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
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 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 collect_data(self):
energies = []
volumes = []
# Get the calculations from workflow
from itertools import chain
# wf_list = list(chain(self.get_step(self.volume_expansions).get_sub_workflows(),
# self.get_step(self.start).get_sub_workflows()))
wf_list = self.get_step(self.volume_expansions).get_sub_workflows()
for wf in wf_list:
dos = wf.get_result('dos').get_array('total_dos')
# self.append_to_report('DOS')
# self.append_to_report('{}'.format(dos.tolist()))
energy = wf.get_result(
'optimized_structure_data').get_dict()['energy']
volume = wf.get_result('final_structure').get_cell_volume()
self.append_to_report('{} {}'.format(volume, energy))
energies.append(energy)
volumes.append(volume)
import numpy as np
# data = ArrayData()
# data.set_array('energy', np.array(energies))
# data.set_array('volume', np.array(volumes))
# data.store()
# self.add_result('data', data)
volumes = []
electronic_energies = []
fe_phonon = []
entropy = []
cv = []
thermal_list = []
structures = []
optimized_data = []
inline_params = {}
wf_list = list(
chain(
self.get_step(self.volume_expansions).get_sub_workflows(),
self.get_step(self.start).get_sub_workflows()))
i = 0
for wf in wf_list:
# Check if suitable for qha (no imaginary frequencies in DOS)
try:
freq = wf.get_result('dos').get_array('frequency')
dos = wf.get_result('dos').get_array('total_dos')
except:
continue
mask_neg = np.ma.masked_less(freq, 0.0).mask
mask_pos = np.ma.masked_greater(freq, 0.0).mask
int_neg = -np.trapz(np.multiply(dos[mask_neg], freq[mask_neg]),
x=freq[mask_neg])
int_pos = np.trapz(np.multiply(dos[mask_pos], freq[mask_pos]),
x=freq[mask_pos])
if int_neg / int_pos > 1e-6:
volume = wf.get_result('final_structure').get_cell_volume()
self.append_to_report(
'Volume {} not suitable for QHA (imaginary frequencies in DOS), skipping it'
.format(volume))
continue
# print ('int_neg: {} int_pos: {} rel: {}'.format(int_neg, int_pos, int_neg/int_pos))
# Get necessary data
thermal_list.append(wf.get_result('thermal_properties'))
structures.append(wf.get_result('final_structure'))
optimized_data.append(wf.get_result('optimized_structure_data'))
electronic_energies.append(
wf.get_result('optimized_structure_data').get_dict()['energy'])
volumes.append(wf.get_result('final_structure').get_cell_volume())
# fe_phonon.append(wf.get_result('thermal_properties').get_array('free_energy'))
# entropy.append(wf.get_result('thermal_properties').get_array('entropy'))
# cv.append(wf.get_result('thermal_properties').get_array('cv'))
temperatures = wf.get_result('thermal_properties').get_array(
'temperature')
temperature_fit = np.arange(
0, 1001,
10) #[100, 200, 300, 400, 500, 600, 700, 800, 900, 1000]
fe_phonon.append(
np.interp(
temperature_fit, temperatures,
wf.get_result('thermal_properties').get_array(
'free_energy')))
entropy.append(
np.interp(
temperature_fit, temperatures,
wf.get_result('thermal_properties').get_array('entropy')))
cv.append(
np.interp(temperature_fit, temperatures,
wf.get_result('thermal_properties').get_array('cv')))
temperatures = temperature_fit
i += 1
# inline_params['structure_{}'.format(i)] = wf.get_result('final_structure')
# inline_params['optimized_data_{}'.format(i)] = wf.get_result('optimized_structure_data')
# inline_params['thermal_properties_{}'.format(i)] = wf.get_result('thermal_properties')
# self.append_to_report('accepted: {} {}'.format(i, wf.get_result('thermal_properties').pk))
# entropy = []
# cv = []
# fe_phonon = []
# temperatures = None
# volumes = [value.get_cell_volume() for key, value in inline_params.items() if 'structure' in key.lower()]
# electronic_energies = [value.get_dict()['energy'] for key, value in inline_params.items() if 'optimized_data' in key.lower()]
#
# thermal_properties_list = [key for key, value in inline_params.items() if 'thermal_properties' in key.lower()]
# for key in thermal_properties_list:
# thermal_properties = inline_params[key]
# fe_phonon.append(thermal_properties.get_array('free_energy'))
# entropy.append(thermal_properties.get_array('entropy'))
# cv.append(thermal_properties.get_array('cv'))
# temperatures = thermal_properties.get_array('temperature')
from phonopy import PhonopyQHA
import numpy as np
# Arrange data sorted by volume and transform them to numpy array
sort_index = np.argsort(volumes)
volumes = np.array(volumes)[sort_index]
electronic_energies = np.array(electronic_energies)[sort_index]
temperatures = np.array(temperatures)
fe_phonon = np.array(fe_phonon).T[:, sort_index]
entropy = np.array(entropy).T[:, sort_index]
cv = np.array(cv).T[:, sort_index]
opt = np.argmin(electronic_energies)
# Check minimum energy volume is within the data
if np.ma.masked_less_equal(volumes, volumes[opt]).mask.all():
self.append_to_report(
'higher volume structures are necessary to compute')
if np.ma.masked_greater_equal(volumes, volumes[opt]).mask.all():
self.append_to_report(
'Lower volume structures are necessary to compute')
self.append_to_report('Dimensions T{} : FE{}'.format(
len(temperatures), len(fe_phonon)))
# Calculate QHA
phonopy_qha = PhonopyQHA(
np.array(volumes),
np.array(electronic_energies),
eos="vinet",
temperatures=np.array(temperatures),
free_energy=np.array(fe_phonon),
cv=np.array(cv),
entropy=np.array(entropy),
# t_max=options.t_max,
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()
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))
qha_output.set_array('volume_temperature',
np.array(volume_temperature))
qha_output.set_array('heat_capacity_P_numerical',
np.array(heat_capacity_P_numerical))
qha_output.set_array('volume_expansion', np.array(volume_expansion))
qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))
qha_output.store()
# Test to leave something on folder
# phonopy_qha.plot_pdf_bulk_modulus_temperature()
# import matplotlib
# matplotlib.use('Agg')
repo_path = self._repo_folder.abspath
data_folder = self.current_folder.get_subfolder('DATA_FILES')
data_folder.create()
# phonopy_qha.plot_pdf_bulk_modulus_temperature(filename=repo_path + '/bulk_modulus-temperature.pdf')
phonopy_qha.write_bulk_modulus_temperature(filename='bm')
file = open('bm')
data_folder.create_file_from_filelike(file, 'bulk_modulus-temperature')
# qha_results = calculate_qha_inline(**inline_params)[1]
self.append_to_report('QHA properties calculated and retrieved')
self.add_result('qha', qha_output)
data = ArrayData()
data.set_array('energy', np.array(electronic_energies))
data.set_array('volume', np.array(volumes))
data.store()
self.add_result('data', data)
self.append_to_report('Finishing workflow_workflow')
self.next(self.exit)
def calculate_qha_inline(**kwargs):
from phonopy import PhonopyQHA
from phonopy.structure.atoms import Atoms as PhonopyAtoms
import numpy as np
# structures = kwargs.pop('structures')
# optimized_data = kwargs.pop('optimized_data')
# thermodyamic_properties = kwargs.pop('thermodyamic_properties')
entropy = []
cv = []
# volumes = []
fe_phonon = []
temperatures = None
# structures = [key for key, value in kwargs.items() if 'structure' in key.lower()]
# for key in structures:
# volumes.append(kwargs.pop(key).get_cell_volume())
volumes = [
value.get_cell_volume() for key, value in kwargs.items()
if 'structure' in key.lower()
]
electronic_energies = [
value.get_dict()['energy'] for key, value in kwargs.items()
if 'optimized_data' in key.lower()
]
thermal_properties_list = [
key for key, value in kwargs.items()
if 'thermal_properties' in key.lower()
]
for key in thermal_properties_list:
thermal_properties = kwargs[key]
fe_phonon.append(thermal_properties.get_array('free_energy'))
entropy.append(thermal_properties.get_array('entropy'))
cv.append(thermal_properties.get_array('cv'))
temperatures = thermal_properties.get_array('temperature')
# Arrange data sorted by volume and transform them to numpy array
sort_index = np.argsort(volumes)
volumes = np.array(volumes)[sort_index]
electronic_energies = np.array(electronic_energies)[sort_index]
temperatures = np.array(temperatures)
fe_phonon = np.array(fe_phonon).T[:, sort_index]
entropy = np.array(entropy).T[:, sort_index]
cv = np.array(cv).T[:, sort_index]
opt = np.argmin(electronic_energies)
# Check minimum energy volume is within the data
if np.ma.masked_less_equal(volumes, volumes[opt]).mask.all():
print('higher volume structures are necessary to compute')
exit()
if np.ma.masked_greater_equal(volumes, volumes[opt]).mask.all():
print('Lower volume structures are necessary to compute')
exit()
# print volumes.shape
# print electronic_energies.shape
# print temperatures.shape
# print fe_phonon.shape
# print cv.shape
# print entropy.shape
qha_output = ArrayData()
qha_output.set_array('volumes', volumes)
qha_output.set_array('electronic_energies', electronic_energies)
qha_output.set_array('temperatures', temperatures)
qha_output.set_array('fe_phonon', fe_phonon)
qha_output.set_array('cv', cv)
qha_output.set_array('entropy', entropy)
# Calculate QHA
phonopy_qha = PhonopyQHA(
np.array(volumes),
np.array(electronic_energies),
eos="vinet",
temperatures=np.array(temperatures),
free_energy=np.array(fe_phonon),
cv=np.array(cv),
entropy=np.array(entropy),
# t_max=options.t_max,
verbose=False)
# print phonopy_qha.get_gibbs_temperature()
qha_output = ArrayData()
qha_output.set_array('volumes', volumes)
qha_output.set_array('electronic_energies', electronic_energies)
qha_output.set_array('temperatures', temperatures)
qha_output.set_array('fe_phonon', fe_phonon)
qha_output.set_array('cv', cv)
qha_output.set_array('entropy', entropy)
return {'qha_output': qha_output}
#Get data
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()
qha_output = ArrayData()
# qha_output.set_array('temperature', temperatures)
# qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
# qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
# qha_output.set_array('volume_temperature', np.array(volume_temperature))
# qha_output.set_array('heat_capacity_P_numerical', np.array(heat_capacity_P_numerical))
# qha_output.set_array('volume_expansion', np.array(volume_expansion))
# qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))
# qha_output.store()
return {'qha_output': qha_output}
def calculate_qha_inline(**kwargs):
from phonopy import PhonopyQHA
import numpy as np
# thermal_properties_list = [key for key, value in kwargs.items() if 'thermal_properties' in key.lower()]
# optimized_structure_data_list = [key for key, value in kwargs.items() if 'optimized_structure_data' in key.lower()]
structure_list = [
key for key, value in kwargs.items()
if 'final_structure' in key.lower()
]
volumes = []
electronic_energies = []
fe_phonon = []
entropy = []
cv = []
for i in range(len(structure_list)):
# volumes.append(kwargs.pop(key).get_cell_volume())
volumes.append(
kwargs.pop('final_structure_{}'.format(i)).get_cell_volume())
electronic_energies.append(
kwargs.pop('optimized_structure_data_{}'.format(i)).dict.energy)
thermal_properties = kwargs.pop('thermal_properties_{}'.format(i))
temperatures = thermal_properties.get_array('temperature')
fe_phonon.append(thermal_properties.get_array('free_energy'))
entropy.append(thermal_properties.get_array('entropy'))
cv.append(thermal_properties.get_array('cv'))
sort_index = np.argsort(volumes)
temperatures = np.array(temperatures)
volumes = np.array(volumes)[sort_index]
electronic_energies = np.array(electronic_energies)[sort_index]
fe_phonon = np.array(fe_phonon).T[:, sort_index]
entropy = np.array(entropy).T[:, sort_index]
cv = np.array(cv).T[:, sort_index]
print volumes
print electronic_energies
print temperatures
print fe_phonon
print cv
print entropy
# Calculate QHA
phonopy_qha = PhonopyQHA(
volumes,
electronic_energies,
eos="vinet",
temperatures=temperatures,
free_energy=fe_phonon,
cv=cv,
entropy=entropy,
# t_max=options.t_max,
verbose=True)
try:
qha_output = ArrayData()
qha_output.set_array('temperature', np.array([1, 2, 3, 4]))
qha_output.store()
except:
print qha_output
exit()
# 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()
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))
qha_output.set_array('volume_temperature', np.array(volume_temperature))
qha_output.set_array('heat_capacity_P_numerical',
np.array(heat_capacity_P_numerical))
qha_output.set_array('volume_expansion', np.array(volume_expansion))
qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))
qha_output.store()
return {'qha_data': qha_output}
def calculate_qha_inline(**kwargs):
from phonopy import PhonopyQHA
from phonon_common import get_helmholtz_volume_from_phonopy_qha
import numpy as np
# thermal_properties_list = [key for key, value in kwargs.items() if 'thermal_properties' in key.lower()]
# optimized_structure_data_list = [key for key, value in kwargs.items() if 'optimized_structure_data' in key.lower()]
structure_list = [
key for key, value in kwargs.items()
if 'final_structure' in key.lower()
]
volumes = []
electronic_energies = []
fe_phonon = []
entropy = []
cv = []
for i in range(len(structure_list)):
# volumes.append(kwargs.pop(key).get_cell_volume())
volumes.append(
kwargs.pop('final_structure_{}'.format(i)).get_cell_volume())
electronic_energies.append(
kwargs.pop('optimized_structure_data_{}'.format(i)).dict.energy)
thermal_properties = kwargs.pop('thermal_properties_{}'.format(i))
temperatures = thermal_properties.get_array('temperature')
fe_phonon.append(thermal_properties.get_array('free_energy'))
entropy.append(thermal_properties.get_array('entropy'))
cv.append(thermal_properties.get_array('cv'))
sort_index = np.argsort(volumes)
temperatures = np.array(temperatures)
volumes = np.array(volumes)[sort_index]
electronic_energies = np.array(electronic_energies)[sort_index]
fe_phonon = np.array(fe_phonon).T[:, sort_index]
entropy = np.array(entropy).T[:, sort_index]
cv = np.array(cv).T[:, sort_index]
# Calculate QHA
phonopy_qha = PhonopyQHA(
np.array(volumes),
np.array(electronic_energies),
eos="vinet",
temperatures=np.array(temperatures),
free_energy=np.array(fe_phonon),
cv=np.array(cv),
entropy=np.array(entropy),
# t_max=options.t_max,
verbose=False)
# Get data
free_energy_volume_fitting = get_helmholtz_volume_from_phonopy_qha(
phonopy_qha)
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()
qha_output = ArrayData()
qha_output.set_array('temperatures', np.array(qha_temperatures))
#qha_output.set_array('helmholtz_volume', np.array(helmholtz_volume))
qha_output.set_array('thermal_expansion', np.array(thermal_expansion))
qha_output.set_array('volume_temperature', np.array(volume_temperature))
qha_output.set_array('heat_capacity_P_numerical',
np.array(heat_capacity_P_numerical))
qha_output.set_array('volume_expansion', np.array(volume_expansion))
qha_output.set_array('gibbs_temperature', np.array(gibbs_temperature))
qha_output.set_array('helmholtz_volume_points',
np.array(free_energy_volume_fitting['points']))
qha_output.set_array('helmholtz_volume_fit',
np.array(free_energy_volume_fitting['fit']))
qha_output.set_array('helmholtz_volume_minimum',
np.array(free_energy_volume_fitting['minimum']))
return {'qha_output': qha_output}
np.array(electronic_energies),
eos="vinet",
temperatures=np.array(temperatures),
free_energy=np.array(fe_phonon),
cv=np.array(cv),
entropy=np.array(entropy),
# t_max=options.t_max,
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()
