.44 16.4419 0.0000 0.0000 0.7434
7 603.32 18.0872 35.9045 18.9075 0.7366
8 656.82 19.6910 0.0000 7.9317 0.7500
9 656.82 19.6910 0.0000 7.9317 0.7500
10 669.67 20.0762 31.5712 5.0265 0.7500
11 738.22 22.1311 0.0000 0.0000 0.7306
12 922.64 27.6600 31.5712 5.0265 0.7500
Some columns (e.g. IR, Raman) may be missing.
"""
assert natoms is not None, ("natoms is None")
cmd = "grep -A{0} 'mode.*cm-1' {1} | grep -v mode".format(3*natoms, filename)
arr = parse.arr2d_from_txt(common.backtick(cmd))
if cols is None:
return arr
else:
dct = {}
for ii,name in cols.items():
if arr.shape[1] >= (ii+1):
dct[name] = arr[:,ii]
else:
dct[name] = None
return dct
def read_dynmat_ir_raman(filename='dynmat.out', natoms=None,
cols={1: 'freqs', 3:'ir', 4: 'raman', 5: 'depol'}):
"""Read ``dynmat.x`` text output file and extract IR and Raman
intensities.
Parameters
----------
filename : str
dynmat.x text output file (e.g. from ``dynmat.x < dynmat.in >
dynmat.out``)
natoms : int
number of atoms in the cell
cols : dict
column numbers of the text block
Returns
-------
cols = None
Return the parsed array as found in the file
cols = dict
Return dict with keys from `cols` and 1d arrays ``{'freqs': <array>,
'ir': <array>, 'raman': <array>, 'depol': <array>}``. If a column is
not present, the array is None.
Notes
-----
The parsed textblock looks like this::
# mode [cm-1] [THz] IR Raman depol.fact
1 0.00 0.0000 0.0000 0.0005 0.7414
2 0.00 0.0000 0.0000 0.0005 0.7465
3 0.00 0.0000 0.0000 0.0018 0.2647
4 252.27 7.5627 0.0000 0.0073 0.7500
5 252.27 7.5627 0.0000 0.0073 0.7500
6 548.44 16.4419 0.0000 0.0000 0.7434
7 603.32 18.0872 35.9045 18.9075 0.7366
8 656.82 19.6910 0.0000 7.9317 0.7500
9 656.82 19.6910 0.0000 7.9317 0.7500
10 669.67 20.0762 31.5712 5.0265 0.7500
11 738.22 22.1311 0.0000 0.0000 0.7306
12 922.64 27.6600 31.5712 5.0265 0.7500
Some columns (e.g. IR, Raman) may be missing.
"""
assert natoms is not None, ("natoms is None")
cmd = "grep -A{0} 'mode.*cm-1' {1} | grep -v mode".format(3*natoms, filename)
arr = parse.arr2d_from_txt(common.backtick(cmd))
if cols is None:
return arr
else:
dct = {}
for ii,name in cols.iteritems():
if arr.shape[1] >= (ii+1):
dct[name] = arr[:,ii]
else:
dct[name] = None
return dct
def test_pwscf_calculator():
if not have_ase():
skip("no ASE found, skipping test")
elif not have_pwx():
skip("no pw.x found, skipping test")
else:
pseudo_dir = pj(testdir, prefix, 'pseudo')
print(common.backtick("mkdir -pv {p}; cp files/qe_pseudos/*.gz {p}/; \
gunzip {p}/*".format(p=pseudo_dir)))
at = get_atoms_with_calc_pwscf(pseudo_dir)
print("scf")
# trigger calculation here
forces = at.get_forces()
etot = at.get_potential_energy()
stress = at.get_stress(voigt=False) # 3x3
st = io.read_pw_scf(at.calc.label + '.out')
assert np.allclose(forces, st.forces)
assert np.allclose(etot, st.etot)
assert np.allclose(st.stress, -stress * constants.eV_by_Ang3_to_GPa)
# files/ase/pw.scf.out.start is a norm-conserving LDA struct,
# calculated with pz-vbc.UPF, so the PBE vc-relax will make the cell
# a bit bigger
print("vc-relax")
from ase.optimize import BFGS
from ase.constraints import UnitCellFilter
opt = BFGS(UnitCellFilter(at))
cell = parse.arr2d_from_txt("""
-1.97281509 0. 1.97281509
0. 1.97281509 1.97281509
-1.97281509 1.97281509 0.""")
assert np.allclose(cell, at.get_cell())
opt.run(fmax=0.05) # run only 2 steps
cell = parse.arr2d_from_txt("""
-2.01837531 0. 2.01837531
0. 2.01837531 2.01837531
-2.01837531 2.01837531 0""")
assert np.allclose(cell, at.get_cell())
# at least 1 backup files must exist: pw.*.0 is the SCF run, backed up
# in the first iter of the vc-relax
assert os.path.exists(at.calc.infile + '.0')
def test_pwscf_calculator():
if not have_ase():
skip("no ASE found, skipping test")
elif not have_pwx():
skip("no pw.x found, skipping test")
else:
pseudo_dir = pj(testdir, prefix, 'pseudo')
print common.backtick("mkdir -pv {p}; cp files/qe_pseudos/*.gz {p}/; \
gunzip {p}/*".format(p=pseudo_dir))
at = get_atoms_with_calc_pwscf(pseudo_dir)
print "scf"
# trigger calculation here
forces = at.get_forces()
etot = at.get_potential_energy()
stress = at.get_stress(voigt=False) # 3x3
st = io.read_pw_scf(at.calc.label + '.out')
assert np.allclose(forces, st.forces)
assert np.allclose(etot, st.etot)
assert np.allclose(st.stress, -stress * constants.eV_by_Ang3_to_GPa)
# files/ase/pw.scf.out.start is a norm-conserving LDA struct,
# calculated with pz-vbc.UPF, so the PBE vc-relax will make the cell
# a bit bigger
print "vc-relax"
from ase.optimize import BFGS
from ase.constraints import UnitCellFilter
opt = BFGS(UnitCellFilter(at))
cell = parse.arr2d_from_txt("""
-1.97281509 0. 1.97281509
0. 1.97281509 1.97281509
-1.97281509 1.97281509 0.""")
assert np.allclose(cell, at.get_cell())
opt.run(fmax=0.05) # run only 2 steps
cell = parse.arr2d_from_txt("""
-2.01837531 0. 2.01837531
0. 2.01837531 2.01837531
-2.01837531 2.01837531 0""")
assert np.allclose(cell, at.get_cell())
# at least 1 backup files must exist: pw.*.0 is the SCF run, backed up
# in the first iter of the vc-relax
assert os.path.exists(at.calc.infile + '.0')
def test_write_lammps():
st = crys.Structure(coords_frac=rand(20, 3),
cell=rand(3, 3),
symbols=['Al'] * 10 + ['N'] * 10)
# align cell to lammps standard [[x,0,0],...]
st.coords = None
st.cell = None
st.set_all()
st_fn = common.pj(testdir, 'lmp.struct')
io.write_lammps(st_fn, st)
symbols = common.file_read(st_fn + '.symbols').split()
assert st.symbols == symbols
cmd = r"grep -A22 Atoms %s | grep '^[0-9]'" % st_fn
arr = parse.arr2d_from_txt(common.backtick(cmd))
assert arr.shape == (20, 5)
assert np.allclose(st.coords, arr[:, 2:])
def test_write_lammps():
st = crys.Structure(coords_frac=rand(20,3),
cell=rand(3,3),
symbols=['Al']*10+['N']*10)
# align cell to lammps standard [[x,0,0],...]
st.coords = None
st.cell = None
st.set_all()
st_fn = common.pj(testdir, 'lmp.struct')
io.write_lammps(st_fn, st)
symbols = common.file_read(st_fn + '.symbols').split()
assert st.symbols == symbols
cmd = r"grep -A22 Atoms %s | grep '^[0-9]'" %st_fn
arr = parse.arr2d_from_txt(common.backtick(cmd))
assert arr.shape == (20,5)
assert np.allclose(st.coords, arr[:,2:])
def read_dyn(filename, natoms=None):
"""Read one dynamical matrix file (for 1 qpoint) produced by ``ph.x`` and
extract the same as :func:`read_matdyn_modes` for this qpoint only.
All arrays have one dim less compared to :func:`read_matdyn_modes`.
Parameters
----------
filename : str
Name of dyn file. Example: "ph.dyn3" for qpoint 3.
natoms : int
number of atoms in the cell (used for nmodes=3*natoms only)
Returns
-------
qpoints, freqs, vecs
qpoints : 1d array (3,)
The qpoint of the dyn file.
freqs : 1d array, (nmodes,) where nmodes = 3*natoms
3*natoms phonon frequencies in [cm^-1] at the q-point.
vecs : 3d complex array (nmodes, natoms, 3)
Complex eigenvectors of the dynamical matrix for the q-point.
"""
assert natoms is not None
cmd = r"egrep 'q.*=.*\(' %s | tail -n1 | sed -re 's/.*q\s*=.*\((.*)\)/\1/'" %filename
qpoints = np.fromstring(common.backtick(cmd), sep=' ')
assert qpoints.shape == (3,)
nmodes = 3*natoms
cmd = r"grep -v 'q.*=' %s | grep '^[ ]*(' | sed -re 's/^\s*\((.*)\)/\1/g'" %filename
# vecs_file_flat: (nmodes * natoms, 6)
# this line is the bottleneck
vecs_file_flat = parse.arr2d_from_txt(common.backtick(cmd))
vecs_flat = np.empty((vecs_file_flat.shape[0], 3), dtype=complex)
vecs_flat[:,0] = vecs_file_flat[:,0] + 1j*vecs_file_flat[:,1]
vecs_flat[:,1] = vecs_file_flat[:,2] + 1j*vecs_file_flat[:,3]
vecs_flat[:,2] = vecs_file_flat[:,4] + 1j*vecs_file_flat[:,5]
vecs = vecs_flat.flatten().reshape(nmodes, natoms, 3)
cmd = r"grep omega %s | sed -re \
's/.*omega.*=.*\[.*=(.*)\s*\[.*/\1/g'" %filename
freqs = np.fromstring(common.backtick(cmd), sep=' ')
return qpoints, freqs, vecs
def read_dyn(filename, natoms=None):
"""Read one dynamical matrix file (for 1 qpoint) produced by ``ph.x`` and
extract the same as :func:`read_matdyn_modes` for this qpoint only.
All arrays have one dim less compared to :func:`read_matdyn_modes`.
Parameters
----------
filename : str
Name of dyn file. Example: "ph.dyn3" for qpoint 3.
natoms : int
number of atoms in the cell (used for nmodes=3*natoms only)
Returns
-------
qpoints, freqs, vecs
qpoints : 1d array (3,)
The qpoint of the dyn file.
freqs : 1d array, (nmodes,) where nmodes = 3*natoms
3*natoms phonon frequencies in [cm^-1] at the q-point.
vecs : 3d complex array (nmodes, natoms, 3)
Complex eigenvectors of the dynamical matrix for the q-point.
"""
assert natoms is not None
cmd = r"egrep 'q.*=.*\(' %s | tail -n1 | sed -re 's/.*q\s*=.*\((.*)\)/\1/'" %filename
qpoints = np.fromstring(common.backtick(cmd), sep=' ')
assert qpoints.shape == (3,)
nmodes = 3*natoms
cmd = r"grep -v 'q.*=' %s | grep '^[ ]*(' | sed -re 's/^\s*\((.*)\)/\1/g'" %filename
# vecs_file_flat: (nmodes * natoms, 6)
# this line is the bottleneck
vecs_file_flat = parse.arr2d_from_txt(common.backtick(cmd))
vecs_flat = np.empty((vecs_file_flat.shape[0], 3), dtype=complex)
vecs_flat[:,0] = vecs_file_flat[:,0] + 1j*vecs_file_flat[:,1]
vecs_flat[:,1] = vecs_file_flat[:,2] + 1j*vecs_file_flat[:,3]
vecs_flat[:,2] = vecs_file_flat[:,4] + 1j*vecs_file_flat[:,5]
vecs = vecs_flat.flatten().reshape(nmodes, natoms, 3)
cmd = r"grep omega %s | sed -re \
's/.*omega.*=.*\[.*=(.*)\s*\[.*/\1/g'" %filename
freqs = np.fromstring(common.backtick(cmd), sep=' ')
return qpoints, freqs, vecs
def test_lammps_calculator():
if not have_ase():
skip("no ASE found, skipping test")
elif not have_lmp():
skip("no lammps found, skipping test")
else:
at = get_atoms_with_calc_lammps()
at.rattle(stdev=0.001, seed=int(time.time()))
common.makedirs(at.calc.directory)
print(common.backtick("cp -v utils/lammps/AlN.tersoff {p}/".format(
p=at.calc.directory)))
print("scf")
forces = at.get_forces()
etot = at.get_potential_energy()
stress = at.get_stress(voigt=False) # 3x3
st = io.read_lammps_md_txt(at.calc.label + '.out')[0]
assert np.allclose(forces, st.forces)
assert np.allclose(etot, st.etot)
assert np.allclose(st.stress, -stress * constants.eV_by_Ang3_to_GPa,
atol=1e-10)
print("relax")
from ase.optimize import BFGS
opt = BFGS(at, maxstep=0.04)
opt.run(fmax=0.001, steps=10)
coords_frac = parse.arr2d_from_txt("""
3.3333341909920072e-01 6.6666683819841532e-01 4.4325467247779138e-03
6.6666681184103216e-01 3.3333362368205072e-01 5.0443254824788963e-01
3.3333341909918301e-01 6.6666683819838046e-01 3.8356759709402671e-01
6.6666681184101539e-01 3.3333362368201563e-01 8.8356759861713752e-01
""")
assert np.allclose(coords_frac, at.get_scaled_positions(), atol=1e-2)
# at least 1 backup files must exist
assert os.path.exists(at.calc.infile + '.0')
assert os.path.exists(at.calc.outfile + '.0')
assert os.path.exists(at.calc.dumpfile + '.0')
assert os.path.exists(at.calc.structfile + '.0')
def test_lammps_calculator():
if not have_ase():
skip("no ASE found, skipping test")
elif not have_lmp():
skip("no lammps found, skipping test")
else:
at = get_atoms_with_calc_lammps()
at.rattle(stdev=0.001, seed=int(time.time()))
common.makedirs(at.calc.directory)
print common.backtick("cp -v utils/lammps/AlN.tersoff {p}/".format(
p=at.calc.directory))
print "scf"
forces = at.get_forces()
etot = at.get_potential_energy()
stress = at.get_stress(voigt=False) # 3x3
st = io.read_lammps_md_txt(at.calc.label + '.out')[0]
assert np.allclose(forces, st.forces)
assert np.allclose(etot, st.etot)
assert np.allclose(st.stress, -stress * constants.eV_by_Ang3_to_GPa,
atol=1e-10)
print "relax"
from ase.optimize import BFGS
opt = BFGS(at, maxstep=0.04)
opt.run(fmax=0.001, steps=10)
coords_frac = parse.arr2d_from_txt("""
3.3333341909920072e-01 6.6666683819841532e-01 4.4325467247779138e-03
6.6666681184103216e-01 3.3333362368205072e-01 5.0443254824788963e-01
3.3333341909918301e-01 6.6666683819838046e-01 3.8356759709402671e-01
6.6666681184101539e-01 3.3333362368201563e-01 8.8356759861713752e-01
""")
assert np.allclose(coords_frac, at.get_scaled_positions(), atol=1e-2)
# at least 1 backup files must exist
assert os.path.exists(at.calc.infile + '.0')
assert os.path.exists(at.calc.outfile + '.0')
assert os.path.exists(at.calc.dumpfile + '.0')
assert os.path.exists(at.calc.structfile + '.0')
def read_matdyn_modes(filename, natoms=None):
"""Parse modes file produced by QE's matdyn.x.
Parameters
----------
filename : str
File to parse (usually "matdyn.modes")
natoms : int
Number of atoms.
Returns
-------
qpoints, freqs, vecs
qpoints : 2d array (nqpoints, 3)
All qpoints on the grid.
freqs : 2d array, (nqpoints, nmodes) where nmodes = 3*natoms
Each row: 3*natoms phonon frequencies in [cm^-1] at each q-point.
vecs : 4d complex array (nqpoints, nmodes, natoms, 3)
Complex eigenvectors of the dynamical matrix for each q-point.
Examples
--------
>>> qpoints,freqs,vecs=read_matdyn_modes('matdyn.modes',natoms=27)
# how many q-points? -> 8
>>> qpoints.shape
(8,3)
# 1st q-point in file, mode #3 (out of 3*27) -> vectors on all 27 atoms
>>> vecs[0,2,...].shape
(27,3)
# 1st q-point in file, mode #3, vector on atom #15
>>> vecs[0,2,14,:].real
array([-0.010832, 0.026063, -0.089511])
>>> vecs[0,2,14,:].imag
array([ 0., 0., 0.])
Notes
-----
The file to be parsed looks like this::
diagonalizing the dynamical matrix ...
q = 0.0000 0.0000 0.0000
**************************************************************************
omega( 1) = -26.663631 [THz] = -889.402992 [cm-1]
( -0.218314 0.000000 -0.025643 0.000000 -0.116601 0.000000 )
( -0.086633 0.000000 0.108966 0.000000 -0.066513 0.000000 )
[... natoms lines: x_real x_imag y_real y_imag z_real z_imag ... until
next omega ...]
omega( 2) = -16.330246 [THz] = -544.718372 [cm-1]
( 0.172149 0.000000 0.008336 0.000000 -0.121991 0.000000 )
( -0.061497 0.000000 0.003782 0.000000 -0.018304 0.000000 )
[... until omega(3*natoms) ...]
**************************************************************************
diagonalizing the dynamical matrix ...
[... until next q-point ...]
q = 0.0000 0.0000 -0.5000
**************************************************************************
omega( 1) = -24.881828 [THz] = -829.968443 [cm-1]
( -0.225020 0.000464 -0.031584 0.000061 -0.130217 0.000202 )
( -0.085499 0.000180 0.107383 -0.000238 -0.086854 0.000096 )
[...]
**************************************************************************
"""
assert natoms is not None
cmd = r"grep 'q.*=' %s | sed -re 's/.*q\s*=(.*)/\1/'" %filename
qpoints = parse.arr2d_from_txt(common.backtick(cmd))
nqpoints = qpoints.shape[0]
nmodes = 3*natoms
cmd = r"grep '^[ ]*(' %s | sed -re 's/^\s*\((.*)\)/\1/g'" %filename
# vecs_file_flat: (nqpoints * nmodes * natoms, 6)
# this line is the bottleneck
vecs_file_flat = parse.arr2d_from_txt(common.backtick(cmd))
vecs_flat = np.empty((vecs_file_flat.shape[0], 3), dtype=complex)
vecs_flat[:,0] = vecs_file_flat[:,0] + 1j*vecs_file_flat[:,1]
vecs_flat[:,1] = vecs_file_flat[:,2] + 1j*vecs_file_flat[:,3]
vecs_flat[:,2] = vecs_file_flat[:,4] + 1j*vecs_file_flat[:,5]
vecs = vecs_flat.flatten().reshape(nqpoints, nmodes, natoms, 3)
cmd = r"grep omega %s | sed -re \
's/.*omega.*=.*\[.*=(.*)\s*\[.*/\1/g'" %filename
freqs = np.fromstring(common.backtick(cmd), sep=' ').reshape((nqpoints, nmodes))
return qpoints, freqs, vecs
def read_matdyn_modes(filename, natoms=None):
"""Parse modes file produced by QE's matdyn.x.
Parameters
----------
filename : str
File to parse (usually "matdyn.modes")
natoms : int
Number of atoms.
Returns
-------
qpoints, freqs, vecs
qpoints : 2d array (nqpoints, 3)
All qpoints on the grid.
freqs : 2d array, (nqpoints, nmodes) where nmodes = 3*natoms
Each row: 3*natoms phonon frequencies in [cm^-1] at each q-point.
vecs : 4d complex array (nqpoints, nmodes, natoms, 3)
Complex eigenvectors of the dynamical matrix for each q-point.
Examples
--------
>>> qpoints,freqs,vecs=read_matdyn_modes('matdyn.modes',natoms=27)
# how many q-points? -> 8
>>> qpoints.shape
(8,3)
# 1st q-point in file, mode #3 (out of 3*27) -> vectors on all 27 atoms
>>> vecs[0,2,...].shape
(27,3)
# 1st q-point in file, mode #3, vector on atom #15
>>> vecs[0,2,14,:].real
array([-0.010832, 0.026063, -0.089511])
>>> vecs[0,2,14,:].imag
array([ 0., 0., 0.])
Notes
-----
The file to be parsed looks like this::
diagonalizing the dynamical matrix ...
q = 0.0000 0.0000 0.0000
**************************************************************************
omega( 1) = -26.663631 [THz] = -889.402992 [cm-1]
( -0.218314 0.000000 -0.025643 0.000000 -0.116601 0.000000 )
( -0.086633 0.000000 0.108966 0.000000 -0.066513 0.000000 )
[... natoms lines: x_real x_imag y_real y_imag z_real z_imag ... until
next omega ...]
omega( 2) = -16.330246 [THz] = -544.718372 [cm-1]
( 0.172149 0.000000 0.008336 0.000000 -0.121991 0.000000 )
( -0.061497 0.000000 0.003782 0.000000 -0.018304 0.000000 )
[... until omega(3*natoms) ...]
**************************************************************************
diagonalizing the dynamical matrix ...
[... until next q-point ...]
q = 0.0000 0.0000 -0.5000
**************************************************************************
omega( 1) = -24.881828 [THz] = -829.968443 [cm-1]
( -0.225020 0.000464 -0.031584 0.000061 -0.130217 0.000202 )
( -0.085499 0.000180 0.107383 -0.000238 -0.086854 0.000096 )
[...]
**************************************************************************
"""
assert natoms is not None
cmd = r"grep 'q.*=' %s | sed -re 's/.*q\s*=(.*)/\1/'" %filename
qpoints = parse.arr2d_from_txt(common.backtick(cmd))
nqpoints = qpoints.shape[0]
nmodes = 3*natoms
cmd = r"grep '^[ ]*(' %s | sed -re 's/^\s*\((.*)\)/\1/g'" %filename
# vecs_file_flat: (nqpoints * nmodes * natoms, 6)
# this line is the bottleneck
vecs_file_flat = parse.arr2d_from_txt(common.backtick(cmd))
vecs_flat = np.empty((vecs_file_flat.shape[0], 3), dtype=complex)
vecs_flat[:,0] = vecs_file_flat[:,0] + 1j*vecs_file_flat[:,1]
vecs_flat[:,1] = vecs_file_flat[:,2] + 1j*vecs_file_flat[:,3]
vecs_flat[:,2] = vecs_file_flat[:,4] + 1j*vecs_file_flat[:,5]
vecs = vecs_flat.flatten().reshape(nqpoints, nmodes, natoms, 3)
cmd = r"grep omega %s | sed -re \
's/.*omega.*=.*\[.*=(.*)\s*\[.*/\1/g'" %filename
freqs = np.fromstring(common.backtick(cmd), sep=' ').reshape((nqpoints, nmodes))
return qpoints, freqs, vecs
# Test parsing the correct SCF cell from a [vc-]relax run (QE 5.x only, IIRC),
# which performs a final SCF run after the relax has converged.
import os
import numpy as np
from pwtools import common, crys, parse, io
# from pw.out: "reduced cell" = cell / alat
cell_2d_red_ref = parse.arr2d_from_txt("""
1.000000 0.000000 0.000000
0.000000 2.902399 0.000000
0.000000 0.000000 2.304846
""")
def test_scf_cell():
filename = 'files/pw.vc_relax_coords_fixed.out'
common.system('gunzip %s.gz' % filename)
pp = parse.PwSCFOutputFile(filename, use_alat=False)
cell_2d_red = pp.get_cell()
assert np.allclose(cell_2d_red, cell_2d_red_ref, atol=1e-15, rtol=0)
pp = parse.PwSCFOutputFile(filename, use_alat=True)
assert np.allclose(pp.get_cell(),
cell_2d_red * pp.get_alat(),
atol=1e-15,
rtol=0)
st = io.read_pw_scf(filename)
tr = io.read_pw_md(filename)
def test_read_dynmat():
table_txt = """
# mode [cm-1] [THz] IR Raman depol.fact
1 0.00 0.0000 0.0000 0.0005 0.7414
2 0.00 0.0000 0.0000 0.0005 0.7465
3 0.00 0.0000 0.0000 0.0018 0.2647
4 252.27 7.5627 0.0000 0.0073 0.7500
5 252.27 7.5627 0.0000 0.0073 0.7500
6 548.44 16.4419 0.0000 0.0000 0.7434
7 603.32 18.0872 35.9045 18.9075 0.7366
8 656.82 19.6910 0.0000 7.9317 0.7500
9 656.82 19.6910 0.0000 7.9317 0.7500
10 669.67 20.0762 31.5712 5.0265 0.7500
11 738.22 22.1311 0.0000 0.0000 0.7306
12 922.64 27.6600 31.5712 5.0265 0.7500
"""
vecs_txt = """
0.03895 -0.03122 -0.00290
0.03895 -0.03122 -0.00290
0.03895 -0.03122 -0.00290
0.03895 -0.03122 -0.00290
-0.03116 -0.03906 0.00186
-0.03116 -0.03906 0.00186
-0.03116 -0.03906 0.00186
-0.03116 -0.03906 0.00186
0.00343 -0.00036 0.04988
0.00343 -0.00036 0.04988
0.00343 -0.00036 0.04988
0.00343 -0.00036 0.04988
0.02589 -0.04674 0.00000
-0.02589 0.04674 0.00000
-0.02244 0.04051 0.00000
0.02244 -0.04051 0.00000
0.04674 0.02589 0.00000
-0.04674 -0.02589 0.00000
-0.04051 -0.02244 0.00000
0.04051 0.02244 0.00000
0.00000 0.00000 0.07029
0.00000 0.00000 -0.07029
0.00000 0.00000 -0.00766
0.00000 0.00000 0.00766
0.00000 0.00000 -0.03258
0.00000 0.00000 -0.03258
0.00000 0.00000 0.06276
0.00000 0.00000 0.06276
-0.02867 -0.00445 0.00000
0.02867 0.00445 0.00000
-0.06372 -0.00990 0.00000
0.06372 0.00990 0.00000
0.00445 -0.02867 0.00000
-0.00445 0.02867 0.00000
0.00990 -0.06372 0.00000
-0.00990 0.06372 0.00000
0.00000 0.03258 0.00000
0.00000 0.03258 0.00000
0.00000 -0.06276 0.00000
0.00000 -0.06276 0.00000
0.00000 0.00000 -0.00399
0.00000 0.00000 0.00399
0.00000 0.00000 -0.07060
0.00000 0.00000 0.07060
-0.03258 0.00000 0.00000
-0.03258 0.00000 0.00000
0.06276 0.00000 0.00000
0.06276 0.00000 0.00000
"""
arr = parse.arr2d_from_txt(table_txt)
freqs_ref = arr[:,1]
ir_ref = arr[:,3]
raman_ref = arr[:,4]
depol_ref = arr[:,5]
vecs_flat = parse.arr2d_from_txt(vecs_txt)
natoms = 4
nmodes = 3*natoms
vecs_ref = np.empty((nmodes, natoms, 3), dtype=float)
for imode in range(nmodes):
for iatom in range(natoms):
idx = imode*natoms + iatom
vecs_ref[imode, iatom,:] = vecs_flat[idx, :]
qpoints,freqs,vecs = pwscf.read_dynmat(path='files/dynmat',
filename='dynmat_all.out',
axsf='dynmat.axsf',
natoms=natoms)
assert np.allclose(freqs_ref, freqs)
assert np.allclose(vecs_ref, vecs)
assert (qpoints == np.array([0,0,0])).all()
dct = pwscf.read_dynmat_ir_raman(filename='files/dynmat/dynmat_all.out',
natoms=natoms)
assert np.allclose(dct['freqs'], freqs_ref)
assert np.allclose(dct['ir'], ir_ref)
assert np.allclose(dct['raman'], raman_ref)
assert np.allclose(dct['depol'], depol_ref)
dct = pwscf.read_dynmat_ir_raman(filename='files/dynmat/dynmat_min.out',
natoms=natoms)
assert np.allclose(dct['freqs'], freqs_ref)
assert np.allclose(dct['ir'], ir_ref)
assert dct['raman'] is None
assert dct['depol'] is None
# Test parsing the correct SCF cell from a [vc-]relax run (QE 5.x only, IIRC),
# which performs a final SCF run after the relax has converged.
import os
import numpy as np
from pwtools import common, crys, parse, io
# from pw.out: "reduced cell" = cell / alat
cell_2d_red_ref = parse.arr2d_from_txt("""
1.000000 0.000000 0.000000
0.000000 2.902399 0.000000
0.000000 0.000000 2.304846
""")
def test_scf_cell():
filename = 'files/pw.vc_relax_coords_fixed.out'
common.system('gunzip %s.gz' %filename)
pp = parse.PwSCFOutputFile(filename, use_alat=False)
cell_2d_red = pp.get_cell()
assert np.allclose(cell_2d_red, cell_2d_red_ref, atol=1e-15, rtol=0)
pp = parse.PwSCFOutputFile(filename, use_alat=True)
assert np.allclose(pp.get_cell(),
cell_2d_red*pp.get_alat(),
atol=1e-15,
rtol=0)
st = io.read_pw_scf(filename)
tr = io.read_pw_md(filename)
