def get_f_vib_phonopy(structure, supercell_matrix, vasprun_path,
qpoint_mesh=(50, 50, 50), t_min=5, t_step=5, t_max=2000.0,):
"""
Return F_vib(T) for the unitcell in eV/atom
Parameters
----------
structure : pymatgen.Structure
Unitcell (not supercell) of interest.
supercell_matrix : numpy.ndarray
3x3 matrix of the supercell deformation, e.g. [[3, 0, 0], [0, 3, 0], [0, 0, 3]].
vasprun_path : str
String pointing to a vasprun.xml file from a force constants run
qpoint_mesh : list
Mesh of q-points to calculate thermal properties on.
t_min : float
Minimum temperature
t_step : float
Temperature step size
t_max : float
Maximum temperature (inclusive)
Returns
-------
tuple
Tuple of (temperature, F_vib, S_vib, Cv_vib, force_constants)
"""
# get codename and version from vasprun.xml file
code_name, code_version = get_code_version(xml=vasprun_path)
force_constant_factor = 1.0
if code_version[0:1] >= '6':
force_constant_factor = 0.004091649655126895
# get the force constants from a vasprun.xml file
vasprun = PhonopyVasprun(vasprun_path)
force_constants, elements = vasprun.read_force_constants()
force_constants *= force_constant_factor
ph_unitcell = get_phonopy_structure(structure)
ph = Phonopy(ph_unitcell, supercell_matrix)
# set the force constants we found
ph.set_force_constants(force_constants)
# calculate the thermal properties
ph.run_mesh(qpoint_mesh)
ph.run_thermal_properties(t_min=t_min, t_max=t_max, t_step=t_step)
# the thermal properties are for the unit cell
tp_dict = ph.get_thermal_properties_dict()
temperatures = tp_dict['temperatures']
# convert the units into our expected eV/atom-form (and per K)
f_vib = tp_dict['free_energy'] * J_per_mol_to_eV_per_atom*1000
s_vib = tp_dict['entropy'] * J_per_mol_to_eV_per_atom
cv_vib = tp_dict['heat_capacity'] * J_per_mol_to_eV_per_atom
return temperatures, f_vib, s_vib, cv_vib, ph.force_constants, code_version
def phonon_dos(fcp_file):
if 'fcc2x2x2' in fcp_file:
prim = read(ref_fcc_conv2x2x2)
else:
prim = read(ref_fcc)
fcp = ForceConstantPotential.read(fcp_file)
mesh = [33, 33, 33]
atoms_phonopy = PhonopyAtoms(symbols=prim.get_chemical_symbols(),
scaled_positions=prim.get_scaled_positions(),
cell=prim.cell)
phonopy = Phonopy(atoms_phonopy,
supercell_matrix=5 * np.eye(3),
primitive_matrix=None)
supercell = phonopy.get_supercell()
supercell = Atoms(cell=supercell.cell,
numbers=supercell.numbers,
pbc=True,
scaled_positions=supercell.get_scaled_positions())
fcs = fcp.get_force_constants(supercell)
phonopy.set_force_constants(fcs.get_fc_array(order=2))
phonopy.set_mesh(mesh, is_eigenvectors=True, is_mesh_symmetry=False)
phonopy.run_total_dos()
phonopy.plot_total_DOS()
plt.savefig("phononDOS.png", dpi=200)
Nq = 51
G2X = get_band(np.array([0, 0, 0]), np.array([0.5, 0.5, 0]), Nq)
X2K2G = get_band(np.array([0.5, 0.5, 1.0]), np.array([0, 0, 0]), Nq)
G2L = get_band(np.array([0, 0, 0]), np.array([0.5, 0.5, 0.5]), Nq)
bands = [G2X, X2K2G, G2L]
phonopy.set_band_structure(bands)
phonopy.plot_band_structure()
xticks = plt.gca().get_xticks()
xticks = [x * hbar * 1e15 for x in xticks] # Convert THz to meV
# plt.gca().set_xticks(xticks)
plt.gca().set_xlabel("Frequency (THz)")
plt.savefig("phononBand.png", dpi=200)
phonopy.run_thermal_properties(t_step=10, t_max=800, t_min=100)
tp_dict = phonopy.get_thermal_properties_dict()
temperatures = tp_dict['temperatures']
free_energy = tp_dict['free_energy']
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
ax.plot(temperatures, free_energy)
plt.show()
phonon.plot_band_structure().show()
# Mesh sampling 20x20x20
phonon.run_mesh(mesh=[20, 20, 20])
phonon.run_thermal_properties(t_step=10, t_max=1000, t_min=0)
# DOS
phonon.run_total_dos(sigma=0.1)
dos_dict = phonon.get_total_dos_dict()
for omega, dos in zip(dos_dict['frequency_points'], dos_dict['total_dos']):
print("%15.7f%15.7f" % (omega, dos))
phonon.plot_total_dos().show()
# Thermal properties
tprop_dict = phonon.get_thermal_properties_dict()
for t, free_energy, entropy, cv in zip(tprop_dict['temperatures'],
tprop_dict['free_energy'],
tprop_dict['entropy'],
tprop_dict['heat_capacity']):
print(("%12.3f " + "%15.7f" * 3) % (t, free_energy, entropy, cv))
phonon.plot_thermal_properties().show()
# PDOS
phonon.run_mesh(mesh=[10, 10, 10],
is_mesh_symmetry=False,
with_eigenvectors=True)
phonon.run_projected_dos(use_tetrahedron_method=True)
pdos_dict = phonon.get_projected_dos_dict()
omegas = pdos_dict['frequency_points']
class PhonopyJob(AtomisticParallelMaster):
"""
Args:
project:
job_name:
"""
def __init__(self, project, job_name):
super(PhonopyJob, self).__init__(project, job_name)
self.__name__ = "PhonopyJob"
self.__version__ = "0.0.1"
self.input["interaction_range"] = (10.0,
"Minimal size of supercell, Ang")
self.input["factor"] = (
VaspToTHz,
"Frequency unit conversion factor (default for VASP)",
)
self.input["displacement"] = (0.01, "atoms displacement, Ang")
self.input["dos_mesh"] = (20, "mesh size for DOS calculation")
self.phonopy = None
self._job_generator = PhonopyJobGenerator(self)
self._disable_phonopy_pickle = False
s.publication_add(phonopy_publication())
@property
def phonopy_pickling_disabled(self):
return self._disable_phonopy_pickle
@phonopy_pickling_disabled.setter
def phonopy_pickling_disabled(self, disable):
self._disable_phonopy_pickle = disable
@property
def _phonopy_unit_cell(self):
if self.structure is not None:
return atoms_to_phonopy(self.structure)
else:
return None
def _enable_phonopy(self):
if self.phonopy is None:
if self.structure is not None:
self.phonopy = Phonopy(
unitcell=self._phonopy_unit_cell,
supercell_matrix=self._phonopy_supercell_matrix(),
factor=self.input["factor"],
)
self.phonopy.generate_displacements(
distance=self.input["displacement"])
self.to_hdf()
else:
raise ValueError(
"No reference job/ No reference structure found.")
def list_structures(self):
if self.structure is not None:
self._enable_phonopy()
return [struct for _, struct in self._job_generator.parameter_list]
else:
return []
def _phonopy_supercell_matrix(self):
if self.structure is not None:
supercell_range = np.ceil(
self.input["interaction_range"] / np.array([
np.linalg.norm(vec)
for vec in self._phonopy_unit_cell.get_cell()
]))
return np.eye(3) * supercell_range
else:
return np.eye(3)
def run_static(self):
# Initialise the phonopy object before starting the first calculation.
self._enable_phonopy()
super(PhonopyJob, self).run_static()
def run_if_interactive(self):
self._enable_phonopy()
super(PhonopyJob, self).run_if_interactive()
def to_hdf(self, hdf=None, group_name=None):
"""
Store the PhonopyJob in an HDF5 file
Args:
hdf (ProjectHDFio): HDF5 group object - optional
group_name (str): HDF5 subgroup name - optional
"""
super(PhonopyJob, self).to_hdf(hdf=hdf, group_name=group_name)
if self.phonopy is not None and not self._disable_phonopy_pickle:
with self.project_hdf5.open("output") as hdf5_output:
hdf5_output["phonopy_pickeled"] = codecs.encode(
pickle.dumps(self.phonopy), "base64").decode()
def from_hdf(self, hdf=None, group_name=None):
"""
Restore the PhonopyJob from an HDF5 file
Args:
hdf (ProjectHDFio): HDF5 group object - optional
group_name (str): HDF5 subgroup name - optional
"""
super(PhonopyJob, self).from_hdf(hdf=hdf, group_name=group_name)
with self.project_hdf5.open("output") as hdf5_output:
if "phonopy_pickeled" in hdf5_output.list_nodes():
self.phonopy = pickle.loads(
codecs.decode(hdf5_output["phonopy_pickeled"].encode(),
"base64"))
if "dos_total" in hdf5_output.list_nodes():
self._dos_total = hdf5_output["dos_total"]
if "dos_energies" in hdf5_output.list_nodes():
self._dos_energies = hdf5_output["dos_energies"]
def collect_output(self):
"""
Returns:
"""
if self.ref_job.server.run_mode.interactive:
forces_lst = self.project_hdf5.inspect(
self.child_ids[0])["output/generic/forces"]
else:
pr_job = self.project_hdf5.project.open(self.job_name + "_hdf5")
forces_lst = [
pr_job.inspect(job_name)["output/generic/forces"][-1]
for job_name in self._get_jobs_sorted()
]
self.phonopy.set_forces(forces_lst)
self.phonopy.produce_force_constants()
self.phonopy.run_mesh(mesh=[self.input["dos_mesh"]] * 3)
mesh_dict = self.phonopy.get_mesh_dict()
self.phonopy.run_total_dos()
dos_dict = self.phonopy.get_total_dos_dict()
self.to_hdf()
with self.project_hdf5.open("output") as hdf5_out:
hdf5_out["dos_total"] = dos_dict['total_dos']
hdf5_out["dos_energies"] = dos_dict['frequency_points']
hdf5_out["qpoints"] = mesh_dict['qpoints']
hdf5_out["supercell_matrix"] = self._phonopy_supercell_matrix()
hdf5_out[
"displacement_dataset"] = self.phonopy.get_displacement_dataset(
)
hdf5_out[
"dynamical_matrix"] = self.phonopy.dynamical_matrix.get_dynamical_matrix(
)
hdf5_out["force_constants"] = self.phonopy.force_constants
def write_phonopy_force_constants(self,
file_name="FORCE_CONSTANTS",
cwd=None):
"""
Args:
file_name:
cwd:
Returns:
"""
if cwd is not None:
file_name = posixpath.join(cwd, file_name)
write_FORCE_CONSTANTS(force_constants=self.phonopy.force_constants,
filename=file_name)
def get_hesse_matrix(self):
"""
Returns:
"""
unit_conversion = (
scipy.constants.physical_constants["Hartree energy in eV"][0] /
scipy.constants.physical_constants["Bohr radius"][0]**2 *
scipy.constants.angstrom**2)
force_shape = np.shape(self.phonopy.force_constants)
force_reshape = force_shape[0] * force_shape[2]
return (np.transpose(self.phonopy.force_constants,
(0, 2, 1, 3)).reshape(
(force_reshape, force_reshape)) /
unit_conversion)
def get_thermal_properties(self,
t_min=1,
t_max=1500,
t_step=50,
temperatures=None):
"""
Args:
t_min:
t_max:
t_step:
temperatures:
Returns:
"""
self.phonopy.run_thermal_properties(t_step=t_step,
t_max=t_max,
t_min=t_min,
temperatures=temperatures)
tp_dict = self.phonopy.get_thermal_properties_dict()
return thermal(tp_dict['temperatures'], tp_dict['free_energy'],
tp_dict['entropy'], tp_dict['heat_capacity'])
@property
def dos_total(self):
"""
Returns:
"""
return self["output/dos_total"]
@property
def dos_energies(self):
"""
Returns:
"""
return self["output/dos_energies"]
@property
def dynamical_matrix(self):
"""
Returns:
"""
return np.real_if_close(
self.phonopy.get_dynamical_matrix().get_dynamical_matrix())
def dynamical_matrix_at_q(self, q):
"""
Args:
q:
Returns:
"""
return np.real_if_close(self.phonopy.get_dynamical_matrix_at_q(q))
def plot_dos(self, ax=None, *args, **qwargs):
"""
Args:
*args:
ax:
**qwargs:
Returns:
"""
try:
import pylab as plt
except ImportError:
import matplotlib.pyplot as plt
if ax is None:
fig, ax = plt.subplots(1, 1)
ax.plot(self["output/dos_energies"], self["output/dos_total"], *args,
**qwargs)
ax.set_xlabel("Frequency [THz]")
ax.set_ylabel("DOS")
ax.set_title("Phonon DOS vs Energy")
return ax
class PhonopyJob(AtomisticParallelMaster):
"""
Phonopy wrapper for the calculation of free energy in the framework of quasi harmonic approximation.
Example:
>>> from pyiron_atomistics import Project
>>> pr = Project('my_project')
>>> lmp = pr.create_job('Lammps', 'lammps')
>>> lmp.structure = pr.create_structure('Fe', 'bcc', 2.832)
>>> phono = lmp.create_job('PhonopyJob', 'phonopy')
>>> phono.run()
Get output via `get_thermal_properties()`.
Note:
- This class does not consider the thermal expansion. For this, use `QuasiHarmonicJob` (find more in its
docstring)
- Depending on the value given in `job.input['interaction_range']`, this class automatically changes the number of
atoms. The input parameters of the reference job might have to be set appropriately (e.g. use `k_mesh_density`
for DFT instead of setting k-points directly).
- The structure used in the reference job should be a relaxed structure.
- Theory behind it: https://en.wikipedia.org/wiki/Quasi-harmonic_approximation
"""
def __init__(self, project, job_name):
super(PhonopyJob, self).__init__(project, job_name)
self.__name__ = "PhonopyJob"
self.__version__ = "0.0.1"
self.input["interaction_range"] = (10.0,
"Minimal size of supercell, Ang")
self.input["factor"] = (
VaspToTHz,
"Frequency unit conversion factor (default for VASP)",
)
self.input["displacement"] = (0.01, "atoms displacement, Ang")
self.input["dos_mesh"] = (20, "mesh size for DOS calculation")
self.input["primitive_matrix"] = None
self.phonopy = None
self._job_generator = PhonopyJobGenerator(self)
self._disable_phonopy_pickle = False
s.publication_add(phonopy_publication())
@property
def phonopy_pickling_disabled(self):
return self._disable_phonopy_pickle
@phonopy_pickling_disabled.setter
def phonopy_pickling_disabled(self, disable):
self._disable_phonopy_pickle = disable
@property
def _phonopy_unit_cell(self):
if self.structure is not None:
return atoms_to_phonopy(self.structure)
else:
return None
def _enable_phonopy(self):
if self.phonopy is None:
if self.structure is not None:
self.phonopy = Phonopy(
unitcell=self._phonopy_unit_cell,
supercell_matrix=self._phonopy_supercell_matrix(),
primitive_matrix=self.input["primitive_matrix"],
factor=self.input["factor"],
)
self.phonopy.generate_displacements(
distance=self.input["displacement"])
self.to_hdf()
else:
raise ValueError(
"No reference job/ No reference structure found.")
def list_structures(self):
if self.structure is not None:
self._enable_phonopy()
return [struct for _, struct in self._job_generator.parameter_list]
else:
return []
def _phonopy_supercell_matrix(self):
if self.structure is not None:
supercell_range = np.ceil(
self.input["interaction_range"] / np.array([
np.linalg.norm(vec)
for vec in self._phonopy_unit_cell.get_cell()
]))
return np.eye(3) * supercell_range
else:
return np.eye(3)
def run_static(self):
# Initialise the phonopy object before starting the first calculation.
self._enable_phonopy()
super(PhonopyJob, self).run_static()
def run_if_interactive(self):
self._enable_phonopy()
super(PhonopyJob, self).run_if_interactive()
def to_hdf(self, hdf=None, group_name=None):
"""
Store the PhonopyJob in an HDF5 file
Args:
hdf (ProjectHDFio): HDF5 group object - optional
group_name (str): HDF5 subgroup name - optional
"""
super(PhonopyJob, self).to_hdf(hdf=hdf, group_name=group_name)
if self.phonopy is not None and not self._disable_phonopy_pickle:
with self.project_hdf5.open("output") as hdf5_output:
hdf5_output["phonopy_pickeled"] = codecs.encode(
pickle.dumps(self.phonopy), "base64").decode()
def from_hdf(self, hdf=None, group_name=None):
"""
Restore the PhonopyJob from an HDF5 file
Args:
hdf (ProjectHDFio): HDF5 group object - optional
group_name (str): HDF5 subgroup name - optional
"""
super(PhonopyJob, self).from_hdf(hdf=hdf, group_name=group_name)
with self.project_hdf5.open("output") as hdf5_output:
if "phonopy_pickeled" in hdf5_output.list_nodes():
self.phonopy = pickle.loads(
codecs.decode(hdf5_output["phonopy_pickeled"].encode(),
"base64"))
if "dos_total" in hdf5_output.list_nodes():
self._dos_total = hdf5_output["dos_total"]
if "dos_energies" in hdf5_output.list_nodes():
self._dos_energies = hdf5_output["dos_energies"]
def collect_output(self):
"""
Returns:
"""
if self.ref_job.server.run_mode.interactive:
forces_lst = self.project_hdf5.inspect(
self.child_ids[0])["output/generic/forces"]
else:
pr_job = self.project_hdf5.project.open(self.job_name + "_hdf5")
forces_lst = [
pr_job.inspect(job_name)["output/generic/forces"][-1]
for job_name in self._get_jobs_sorted()
]
self.phonopy.set_forces(forces_lst)
self.phonopy.produce_force_constants()
self.phonopy.run_mesh(mesh=[self.input["dos_mesh"]] * 3)
mesh_dict = self.phonopy.get_mesh_dict()
self.phonopy.run_total_dos()
dos_dict = self.phonopy.get_total_dos_dict()
self.to_hdf()
with self.project_hdf5.open("output") as hdf5_out:
hdf5_out["dos_total"] = dos_dict['total_dos']
hdf5_out["dos_energies"] = dos_dict['frequency_points']
hdf5_out["qpoints"] = mesh_dict['qpoints']
hdf5_out["supercell_matrix"] = self._phonopy_supercell_matrix()
hdf5_out[
"displacement_dataset"] = self.phonopy.get_displacement_dataset(
)
hdf5_out[
"dynamical_matrix"] = self.phonopy.dynamical_matrix.get_dynamical_matrix(
)
hdf5_out["force_constants"] = self.phonopy.force_constants
def write_phonopy_force_constants(self,
file_name="FORCE_CONSTANTS",
cwd=None):
"""
Args:
file_name:
cwd:
Returns:
"""
if cwd is not None:
file_name = posixpath.join(cwd, file_name)
write_FORCE_CONSTANTS(force_constants=self.phonopy.force_constants,
filename=file_name)
def get_hesse_matrix(self):
"""
Returns:
"""
unit_conversion = (
scipy.constants.physical_constants["Hartree energy in eV"][0] /
scipy.constants.physical_constants["Bohr radius"][0]**2 *
scipy.constants.angstrom**2)
force_shape = np.shape(self.phonopy.force_constants)
force_reshape = force_shape[0] * force_shape[2]
return (np.transpose(self.phonopy.force_constants,
(0, 2, 1, 3)).reshape(
(force_reshape, force_reshape)) /
unit_conversion)
def get_thermal_properties(self,
t_min=1,
t_max=1500,
t_step=50,
temperatures=None):
"""
Returns thermal properties at constant volume in the given temperature range. Can only be called after job
successfully ran.
Args:
t_min (float): minimum sample temperature
t_max (float): maximum sample temperature
t_step (int): tempeature sample interval
temperatures (array_like, float): custom array of temperature samples, if given t_min, t_max, t_step are
ignored.
Returns:
:class:`Thermal`: thermal properties as returned by Phonopy
"""
self.phonopy.run_thermal_properties(t_step=t_step,
t_max=t_max,
t_min=t_min,
temperatures=temperatures)
tp_dict = self.phonopy.get_thermal_properties_dict()
kJ_mol_to_eV = 1000 / scipy.constants.Avogadro / scipy.constants.electron_volt
return Thermal(tp_dict['temperatures'],
tp_dict['free_energy'] * kJ_mol_to_eV,
tp_dict['entropy'], tp_dict['heat_capacity'])
@property
def dos_total(self):
"""
Returns:
"""
return self["output/dos_total"]
@property
def dos_energies(self):
"""
Returns:
"""
return self["output/dos_energies"]
@property
def dynamical_matrix(self):
"""
Returns:
"""
return np.real_if_close(
self.phonopy.get_dynamical_matrix().get_dynamical_matrix())
def dynamical_matrix_at_q(self, q):
"""
Args:
q:
Returns:
"""
return np.real_if_close(self.phonopy.get_dynamical_matrix_at_q(q))
def plot_dos(self, ax=None, *args, **qwargs):
"""
Args:
*args:
ax:
**qwargs:
Returns:
"""
try:
import pylab as plt
except ImportError:
import matplotlib.pyplot as plt
if ax is None:
fig, ax = plt.subplots(1, 1)
ax.plot(self["output/dos_energies"], self["output/dos_total"], *args,
**qwargs)
ax.set_xlabel("Frequency [THz]")
ax.set_ylabel("DOS")
ax.set_title("Phonon DOS vs Energy")
return ax
def get_band_structure(self,
npoints=101,
with_eigenvectors=False,
with_group_velocities=False):
"""
Calculate band structure with automatic path through reciprocal space.
Can only be called after job is finished.
Args:
npoints (int, optional): Number of sample points between high symmetry points.
with_eigenvectors (boolean, optional): Calculate eigenvectors, too
with_group_velocities (boolean, optional): Calculate group velocities, too
Returns:
:class:`dict` of the results from phonopy under the following keys
- 'qpoints': list of (npoints, 3), samples paths in reciprocal space
- 'distances': list of (npoints,), distance along the paths in reciprocal space
- 'frequencies': list of (npoints, band), phonon frequencies
- 'eigenvectors': list of (npoints, band, band//3, 3), phonon eigenvectors
- 'group_velocities': list of (npoints, band), group velocities
where band is the number of bands (number of atoms * 3). Each entry is a list of arrays, and each array
corresponds to one path between two high-symmetry points automatically picked by Phonopy and may be of
different length than other paths. As compared to the phonopy output this method also reshapes the
eigenvectors so that they directly have the same shape as the underlying structure.
Raises:
:exception:`ValueError`: method is called on a job that is not finished or aborted
"""
if not self.status.finished:
raise ValueError(
"Job must be successfully run, before calling this method.")
self.phonopy.auto_band_structure(
npoints,
with_eigenvectors=with_eigenvectors,
with_group_velocities=with_group_velocities)
results = self.phonopy.get_band_structure_dict()
if results["eigenvectors"] is not None:
# see https://phonopy.github.io/phonopy/phonopy-module.html#eigenvectors for the way phonopy stores the
# eigenvectors
results["eigenvectors"] = [
e.transpose(0, 2, 1).reshape(*e.shape[:2], -1, 3)
for e in results["eigenvectors"]
]
return results
def plot_band_structure(self, axis=None):
"""
Plot bandstructure calculated with :method:`.get_bandstructure`.
If :method:`.get_bandstructure` hasn't been called before, it is automatically called with the default arguments.
Args:
axis (matplotlib axis, optional): plot to this axis, if not given a new one is created.
Returns:
matplib axis: the axis the figure has been drawn to, if axis is given the same object is returned
"""
try:
import pylab as plt
except ImportError:
import matplotlib.pyplot as plt
if axis is None:
_, axis = plt.subplots(1, 1)
try:
results = self.phonopy.get_band_structure_dict()
except RuntimeError:
results = self.get_band_structure()
distances = results["distances"]
frequencies = results["frequencies"]
# HACK: strictly speaking this breaks phonopy API and could bite us
path_connections = self.phonopy._band_structure.path_connections
labels = self.phonopy._band_structure.labels
offset = 0
tick_positions = [distances[0][0]]
for di, fi, ci in zip(distances, frequencies, path_connections):
axis.axvline(tick_positions[-1], color="black", linestyle="--")
axis.plot(offset + di, fi, color="black")
tick_positions.append(di[-1] + offset)
if not ci:
offset += .05
plt.axvline(tick_positions[-1], color="black", linestyle="--")
tick_positions.append(di[-1] + offset)
axis.set_xticks(tick_positions[:-1])
axis.set_xticklabels(labels)
axis.set_xlabel("Bandpath")
axis.set_ylabel("Frequency [THz]")
axis.set_title("Bandstructure")
return axis
def validate_ready_to_run(self):
if self.ref_job._generic_input["calc_mode"] != "static":
raise ValueError(
"Phonopy reference jobs should be static calculations, but got {}"
.format(self.ref_job._generic_input["calc_mode"]))
super().validate_ready_to_run()