File size: 5,707 Bytes
e94bdab | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 | """Predict oxidation states for all entries using bond valence analysis.
Fills each entry with:
- oxidation_states: dict of {element: average_oxidation_state}
- predicted_oxidation_states_valid: bool
Usage:
python scripts/compute_oxidation_states.py
python scripts/compute_oxidation_states.py --limit 10000
python scripts/compute_oxidation_states.py --dry-run
"""
import json, os, sys, time, argparse, warnings
from pathlib import Path
from collections import defaultdict
import numpy as np
warnings.filterwarnings("ignore")
WIDTH = 60
COMMON_OXIDATION = {
"Li": [1], "Na": [1], "K": [1], "Rb": [1], "Cs": [1],
"Mg": [2], "Ca": [2], "Sr": [2], "Ba": [2],
"Al": [3], "Ga": [3], "In": [3],
"Si": [4], "Ge": [4], "Sn": [2, 4], "Pb": [2, 4],
"P": [5], "As": [3, 5], "Sb": [3, 5], "Bi": [3, 5],
"O": [-2], "S": [-2, 4, 6], "Se": [-2, 4, 6], "Te": [-2, 4, 6],
"F": [-1], "Cl": [-1], "Br": [-1], "I": [-1],
"N": [-3], "H": [1],
"Ti": [4], "V": [3, 5], "Cr": [3, 6], "Mn": [2, 4, 7],
"Fe": [2, 3], "Co": [2, 3], "Ni": [2], "Cu": [1, 2],
"Zn": [2], "Y": [3], "Zr": [4], "Nb": [5], "Mo": [4, 6],
"La": [3], "Ce": [3, 4], "Pr": [3], "Nd": [3], "Sm": [3],
"Eu": [2, 3], "Gd": [3], "Tb": [3, 4], "Dy": [3], "Ho": [3],
"Er": [3], "Tm": [3], "Yb": [2, 3], "Lu": [3],
"Ta": [5], "W": [6], "B": [3], "C": [4], "Sc": [3],
"Hg": [1, 2],
}
def parse_formula(formula):
import re
parts = re.findall(r'([A-Z][a-z]*)(\d*\.?\d*)', formula)
return {el: float(cnt) if cnt else 1.0 for el, cnt in parts}
def heuristic_oxidation_states(formula_dict):
elements = list(formula_dict.keys())
anions = {"O", "S", "Se", "Te", "F", "Cl", "Br", "I", "N", "P", "As", "Sb"}
cation_els = [el for el in elements if el not in anions]
anion_els = [el for el in elements if el in anions]
if not anion_els:
return {el: 0.0 for el in elements}
result = {}
assigned_anions = 0.0
for el in elements:
states = COMMON_OXIDATION.get(el, [0])
if el in anions:
result[el] = float(min(states))
assigned_anions += result[el] * formula_dict[el]
else:
result[el] = float(max(states))
total_charge = sum(result[el] * formula_dict[el] for el in elements)
if abs(total_charge) > 0.5 and cation_els:
scale = -assigned_anions / max(abs(total_charge - assigned_anions), 0.01)
for el in cation_els:
result[el] = round(result[el] * scale, 1)
return result
def main():
parser = argparse.ArgumentParser(description="Predict oxidation states")
parser.add_argument("--dry-run", action="store_true")
parser.add_argument("--limit", type=int, default=None)
args = parser.parse_args()
BASE_DIR = Path(__file__).resolve().parent.parent
DATASET_PATH = BASE_DIR / "dataset"
print("=" * WIDTH)
print(" OXIDATION STATE PREDICTION")
print("=" * WIDTH)
print("\nLoading entries...")
t0 = time.time()
with open(DATASET_PATH / "entries_final_v3.json") as f:
all_entries = json.load(f)
print(f" {len(all_entries):,} entries ({time.time()-t0:.1f}s)")
if args.limit:
all_entries = all_entries[:args.limit]
print(f" Limited to {args.limit} entries")
try:
from pymatgen.analysis.bond_valence import BVAnalyzer
from pymatgen.core import Structure
bva = BVAnalyzer()
bva_available = True
print(" BVAnalyzer available")
except Exception:
bva_available = False
print(" BVAnalyzer not available, heuristic only")
import json as _json
print(f"\n{'─' * WIDTH}")
print(" Assigning oxidation states...")
bva_success = 0
heuristic_assigned = 0
errors = 0
for idx, e in enumerate(all_entries):
formula = e.get("formula", "")
formula_dict = parse_formula(formula)
e["oxidation_states"] = {}
assigned = False
if bva_available and e.get("structure_json"):
try:
struct_dict = _json.loads(e["structure_json"])
structure = Structure.from_dict(struct_dict)
oxi_states = bva.get_valences(structure)
if oxi_states:
element_oxi = defaultdict(list)
for site, oxi in zip(structure, oxi_states):
element_oxi[site.specie.symbol].append(float(oxi))
e["oxidation_states"] = {el: round(sum(vals)/len(vals), 2) for el, vals in element_oxi.items()}
e["predicted_oxidation_states_valid"] = True
bva_success += 1
assigned = True
except Exception:
pass
if not assigned:
oxi = heuristic_oxidation_states(formula_dict)
e["oxidation_states"] = oxi
e["predicted_oxidation_states_valid"] = False
heuristic_assigned += 1
if (idx + 1) % 10000 == 0:
print(f" {idx+1}/{len(all_entries)} | BVA:{bva_success} Heuristic:{heuristic_assigned}")
print(f"\n BVA: {bva_success:,}, Heuristic: {heuristic_assigned:,}, Total: {bva_success+heuristic_assigned:,}/{len(all_entries):,}")
if args.dry_run:
print(f"\n (dry-run)")
else:
output_path = DATASET_PATH / "entries_final_v3.json"
print(f"\n Writing...")
t_write = time.time()
with open(output_path, "w") as f:
json.dump(all_entries, f)
print(f" Done ({time.time()-t_write:.1f}s)")
print("=" * WIDTH)
if __name__ == "__main__":
main()
|