def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
print(phbands)
assert PhononBands.as_phbands(phbands) is phbands
assert np.array_equal(
PhononBands.as_phbands(filename).phfreqs, phbands.phfreqs)
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
self.assertEqual(phbands.minfreq, 0.0)
#self.assertEqual(phbands.maxfreq, 30)
# Test XYZ vib
_, filename = tempfile.mkstemp(text=True)
phbands.create_xyz_vib(iqpt=0,
filename=filename,
max_supercell=[4, 4, 4])
# Test convertion to eigenvectors. Verify that they are orthonormal
# Allow relatively large tolerance due to possible mismatching in the atomic masses between abinit and pmg
eig = phbands.dyn_mat_eigenvect
self.assertTrue(
np.allclose(np.dot(eig[0], eig[0].T),
np.eye(len(eig[0]), dtype=np.complex),
atol=1e-5,
rtol=1e-3))
def read_phbands_on_qpath(self):
"""
Return a list of |PhononBands| computed at the different volumes.
The ``iv0`` entry corresponds to the central point used to compute Grunesein parameters
with finite differences. This object stores the Grunesein parameters in ``grun_vals``.
"""
if "gruns_qpath" not in self.rootgrp.variables:
cprint(
"File `%s` does not contain phonon bands, returning empty list."
% self.path, "yellow")
return []
qfrac_coords = self.read_value("gruns_qpath")
grun_vals = self.read_value("gruns_gvals_qpath")
freqs_vol = self.read_value("gruns_wvols_qpath") * abu.Ha_eV
# TODO: Convert?
dwdq_qpath = self.read_value("gruns_dwdq_qpath")
amuz = self.read_amuz_dict()
#print("amuz", amuz)
# nctkarr_t("gruns_phdispl_cart_qpath", "dp", &
# "two, number_of_phonon_modes, number_of_phonon_modes, gruns_nvols, gruns_nqpath") &
# NOTE: in GRUNS the displacements are in Bohr. here we convert to Ang to be
# consistent with the PhononBands API.
phdispl_cart_qptsvol = self.read_value("gruns_phdispl_cart_qpath",
cmode="c") * abu.Bohr_Ang
lattices = self.read_value(
"gruns_rprimd"
) * abu.Bohr_Ang #, "dp", "three, three, gruns_nvols")
gruns_xred = self.read_value(
"gruns_xred") #, "dp", "three, number_of_atoms, gruns_nvols")
structures = self.read_structures()
phbands_qpath_vol = []
for ivol in range(self.num_volumes):
structure = structures[ivol]
# TODO non_anal_ph
qpoints = Kpath(structure.reciprocal_lattice, qfrac_coords)
phdispl_cart = phdispl_cart_qptsvol[:, ivol].copy()
phb = PhononBands(structure,
qpoints,
freqs_vol[:, ivol],
phdispl_cart,
non_anal_ph=None,
amu=amuz)
# Add Grunesein parameters.
if ivol == self.iv0: phb.grun_vals = grun_vals
phbands_qpath_vol.append(phb)
return phbands_qpath_vol
def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
print(phbands)
assert PhononBands.as_phbands(phbands) is phbands
assert np.array_equal(
PhononBands.as_phbands(filename).phfreqs, phbands.phfreqs)
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
self.assertEqual(phbands.minfreq, 0.0)
#self.assertEqual(phbands.maxfreq, 30)
# Test XYZ vib
phbands.create_xyz_vib(iqpt=0,
filename=self.get_tmpname(text=True),
max_supercell=[4, 4, 4])
# Test ascii file
phbands.create_ascii_vib(iqpts=0,
filename=self.get_tmpname(text=True),
pre_factor=1)
# Test phononwebsite file
phbands.create_phononwebsite_json(filename=self.get_tmpname(text=True),
name='test')
# Test xmgrace
phbands.to_xmgrace(self.get_tmpname(text=True))
# Test convertion to eigenvectors. Verify that they are orthonormal
# Allow relatively large tolerance due to possible mismatching in the atomic masses between abinit and pmg
eig = phbands.dyn_mat_eigenvect
assert np.allclose(np.dot(eig[0], eig[0].T),
np.eye(len(eig[0]), dtype=np.complex),
atol=1e-5,
rtol=1e-3)
if self.has_matplotlib():
phbands.plot(show=False)
phbands.plot_fatbands(show=False)
phbands.plot_colored_matched(show=False)
# Cannot compute PHDOS with q-path
with self.assertRaises(ValueError):
phdos = phbands.get_phdos()
# convert to pymatgen object
phbands.to_pymatgen()
def read_phbands_on_qpath(self):
"""
Return a list of |PhononBands| computed at the different volumes.
The ``iv0`` entry corresponds to the central point used to compute Grunesein parameters
with finite differences. This object stores the Grunesein parameters in ``grun_vals``.
"""
if "gruns_qpath" not in self.rootgrp.variables:
cprint("File `%s` does not contain phonon bands, returning empty list." % self.path, "yellow")
return []
qfrac_coords = self.read_value("gruns_qpath")
grun_vals = self.read_value("gruns_gvals_qpath")
freqs_vol = self.read_value("gruns_wvols_qpath") * abu.Ha_eV
# TODO: Convert?
dwdq_qpath = self.read_value("gruns_dwdq_qpath")
amuz = self.read_amuz_dict()
#print("amuz", amuz)
# nctkarr_t("gruns_phdispl_cart_qpath", "dp", &
# "two, number_of_phonon_modes, number_of_phonon_modes, gruns_nvols, gruns_nqpath") &
# NOTE: in GRUNS the displacements are in Bohr. here we convert to Ang to be
# consistent with the PhononBands API.
phdispl_cart_qptsvol = self.read_value("gruns_phdispl_cart_qpath", cmode="c") * abu.Bohr_Ang
lattices = self.read_value("gruns_rprimd") * abu.Bohr_Ang #, "dp", "three, three, gruns_nvols")
gruns_xred = self.read_value("gruns_xred") #, "dp", "three, number_of_atoms, gruns_nvols")
phbands_qpath_vol = []
for ivol in range(self.num_volumes):
# TODO structure depends on:
# volumes
# non_anal_ph
# amu: DONE
# phdispl_cart DONE
if ivol == self.iv0:
structure = self.structure
else:
structure = self.structure.__class__(lattices[ivol], self.structure.species, gruns_xred[ivol])
qpoints = Kpath(structure.reciprocal_lattice, qfrac_coords)
phdispl_cart = phdispl_cart_qptsvol[:, ivol].copy()
phb = PhononBands(structure, qpoints, freqs_vol[:, ivol], phdispl_cart, non_anal_ph=None, amu=amuz)
# Add Grunesein parameters.
if ivol == self.iv0: phb.grun_vals = grun_vals
phbands_qpath_vol.append(phb)
return phbands_qpath_vol
def setUpClass(cls):
cls.strains = [-4, -2, 0, 2, 4, 6]
path = os.path.join(abidata.dirpath, "refs", "si_qha")
cls.gsr_paths = [os.path.join(path, "mp-149_{:+d}_GSR.nc".format(s)) for s in cls.strains]
cls.dos_paths = [os.path.join(path, "mp-149_{:+d}_PHDOS.nc".format(s)) for s in cls.strains]
cls.phbs = [PhononBands.from_file(os.path.join(path, "mp-149_{:+d}_PHBST.nc".format(s))) for s in
cls.strains[2:4]]
def test_base(self):
"""Testing DielectricTensor"""
anaddbnc_fname = abidata.ref_file("AlAs_nl_dte_anaddb.nc")
phbstnc_fname = abidata.ref_file("AlAs_nl_dte_PHBST.nc")
d = DielectricTensorGenerator.from_files(phbstnc_fname, anaddbnc_fname)
assert d.eps0.shape == (3, 3)
df = d.epsinf.get_dataframe()
assert d.epsinf._repr_html_()
repr(d); str(d)
assert d.to_string(verbose=2)
df = d.get_oscillator_dataframe(reim="all", tol=1e-8)
df = d.get_oscillator_dataframe(reim="im", tol=1e-8)
df = d.get_oscillator_dataframe(reim="re", tol=1e-8)
self.assertAlmostEqual(d.tensor_at_frequency(0.001, units='Ha', gamma_ev=0.0)[0, 0], 11.917178540635028)
d = DielectricTensorGenerator.from_objects(PhononBands.from_file(phbstnc_fname),
AnaddbNcFile.from_file(anaddbnc_fname))
self.assertAlmostEqual(d.tensor_at_frequency(0.001, units='Ha', gamma_ev=0.0)[0, 0], 11.917178540635028)
if self.has_matplotlib():
assert d.plot_vs_w(w_min=0.0001, w_max=0.01, num=10, units="Ha", show=False)
assert d.plot_vs_w(w_min=0, w_max=None, num=10, units="cm-1", show=False)
for comp in ["diag", "all", "diag_av"]:
assert d.plot_vs_w(num=10, component=comp, units="cm-1", show=False)
def test_frozen(self):
"""Base tests for FrozenPhonon"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
qpt_frac_coords = [0.5, 0.5, 0.5]
fp = FrozenPhonon.from_phbands(phbands, qpt_frac_coords, 0 ,
etas=[-0.2, -0.1, 0, 0.1, 0.2], max_supercell=[5,5,5])
self.assertArrayEqual(fp.scale_matrix, [[-1, 0, 1], [-1, 1, 0], [-1, -1, 0]])
w = phbands.phfreqs[phbands.qindex(qpt_frac_coords), 0]
energies = [0.0704, 0.0176, 0. , 0.0175, 0.0703]
with self.assertRaises(ValueError):
fp.energies = energies[:3]
fp.energies = energies
assert fp.ieta0 == 2
assert fp.n_displ == 5
fit_data = fp.fit_to_frequency()
self.assertAlmostEqual(w, fit_data.freq, places=5)
fit_data = fp.fit_to_frequency(min_fit_eta=-0.15, max_fit_eta=0.15)
self.assertNotAlmostEqual(w, fit_data.freq, places=5)
self.assertArrayAlmostEqual(fp.qpt_cart_coords, [0.55954285702497808, 0.55954285702497808, 0.55954285702497808])
if self.has_matplotlib():
assert fp.plot_fit_energies(freq=w, show=False)
assert fp.plot_anharmonic_contribution(freq=w, show=False)
assert fp.plot_anharmonic_contribution(freq=w, relative=True, show=False)
def test_base(self):
"""Testing DielectricTensor"""
anaddbnc_fname = abidata.ref_file("AlAs_nl_dte_anaddb.nc")
phbstnc_fname = abidata.ref_file("AlAs_nl_dte_PHBST.nc")
d = DielectricTensorGenerator.from_files(phbstnc_fname, anaddbnc_fname)
repr(d)
str(d)
self.assertAlmostEqual(
d.tensor_at_frequency(0.001, units='Ha')[0, 0], 11.917178540635028)
d = DielectricTensorGenerator.from_objects(
PhononBands.from_file(phbstnc_fname),
AnaddbNcFile.from_file(anaddbnc_fname))
self.assertAlmostEqual(
d.tensor_at_frequency(0.001, units='Ha')[0, 0], 11.917178540635028)
if self.has_matplotlib():
assert d.plot_vs_w(w_min=0.0001,
w_max=0.01,
num=10,
units="Ha",
show=False)
assert d.plot_vs_w(w_min=0,
w_max=None,
num=10,
units="cm-1",
show=False)
for comp in ["diag", "all", "diag_av"]:
assert d.plot_vs_w(num=10,
component=comp,
units="cm-1",
show=False)
def setUpClass(cls):
cls.strains = [-4, -2, 0, 2, 4, 6]
dirpath = os.path.join(abidata.dirpath, "refs", "si_qha")
cls.gsr_paths = [os.path.join(dirpath, "mp-149_{:+d}_GSR.nc".format(s)) for s in cls.strains]
cls.dos_paths = [os.path.join(dirpath, "mp-149_{:+d}_PHDOS.nc".format(s)) for s in cls.strains]
cls.ddb_paths = [os.path.join(dirpath, "mp-149_{:+d}_DDB".format(s)) for s in cls.strains]
cls.phbs_list = [PhononBands.from_file(os.path.join(dirpath, "mp-149_{:+d}_PHBST.nc".format(s))) for s in
cls.strains[2:4]]
def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
print(phbands)
assert PhononBands.as_phbands(phbands) is phbands
assert np.array_equal(PhononBands.as_phbands(filename).phfreqs, phbands.phfreqs)
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
self.assertEqual(phbands.minfreq, 0.0)
#self.assertEqual(phbands.maxfreq, 30)
# Test XYZ vib
_, filename = tempfile.mkstemp(text=True)
phbands.create_xyz_vib(iqpt=0, filename=filename, max_supercell=[4,4,4])
# Test convertion to eigenvectors. Verify that they are orthonormal
# Allow relatively large tolerance due to possible mismatching in the atomic masses between abinit and pmg
eig = phbands.dyn_mat_eigenvect
self.assertTrue(np.allclose(np.dot(eig[0], eig[0].T), np.eye(len(eig[0]), dtype=np.complex), atol=1e-5, rtol=1e-3))
def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
print(phbands)
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
self.assertEqual(phbands.minfreq, 0.0)
#self.assertEqual(phbands.maxfreq, 30)
# Test XYZ vib
_, filename = tempfile.mkstemp(text=True)
phbands.create_xyz_vib(iqpt=0, filename=filename, max_supercell=[4,4,4])
def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
print(phbands)
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
self.assertEqual(phbands.minfreq, 0.0)
#self.assertEqual(phbands.maxfreq, 30)
# Test XYZ vib
_, filename = tempfile.mkstemp(text=True)
phbands.create_xyz_vib(iqpt=0,
filename=filename,
max_supercell=[4, 4, 4])
def test_frozen(self):
"""Base tests for FrozenPhonon"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
qpt_frac_coords = [0.5, 0.5, 0.5]
fp = FrozenPhonon.from_phbands(phbands,
qpt_frac_coords,
0,
etas=[-0.2, -0.1, 0, 0.1, 0.2],
max_supercell=[5, 5, 5])
self.assertArrayEqual(fp.scale_matrix,
[[-1, 0, 1], [-1, 1, 0], [-1, -1, 0]])
w = phbands.phfreqs[phbands.qindex(qpt_frac_coords), 0]
energies = [0.0704, 0.0176, 0., 0.0175, 0.0703]
with self.assertRaises(ValueError):
fp.energies = energies[:3]
fp.energies = energies
assert fp.ieta0 == 2
assert fp.n_displ == 5
fit_data = fp.fit_to_frequency()
self.assertAlmostEqual(w, fit_data.freq, places=5)
fit_data = fp.fit_to_frequency(min_fit_eta=-0.15, max_fit_eta=0.15)
self.assertNotAlmostEqual(w, fit_data.freq, places=5)
self.assertArrayAlmostEqual(
fp.qpt_cart_coords,
[0.55954285702497808, 0.55954285702497808, 0.55954285702497808])
if self.has_matplotlib():
assert fp.plot_fit_energies(freq=w, show=False)
assert fp.plot_anharmonic_contribution(freq=w, show=False)
assert fp.plot_anharmonic_contribution(freq=w,
relative=True,
show=False)
# The PHDOS.nc files can be obtained from the DDB used ddb.anaget_phbst_and_phdos_files(...)
qha = QHA.from_files(gsr_paths, dos_paths)
# To change the default EOS (vinet), use
#qha.set_eos("murnaghan")
qha.plot_energies(title="Energies as a function of volume for different T")
qha.plot_thermal_expansion_coeff(
title="Thermal expansion coefficient as a function of T")
qha.plot_vol_vs_t(title="Volume as a function of T")
# Fake temperatures to test the plotting function.
phbs_list = [
PhononBands.from_file(
os.path.join(dirpath, "mp-149_{:+d}_PHBST.nc".format(s)))
for s in strains[2:4]
]
qha.plot_phbs(phbs_list,
temperatures=[10, 20],
title="Phonon band structures with color depending on T")
# Here we build a Phonopy QHA object.
# Cannot run this code because it breaks sphinx-gallery
#qha_phonopy = qha.get_phonopy_qha(tstop=500, num=11)
#qha_phonopy.run()
#qha_phonopy.plot_bulk_modulus_temperature().show()
def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
repr(phbands); str(phbands)
assert phbands.to_string(title="Title", with_structure=False, with_qpoints=True, verbose=1)
assert PhononBands.as_phbands(phbands) is phbands
with self.assertRaises(TypeError):
PhononBands.as_phbands({})
assert np.array_equal(PhononBands.as_phbands(filename).phfreqs, phbands.phfreqs)
with abilab.abiopen(abidata.ref_file("trf2_5.out_PHBST.nc")) as nc:
repr(nc); str(nc)
assert nc.to_string(verbose=1)
assert nc.params["nqpt"] == len(nc.qpoints)
assert nc.qpoints.is_path
assert any(q.name is not None for q in nc.qpoints)
same_phbands_nc = PhononBands.as_phbands(nc)
self.assert_equal(same_phbands_nc.phfreqs, phbands.phfreqs)
assert phbands.phdispl_cart.shape == (phbands.nqpt, phbands.num_branches, phbands.num_branches)
# a + b gives plotter
assert hasattr(same_phbands_nc + phbands, "combiplot")
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
# From pickle file.
tmp_path = self.get_tmpname(suffix=".pickle")
with open(tmp_path, "wb") as fh:
pickle.dump(phbands, fh)
same_phbands = PhononBands.as_phbands(tmp_path)
self.assert_equal(same_phbands.phfreqs, phbands.phfreqs)
# a + b + c gives plotter
p = phbands + same_phbands + same_phbands_nc
assert hasattr(p, "combiplot")
assert phbands.minfreq == 0.0
#self.assertEqual(phbands.maxfreq, 30)
assert phbands.phfactor_ev2units("eV") == abu.phfactor_ev2units("eV")
# Test XYZ vib
phbands.create_xyz_vib(iqpt=0, filename=self.get_tmpname(text=True), max_supercell=[4, 4, 4])
# Test ascii file
phbands.create_ascii_vib(iqpts=0, filename=self.get_tmpname(text=True), pre_factor=1)
# Test phononwebsite file
phbands.create_phononwebsite_json(filename=self.get_tmpname(text=True), name='test')
assert phbands.view_phononwebsite(verbose=1, dryrun=True) == 0
# Test xmgrace
phbands.to_xmgrace(self.get_tmpname(text=True))
#phbands.to_xmgrace(sys.stdout)
df = phbands.get_dataframe()
assert "freq" in df and "mode" in df
self.assert_almost_equal(df["freq"].values.min(), 0)
umodes = phbands.get_unstable_modes(below_mev=-1000)
assert len(umodes) == 0
acoustic_modes = phbands.acoustic_indices((0, 0, 0))
self.assertArrayEqual(acoustic_modes, [0, 1, 2])
asr_breaking = phbands.asr_breaking()
assert asr_breaking.absmax_break == 0
# Test convertion to eigenvectors. Verify that they are orthonormal
# Allow relatively large tolerance due to possible mismatching in the atomic masses between abinit and pmg
# (Note that amu is None here)
assert phbands.amu is None
eig = phbands.dyn_mat_eigenvect
assert len(eig) == phbands.nqpt
cidentity = np.eye(len(eig[0]), dtype=np.complex)
for iq in range(len(eig)):
#print("About to test iq", iq, np.dot(eig[iq], eig[iq].T))
#assert np.allclose(np.dot(eig[iq], eig[iq].T), cidentity , atol=1e-5, rtol=1e-3)
assert np.allclose(np.dot(eig[iq].conjugate().T, eig[iq]), cidentity , atol=1e-5, rtol=1e-3)
#self.assert_almost_equal(np.dot(eig[iq].conjugate().T, eig[iq]), cidentity)
# Mapping reduced coordinates -> labels
qlabels = {
(0,0,0): r"$\Gamma$",
(0.375, 0.375, 0.75): "K",
(0.5, 0.5, 1.0): "X",
(0.5, 0.5, 0.5): "L",
(0.5, 0.0, 0.5): "X",
(0.5, 0.25, 0.75): "W",
}
if self.has_matplotlib():
assert phbands.plot(units="Thz", show=False)
assert phbands.plot_fatbands(units="ha", qlabels=qlabels, show=False)
assert phbands.plot_fatbands(phdos_file=abidata.ref_file("trf2_5.out_PHDOS.nc"), units="thz", show=False)
assert phbands.plot_colored_matched(units="cm^-1", show=False)
assert phbands.plot_phdispl(qpoint=(0, 0, 0), units="cm^-1", hatches=None, show=False)
assert phbands.plot_phdispl(qpoint=(0, 0, 0), units="cm^-1", hatches=None, show=False, cart_dir="x+y")
assert phbands.plot_phdispl(qpoint=(0, 0, 0), units="cm^-1", hatches=None, show=False, use_sqrt=True,
normalize=False)
with self.assertRaises(ValueError):
# No LO-TO terms
assert phbands.plot_phdispl(qpoint=1, is_non_analytical_direction=True, show=False)
assert phbands.plot_phdispl_cartdirs(qpoint=0, units="cm^-1", show=False)
assert phbands.boxplot(units="ev", mode_range=[2, 4], show=False)
# Cannot compute PHDOS with q-path
with self.assertRaises(ValueError):
phdos = phbands.get_phdos()
# convert to pymatgen object
phbands.to_pymatgen()
# get frozen phonons
phbands.get_frozen_phonons((0.5, 0.5, 1.0), 1, eta=0.5, max_supercell=[5,5,5])
assert not phbands.has_linewidths
phbands.linewidths = np.ones(phbands.shape)
assert phbands.has_linewidths
def test_base(self):
"""Base tests for PhononBands"""
filename = abidata.ref_file("trf2_5.out_PHBST.nc")
phbands = PhononBands.from_file(filename)
repr(phbands)
str(phbands)
assert phbands.to_string(title="Title",
with_structure=False,
with_qpoints=True,
verbose=1)
assert PhononBands.as_phbands(phbands) is phbands
with self.assertRaises(TypeError):
PhononBands.as_phbands({})
assert np.array_equal(
PhononBands.as_phbands(filename).phfreqs, phbands.phfreqs)
with abilab.abiopen(abidata.ref_file("trf2_5.out_PHBST.nc")) as nc:
repr(nc)
str(nc)
assert nc.to_string(verbose=1)
assert nc.params["nqpt"] == len(nc.qpoints)
assert nc.qpoints.is_path
assert any(q.name is not None for q in nc.qpoints)
same_phbands_nc = PhononBands.as_phbands(nc)
self.assert_equal(same_phbands_nc.phfreqs, phbands.phfreqs)
assert phbands.phdispl_cart.shape == (phbands.nqpt,
phbands.num_branches,
phbands.num_branches)
# a + b gives plotter
assert hasattr(same_phbands_nc + phbands, "combiplot")
assert phbands.epsinf is None and phbands.zcart is None
self.serialize_with_pickle(phbands, protocols=[-1], test_eq=False)
# From pickle file.
tmp_path = self.get_tmpname(suffix=".pickle")
with open(tmp_path, "wb") as fh:
pickle.dump(phbands, fh)
same_phbands = PhononBands.as_phbands(tmp_path)
self.assert_equal(same_phbands.phfreqs, phbands.phfreqs)
# a + b + c gives plotter
p = phbands + same_phbands + same_phbands_nc
assert hasattr(p, "combiplot")
assert phbands.minfreq == 0.0
#self.assertEqual(phbands.maxfreq, 30)
assert phbands.phfactor_ev2units("eV") == abu.phfactor_ev2units("eV")
# Test XYZ vib
phbands.create_xyz_vib(iqpt=0,
filename=self.get_tmpname(text=True),
max_supercell=[4, 4, 4])
# Test ascii file
phbands.create_ascii_vib(iqpts=0,
filename=self.get_tmpname(text=True),
pre_factor=1)
# Test phononwebsite file
phbands.create_phononwebsite_json(filename=self.get_tmpname(text=True),
name='test')
assert phbands.view_phononwebsite(verbose=1, dryrun=True) == 0
# Test xmgrace
phbands.to_xmgrace(self.get_tmpname(text=True))
#phbands.to_xmgrace(sys.stdout)
df = phbands.get_dataframe()
assert "freq" in df and "mode" in df
self.assert_almost_equal(df["freq"].values.min(), 0)
umodes = phbands.get_unstable_modes(below_mev=-1000)
assert len(umodes) == 0
acoustic_modes = phbands.acoustic_indices((0, 0, 0))
self.assertArrayEqual(acoustic_modes, [0, 1, 2])
asr_breaking = phbands.asr_breaking()
assert asr_breaking.absmax_break == 0
# Test convertion to eigenvectors. Verify that they are orthonormal
# Allow relatively large tolerance due to possible mismatching in the atomic masses between abinit and pmg
# (Note that amu is None here)
assert phbands.amu is None
eig = phbands.dyn_mat_eigenvect
assert len(eig) == phbands.nqpt
cidentity = np.eye(len(eig[0]), dtype=np.complex)
for iq in range(len(eig)):
#print("About to test iq", iq, np.dot(eig[iq], eig[iq].T))
#assert np.allclose(np.dot(eig[iq], eig[iq].T), cidentity , atol=1e-5, rtol=1e-3)
assert np.allclose(np.dot(eig[iq].conjugate().T, eig[iq]),
cidentity,
atol=1e-5,
rtol=1e-3)
#self.assert_almost_equal(np.dot(eig[iq].conjugate().T, eig[iq]), cidentity)
# Mapping reduced coordinates -> labels
qlabels = {
(0, 0, 0): r"$\Gamma$",
(0.375, 0.375, 0.75): "K",
(0.5, 0.5, 1.0): "X",
(0.5, 0.5, 0.5): "L",
(0.5, 0.0, 0.5): "X",
(0.5, 0.25, 0.75): "W",
}
if self.has_matplotlib():
assert phbands.plot(units="Thz", show=False, temp=300)
assert phbands.plot_fatbands(units="ha",
qlabels=qlabels,
show=False)
assert phbands.plot_fatbands(
phdos_file=abidata.ref_file("trf2_5.out_PHDOS.nc"),
units="thz",
show=False)
assert phbands.plot_colored_matched(units="cm^-1", show=False)
assert phbands.plot_phdispl(qpoint=(0, 0, 0),
units="cm^-1",
hatches=None,
show=False)
assert phbands.plot_phdispl(qpoint=(0, 0, 0),
units="cm^-1",
hatches=None,
show=False,
cart_dir="x+y")
assert phbands.plot_phdispl(qpoint=(0, 0, 0),
units="cm^-1",
hatches=None,
show=False,
use_sqrt=True,
normalize=False)
with self.assertRaises(ValueError):
# No LO-TO terms
assert phbands.plot_phdispl(qpoint=1,
is_non_analytical_direction=True,
show=False)
assert phbands.plot_phdispl_cartdirs(qpoint=0,
units="cm^-1",
show=False)
assert phbands.boxplot(units="ev", mode_range=[2, 4], show=False)
# Cannot compute PHDOS with q-path
with self.assertRaises(ValueError):
phdos = phbands.get_phdos()
# convert to pymatgen object
phbands.to_pymatgen()
# get frozen phonons
phbands.get_frozen_phonons((0.5, 0.5, 1.0),
1,
eta=0.5,
max_supercell=[5, 5, 5])
assert not phbands.has_linewidths
phbands.linewidths = np.ones(phbands.shape)
assert phbands.has_linewidths
def from_phbst(cls, phbst_path, ignore_neg_freqs=True, labels=None):
"""
Creates an instance of the object starting interpolating the acoustic frequencies
from a PHBST netcdf file.
The file should contain a series of directions starting from gamma and with the
same number of points for each direction, as the one produced in the from_ddb method.
Args:
phbst_path: path to the PHBST netcdf file.
ignore_neg_freqs (bool): if True points with negative frequencies will not be
considered in the fit, in order to ignore inaccuracies in the long range
behavior.
labels (list): list of string with the name of the directions.
Returns:
an instance of SoundVelocity
"""
phb = PhononBands.from_file(phbst_path)
structure = phb.structure
rlatt = structure.lattice.reciprocal_lattice
# q points in cartesian coordinate in 1/bohr, the original units are 1/A
qpt_cart_coords = [
rlatt.get_cartesian_coords(c) * bohr_to_angstrom
for c in phb.qpoints.frac_coords
]
qpt_cart_norms = np.linalg.norm(qpt_cart_coords, axis=1)
# find the indices of the gamma points
gamma_ind = []
for i, q in enumerate(phb.qpoints.frac_coords):
if np.array_equal(q, [0, 0, 0]):
gamma_ind.append(i)
n_directions = len(gamma_ind)
n_points = len(phb.qpoints) / n_directions
if not n_points.is_integer():
raise ValueError(
'Error extracting information from {}'.format(phbst_path))
n_points = int(n_points)
phfreqs = phb.phfreqs
eigdisp = phb.phdispl_cart
sound_velocities = []
mode_types = []
directions = []
all_acoustic_freqs = []
all_qpts = []
for i in range(n_directions):
start = n_points * i
# index of the end point used for the slice
# (the position of the last point is actually end-1)
end = n_points * (i + 1)
dir_freqs = phfreqs[start:end]
dir_displ = eigdisp[start:end]
# matching bands
dir_eigv = get_dyn_mat_eigenvec(dir_displ, structure, amu=phb.amu)
n_freqs = 3 * len(structure)
ind_match = np.zeros((n_points, n_freqs), dtype=np.int)
ind_match[0] = range(n_freqs)
for j in range(1, n_points):
k = j - 1
match = match_eigenvectors(dir_eigv[k], dir_eigv[j])
ind_match[j] = [match[m] for m in ind_match[k]]
acoustic_freqs = (dir_freqs[np.arange(n_points)[:, None],
ind_match])[:, 0:3]
acoustic_displ = (dir_displ[np.arange(n_points)[:, None],
ind_match])[:, 0:3]
direction = phb.qpoints[end - 1].frac_coords
direction = np.array(direction) / np.linalg.norm(direction)
directions.append(direction)
# identify the first (not gamma) qpoint with all positive frequencies
first_positive_freq_ind = None
for j in range(1, n_points):
if min(acoustic_freqs[j]) > 0:
first_positive_freq_ind = j
break
if first_positive_freq_ind is None or first_positive_freq_ind - n_points / 2 > 0:
raise ValueError(
"too many negative frequencies along direction {}".format(
direction))
sv = []
mt = []
cart_versor = qpt_cart_coords[end - 1] / np.linalg.norm(
qpt_cart_coords[end - 1])
for k in range(3):
start_fit = 0
if ignore_neg_freqs and first_positive_freq_ind > 1:
start_fit = first_positive_freq_ind
slope, se, _, _ = np.linalg.lstsq(
qpt_cart_norms[start + start_fit:end][:, np.newaxis],
acoustic_freqs[start_fit:, k] * eV_to_Ha,
rcond=None)
sv.append(slope[0] * abu.velocity_at_to_si)
# identify the type of the mode (longitudinal/transversal) based on the
# scalar product between the eigendisplacement and the direction.
disp_0 = acoustic_displ[first_positive_freq_ind + 1, k, 0:3]
disp_0 = disp_0 / np.linalg.norm(disp_0)
scalar_prod = np.abs(np.dot(disp_0, cart_versor))
if scalar_prod > 0.9:
mt.append("longitudinal")
elif scalar_prod < 0.1:
mt.append("transversal")
else:
mt.append(None)
# sort the lists based on the sound velocites
sv, mt, freqs = zip(*sorted(zip(sv, mt, acoustic_freqs.T)))
sound_velocities.append(sv)
mode_types.append(mt)
all_acoustic_freqs.append(freqs)
all_qpts.append(phb.qpoints.frac_coords[start:end])
return cls(directions=directions,
sound_velocities=sound_velocities,
mode_types=mode_types,
structure=structure,
labels=labels,
phfreqs=all_acoustic_freqs,
qpts=all_qpts)
