def get_qha(eos, temperatures, fe_phonon, cv, entropy, t_max=1000):
from phonopy import PhonopyQHA
import numpy as np
phonopy_qha = PhonopyQHA(eos.get_array('volumes'),
eos.get_array('energies'),
eos="vinet",
temperatures=np.array(temperatures),
free_energy=np.array(fe_phonon).T,
cv=np.array(cv),
entropy=np.array(entropy),
t_max=t_max,
verbose=False)
# testing
if __testing__:
import matplotlib.pyplot as plt
plt = phonopy_qha.plot_qha()
plt.show()
qha_results = {'qha_temperatures': phonopy_qha._qha._temperatures[:phonopy_qha._qha._max_t_index],
'helmholtz_volume': phonopy_qha.get_helmholtz_volume(),
'thermal_expansion': phonopy_qha.get_thermal_expansion(),
'volume_temperature': phonopy_qha.get_volume_temperature(),
'heat_capacity_P_numerical': phonopy_qha.get_heat_capacity_P_numerical(),
'volume_expansion': phonopy_qha.get_volume_expansion(),
'gibbs_temperature': phonopy_qha.get_gibbs_temperature()}
return qha_results
class QuasiparticlesQHA():
def __init__(self, args, load_data=False, verbose=False, tmin=None):
input_parameters = reading.read_parameters_from_input_file(args.input_file)
if 'structure_file_name_outcar' in input_parameters:
structure = reading.read_from_file_structure_outcar(input_parameters['structure_file_name_outcar'])
else:
structure = reading.read_from_file_structure_poscar(input_parameters['structure_file_name_poscar'])
structure.get_data_from_dict(input_parameters)
if 'supercell_phonon' in input_parameters:
supercell_phonon = input_parameters['supercell_phonon']
else:
supercell_phonon = np.identity(3)
structure.set_force_constants(get_force_constants_from_file(file_name=input_parameters['force_constants_file_name'],
fc_supercell=supercell_phonon))
if '_mesh_phonopy' in input_parameters:
mesh = input_parameters['_mesh_phonopy']
else:
mesh = [20, 20, 20] # Default
print ('mesh set to: {}'.format(mesh))
if 'bands' in input_parameters is None:
self._bands = structure.get_path_using_seek_path()
else:
self._bands = input_parameters['_band_ranges']
volumes, energies = read_v_e(args.ev, factor=1.0, volume_factor=1.0, pressure=args.pressure)
self._fc_fit = ForceConstantsFitting(structure,
files_temperature=args.ct_data,
files_volume=args.cv_data,
temperatures=args.temperatures,
volumes=volumes,
mesh=mesh,
ref_temperature=args.ref_temperature,
fitting_order=args.order,
tmin=tmin,
use_NAC=True)
if not load_data:
temperatures = self._fc_fit.get_temperature_range()
free_energy = []
entropy = []
cv = []
for v, e in zip(volumes, energies):
print ('Volume: {} Ang. Energy(U): {} eV'.format(v, e))
tp_data = self._fc_fit.get_thermal_properties(volume=v)
free_energy.append(tp_data[0])
entropy.append(tp_data[1])
cv.append(tp_data[2])
free_energy = np.array(free_energy).T
entropy = np.array(entropy).T
cv = np.array(cv).T
np.save('free_energy.npy', free_energy)
np.save('temperatures.npy', temperatures)
np.save('cv.npy', cv)
np.save('entropy.npy', entropy)
else:
free_energy = np.load('free_energy.npy')
temperatures = np.load('temperatures.npy')
cv = np.load('cv.npy')
entropy = np.load('entropy.npy')
self.phonopy_qha = PhonopyQHA(volumes,
energies,
eos="vinet", # options: 'vinet', 'murnaghan' or 'birch_murnaghan'
temperatures=temperatures,
free_energy=free_energy,
cv=cv,
entropy=entropy,
t_max=self.fc_fit.get_temperature_range()[-1],
verbose=False)
# Write data files to disk
self.phonopy_qha.write_bulk_modulus_temperature()
self.phonopy_qha.write_gibbs_temperature()
self.phonopy_qha.write_heat_capacity_P_numerical()
self.phonopy_qha.write_gruneisen_temperature()
self.phonopy_qha.write_thermal_expansion()
self.phonopy_qha.write_helmholtz_volume()
self.phonopy_qha.write_volume_expansion()
self.phonopy_qha.write_volume_temperature()
if verbose:
self.phonopy_qha.plot_qha().show()
# Designed for test only
def volume_shift(self, volume_range=np.arange(-2.0, 2.0, 0.1)):
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
volumes = self.phonopy_qha._qha._volumes
energies = self.phonopy_qha._qha._electronic_energies
free_energy = np.load('free_energy.npy')
temperatures = np.load('temperatures.npy')
cv = np.load('cv.npy')
entropy = np.load('entropy.npy')
for i in volume_range:
volumesi = np.array(volumes) + i
print volumesi
phonopy_qha = PhonopyQHA(volumesi,
energies,
eos="vinet", # options: 'vinet', 'murnaghan' or 'birch_murnaghan'
temperatures=temperatures,
free_energy=free_energy,
cv=cv,
entropy=entropy,
t_max=self.fc_fit.get_temperature_range()[-1],
verbose=False)
cp = phonopy_qha.get_heat_capacity_P_numerical()
import matplotlib.pyplot as plt
import matplotlib.colors as colors
cNorm = colors.Normalize(vmin=volume_range[0], vmax=volume_range[-1])
scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=plt.cm.get_cmap('plasma'))
ax.plot(phonopy_qha._qha._temperatures[:-3], cp, label='{}'.format(i), color=scalarMap.to_rgba(i))
import matplotlib as mpl
ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
mpl.colorbar.ColorbarBase(ax2, cmap=plt.cm.get_cmap('plasma'), norm=cNorm,
spacing='proportional', ticks=volume_range,
boundaries=None, format='%1i')
plt.show()
def plot_dos_gradient(self):
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
volumes = self.phonopy_qha.get_volume_temperature()
temperatures = self.fc_fit.get_temperature_range()
fig, ax = plt.subplots(1,1)
for t, v in zip(temperatures[::40], volumes[::20]):
print ('temperature: {} K'.format(t))
dos = self.fc_fit.get_dos(t, v)
cNorm = colors.Normalize(vmin=temperatures[0], vmax=temperatures[-1])
scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=plt.cm.get_cmap('plasma'))
ax.plot(dos[0], dos[1], color=scalarMap.to_rgba(t))
plt.suptitle('Phonon density of states')
plt.xlabel('Frequency [THz]')
ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
colorbar.ColorbarBase(ax2, cmap=plt.cm.get_cmap('plasma'), norm=cNorm,
spacing='proportional', ticks=temperatures[::40],
boundaries=None, format='%1i')
plt.show()
def plot_band_structure_gradient(self, tmin=300, tmax=1600, tstep=100):
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
def replace_list(text_string):
substitutions = {'GAMMA': u'$\Gamma$',
}
for item in substitutions.iteritems():
text_string = text_string.replace(item[0], item[1])
return text_string
volumes = self.phonopy_qha.get_volume_temperature()
cNorm = colors.Normalize(vmin=tmin, vmax=tmax)
fig, ax = plt.subplots(1,1)
for t in np.arange(tmin, tmax, tstep):
print ('temperature: {} K'.format(t))
v = self.get_volume_at_temperature(t)
scalarMap = plt.cm.ScalarMappable(norm=cNorm, cmap=plt.cm.get_cmap('plasma'))
band_data = self.fc_fit.get_band_structure(t, v, band_ranges=self._bands['ranges'])
for i, freq in enumerate(band_data[1]):
ax.plot(band_data[1][i], band_data[2][i], color=scalarMap.to_rgba(t))
# plt.axes().get_xaxis().set_visible(False)
#plt.axes().get_xaxis().set_ticks([])
plt.ylabel('Frequency [THz]')
plt.xlabel('Wave vector')
plt.xlim([0, band_data[1][-1][-1]])
plt.axhline(y=0, color='k', ls='dashed')
plt.suptitle('Phonon dispersion')
if 'labels' in self._bands:
plt.rcParams.update({'mathtext.default': 'regular'})
labels = self._bands['labels']
labels_e = []
x_labels = []
for i in range(len(band_data[1])):
if labels[i][0] == labels[i - 1][1]:
labels_e.append(replace_list(labels[i][0]))
else:
labels_e.append(
replace_list(labels[i - 1][1]) + '/' + replace_list(labels[i][0]))
x_labels.append(band_data[1][i][0])
x_labels.append(band_data[1][-1][-1])
labels_e.append(replace_list(labels[-1][1]))
labels_e[0] = replace_list(labels[0][0])
plt.xticks(x_labels, labels_e, rotation='horizontal')
ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
colorbar.ColorbarBase(ax2, cmap=plt.cm.get_cmap('plasma'), norm=cNorm,
spacing='proportional', ticks=np.arange(tmin, tmax, tstep),
boundaries=None, format='%1i')
plt.show()
def get_volume_at_temperature(self, temperature):
temperatures = self.get_qha_temperatures()
volumes = self.phonopy_qha.get_volume_temperature()
volume = np.interp(temperature, temperatures, volumes)
return volume
def plot_band_structure_constant_pressure(self, temperature=300, external_data=None):
import matplotlib.pyplot as plt
def replace_list(text_string):
substitutions = {'GAMMA': u'$\Gamma$',
}
for item in substitutions.iteritems():
text_string = text_string.replace(item[0], item[1])
return text_string
volume = self.get_volume_at_temperature(temperature)
fig, ax = plt.subplots(1,1)
band_data = self.fc_fit.get_band_structure(temperature, volume, band_ranges=self._bands['ranges'])
for i, freq in enumerate(band_data[1]):
ax.plot(band_data[1][i], band_data[2][i], color='r')
#plt.axes().get_xaxis().set_ticks([])
plt.ylabel('Frequency [THz]')
plt.xlabel('Wave vector')
plt.xlim([0, band_data[1][-1][-1]])
plt.axhline(y=0, color='k', ls='dashed')
plt.suptitle('Phonon dispersion')
if 'labels' in self._bands:
plt.rcParams.update({'mathtext.default': 'regular'})
labels = self._bands['labels']
labels_e = []
x_labels = []
for i in range(len(band_data[1])):
if labels[i][0] == labels[i - 1][1]:
labels_e.append(replace_list(labels[i][0]))
else:
labels_e.append(
replace_list(labels[i - 1][1]) + '/' + replace_list(labels[i][0]))
x_labels.append(band_data[1][i][0])
x_labels.append(band_data[1][-1][-1])
labels_e.append(replace_list(labels[-1][1]))
labels_e[0] = replace_list(labels[0][0])
plt.xticks(x_labels, labels_e, rotation='horizontal')
ax.plot(external_data[:, 0], external_data[:, 1], 'o', color='b')
plt.show()
def get_qha_temperatures(self):
max_t_index = self.phonopy_qha._qha._get_max_t_index(self.phonopy_qha._qha._temperatures)
temperatures = self.phonopy_qha._qha._temperatures[:max_t_index]
return temperatures
def get_FC_constant_pressure(self):
temperatures = self.get_qha_temperatures()
volumes = self.phonopy_qha.get_volume_temperature()
for t, v in zip(temperatures[::20], volumes[::20]):
fc = self.fc_fit.get_total_force_constants(temperature=t, volume=v)
write_FORCE_CONSTANTS(fc.get_array(), filename='FC_{}'.format(t))
def get_total_shift_constant_pressure(self, qpoint=(0, 0, 0)):
qindex = self.fc_fit.qpoint_to_index(qpoint)
volumes = self.phonopy_qha.get_volume_temperature()
temperatures = self.get_qha_temperatures()
h_frequencies, ev = self.fc_fit.get_harmonic_frequencies_and_eigenvectors()
chk_shift_matrix = []
for v, t in zip(volumes, temperatures):
total_shifts = self.fc_fit.get_total_shifts(volume=v, temperature=t)
chk_shift_matrix.append(total_shifts)
chk_shift_matrix = np.array(chk_shift_matrix).T
return chk_shift_matrix[:, qindex]
def plot_total_shift_constant_pressure(self, qpoint=(0, 0, 0), branch=None):
import matplotlib.pyplot as plt
temperatures = self.get_qha_temperatures()
chk_shift_matrix = self.get_total_shift_constant_pressure(qpoint=qpoint)
plt.suptitle('Total frequency shift at wave vector={} (relative to {} K)'.format(qpoint, self.fc_fit.ref_temperature))
plt.xlabel('Temperature [K]')
plt.ylabel('Frequency shift [THz]')
if branch is None:
plt.plot(temperatures, chk_shift_matrix.T, '-')
else:
plt.title('Branch {}'.format(branch))
plt.plot(temperatures, chk_shift_matrix[branch].T, '-')
plt.show()
@property
def fc_fit(self):
return self._fc_fit
class QuasiparticlesQHA():
def __init__(self, args, load_data=False, verbose=False, tmin=None):
input_parameters = reading.read_parameters_from_input_file(
args.input_file)
if 'structure_file_name_outcar' in input_parameters:
structure = reading.read_from_file_structure_outcar(
input_parameters['structure_file_name_outcar'])
else:
structure = reading.read_from_file_structure_poscar(
input_parameters['structure_file_name_poscar'])
structure.get_data_from_dict(input_parameters)
if 'supercell_phonon' in input_parameters:
supercell_phonon = input_parameters['supercell_phonon']
else:
supercell_phonon = np.identity(3)
structure.set_force_constants(
get_force_constants_from_file(
file_name=input_parameters['force_constants_file_name'],
fc_supercell=supercell_phonon))
if '_mesh_phonopy' in input_parameters:
mesh = input_parameters['_mesh_phonopy']
else:
mesh = [20, 20, 20] # Default
print('mesh set to: {}'.format(mesh))
if 'bands' in input_parameters is None:
self._bands = structure.get_path_using_seek_path()
else:
self._bands = input_parameters['_band_ranges']
volumes, energies = read_v_e(args.ev,
factor=1.0,
volume_factor=1.0,
pressure=args.pressure)
self._fc_fit = ForceConstantsFitting(
structure,
files_temperature=args.ct_data,
files_volume=args.cv_data,
temperatures=args.temperatures,
volumes=volumes,
mesh=mesh,
ref_temperature=args.ref_temperature,
fitting_order=args.order,
tmin=tmin,
use_NAC=True)
if not load_data:
temperatures = self._fc_fit.get_temperature_range()
free_energy = []
entropy = []
cv = []
for v, e in zip(volumes, energies):
print('Volume: {} Ang. Energy(U): {} eV'.format(v, e))
tp_data = self._fc_fit.get_thermal_properties(volume=v)
free_energy.append(tp_data[0])
entropy.append(tp_data[1])
cv.append(tp_data[2])
free_energy = np.array(free_energy).T
entropy = np.array(entropy).T
cv = np.array(cv).T
np.save('free_energy.npy', free_energy)
np.save('temperatures.npy', temperatures)
np.save('cv.npy', cv)
np.save('entropy.npy', entropy)
else:
free_energy = np.load('free_energy.npy')
temperatures = np.load('temperatures.npy')
cv = np.load('cv.npy')
entropy = np.load('entropy.npy')
self.phonopy_qha = PhonopyQHA(
volumes,
energies,
eos="vinet", # options: 'vinet', 'murnaghan' or 'birch_murnaghan'
temperatures=temperatures,
free_energy=free_energy,
cv=cv,
entropy=entropy,
t_max=self.fc_fit.get_temperature_range()[-1],
verbose=False)
# Write data files to disk
self.phonopy_qha.write_bulk_modulus_temperature()
self.phonopy_qha.write_gibbs_temperature()
self.phonopy_qha.write_heat_capacity_P_numerical()
self.phonopy_qha.write_gruneisen_temperature()
self.phonopy_qha.write_thermal_expansion()
self.phonopy_qha.write_helmholtz_volume()
self.phonopy_qha.write_volume_expansion()
self.phonopy_qha.write_volume_temperature()
if verbose:
self.phonopy_qha.plot_qha().show()
# Designed for test only
def volume_shift(self, volume_range=np.arange(-2.0, 2.0, 0.1)):
import matplotlib.pyplot as plt
fig, ax = plt.subplots(1, 1)
volumes = self.phonopy_qha._qha._volumes
energies = self.phonopy_qha._qha._electronic_energies
free_energy = np.load('free_energy.npy')
temperatures = np.load('temperatures.npy')
cv = np.load('cv.npy')
entropy = np.load('entropy.npy')
for i in volume_range:
volumesi = np.array(volumes) + i
print volumesi
phonopy_qha = PhonopyQHA(
volumesi,
energies,
eos=
"vinet", # options: 'vinet', 'murnaghan' or 'birch_murnaghan'
temperatures=temperatures,
free_energy=free_energy,
cv=cv,
entropy=entropy,
t_max=self.fc_fit.get_temperature_range()[-1],
verbose=False)
cp = phonopy_qha.get_heat_capacity_P_numerical()
import matplotlib.pyplot as plt
import matplotlib.colors as colors
cNorm = colors.Normalize(vmin=volume_range[0],
vmax=volume_range[-1])
scalarMap = plt.cm.ScalarMappable(norm=cNorm,
cmap=plt.cm.get_cmap('plasma'))
ax.plot(phonopy_qha._qha._temperatures[:-3],
cp,
label='{}'.format(i),
color=scalarMap.to_rgba(i))
import matplotlib as mpl
ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
mpl.colorbar.ColorbarBase(ax2,
cmap=plt.cm.get_cmap('plasma'),
norm=cNorm,
spacing='proportional',
ticks=volume_range,
boundaries=None,
format='%1i')
plt.show()
def plot_dos_gradient(self):
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
volumes = self.phonopy_qha.get_volume_temperature()
temperatures = self.fc_fit.get_temperature_range()
fig, ax = plt.subplots(1, 1)
for t, v in zip(temperatures[::40], volumes[::20]):
print('temperature: {} K'.format(t))
dos = self.fc_fit.get_dos(t, v)
cNorm = colors.Normalize(vmin=temperatures[0],
vmax=temperatures[-1])
scalarMap = plt.cm.ScalarMappable(norm=cNorm,
cmap=plt.cm.get_cmap('plasma'))
ax.plot(dos[0], dos[1], color=scalarMap.to_rgba(t))
plt.suptitle('Phonon density of states')
plt.xlabel('Frequency [THz]')
ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
colorbar.ColorbarBase(ax2,
cmap=plt.cm.get_cmap('plasma'),
norm=cNorm,
spacing='proportional',
ticks=temperatures[::40],
boundaries=None,
format='%1i')
plt.show()
def plot_band_structure_gradient(self, tmin=300, tmax=1600, tstep=100):
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
def replace_list(text_string):
substitutions = {
'GAMMA': u'$\Gamma$',
}
for item in substitutions.iteritems():
text_string = text_string.replace(item[0], item[1])
return text_string
volumes = self.phonopy_qha.get_volume_temperature()
cNorm = colors.Normalize(vmin=tmin, vmax=tmax)
fig, ax = plt.subplots(1, 1)
for t in np.arange(tmin, tmax, tstep):
print('temperature: {} K'.format(t))
v = self.get_volume_at_temperature(t)
scalarMap = plt.cm.ScalarMappable(norm=cNorm,
cmap=plt.cm.get_cmap('plasma'))
band_data = self.fc_fit.get_band_structure(
t, v, band_ranges=self._bands['ranges'])
for i, freq in enumerate(band_data[1]):
ax.plot(band_data[1][i],
band_data[2][i],
color=scalarMap.to_rgba(t))
# plt.axes().get_xaxis().set_visible(False)
#plt.axes().get_xaxis().set_ticks([])
plt.ylabel('Frequency [THz]')
plt.xlabel('Wave vector')
plt.xlim([0, band_data[1][-1][-1]])
plt.axhline(y=0, color='k', ls='dashed')
plt.suptitle('Phonon dispersion')
if 'labels' in self._bands:
plt.rcParams.update({'mathtext.default': 'regular'})
labels = self._bands['labels']
labels_e = []
x_labels = []
for i in range(len(band_data[1])):
if labels[i][0] == labels[i - 1][1]:
labels_e.append(replace_list(labels[i][0]))
else:
labels_e.append(
replace_list(labels[i - 1][1]) + '/' +
replace_list(labels[i][0]))
x_labels.append(band_data[1][i][0])
x_labels.append(band_data[1][-1][-1])
labels_e.append(replace_list(labels[-1][1]))
labels_e[0] = replace_list(labels[0][0])
plt.xticks(x_labels, labels_e, rotation='horizontal')
ax2 = fig.add_axes([0.93, 0.1, 0.02, 0.8])
colorbar.ColorbarBase(ax2,
cmap=plt.cm.get_cmap('plasma'),
norm=cNorm,
spacing='proportional',
ticks=np.arange(tmin, tmax, tstep),
boundaries=None,
format='%1i')
plt.show()
def get_volume_at_temperature(self, temperature):
temperatures = self.get_qha_temperatures()
volumes = self.phonopy_qha.get_volume_temperature()
volume = np.interp(temperature, temperatures, volumes)
return volume
def plot_band_structure_constant_pressure(self,
temperature=300,
external_data=None):
import matplotlib.pyplot as plt
def replace_list(text_string):
substitutions = {
'GAMMA': u'$\Gamma$',
}
for item in substitutions.iteritems():
text_string = text_string.replace(item[0], item[1])
return text_string
volume = self.get_volume_at_temperature(temperature)
fig, ax = plt.subplots(1, 1)
band_data = self.fc_fit.get_band_structure(
temperature, volume, band_ranges=self._bands['ranges'])
for i, freq in enumerate(band_data[1]):
ax.plot(band_data[1][i], band_data[2][i], color='r')
#plt.axes().get_xaxis().set_ticks([])
plt.ylabel('Frequency [THz]')
plt.xlabel('Wave vector')
plt.xlim([0, band_data[1][-1][-1]])
plt.axhline(y=0, color='k', ls='dashed')
plt.suptitle('Phonon dispersion')
if 'labels' in self._bands:
plt.rcParams.update({'mathtext.default': 'regular'})
labels = self._bands['labels']
labels_e = []
x_labels = []
for i in range(len(band_data[1])):
if labels[i][0] == labels[i - 1][1]:
labels_e.append(replace_list(labels[i][0]))
else:
labels_e.append(
replace_list(labels[i - 1][1]) + '/' +
replace_list(labels[i][0]))
x_labels.append(band_data[1][i][0])
x_labels.append(band_data[1][-1][-1])
labels_e.append(replace_list(labels[-1][1]))
labels_e[0] = replace_list(labels[0][0])
plt.xticks(x_labels, labels_e, rotation='horizontal')
ax.plot(external_data[:, 0], external_data[:, 1], 'o', color='b')
plt.show()
def get_qha_temperatures(self):
max_t_index = self.phonopy_qha._qha._get_max_t_index(
self.phonopy_qha._qha._temperatures)
temperatures = self.phonopy_qha._qha._temperatures[:max_t_index]
return temperatures
def get_FC_constant_pressure(self):
temperatures = self.get_qha_temperatures()
volumes = self.phonopy_qha.get_volume_temperature()
for t, v in zip(temperatures[::20], volumes[::20]):
fc = self.fc_fit.get_total_force_constants(temperature=t, volume=v)
write_FORCE_CONSTANTS(fc.get_array(), filename='FC_{}'.format(t))
def get_total_shift_constant_pressure(self, qpoint=(0, 0, 0)):
qindex = self.fc_fit.qpoint_to_index(qpoint)
volumes = self.phonopy_qha.get_volume_temperature()
temperatures = self.get_qha_temperatures()
h_frequencies, ev = self.fc_fit.get_harmonic_frequencies_and_eigenvectors(
)
chk_shift_matrix = []
for v, t in zip(volumes, temperatures):
total_shifts = self.fc_fit.get_total_shifts(volume=v,
temperature=t)
chk_shift_matrix.append(total_shifts)
chk_shift_matrix = np.array(chk_shift_matrix).T
return chk_shift_matrix[:, qindex]
def plot_total_shift_constant_pressure(self,
qpoint=(0, 0, 0),
branch=None):
import matplotlib.pyplot as plt
temperatures = self.get_qha_temperatures()
chk_shift_matrix = self.get_total_shift_constant_pressure(
qpoint=qpoint)
plt.suptitle(
'Total frequency shift at wave vector={} (relative to {} K)'.
format(qpoint, self.fc_fit.ref_temperature))
plt.xlabel('Temperature [K]')
plt.ylabel('Frequency shift [THz]')
if branch is None:
plt.plot(temperatures, chk_shift_matrix.T, '-')
else:
plt.title('Branch {}'.format(branch))
plt.plot(temperatures, chk_shift_matrix[branch].T, '-')
plt.show()
@property
def fc_fit(self):
return self._fc_fit
verbose=False)
# Get data
qha_temperatures = phonopy_qha._qha._temperatures[:phonopy_qha._qha.
_max_t_index]
helmholtz_volume = phonopy_qha.get_helmholtz_volume()
thermal_expansion = phonopy_qha.get_thermal_expansion()
volume_temperature = phonopy_qha.get_volume_temperature()
heat_capacity_P_numerical = phonopy_qha.get_heat_capacity_P_numerical()
volume_expansion = phonopy_qha.get_volume_expansion()
gibbs_temperature = phonopy_qha.get_gibbs_temperature()
#phonopy_qha.plot_bulk_modulus()
#plt.show()
phonopy_qha.plot_qha()
plt.show()
phonopy_qha.plot_gruneisen_temperature()
plt.show()
phonopy_qha.plot_gibbs_temperature()
plt.show()
phonopy_qha.plot_heat_capacity_P_numerical()
plt.show()
phonopy_qha.write_gibbs_temperature()
phonopy_qha.write_heat_capacity_P_numerical()
qha_output = ArrayData()
qha_output.set_array('temperature', np.array(qha_temperatures))
qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
