+# Copyright (c) lobsterpy development team
+# Distributed under the terms of a BSD 3-Clause "New" or "Revised" License
+
+"""This module defines classes to analyze the COHPs automatically."""
+from __future__ import annotations
+
+import warnings
+from collections import Counter
+from pathlib import Path
+
+import numpy as np
+from pymatgen.analysis.bond_valence import BVAnalyzer
+from pymatgen.core.structure import Structure
+from pymatgen.electronic_structure.cohp import CompleteCohp
+from pymatgen.electronic_structure.core import Spin
+from pymatgen.electronic_structure.dos import LobsterCompleteDos
+from pymatgen.io.lobster import (
+ Bandoverlaps,
+ Charge,
+ Doscar,
+ Icohplist,
+ Lobsterin,
+ Lobsterout,
+ MadelungEnergies,
+)
+from pymatgen.io.lobster.lobsterenv import LobsterNeighbors
+from pymatgen.io.vasp.outputs import Vasprun
+from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
+
+
+[docs]class Analysis:
+
"""
+
Class to automatically analyze COHP/COOP/COBI populations from Lobster.
+
+
:param are_cobis: bool indicating if file contains COBI/ICOBI data
+
:param are_coops: bool indicating if file contains COOP/ICOOP data
+
:param cutoff_icohp: Cutoff in percentage for evaluating neighbors based on ICOHP values.
+
cutoff_icohp*max_icohp limits the number of considered neighbours for evaluating environments.
+
:param path_to_cohpcar: path to `COHPCAR.lobster` or `COBICAR.lobster` or `COOPCAR.lobster` .
+
:param path_to_charge: path to `CHARGE.lobster`.
+
:param path_to_icohplist: path to `ICOHPLIST.lobster` or `ICOBILIST.lobster` or `ICOOPLIST.lobster`.
+
:param path_to_poscar: path to structure (e.g., `POSCAR` or `POSCAR.lobster`)
+
:param path_to_madelung: path to `MadelungEnergies.lobster`.
+
:param charge_obj: pymatgen lobster.io.charge object
+
:param completecohp_obj: pymatgen.electronic_structure.cohp.CompleteCohp object
+
:param icohplist_obj: pymatgen lobster.io.Icohplist object
+
:param madelung_obj: pymatgen lobster.io.MadelungEnergies object
+
:param noise_cutoff: Sets the lower limit tolerance for ICOHPs or ICOOPs or ICOBIs considered
+
in analysis.
+
:param orbital_cutoff: Sets the minimum percentage for the orbital contribution considered to be
+
relevant in orbital resolved analysis. (Affects only when orbital_resolved argument is set to True)
+
Set it to 0 to get results of all orbitals in the detected relevant bonds. Default is to 0.05 i.e.
+
only analyzes if orbital contribution is 5 % or more.
+
:param orbital_resolved: bool indicating whether orbital wise analysis is performed
+
:param type_charge: If no path_to_charge is given, Valences will be used. Otherwise, Mulliken charges.
+
Löwdin charges cannot be selected at the moment.
+
:param which_bonds: Selects kinds of bonds that are analyzed. `cation-anion` is the default.
+
Alternatively, `all` bonds can also be selected. Support to other kinds of bonds will be
+
added soon.
+
:param summed_spins: if True, COHP `Spin.up` and `Spin.down` populations will be summed
+
:param start: sets the lower limit of energy for evaluation of bonding and antibonding
+
percentages below efermi. Defaults to None (i.e., all populations below efermi are included)
+
+
Attributes:
+
- condensed_bonding_analysis: dict including a summary of the most important bonding properties
+
- final_dict_bonds: dict including information on ICOHPs per bond type
+
- final_dict_ions: dict including information on environments of cations
+
- chemenv: pymatgen.io.lobster.lobsterenv.LobsterNeighbors object
+
- lse: LightStructureEnvironment from pymatgen
+
- anion_types: Set of Element objects from pymatgen
+
- list_equivalent_sites: list of site indices of sites that indicate which sites are equivalent
+
e.g., [0 1 2 2 2] where site 0, 1, 2 indicate sites that are independent from each other
+
- seq_cohps: list of cohps
+
- seq_coord_ions: list of co-ordination environment strings for each cation
+
- seq_equivalent_sites: seq of inequivalent sites
+
- seq_ineq_ions: seq of inequivalent cations/sites in the structure
+
- seq_infos_bonds (list): information on cation anion bonds (lists
+
of pymatgen.io.lobster.lobsterenv.ICOHPNeighborsInfo)
+
- spg: space group information
+
- structure: Structure object
+
+
"""
+
+
def __init__(
+
self,
+
path_to_poscar: str | Path | None,
+
path_to_icohplist: str | Path | None,
+
path_to_cohpcar: str | Path | None,
+
path_to_charge: str | Path | None = None,
+
path_to_madelung: str | Path | None = None,
+
icohplist_obj: Icohplist | None = None,
+
completecohp_obj: CompleteCohp | None = None,
+
charge_obj: Charge | None = None,
+
madelung_obj: MadelungEnergies | None = None,
+
are_cobis: bool = False,
+
are_coops: bool = False,
+
cutoff_icohp: float = 0.1,
+
noise_cutoff: float = 0.1,
+
orbital_cutoff: float = 0.05,
+
orbital_resolved: bool = False,
+
start: float | None = None,
+
summed_spins: bool = True,
+
type_charge: str | None = None,
+
which_bonds: str = "cation-anion",
+
):
+
"""
+
Initialize automatic bonding analysis.
+
+
:param are_cobis: bool indicating if file contains COBI/ICOBI data
+
:param are_coops: bool indicating if file contains COOP/ICOOP data
+
:param cutoff_icohp: Cutoff in percentage for evaluating neighbors based on ICOHP values.
+
cutoff_icohp*max_icohp limits the number of considered neighbours for evaluating environments.
+
:param path_to_cohpcar: path to `COHPCAR.lobster` or `COBICAR.lobster` or `COOPCAR.lobster` .
+
:param path_to_charge: path to `CHARGE.lobster`.
+
:param path_to_icohplist: path to `ICOHPLIST.lobster` or `ICOBILIST.lobster` or `ICOOPLIST.lobster`.
+
:param path_to_poscar: path to structure (e.g., `POSCAR` or `POSCAR.lobster`)
+
:param path_to_madelung: path to `MadelungEnergies.lobster`.
+
:param charge_obj: pymatgen lobster.io.charge object (Optional)
+
:param completecohp_obj: pymatgen.electronic_structure.cohp.CompleteCohp object
+
:param icohplist_obj: pymatgen lobster.io.Icohplist object
+
:param madelung_obj: pymatgen lobster.io.MadelungEnergies object
+
:param noise_cutoff: Sets the lower limit tolerance for ICOHPs or ICOOPs or ICOBIs considered
+
in analysis.
+
:param orbital_cutoff: Sets the minimum percentage for the orbital contribution considered to be
+
relevant in orbital resolved analysis. (Affects only when orbital_resolved argument is set to True)
+
Set it to 0 to get results of all orbitals in the detected relevant bonds. Default is to 0.05 i.e.
+
only analyzes if orbital contribution is 5 % or more.
+
:param orbital_resolved: bool indicating whether orbital wise analysis is performed
+
:param type_charge: If no path_to_charge is given, Valences will be used. Otherwise, Mulliken charges.
+
Löwdin charges cannot be selected at the moment.
+
:param which_bonds: Selects kinds of bonds that are analyzed. `cation-anion` is the default.
+
Alternatively, `all` bonds can also be selected. Support to other kinds of bonds will be
+
added soon.
+
:param summed_spins: if True, COHP `Spin.up` and `Spin.down` populations will be summed
+
:param start: sets the lower limit of energy for evaluation of bonding and antibonding
+
percentages below efermi. Defaults to None (i.e., all populations below efermi are included)
+
+
"""
+
self.start = start
+
self.completecohp_obj = completecohp_obj
+
self.icohplist_obj = icohplist_obj
+
# checks to ensure LobsterEnv inputs are not duplicated in case users provide both path and obj
+
if self.completecohp_obj is not None and self.icohplist_obj is not None:
+
self.path_to_poscar = None
+
self.path_to_cohpcar = None
+
self.path_to_icohplist = None
+
else:
+
self.path_to_poscar = path_to_poscar
+
self.path_to_icohplist = path_to_icohplist
+
self.path_to_cohpcar = path_to_cohpcar
+
self.which_bonds = which_bonds
+
self.cutoff_icohp = cutoff_icohp
+
self.orbital_cutoff = orbital_cutoff
+
self.path_to_charge = path_to_charge
+
self.charge_obj = charge_obj
+
self.path_to_madelung = path_to_madelung
+
self.madelung_obj = madelung_obj
+
self.are_cobis = are_cobis
+
self.are_coops = are_coops
+
self.noise_cutoff = noise_cutoff
+
self.setup_env()
+
self.get_information_all_bonds(summed_spins=summed_spins)
+
self.orbital_resolved = orbital_resolved
+
+
# This determines how cations and anions
+
if path_to_charge is None and charge_obj is None:
+
self.type_charge = "Valences"
+
else:
+
if type_charge is None:
+
self.type_charge = "Mulliken"
+
elif type_charge == "Mulliken":
+
self.type_charge = "Mulliken"
+
elif type_charge == "Löwdin":
+
raise ValueError("Only Mulliken charges can be used here at the moment. Implementation will follow.")
+
else:
+
self.type_charge = "Valences"
+
print("type_charge cannot be read! Please use Mulliken/Löwdin. Now, we will use valences")
+
+
self.set_condensed_bonding_analysis()
+
self.set_summary_dicts()
+
self.path_to_madelung = path_to_madelung
+
+
[docs] def setup_env(self):
+
"""
+
Set up the light structure environments based on COHPs using this method.
+
+
Returns:
+
None
+
+
"""
+
self.structure = (
+
Structure.from_file(self.path_to_poscar) if self.path_to_poscar else self.completecohp_obj.structure
+
)
+
sga = SpacegroupAnalyzer(structure=self.structure)
+
symmetry_dataset = sga.get_symmetry_dataset()
+
equivalent_sites = symmetry_dataset["equivalent_atoms"]
+
self.list_equivalent_sites = equivalent_sites
+
self.seq_equivalent_sites = list(set(equivalent_sites))
+
self.spg = symmetry_dataset["international"]
+
+
if self.which_bonds == "cation-anion":
+
try:
+
self.chemenv = LobsterNeighbors(
+
filename_icohp=self.path_to_icohplist,
+
obj_icohp=self.icohplist_obj,
+
structure=self.structure,
+
additional_condition=1,
+
perc_strength_icohp=self.cutoff_icohp,
+
filename_charge=self.path_to_charge,
+
obj_charge=self.charge_obj,
+
valences=None,
+
valences_from_charges=True,
+
adapt_extremum_to_add_cond=True,
+
are_cobis=self.are_cobis,
+
are_coops=self.are_coops,
+
noise_cutoff=self.noise_cutoff,
+
)
+
except ValueError as err:
+
if (
+
str(err) == "min() arg is an empty sequence"
+
or str(err) == "All valences are equal to 0, additional_conditions 1, 3, 5 and 6 will not work"
+
):
+
raise ValueError(
+
"Consider switching to an analysis of all bonds and not only cation-anion bonds."
+
" It looks like no cations are detected."
+
)
+
raise err
+
elif self.which_bonds == "all":
+
# raise ValueError("only cation anion bonds implemented so far")
+
self.chemenv = LobsterNeighbors(
+
filename_icohp=self.path_to_icohplist,
+
obj_icohp=self.icohplist_obj,
+
structure=self.structure,
+
additional_condition=0,
+
perc_strength_icohp=self.cutoff_icohp,
+
filename_charge=self.path_to_charge,
+
obj_charge=self.charge_obj,
+
valences_from_charges=True,
+
adapt_extremum_to_add_cond=True,
+
are_cobis=self.are_cobis,
+
are_coops=self.are_coops,
+
noise_cutoff=self.noise_cutoff,
+
)
+
+
else:
+
raise ValueError("only cation anion and all bonds implemented so far")
+
+
# determine cations and anions
+
try:
+
if self.which_bonds == "cation-anion":
+
self.lse = self.chemenv.get_light_structure_environment(only_cation_environments=True)
+
elif self.which_bonds == "all":
+
self.lse = self.chemenv.get_light_structure_environment(only_cation_environments=False)
+
except ValueError:
+
+
class Lse:
+
"""Test class when error was raised."""
+
+
def __init__(self, chemenv, valences=None):
+
"""
+
Test class when error was raised.
+
+
:param chemenv: LobsterNeighbors object
+
:param valences: list of valences
+
+
"""
+
if valences is None:
+
self.coordination_environments = []
+
for coord in chemenv:
+
if len(coord) > 0:
+
self.coordination_environments.append([{"ce_symbol": str(len(coord))}])
+
else:
+
self.coordination_environments.append([{"ce_symbol": None}])
+
else:
+
self.coordination_environments = []
+
+
for val, coord in zip(valences, chemenv):
+
if val >= 0.0 and len(coord) > 0:
+
self.coordination_environments.append([{"ce_symbol": str(len(coord))}])
+
else:
+
self.coordination_environments.append([{"ce_symbol": None}])
+
+
if self.which_bonds == "all":
+
self.lse = Lse(self.chemenv.list_coords)
+
elif self.which_bonds == "cation-anion":
+
# make a new list
+
self.lse = Lse(self.chemenv.list_coords, self.chemenv.valences)
+
+
+
+
[docs] def get_site_bond_resolved_labels(self):
+
"""
+
Return relevant bond labels for each symmetrically independent site.
+
+
Returns:
+
dict with bond labels for each site, e.g.
+
{'Na1: Na-Cl': ['21', '23', '24', '27', '28', '30']}
+
+
"""
+
bonds = [[] for _ in range(len(self.seq_infos_bonds))] # type: ignore
+
labels = [[] for _ in range(len(self.seq_infos_bonds))] # type: ignore
+
for inx, bond_info in enumerate(self.seq_infos_bonds):
+
for ixx, val in enumerate(bond_info.atoms):
+
label_srt = sorted(val.copy())
+
bonds[inx].append(
+
self.structure.sites[bond_info.central_isites[0]].species_string
+
+ str(bond_info.central_isites[0] + 1)
+
+ ": "
+
+ label_srt[0].strip("0123456789")
+
+ "-"
+
+ label_srt[1].strip("0123456789")
+
)
+
labels[inx].append(bond_info.labels[ixx])
+
+
label_data = {}
+
for indx, atom_pairs in enumerate(bonds):
+
searched_atom_pairs = set(atom_pairs)
+
for search_item in searched_atom_pairs:
+
indices = [i for i, pair in enumerate(atom_pairs) if pair == search_item]
+
filtered_bond_label_list = [labels[indx][i] for i in indices]
+
label_data.update({search_item: filtered_bond_label_list})
+
+
return label_data
+
+
def _get_orbital_resolved_data(
+
self,
+
nameion: str,
+
iion: int,
+
labels: list[str],
+
bond_resolved_labels: dict[str, list[str]],
+
type_pop: str,
+
):
+
"""
+
Retrieve orbital-wise analysis data.
+
+
:param nameion: name of symmetrically relevant cation or anion
+
:param iion: index of symmetrically relevant cation or anion
+
:param labels: list of bond label names
+
:param bond_resolved_labels: dict of bond labels from ICOHPLIST resolved for each bond
+
:param type_pop: population type analyzed. e.g. COHP or COOP or COBI
+
+
Returns:
+
dict consisting of relevant orbitals (contribution > 5 % to overall ICOHP or ICOBI or ICOOP),
+
bonding and antibonding percentages with bond label names as keys.
+
"""
+
orb_resolved_bond_info = {}
+
for label in labels:
+
if label is not None:
+
bond_resolved_label_key = nameion + str(iion + 1) + ":" + label.split("x")[-1]
+
bond_labels = bond_resolved_labels[bond_resolved_label_key]
+
available_orbitals = list(self.chemenv.completecohp.orb_res_cohp[bond_labels[0]].keys())
+
# initialize empty list to store orb paris for bonding,
+
# antibonding integrals and percentages
+
bndg_orb_pair_list = []
+
bndg_orb_integral_list = []
+
bndg_orb_perc_list = []
+
bndg_orb_icohp_list = []
+
antibndg_orb_integral_list = []
+
antibndg_orb_perc_list = []
+
antibndg_orb_pair_list = []
+
antibndg_orb_icohp_list = []
+
+
# get total summed cohps using label list
+
cohp_summed = self.chemenv.completecohp.get_summed_cohp_by_label_list(label_list=bond_labels)
+
if type_pop.lower() == "cohp":
+
(
+
antibndg_tot,
+
per_anti_tot,
+
bndg_tot,
+
per_bndg_tot,
+
) = self._integrate_antbdstates_below_efermi(cohp=cohp_summed, start=self.start)
+
else:
+
(
+
bndg_tot,
+
per_bndg_tot,
+
antibndg_tot,
+
per_anti_tot,
+
) = self._integrate_antbdstates_below_efermi(cohp=cohp_summed, start=self.start)
+
+
orb_bonding_dict_data = {} # type: ignore
+
# For each orbital collect the contributions of summed bonding
+
# and antibonding interactions separately
+
for orb in available_orbitals:
+
cohp_summed_orb = self.chemenv.completecohp.get_summed_cohp_by_label_and_orbital_list(
+
label_list=bond_labels, orbital_list=[orb] * len(bond_labels)
+
)
+
+
if type_pop.lower() == "cohp":
+
(
+
antibndg_orb,
+
per_anti_orb,
+
bndg_orb,
+
per_bndg_orb,
+
) = self._integrate_antbdstates_below_efermi(cohp=cohp_summed_orb, start=self.start)
+
else:
+
(
+
bndg_orb,
+
per_bndg_orb,
+
antibndg_orb,
+
per_anti_orb,
+
) = self._integrate_antbdstates_below_efermi(cohp=cohp_summed_orb, start=self.start)
+
+
# replace nan values with zero (tackle numerical integration issues)
+
bndg_orb = bndg_orb if not np.isnan(bndg_orb) else 0
+
per_bndg_orb = per_bndg_orb if not np.isnan(per_bndg_orb) else 0
+
bndg_tot = bndg_tot if not np.isnan(bndg_tot) else 0
+
per_bndg_tot = per_bndg_tot if not np.isnan(per_bndg_tot) else 0
+
# skip collecting orb contributions if no summed bonding contribution exists
+
if bndg_tot > 0:
+
orb_icohps_bndg = []
+
for bond_label in bond_labels:
+
orb_icohp_bn = self.chemenv.Icohpcollection.get_icohp_by_label(
+
label=bond_label, orbitals=orb
+
)
+
orb_icohps_bndg.append(orb_icohp_bn)
+
bndg_orb_pair_list.append(orb)
+
bndg_orb_icohp_list.append(orb_icohps_bndg)
+
bndg_orb_integral_list.append(bndg_orb)
+
bndg_orb_perc_list.append(per_bndg_orb)
+
+
# replace nan values with zero (tackle numerical integration issues)
+
antibndg_orb = antibndg_orb if not np.isnan(antibndg_orb) else 0
+
per_anti_orb = per_anti_orb if not np.isnan(per_anti_orb) else 0
+
antibndg_tot = antibndg_tot if not np.isnan(antibndg_tot) else 0
+
per_anti_tot = per_anti_tot if not np.isnan(per_anti_tot) else 0
+
# skip collecting orb contributions if no summed antibonding contribution exists
+
if antibndg_tot > 0:
+
orb_icohps_anti = []
+
for bond_label in bond_labels:
+
orb_icohp_an = self.chemenv.Icohpcollection.get_icohp_by_label(
+
label=bond_label, orbitals=orb
+
)
+
orb_icohps_anti.append(orb_icohp_an)
+
+
antibndg_orb_pair_list.append(orb)
+
antibndg_orb_icohp_list.append(orb_icohps_anti)
+
antibndg_orb_integral_list.append(antibndg_orb)
+
antibndg_orb_perc_list.append(per_anti_orb)
+
+
# Populate the dictionary with relevant orbitals for bonding interactions
+
for inx, bndg_orb_pair in enumerate(bndg_orb_pair_list):
+
bndg_contri_perc = round(bndg_orb_integral_list[inx] / sum(bndg_orb_integral_list), 2)
+
# filter out very small bonding interactions (<self.orbital_cutoff)
+
if bndg_contri_perc > self.orbital_cutoff:
+
if bndg_orb_pair in orb_bonding_dict_data:
+
orb_bonding_dict_data[bndg_orb_pair].update(
+
{
+
"orb_contribution_perc_bonding": bndg_contri_perc,
+
"bonding": {
+
"integral": bndg_orb_integral_list[inx],
+
"perc": bndg_orb_perc_list[inx],
+
},
+
}
+
)
+
else:
+
orb_bonding_dict_data[bndg_orb_pair] = {
+
f"I{type_pop}_mean": round(np.mean(bndg_orb_icohp_list[inx]), 4),
+
f"I{type_pop}_sum": round(np.sum(bndg_orb_icohp_list[inx]), 4),
+
"orb_contribution_perc_bonding": round(
+
bndg_orb_integral_list[inx] / sum(bndg_orb_integral_list),
+
2,
+
),
+
"bonding": {
+
"integral": bndg_orb_integral_list[inx],
+
"perc": bndg_orb_perc_list[inx],
+
},
+
}
+
+
# Populate the dictionary with relevant orbitals for antibonding interactions
+
for inx, antibndg_orb_pair in enumerate(antibndg_orb_pair_list):
+
antibndg_contri_perc = round(
+
antibndg_orb_integral_list[inx] / sum(antibndg_orb_integral_list),
+
2,
+
)
+
# filter out very small antibonding interactions (<self.orbital_cutoff)
+
if antibndg_contri_perc > self.orbital_cutoff:
+
if antibndg_orb_pair in orb_bonding_dict_data:
+
orb_bonding_dict_data[antibndg_orb_pair].update(
+
{
+
"orb_contribution_perc_antibonding": round(
+
antibndg_orb_integral_list[inx] / sum(antibndg_orb_integral_list),
+
2,
+
),
+
"antibonding": {
+
"integral": antibndg_orb_integral_list[inx],
+
"perc": antibndg_orb_perc_list[inx],
+
},
+
}
+
)
+
else:
+
orb_bonding_dict_data[antibndg_orb_pair] = {
+
f"I{type_pop}_mean": round(np.mean(antibndg_orb_icohp_list[inx]), 4),
+
f"I{type_pop}_sum": round(np.sum(antibndg_orb_icohp_list[inx]), 4),
+
"orb_contribution_perc_antibonding": round(
+
antibndg_orb_integral_list[inx] / sum(antibndg_orb_integral_list),
+
2,
+
),
+
"antibonding": {
+
"integral": antibndg_orb_integral_list[inx],
+
"perc": antibndg_orb_perc_list[inx],
+
},
+
}
+
+
orb_bonding_dict_data["relevant_bonds"] = bond_labels # type: ignore
+
+
orb_resolved_bond_info[bond_resolved_label_key] = orb_bonding_dict_data
+
+
return orb_resolved_bond_info
+
+
def _get_bond_resolved_data_stats(self, orb_resolved_bond_data: dict):
+
"""
+
Retrieve the maximum bonding and anti-bonding orbital contributions.
+
+
:param orb_resolved_bond_data: A dictionary with orbital names as keys and corresponding bonding data
+
+
Returns:
+
dict with orbital data stats the site for relevant orbitals, e.g.
+
{'orbital_summary_stats': {'max_bonding_contribution': {'2s-3s': 0.68},
+
'max_antibonding_contribution': {'2s-2pz': 0.36}}}
+
+
"""
+
# get max orbital bonding and contribution for the site
+
orb_pairs_bndg = []
+
orb_pairs_antibndg = []
+
orb_contri_bndg = []
+
orb_contri_antibndg = []
+
orbital_summary_stats = {"orbital_summary_stats": {}} # type: ignore
+
if orb_resolved_bond_data:
+
for orb_pair, data in orb_resolved_bond_data.items():
+
if "orb_contribution_perc_bonding" in data:
+
orb_pairs_bndg.append(orb_pair)
+
orb_contri_bndg.append(data["orb_contribution_perc_bonding"])
+
+
if "orb_contribution_perc_antibonding" in data:
+
orb_pairs_antibndg.append(orb_pair)
+
orb_contri_antibndg.append(data["orb_contribution_perc_antibonding"])
+
+
if orb_contri_bndg:
+
max_orb_contri_bndg = max(orb_contri_bndg)
+
max_orb_contri_bndg_inxs = [
+
inx for inx, orb_contri in enumerate(orb_contri_bndg) if orb_contri == max_orb_contri_bndg
+
]
+
max_orb_contri_bndg_dict = {}
+
for inx in max_orb_contri_bndg_inxs:
+
max_orb_contri_bndg_dict[orb_pairs_bndg[inx]] = orb_contri_bndg[inx]
+
orbital_summary_stats["orbital_summary_stats"]["max_bonding_contribution"] = max_orb_contri_bndg_dict
+
if orb_contri_antibndg:
+
max_orb_contri_antibndg = max(orb_contri_antibndg)
+
max_antibndg_contri_inxs = [
+
inx
+
for inx, orb_anti_per in enumerate(orb_contri_antibndg)
+
if orb_anti_per == max_orb_contri_antibndg
+
]
+
max_antibndg_contri_dict = {}
+
for inx in max_antibndg_contri_inxs:
+
max_antibndg_contri_dict[orb_pairs_antibndg[inx]] = orb_contri_antibndg[inx]
+
orbital_summary_stats["orbital_summary_stats"][
+
"max_antibonding_contribution"
+
] = max_antibndg_contri_dict
+
+
return orbital_summary_stats
+
+
[docs] def get_site_orbital_resolved_labels(self):
+
"""
+
Return relevant orbitals and bond labels for each symmetrically independent site.
+
+
Returns:
+
dict with bond labels for each site for relevant orbitals, e.g.
+
{'Na1: Na-Cl': {'3s-3s': ['21', '23', '24', '27', '28', '30']}
+
+
"""
+
site_bond_labels = self.get_site_bond_resolved_labels()
+
orb_plot_data = {atom_pair: {} for atom_pair in site_bond_labels}
+
if self.orbital_resolved:
+
for site_index, cba_data in self.condensed_bonding_analysis["sites"].items():
+
for atom in cba_data["bonds"]:
+
for orb_pair in cba_data["bonds"][atom]["orbital_data"]:
+
if orb_pair not in ("orbital_summary_stats", "relevant_bonds"):
+
atom_pair = [cba_data["ion"], atom]
+
atom_pair.sort()
+
key = (
+
self.structure.sites[site_index].species_string
+
+ str(site_index + 1)
+
+ ": "
+
+ "-".join(atom_pair)
+
)
+
label_list = site_bond_labels[key]
+
orb_plot_data[key].update({orb_pair: label_list})
+
else:
+
print("Please set orbital_resolved to True when instantiating Analysis object, to get this data")
+
+
return orb_plot_data
+
+
@staticmethod
+
def _get_strenghts_for_each_bond(pairs: list[list[str]], strengths: list[float], nameion: str | None = None):
+
"""
+
Return a dictionary of bond strengths.
+
+
:param pairs: list of list including labels for the atoms, e.g., [['O3', 'Cu1'], ['O3', 'Cu1']]
+
:param strengths: list that gives the icohp strengths as a float, [-1.86287, -1.86288]
+
:param nameion: string including the name of the cation in the list, e.g Cu1
+
+
Returns:
+
dict including inormation on icohps for each bond type, e.g.
+
{'Yb-Sb': [-1.59769, -2.14723, -1.7925, -1.60773, -1.80149, -2.14335]}
+
+
+
"""
+
dict_strenghts = {} # type: ignore
+
+
for pair, strength in zip(pairs, strengths):
+
if nameion is not None:
+
new = [
+
LobsterNeighbors._split_string(pair[0])[0],
+
LobsterNeighbors._split_string(pair[1])[0],
+
]
+
new = Analysis._sort_name(new, nameion)
+
string_here = new[0] + "-" + new[1]
+
else:
+
new = sorted(
+
[
+
LobsterNeighbors._split_string(pair[0])[0],
+
LobsterNeighbors._split_string(pair[1])[0],
+
]
+
)
+
string_here = new[0] + "-" + new[1]
+
+
if string_here not in dict_strenghts:
+
dict_strenghts[string_here] = []
+
dict_strenghts[string_here].append(strength)
+
return dict_strenghts
+
+
@staticmethod
+
def _sort_name(pair: list[str], nameion: str | None = None):
+
"""
+
Place the cation first in a list of name strings.
+
+
:param pair: ["O","Cu"]
+
:param nameion: "Cu"
+
+
Returns:
+
will return list of str, e.g. ["Cu", "O"]
+
+
"""
+
if nameion is not None:
+
new = []
+
if pair[0] == nameion:
+
new.append(pair[0])
+
new.append(pair[1])
+
+
elif pair[1] == nameion:
+
new.append(pair[1])
+
new.append(pair[0])
+
+
return new
+
+
@staticmethod
+
def _sort_orbital_atom_pair(
+
atom_pair: list[str],
+
label: str,
+
complete_cohp: CompleteCohp,
+
orb_pair: str,
+
):
+
"""
+
Place the cation first in a list of name strings and add the associated orbital name alongside the atom name.
+
+
:param atom_pair: list of atom pair with cation first eg., ["Cl","Na"]
+
:param label: LOBSTER relevant bond label eg ., "3"
+
:param complete_cohp: pymatgen CompleteCohp object
+
:param orb_pair: relevant orbital pair eg., "2px-3s"
+
+
Returns:
+
will return list of str, e.g. ["Na(2px)", "Cl(3s)"]
+
+
"""
+
orb_atom = {} # type: ignore
+
orb_pair_list = orb_pair.split("-")
+
# get orbital associated to the atom and store in a dict
+
for _inx, (site, site_orb) in enumerate(zip(complete_cohp.bonds[label]["sites"], orb_pair_list)):
+
if site.species_string in orb_atom: # check necessary for bonds between same atoms
+
orb_atom[site.species_string].append(site_orb)
+
else:
+
orb_atom[site.species_string] = [site_orb]
+
+
orb_atom_list = []
+
# add orbital name next to atom_pair
+
for inx, atom in enumerate(atom_pair):
+
# check to ensure getting 2nd orbital if bond is between same atomic species
+
if inx == 1 and len(orb_atom.get(atom)) > 1: # type: ignore
+
atom_with_orb_name = f"{atom}({orb_atom.get(atom)[1]})" # type: ignore
+
else:
+
atom_with_orb_name = f"{atom}({orb_atom.get(atom)[0]})" # type: ignore
+
orb_atom_list.append(atom_with_orb_name)
+
+
return orb_atom_list
+
+
def _get_antibdg_states(self, cohps, labels: list[str], nameion: str | None = None, limit=0.01):
+
"""
+
Return a dictionary containing information on anti-bonding states.
+
+
e.g., similar to: {'Cu-O': True, 'Cu-F': True}
+
+
:param cohps: list of pymatgen.electronic_structure.cohp.Cohp objects
+
:param labels: ['2 x Cu-O', '4 x Cu-F']
+
:param nameion: string of the cation name, e.g. "Cu"
+
:param limit: limit to detect antibonding states
+
+
Returns:
+
dict including in formation on whether antibonding interactions exist,
+
e.g., {'Cu-O': True, 'Cu-F': True}
+
+
+
"""
+
dict_antibd = {}
+
for label, cohp in zip(labels, cohps):
+
if label is not None:
+
if nameion is not None:
+
new = label.split(" ")[2].split("-")
+
sorted_new = self._sort_name(new, nameion)
+
new_label = sorted_new[0] + "-" + sorted_new[1]
+
else:
+
new = label.split(" ")[2].split("-")
+
sorted_new = sorted(new.copy())
+
new_label = sorted_new[0] + "-" + sorted_new[1]
+
+
antbd = cohp.has_antibnd_states_below_efermi(limit=limit)
+
if Spin.down in antbd:
+
dict_antibd[new_label] = antbd[Spin.up] or antbd[Spin.down]
+
else:
+
dict_antibd[new_label] = antbd[Spin.up]
+
+
return dict_antibd
+
+
def _integrate_antbdstates_below_efermi_for_set_cohps(self, labels: list[str], cohps, nameion: str):
+
"""
+
Return a dictionary containing information on antibonding states.
+
+
.. warning:: NEEDS MORE TESTS
+
+
It is important to note that only the energy range that has been computed can be considered
+
(i.e., this might not be all)
+
+
e.g. output: {'Cu-O': {'integral': 4.24374775705, 'perc': 5.7437713186999995},
+
'Cu-F': {'integral': 3.07098300965, 'perc': 4.25800841445}}
+
+
:param cohps: list of pymatgen.electronic_structure.cohp.Cohp objects
+
:param labels: ['2 x Cu-O', '4 x Cu-F']
+
:param nameion: string of the cation name, e.g. "Cu"
+
+
Returns:
+
dict including in formation on whether antibonding interactions exist,
+
e.g., {'Cu-O': {'integral': 4.24374775705, 'perc': 5.7437713186999995},
+
'Cu-F': {'integral': 3.07098300965, 'perc': 4.25800841445}}}
+
"""
+
dict_bd_antibd = {}
+
for label, cohp in zip(labels, cohps):
+
if label is not None:
+
new = label.split(" ")[2].split("-")
+
sorted_new = self._sort_name(new, nameion)
+
new_label = sorted_new[0] + "-" + sorted_new[1]
+
if not self.are_cobis and not self.are_coops:
+
(
+
integral,
+
perc,
+
integral2,
+
perc2,
+
) = self._integrate_antbdstates_below_efermi(cohp, start=self.start)
+
else:
+
(
+
integral2,
+
perc2,
+
integral,
+
perc,
+
) = self._integrate_antbdstates_below_efermi(cohp, start=self.start)
+
+
if integral == 0 and integral2 != 0.0:
+
dict_bd_antibd[new_label] = {
+
"bonding": {"integral": integral2, "perc": perc2},
+
"antibonding": {"integral": integral, "perc": 0.0},
+
}
+
elif integral2 == 0.0 and integral != 0.0:
+
dict_bd_antibd[new_label] = {
+
"bonding": {"integral": integral2, "perc": 0.0},
+
"antibonding": {"integral": integral, "perc": perc},
+
}
+
elif integral == 0.0 and integral2 == 0.0:
+
dict_bd_antibd[new_label] = {
+
"bonding": {"integral": integral2, "perc": 0.0},
+
"antibonding": {"integral": integral, "perc": 0.0},
+
}
+
else:
+
dict_bd_antibd[new_label] = {
+
"bonding": {"integral": integral2, "perc": perc2},
+
"antibonding": {"integral": integral, "perc": perc},
+
}
+
+
return dict_bd_antibd
+
+
def _integrate_antbdstates_below_efermi(self, cohp, start: float | None):
+
"""
+
Integrate the cohp data to compute bonding and anti-bonding contribution below efermi.
+
+
.. warning:: NEEDS MORE TESTS
+
+
This integrates the whole COHP curve that has been computed.
+
The energy range is very important.
+
At present the energy range considered is dependent on COHPstartEnergy
+
set during lobster runs. The bonding / antibonding integral values are sensitive to this parameter.
+
If COHPstartEnergy value does not cover entire range of VASP calculations then
+
absolute value of ICOHP_sum might not be equivalent to (bonding- antibonding) integral values.
+
+
:param cohp: cohp object
+
:param start: integration start energy in eV , eg start = -15
+
+
Returns:
+
absolute value of antibonding, percentage value of antibonding,
+
absolute value of bonding and percentage value of bonding interactions
+
"""
+
warnings.warn(
+
"The bonding, antibonding integral/percent values are numerical estimate."
+
" These values are sensitive to COHPstartEnergy parameter."
+
" If COHPstartEnergy value does not cover entire range of VASP calculations then"
+
" absolute value of ICOHP_sum might not be equivalent to (bonding- antibonding) integral values."
+
)
+
+
from scipy.integrate import trapezoid
+
+
def integrate_positive(y, x):
+
"""
+
Integrate only bonding interactions of COHPs.
+
+
:param y: COHP values
+
:param x: Energy values
+
+
Returns:
+
integrated value of bonding interactions
+
"""
+
y = np.asanyarray(y)
+
x = np.asanyarray(x)
+
+
bonding = trapezoid(y, x)
+
+
return np.round(bonding, 2)
+
+
def integrate_negative(y, x):
+
"""
+
Integrate only anti-bonding interactions of COHPs.
+
+
:param y: COHP values
+
:param x: Energy values
+
+
Returns:
+
integrated value of anti-bonding interactions
+
"""
+
y = np.asanyarray(y)
+
x = np.asanyarray(x)
+
antibonding = trapezoid(y, x)
+
+
return np.round(antibonding, 2)
+
+
# will integrate spin.up and spin.down only below efermi
+
energies_corrected = cohp.energies - cohp.efermi
+
summedcohp = cohp.cohp[Spin.up] + cohp.cohp[Spin.down] if Spin.down in cohp.cohp else cohp.cohp[Spin.up]
+
+
cohp_bf = []
+
en_bf = []
+
+
for i, en in enumerate(energies_corrected):
+
if (start is None) and en <= 0:
+
en_bf.append(en)
+
cohp_bf.append(-1 * summedcohp[i])
+
if (start is not None) and 0 >= en >= start:
+
en_bf.append(en)
+
cohp_bf.append(-1 * summedcohp[i])
+
+
# Separate the bonding and antibonding COHP values in separate lists
+
pos = []
+
en_pos = []
+
neg = []
+
en_neg = []
+
+
for i, scohp in enumerate(cohp_bf):
+
if scohp >= 0:
+
pos.append(scohp)
+
en_pos.append(energies_corrected[i])
+
+
for i, scohp in enumerate(cohp_bf):
+
if scohp <= 0:
+
neg.append(-1 * scohp)
+
en_neg.append(energies_corrected[i])
+
+
antibonding = integrate_negative(y=neg, x=en_neg)
+
+
bonding = integrate_positive(y=pos, x=en_pos)
+
+
return (
+
antibonding,
+
np.round(abs(antibonding) / (abs(bonding) + abs(antibonding)), 5),
+
bonding,
+
np.round(abs(bonding) / (abs(bonding) + abs(antibonding)), 5),
+
)
+
+
def _get_pop_type(self):
+
"""
+
Return the type of the input population file.
+
+
Returns:
+
A String of analysed population can be COOP/COBI/COHP
+
"""
+
if self.are_cobis:
+
type_pop = "COBI"
+
elif self.are_coops:
+
type_pop = "COOP"
+
else:
+
type_pop = "COHP"
+
+
return type_pop
+
+
@staticmethod
+
def _get_bond_dict(
+
bond_strength_dict: dict,
+
small_antbd_dict: dict,
+
nameion: str | None = None,
+
large_antbd_dict: dict | None = None,
+
type_pop: str | None = None,
+
):
+
"""
+
Return a bond_dict that contains information for each site.
+
+
:param bond_strength_dict: dict with bond names as key and lists of bond strengths as items
+
:param small_antbd_dict: dict including if there are antibonding interactions, {'Yb-Sb': False}
+
:param nameion: name of the cation, e.g. Yb
+
:param large_antbd_dict: will be implemented later
+
:param type_pop: population type analyzed. eg. COHP
+
+
Returns:
+
Eg., if type_pop == 'COHP', will return
+
dict including information on the anion (as label) and the ICOHPs in the item of the dict
+
ICOHP_mean refers to the mean ICOHP in eV
+
ICOHP_sum refers to the sum of the ICOHPs in eV
+
has_antibdg_states_below_Efermi is True if there are antibonding interactions below Efermi
+
"number_of_bonds" will count the numbers of bonds to the cation
+
+
Example:
+
{'Sb': {'ICOHP_mean': '-1.85', 'ICOHP_sum': '-11.09',
+
'has_antibdg_states_below_Efermi': False, 'number_of_bonds': 6}}
+
+
"""
+
bond_dict = {}
+
+
for key, item in bond_strength_dict.items():
+
if nameion is not None:
+
a = key.split("-")[0]
+
b = key.split("-")[1]
+
if a == nameion:
+
key_here = b
+
elif b == nameion:
+
key_here = a
+
+
if large_antbd_dict is None:
+
bond_dict[key_here] = {
+
f"I{type_pop}_mean": str(round(np.mean(item), 2)),
+
f"I{type_pop}_sum": str(round(np.sum(item), 2)),
+
"has_antibdg_states_below_Efermi": small_antbd_dict[key],
+
"number_of_bonds": len(item),
+
}
+
else:
+
bond_dict[key_here] = {
+
f"I{type_pop}_mean": str(round(np.mean(item), 2)),
+
f"I{type_pop}_sum": str(round(np.sum(item), 2)),
+
"has_antibdg_states_below_Efermi": small_antbd_dict[key],
+
"number_of_bonds": len(item),
+
"perc_antibdg_states_below_Efermi": large_antbd_dict[key],
+
}
+
+
return bond_dict
+
+
[docs] def set_condensed_bonding_analysis(self):
+
"""
+
Condense the bonding analysis into a summary dictionary.
+
+
Returns:
+
None
+
+
"""
+
self.condensed_bonding_analysis = {}
+
# which icohps are considered
+
if self.which_bonds == "cation-anion":
+
limit_icohps = self.chemenv._get_limit_from_extremum(
+
self.chemenv.Icohpcollection,
+
self.cutoff_icohp,
+
adapt_extremum_to_add_cond=True,
+
additional_condition=1,
+
)
+
elif self.which_bonds == "all":
+
limit_icohps = self.chemenv._get_limit_from_extremum(
+
self.chemenv.Icohpcollection,
+
self.cutoff_icohp,
+
adapt_extremum_to_add_cond=True,
+
additional_condition=0,
+
)
+
# formula of the compound
+
formula = str(self.structure.composition.reduced_formula)
+
# set population type
+
type_pop = self._get_pop_type()
+
# how many inequivalent cations are in the structure
+
if self.which_bonds == "cation-anion":
+
number_considered_ions = len(self.seq_ineq_ions)
+
elif self.which_bonds == "all":
+
number_considered_ions = len(self.seq_ineq_ions)
+
+
# what was the maximum bond lengths that was considered
+
max_bond_lengths = max(self.chemenv.Icohpcollection._list_length)
+
+
# what are the charges for the cations in the structure
+
charge_list = self.chemenv.valences
+
+
# dictionary including bonding information for each site
+
site_dict = {}
+
if self.which_bonds == "cation-anion":
+
for ication, ce, cation_anion_infos, labels, cohps in zip(
+
self.seq_ineq_ions,
+
self.seq_coord_ions,
+
self.seq_infos_bonds,
+
self.seq_labels_cohps,
+
self.seq_cohps,
+
):
+
namecation = str(self.structure[ication].specie)
+
+
# This will compute the mean strengths of ICOHPs
+
mean_icohps = self._get_strenghts_for_each_bond(
+
pairs=cation_anion_infos[4],
+
strengths=cation_anion_infos[1],
+
nameion=namecation,
+
)
+
# pairs, strengths, nameion
+
# will collect if there are antibonding states present
+
antbdg = self._get_antibdg_states(cohps, labels, namecation)
+
dict_antibonding = self._integrate_antbdstates_below_efermi_for_set_cohps(
+
labels, cohps, nameion=namecation
+
)
+
bond_dict = self._get_bond_dict(mean_icohps, antbdg, namecation, type_pop=type_pop)
+
bond_resolved_labels = self.get_site_bond_resolved_labels()
+
+
for cation_name, icohp_data in bond_dict.items():
+
for atom_pair, bonding_data in dict_antibonding.items():
+
if namecation == atom_pair.split("-")[0] and cation_name == atom_pair.split("-")[1]:
+
icohp_data["bonding"] = bonding_data["bonding"]
+
icohp_data["antibonding"] = bonding_data["antibonding"]
+
if self.orbital_resolved:
+
# get orb resolved data to be added
+
orb_resolved_bond_info = self._get_orbital_resolved_data(
+
nameion=namecation,
+
iion=ication,
+
labels=labels,
+
bond_resolved_labels=bond_resolved_labels,
+
type_pop=type_pop,
+
)
+
# match the dict key in bond_dict and get corresponding orbital data
+
for ion_atom_pair_orb in orb_resolved_bond_info:
+
orb_data_atom_pair = ion_atom_pair_orb.split(": ")[-1]
+
atom_pair_here = atom_pair.split("-")
+
atom_pair_here.sort()
+
if (
+
orb_data_atom_pair == "-".join(atom_pair_here)
+
and (namecation + str(ication + 1) + ":") in ion_atom_pair_orb
+
):
+
icohp_data["orbital_data"] = orb_resolved_bond_info[ion_atom_pair_orb]
+
+
orb_data_stats = self._get_bond_resolved_data_stats(
+
orb_resolved_bond_data=orb_resolved_bond_info[ion_atom_pair_orb],
+
)
+
+
icohp_data["orbital_data"].update(orb_data_stats)
+
+
site_dict[ication] = {
+
"env": ce,
+
"bonds": bond_dict,
+
"ion": namecation,
+
"charge": charge_list[ication],
+
"relevant_bonds": cation_anion_infos[3],
+
}
+
elif self.which_bonds == "all":
+
for iion, ce, bond_infos, labels, cohps in zip(
+
self.seq_ineq_ions,
+
self.seq_coord_ions,
+
self.seq_infos_bonds,
+
self.seq_labels_cohps,
+
self.seq_cohps,
+
):
+
nameion = str(self.structure[iion].specie)
+
+
# This will compute the mean strengths of ICOHPs
+
mean_icohps = self._get_strenghts_for_each_bond(
+
pairs=bond_infos[4], strengths=bond_infos[1], nameion=None
+
)
+
# pairs, strengths, nameion
+
# will collect if there are antibonding states present
+
antbdg = self._get_antibdg_states(cohps, labels, nameion=None)
+
+
dict_antibonding = self._integrate_antbdstates_below_efermi_for_set_cohps(labels, cohps, nameion)
+
+
bond_dict = self._get_bond_dict(mean_icohps, antbdg, nameion=nameion, type_pop=type_pop)
+
bond_resolved_labels = self.get_site_bond_resolved_labels()
+
+
for cation_name, icohp_data in bond_dict.items():
+
for atom_pair, bonding_data in dict_antibonding.items():
+
if nameion == atom_pair.split("-")[0] and cation_name == atom_pair.split("-")[1]:
+
icohp_data["bonding"] = bonding_data["bonding"]
+
icohp_data["antibonding"] = bonding_data["antibonding"]
+
if self.orbital_resolved:
+
# get orb resolved data to be added
+
orb_resolved_bond_info = self._get_orbital_resolved_data(
+
nameion=nameion,
+
iion=iion,
+
labels=labels,
+
bond_resolved_labels=bond_resolved_labels,
+
type_pop=type_pop,
+
)
+
# match the dict key in bond_dict and get corresponding orbital data
+
for ion_atom_pair_orb in orb_resolved_bond_info:
+
orb_data_atom_pair = ion_atom_pair_orb.split(": ")[-1]
+
atom_pair_here = atom_pair.split("-")
+
atom_pair_here.sort()
+
if (
+
orb_data_atom_pair == "-".join(atom_pair_here)
+
and (nameion + str(iion + 1) + ":") in ion_atom_pair_orb
+
):
+
icohp_data["orbital_data"] = orb_resolved_bond_info[ion_atom_pair_orb]
+
+
orb_data_stats = self._get_bond_resolved_data_stats(
+
orb_resolved_bond_data=orb_resolved_bond_info[ion_atom_pair_orb],
+
)
+
+
icohp_data["orbital_data"].update(orb_data_stats)
+
+
site_dict[iion] = {
+
"env": ce,
+
"bonds": bond_dict,
+
"ion": nameion,
+
"charge": charge_list[iion],
+
"relevant_bonds": bond_infos[3],
+
}
+
+
if self.path_to_madelung is None and self.madelung_obj is None:
+
if self.which_bonds == "cation-anion":
+
# This sets the dictionary including the most important information on the compound
+
self.condensed_bonding_analysis = {
+
"formula": formula,
+
"max_considered_bond_length": max_bond_lengths,
+
f"limit_i{type_pop.lower()}": limit_icohps,
+
"number_of_considered_ions": number_considered_ions,
+
"sites": site_dict,
+
"type_charges": self.type_charge,
+
}
+
elif self.which_bonds == "all":
+
self.condensed_bonding_analysis = {
+
"formula": formula,
+
"max_considered_bond_length": max_bond_lengths,
+
f"limit_i{type_pop.lower()}": limit_icohps,
+
"number_of_considered_ions": number_considered_ions,
+
"sites": site_dict,
+
"type_charges": self.type_charge,
+
}
+
else:
+
madelung = MadelungEnergies(self.path_to_madelung) if self.path_to_madelung else self.madelung_obj
+
if self.type_charge == "Mulliken":
+
madelung_energy = madelung.madelungenergies_mulliken
+
elif self.type_charge == "Löwdin":
+
madelung_energy = madelung.madelungenergies_loewdin
+
else:
+
madelung_energy = None
+
# This sets the dictionary including the most important information on the compound
+
if self.which_bonds == "cation-anion":
+
self.condensed_bonding_analysis = {
+
"formula": formula,
+
"max_considered_bond_length": max_bond_lengths,
+
f"limit_i{type_pop.lower()}": limit_icohps,
+
"number_of_considered_ions": number_considered_ions,
+
"sites": site_dict,
+
"type_charges": self.type_charge,
+
"madelung_energy": madelung_energy,
+
}
+
elif self.which_bonds == "all":
+
self.condensed_bonding_analysis = {
+
"formula": formula,
+
"max_considered_bond_length": max_bond_lengths,
+
f"limit_i{type_pop.lower()}": limit_icohps,
+
"number_of_considered_ions": number_considered_ions,
+
"sites": site_dict,
+
"type_charges": self.type_charge,
+
"madelung_energy": madelung_energy,
+
}
+
+
[docs] def set_summary_dicts(self):
+
"""
+
Set summary dict that can be used for correlations.
+
+
bond_dict that includes information on each bond
+
+
"has_antbd" tells if there are antbonding states
+
"ICOHP_mean" shows the mean of all ICOHPs in EV
+
+
{'Yb-Sb': { 'has_antbdg': False, 'ICOHP_mean': -1.7448},
+
'Mn-Sb': { 'has_antbdg': True, 'ICOHP_mean': -1.525}}
+
+
a cation dict that includes all different coordination environments and counts for them
+
{'Na': {'T:4': 4, 'A:2': 4}, 'Si': {'T:6': 4, 'PP:6': 4}}
+
+
Returns:
+
None
+
+
"""
+
relevant_ion_ids = [isite for isite in self.list_equivalent_sites if isite in self.seq_ineq_ions]
+
# set population type
+
type_pop = self._get_pop_type()
+
+
final_dict_bonds = {}
+
for key in relevant_ion_ids:
+
item = self.condensed_bonding_analysis["sites"][key]
+
for type, properties in item["bonds"].items():
+
label_list = [item["ion"], str(type)]
+
new_label = sorted(label_list.copy())
+
label = str(new_label[0]) + "-" + str(new_label[1])
+
+
if label not in final_dict_bonds:
+
final_dict_bonds[label] = {
+
"number_of_bonds": int(properties["number_of_bonds"]),
+
f"I{type_pop}_sum": float(properties[f"I{type_pop}_sum"]),
+
"has_antbdg": properties["has_antibdg_states_below_Efermi"],
+
}
+
else:
+
final_dict_bonds[label]["number_of_bonds"] += int(properties["number_of_bonds"])
+
final_dict_bonds[label][f"I{type_pop}_sum"] += float(properties[f"I{type_pop}_sum"])
+
final_dict_bonds[label]["has_antbdg"] = (
+
final_dict_bonds[label]["has_antbdg"] or properties["has_antibdg_states_below_Efermi"]
+
)
+
self.final_dict_bonds = {}
+
for key, item in final_dict_bonds.items():
+
self.final_dict_bonds[key] = {}
+
self.final_dict_bonds[key][f"I{type_pop}_mean"] = item[f"I{type_pop}_sum"] / (item["number_of_bonds"])
+
self.final_dict_bonds[key]["has_antbdg"] = item["has_antbdg"]
+
+
# rework, add all environments!
+
final_dict_ions = {}
+
for key in relevant_ion_ids:
+
if self.condensed_bonding_analysis["sites"][key]["ion"] not in final_dict_ions:
+
final_dict_ions[self.condensed_bonding_analysis["sites"][key]["ion"]] = [
+
self.condensed_bonding_analysis["sites"][key]["env"]
+
]
+
else:
+
final_dict_ions[self.condensed_bonding_analysis["sites"][key]["ion"]].append(
+
self.condensed_bonding_analysis["sites"][key]["env"]
+
)
+
+
self.final_dict_ions = {}
+
for key, item in final_dict_ions.items():
+
self.final_dict_ions[key] = dict(Counter(item))
+
+
[docs] @staticmethod
+
def get_lobster_calc_quality_summary(
+
path_to_poscar: str | None = None,
+
path_to_lobsterout: str | None = None,
+
path_to_lobsterin: str | None = None,
+
path_to_potcar: str | None = None,
+
potcar_symbols: list | None = None,
+
path_to_charge: str | None = None,
+
path_to_bandoverlaps: str | None = None,
+
path_to_doscar: str | None = None,
+
path_to_vasprun: str | None = None,
+
structure_obj: Structure | None = None,
+
lobsterin_obj: Lobsterin | None = None,
+
lobsterout_obj: Lobsterout | None = None,
+
charge_obj: Charge | None = None,
+
bandoverlaps_obj: Bandoverlaps | None = None,
+
lobster_completedos_obj: LobsterCompleteDos | None = None,
+
vasprun_obj: Vasprun | None = None,
+
dos_comparison: bool = False,
+
e_range: list = [-5, 0],
+
n_bins: int | None = None,
+
bva_comp: bool = False,
+
) -> dict:
+
"""
+
Analyze LOBSTER calculation quality.
+
+
:param path_to_poscar: path to structure file
+
:param path_to_lobsterout: path to lobsterout file
+
:param path_to_lobsterin: path to lobsterin file
+
:param path_to_potcar: path to VASP potcar file
+
:param potcar_symbols: list of potcar symbols from potcar file (can be used if no potcar available)
+
:param path_to_charge: path to CHARGE.lobster file
+
:param path_to_bandoverlaps: path to bandOverlaps.lobster file
+
:param path_to_doscar: path to DOSCAR.lobster or DOSCAR.LSO.lobster file
+
:param path_to_vasprun: path to vasprun.xml file
+
:param structure_obj: pymatgen pymatgen.core.structure.Structure object
+
:param lobsterin_obj: pymatgen.lobster.io.Lobsterin object
+
:param lobsterout_obj: pymatgen lobster.io.Lobsterout object
+
:param charge_obj: pymatgen lobster.io.Charge object
+
:param bandoverlaps_obj: pymatgen lobster.io.BandOverlaps object
+
:param lobster_completedos_obj: pymatgen.electronic_structure.dos.LobsterCompleteDos object
+
:param vasprun_obj: pymatgen vasp.io.Vasprun object
+
:param dos_comparison: will compare DOS from VASP and LOBSTER and return tanimoto index
+
:param e_range: energy range for DOS comparisons
+
:param n_bins: number of bins to discretize DOS for comparisons
+
:param bva_comp: Compares LOBSTER charge signs with Bond valence charge signs
+
+
Returns:
+
A dict of summary of LOBSTER calculation quality by analyzing basis set used,
+
charge spilling from lobsterout/ PDOS comparisons of VASP and LOBSTER /
+
BVA charge comparisons
+
+
"""
+
quality_dict = {}
+
+
if path_to_potcar and not potcar_symbols and not path_to_vasprun and not vasprun_obj:
+
potcar_names = Lobsterin._get_potcar_symbols(POTCAR_input=path_to_potcar)
+
elif not path_to_potcar and not path_to_vasprun and not vasprun_obj and potcar_symbols:
+
potcar_names = potcar_symbols
+
elif path_to_vasprun and not vasprun_obj:
+
vasprun = Vasprun(path_to_vasprun, parse_potcar_file=False, parse_eigen=False)
+
potcar_names = [potcar.split(" ")[1] for potcar in vasprun.potcar_symbols]
+
elif vasprun_obj and not path_to_vasprun:
+
potcar_names = [potcar.split(" ")[1] for potcar in vasprun_obj.potcar_symbols]
+
else:
+
raise ValueError(
+
"Please provide either path_to_potcar or list of "
+
"potcar_symbols or path to vasprun.xml or vasprun object. "
+
"Crucial to identify basis used for projections"
+
)
+
+
if path_to_poscar:
+
struct = Structure.from_file(path_to_poscar)
+
elif structure_obj:
+
struct = structure_obj
+
else:
+
raise ValueError("Please provide path_to_poscar or structure_obj")
+
+
ref_bases = Lobsterin.get_all_possible_basis_functions(structure=struct, potcar_symbols=potcar_names)
+
+
if path_to_lobsterin:
+
lobs_in = Lobsterin.from_file(path_to_lobsterin)
+
elif lobsterin_obj:
+
lobs_in = lobsterin_obj
+
else:
+
raise ValueError("Please provide path_to_lobsterin or lobsterin_obj")
+
+
calc_basis = []
+
for basis in lobs_in["basisfunctions"]:
+
basis_sep = basis.split()[1:]
+
basis_comb = " ".join(basis_sep)
+
calc_basis.append(basis_comb)
+
+
if calc_basis == list(ref_bases[0].values()):
+
quality_dict["minimal_basis"] = True # type: ignore
+
else:
+
quality_dict["minimal_basis"] = False # type: ignore
+
warnings.warn(
+
"Consider rerunning the calc with the minimum basis as well. Choosing is "
+
"larger basis set is recommended if you see a significant improvement of "
+
"the charge spilling and material has non-zero band gap."
+
)
+
+
if path_to_lobsterout:
+
lob_out = Lobsterout(path_to_lobsterout)
+
elif lobsterout_obj:
+
lob_out = lobsterout_obj
+
else:
+
raise ValueError("Please provide path_to_lobsterout or lobsterout_obj")
+
+
quality_dict["charge_spilling"] = {
+
"abs_charge_spilling": round((sum(lob_out.charge_spilling) / 2) * 100, 4),
+
"abs_total_spilling": round((sum(lob_out.total_spilling) / 2) * 100, 4),
+
} # type: ignore
+
+
if path_to_bandoverlaps is not None and not bandoverlaps_obj:
+
band_overlaps = Bandoverlaps(filename=path_to_bandoverlaps) if Path(path_to_bandoverlaps).exists() else None
+
elif path_to_bandoverlaps is None and bandoverlaps_obj:
+
band_overlaps = bandoverlaps_obj
+
else:
+
band_overlaps = None
+
+
if band_overlaps is not None:
+
for line in lob_out.warning_lines:
+
if "k-points could not be orthonormalized" in line:
+
total_kpoints = int(line.split(" ")[2])
+
+
# store actual number of devations above pymatgen default limit of 0.1
+
dev_val = []
+
for dev in band_overlaps.max_deviation:
+
if dev > 0.1:
+
dev_val.append(dev)
+
+
quality_dict["band_overlaps_analysis"] = { # type: ignore
+
"file_exists": True,
+
"limit_maxDeviation": 0.1,
+
"has_good_quality_maxDeviation": band_overlaps.has_good_quality_maxDeviation(limit_maxDeviation=0.1),
+
"max_deviation": round(max(band_overlaps.max_deviation), 4),
+
"percent_kpoints_abv_limit": round((len(dev_val) / total_kpoints) * 100, 4),
+
}
+
+
else:
+
quality_dict["band_overlaps_analysis"] = { # type: ignore
+
"file_exists": False,
+
"limit_maxDeviation": None,
+
"has_good_quality_maxDeviation": True,
+
"max_deviation": None,
+
"percent_kpoints_abv_limit": None,
+
}
+
+
if bva_comp:
+
try:
+
bond_valence = BVAnalyzer()
+
+
bva_oxi = []
+
if path_to_charge and not charge_obj:
+
lobs_charge = Charge(filename=path_to_charge)
+
elif not path_to_charge and charge_obj:
+
lobs_charge = charge_obj
+
else:
+
raise Exception("BVA comparison is requested, thus please provide path_to_charge or charge_obj")
+
for i in bond_valence.get_valences(structure=struct):
+
if i >= 0:
+
bva_oxi.append("POS")
+
else:
+
bva_oxi.append("NEG")
+
+
mull_oxi = []
+
for i in lobs_charge.Mulliken:
+
if i >= 0:
+
mull_oxi.append("POS")
+
else:
+
mull_oxi.append("NEG")
+
+
loew_oxi = []
+
for i in lobs_charge.Loewdin:
+
if i >= 0:
+
loew_oxi.append("POS")
+
else:
+
loew_oxi.append("NEG")
+
+
quality_dict["charge_comparisons"] = {} # type: ignore
+
if mull_oxi == bva_oxi:
+
quality_dict["charge_comparisons"]["bva_mulliken_agree"] = True # type: ignore
+
else:
+
quality_dict["charge_comparisons"]["bva_mulliken_agree"] = False # type: ignore
+
+
if mull_oxi == bva_oxi:
+
quality_dict["charge_comparisons"]["bva_loewdin_agree"] = True # type: ignore
+
else:
+
quality_dict["charge_comparisons"]["bva_loewdin_agree"] = False # type: ignore
+
+
except ValueError:
+
quality_dict["charge_comparisons"] = {} # type: ignore
+
warnings.warn(
+
"Oxidation states from BVA analyzer cannot be determined. "
+
"Thus BVA charge comparison will be skipped"
+
)
+
if dos_comparison:
+
if "LSO" not in str(path_to_doscar).split("."):
+
warnings.warn(
+
"Consider using DOSCAR.LSO.lobster, as non LSO DOS from LOBSTER can have negative DOS values"
+
)
+
if path_to_doscar:
+
doscar_lobster = Doscar(
+
doscar=path_to_doscar,
+
structure_file=path_to_poscar,
+
structure=structure_obj,
+
)
+
+
dos_lobster = doscar_lobster.completedos
+
elif lobster_completedos_obj:
+
dos_lobster = lobster_completedos_obj
+
else:
+
raise ValueError(
+
"Dos comparison is requested, so please provide either path_to_doscar or lobster_completedos_obj"
+
)
+
+
if path_to_vasprun:
+
vasprun = Vasprun(path_to_vasprun, parse_potcar_file=False, parse_eigen=False)
+
elif vasprun_obj:
+
vasprun = vasprun_obj
+
else:
+
raise ValueError(
+
"Dos comparison is requested, so please provide either path to vasprun.xml or vasprun_obj"
+
)
+
dos_vasp = vasprun.complete_dos
+
+
quality_dict["dos_comparisons"] = {} # type: ignore
+
+
for orb in dos_lobster.get_spd_dos():
+
if e_range[0] >= min(dos_vasp.energies) and e_range[0] >= min(dos_lobster.energies):
+
min_e = e_range[0]
+
else:
+
warnings.warn(
+
"Minimum energy range requested for DOS comparisons is not available "
+
"in VASP or LOBSTER calculation. Thus, setting min_e to -5 eV"
+
)
+
min_e = -5
+
+
if e_range[-1] <= max(dos_vasp.energies) and e_range[-1] <= max(dos_lobster.energies):
+
max_e = e_range[-1]
+
else:
+
warnings.warn(
+
"Maximum energy range requested for DOS comparisons is not available "
+
"in VASP or LOBSTER calculation. Thus, setting max_e to 0 eV"
+
)
+
max_e = 0
+
+
if np.diff(dos_vasp.energies)[0] >= 0.1 or np.diff(dos_lobster.energies)[0] >= 0.1:
+
warnings.warn(
+
"Input DOS files have very few points in the energy interval and thus "
+
"comparisons will not be reliable. Please rerun the calculations with "
+
"higher number of DOS points. Set NEDOS and COHPSteps tags to >= 2000 in VASP and LOBSTER "
+
"calculations, respectively."
+
)
+
+
if not n_bins:
+
n_bins = 56
+
+
fp_lobster_orb = dos_lobster.get_dos_fp(
+
min_e=min_e,
+
max_e=max_e,
+
n_bins=n_bins,
+
normalize=True,
+
type=orb.name,
+
)
+
fp_vasp_orb = dos_vasp.get_dos_fp(
+
min_e=min_e,
+
max_e=max_e,
+
n_bins=n_bins,
+
normalize=True,
+
type=orb.name,
+
)
+
+
tani_orb = round(
+
dos_vasp.get_dos_fp_similarity(fp_lobster_orb, fp_vasp_orb, tanimoto=True),
+
4,
+
)
+
quality_dict["dos_comparisons"][f"tanimoto_orb_{orb.name}"] = tani_orb # type: ignore
+
+
fp_lobster = dos_lobster.get_dos_fp(
+
min_e=min_e,
+
max_e=max_e,
+
n_bins=n_bins,
+
normalize=True,
+
type="summed_pdos",
+
)
+
fp_vasp = dos_vasp.get_dos_fp(
+
min_e=min_e,
+
max_e=max_e,
+
n_bins=n_bins,
+
normalize=True,
+
type="summed_pdos",
+
)
+
+
tanimoto_summed = round(dos_vasp.get_dos_fp_similarity(fp_lobster, fp_vasp, tanimoto=True), 4)
+
quality_dict["dos_comparisons"]["tanimoto_summed"] = tanimoto_summed # type: ignore
+
quality_dict["dos_comparisons"]["e_range"] = [min_e, max_e] # type: ignore
+
quality_dict["dos_comparisons"]["n_bins"] = n_bins # type: ignore
+
+
return quality_dict
+
+
+
+
+
+
+
+
+
+
+
+
+