/
funct.py
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/
funct.py
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# coding: utf-8
# Copyright (c) Max-Planck-Institut für Eisenforschung GmbH - Computational Materials Design (CM) Department
# Distributed under the terms of "New BSD License", see the LICENSE file.
import json
import numpy as np
import warnings
from pyiron.atomistics.structure.atoms import Atoms, pyiron_to_ase
def _get_value_from_incar(job, key):
return eval(
job["input/incar/data_dict"]["Value"][
job["input/incar/data_dict"]["Parameter"].index(key)
]
)
def get_majority(lst, minority=False):
elements_dict = {name: lst.count(name) for name in set(lst)}
max_value = np.max(list(elements_dict.values()))
majority_element = [
key for key, value in elements_dict.items() if value == max_value
][0]
if minority:
minority_lst = list(elements_dict.keys())
del minority_lst[minority_lst.index(majority_element)]
return majority_element, minority_lst
else:
return majority_element
def get_incar(job):
data_dict = job["input/incar/data_dict"]
return {
key: value for key, value in zip(data_dict["Parameter"], data_dict["Value"])
}
def get_sigma(job):
return {"sigma": _get_value_from_incar(job=job, key="SIGMA")}
def get_ismear(job):
return {"ismear": _get_value_from_incar(job=job, key="ISMEAR")}
def get_encut(job):
return {"encut": _get_value_from_incar(job=job, key="ENCUT")}
def get_n_kpts(job):
return {"n_kpts": eval(job["input/kpoints/data_dict"]["Value"][3].split()[0])}
def get_n_equ_kpts(job):
return {"n_equ_kpts": len(job['output/generic/dft/bands/k_points'])}
def get_total_number_of_atoms(job):
return {"Number_of_atoms": len(job["input/structure/indices"])}
def get_average_waves(job):
_, weights, planewaves = job["output/outcar/irreducible_kpoints"]
return {"avg. plane waves": sum(weights * planewaves) / sum(weights)}
def get_plane_waves(job):
_, weights, planewaves = job["output/outcar/irreducible_kpoints"]
return {"plane waves": sum(weights * planewaves)}
def get_ekin_error(job):
return {"energy_tot_wo_kin_corr": job["output/outcar/kin_energy_error"] + job["output/generic/energy_tot"][-1]}
def get_volume(job):
return {"volume": job["output/generic/volume"][-1]}
def get_volume_per_atom(job):
return {"volume": job["output/generic/volume"][-1] / get_total_number_of_atoms(job=job)["Number_of_atoms"]}
def get_elements(job):
species = job["input/structure/species"]
indices_lst = job["input/structure/indices"]
indices_set = set(indices_lst)
count_lst = [indices_lst.tolist().count(ind) for ind in indices_set]
main_element = species[count_lst.index(np.max(count_lst))]
return {species[ind]: count_lst[ind] for ind in indices_set}
def get_convergence_check(job):
try:
conv = job.project.load(job.job_id).convergence_check()
except:
conv = None
return {"Convergence": conv}
def get_number_of_species(job):
return {"Number_of_species": len(job["output/structure/species"])}
def get_number_of_ionic_steps(job):
return {"Number_of_ionic_steps": len(job["output/generic/energy_tot"])}
def get_number_of_final_electronic_steps(job):
el_steps = job["output/generic/scf_energies"]
if len(el_steps) != 0:
return {"Number_of_final_electronic_steps": len(el_steps[-1])}
else:
return {"Number_of_final_electronic_steps": None}
def get_majority_species(job):
indices_lst = job["input/structure/indices"].tolist()
element_lst = job["input/structure/species"]
majority_element, minority_lst = get_majority(
[element_lst[ind] for ind in indices_lst], minority=True
)
return {"majority_element": majority_element, "minority_element_list": minority_lst}
def get_majority_crystal_structure(job):
basis = Atoms().from_hdf(job["input"])
majority_element = basis.get_majority_species()["symbol"]
majority_index = [
ind for ind, el in enumerate(basis) if el.symbol == majority_element
]
type_list = list(basis[majority_index].analyse_pyscal_cna_adaptive(
mode="str",
ovito_compatibility=True
))
return {"crystal_structure": get_majority(type_list, minority=False)}
def get_job_name(job):
return {"job_name": job.job_name}
def get_job_id(job):
return {"job_id": job.job_id}
def get_energy_tot_per_atom(job):
return {"energy_tot": job["output/generic/energy_tot"][-1] / get_total_number_of_atoms(job=job)["Number_of_atoms"]}
def get_energy_tot(job):
return {"energy_tot": job["output/generic/energy_tot"][-1]}
def get_energy_pot_per_atom(job):
return {"energy_pot": job["output/generic/energy_pot"][-1] / get_total_number_of_atoms(job=job)["Number_of_atoms"]}
def get_energy_pot(job):
return {"energy_pot": job["output/generic/energy_pot"][-1]}
def get_energy_free_per_atom(job):
return {"energy_free": job["output/generic/dft/energy_free"][-1] / get_total_number_of_atoms(job=job)["Number_of_atoms"]}
def get_energy_free(job):
return {"energy_free": job["output/generic/dft/energy_free"][-1]}
def get_energy_int_per_atom(job):
return {"energy_int": job["output/generic/dft/energy_int"][-1] / get_total_number_of_atoms(job=job)["Number_of_atoms"]}
def get_energy_int(job):
return {"energy_int": job["output/generic/dft/energy_int"][-1]}
def get_f_states(job):
if "occ_matrix" in job["output/electronic_structure"].list_nodes():
return {
"f_states": job["output/electronic_structure/occ_matrix"].flatten().tolist()
}
elif "occupancy_matrix" in job["output/electronic_structure"].list_nodes():
return {
"f_states": job["output/electronic_structure/occupancy_matrix"]
.flatten()
.tolist()
}
else:
print("get_f_states(): ", job.job_name, job.status)
return {"f_states": [0.0]}
def get_e_band(job):
if "occ_matrix" in job["output/electronic_structure"].list_nodes():
f_occ = job["output/electronic_structure/occ_matrix"].flatten()
ev_mat = job["output/electronic_structure/eig_matrix"].flatten()
elif "occupancy_matrix" in job["output/electronic_structure"].list_nodes():
f_occ = job["output/electronic_structure/occupancy_matrix"].flatten()
ev_mat = job["output/electronic_structure/eigenvalue_matrix"].flatten()
else:
print("get_e_band(): ", job.job_name, job.status)
f_occ = np.array([0.0])
ev_mat = np.array([0.0])
return {"e_band": np.sum(ev_mat * f_occ)}
def get_equilibrium_parameters(job):
return {
key: job["output/" + key]
for key in [
"equilibrium_energy",
"equilibrium_b_prime",
"equilibrium_bulk_modulus",
"equilibrium_volume",
]
}
def get_structure(job):
atoms = pyiron_to_ase(job.load_object().get_structure())
atoms_dict = {
"symbols": atoms.get_chemical_symbols(),
"positions": atoms.get_positions().tolist(),
"cell": atoms.get_cell().tolist(),
"pbc": atoms.get_pbc().tolist(),
"celldisp": atoms.get_celldisp().tolist(),
}
if atoms.has("tags"):
atoms_dict["tags"] = atoms.get_tags().tolist()
if atoms.has("masses"):
atoms_dict["masses"] = atoms.get_masses().tolist()
if atoms.has("momenta"):
atoms_dict["momenta"] = atoms.get_momenta().tolist()
if atoms.has("initial_magmoms"):
atoms_dict["magmoms"] = atoms.get_initial_magnetic_moments().tolist()
if atoms.has("initial_charges"):
atoms_dict["charges"] = atoms.get_initial_charges().tolist()
if not atoms.__dict__["_calc"] == None:
warnings.warn("Found calculator: " + str(atoms.__dict__["_calc"]))
if not atoms.__dict__["_constraints"] == []:
warnings.warn("Found constraint: " + str(atoms.__dict__["_constraints"]))
return {"structure": json.dumps(atoms_dict)}
def get_forces(job):
return {"forces": json.dumps(job["output/generic/forces"][-1].tolist())}
def get_magnetic_structure(job):
basis = Atoms().from_hdf(job["input"])
magmons = basis.get_initial_magnetic_moments()
if all(magmons == None):
return {"magnetic_structure": "non magnetic"}
else:
abs_sum_mag = sum(np.abs(magmons))
sum_mag = sum(magmons)
if abs_sum_mag == 0 and sum_mag == 0:
return {"magnetic_structure": "non magnetic"}
elif abs_sum_mag == np.abs(sum_mag):
return {"magnetic_structure": "ferro-magnetic"}
elif abs_sum_mag > 0 and sum_mag == 0:
return {"magnetic_structure": "para-magnetic"}
else:
return {"magnetic_structure": "unknown"}
def get_e_conv_level(job):
return {'el_conv': np.max(np.abs(
job['output/generic/dft/scf_energy_free'][0] -
job['output/generic/dft/scf_energy_free'][0][-1]
)[-10:])}