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29e3113 85c01c7 29e3113 894b6ee 29e3113 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 | """Parallel BVSE processor — processes Li/Na entries using multiprocessing.
Launched from nohup; checkpoints every N entries per worker.
"""
import json, os, sys, time, argparse, warnings
from pathlib import Path
from collections import defaultdict
from multiprocessing import Pool, cpu_count
import numpy as np
BASE_DIR = Path(__file__).resolve().parent.parent
sys.path.insert(0, str(BASE_DIR / "dataset"))
os.environ["OPENBLAS_NUM_THREADS"] = "1"
os.environ["OMP_NUM_THREADS"] = "1"
os.environ["MKL_NUM_THREADS"] = "1"
warnings.filterwarnings("ignore")
PARQUET_PATH = BASE_DIR / "dataset" / "entries_v3.parquet"
INDEX_PATH = BASE_DIR / "dataset" / "entries_v3.index.json"
CHECKPOINT_PATH = BASE_DIR / "dataset" / "bvse_checkpoint.json"
MOBILITY_THRESHOLDS = [
("superionic", 0.25),
("good", 0.50),
("moderate", 0.75),
("poor", float('inf')),
]
def process_one(args):
sid, struct_json, mobile_ion = args
from pymatgen.core import Structure
from pymatgen.analysis.bond_valence import BVAnalyzer
from bvlain import Lain
result = {"sid": sid, "barrier": None, "cls": "none", "dim": "none", "skip": ""}
try:
struct = Structure.from_dict(json.loads(struct_json))
bva = BVAnalyzer()
st_oxi = bva.get_oxi_state_decorated_structure(struct)
lain = Lain(verbose=False)
lain.read_structure(st_oxi, oxi_check=False)
lain.bvse_distribution(mobile_ion=f"{mobile_ion}1+", resolution=0.5)
barriers = lain.percolation_barriers(encut=10.0, n_jobs=1)
min_barrier = min(v for v in barriers.values())
if min_barrier == float('inf') or min_barrier < 0:
result["skip"] = "no connected pathway"
return result
eps = 0.05
dim_map = {1: "1D", 2: "2D", 3: "3D"}
dims = []
for d in [1, 2, 3]:
if barriers[f"E_{d}D"] <= min_barrier + eps:
dims.append(d)
percolation_dim = dim_map.get(max(dims), "3D") if dims else "none"
mobility_class = "poor"
for cls_name, threshold in MOBILITY_THRESHOLDS:
if min_barrier < threshold:
mobility_class = cls_name
break
result["barrier"] = round(float(min_barrier), 4)
result["cls"] = mobility_class
result["dim"] = percolation_dim
except Exception as exc:
err = str(exc)
if "No BVSE data" in err:
result["skip"] = "no BV params"
elif "oxidation state" in err.lower():
result["skip"] = "oxidation failed"
elif "min() iterable" in err:
result["skip"] = "no path"
else:
result["skip"] = f"error: {err[:80]}"
return result
def _write_checkpoint(table, updated_rows, all_ssb, sid_to_idx, all_table_rows):
"""Write updated ssb_screening values back to the Parquet table."""
import pyarrow as pa
import pyarrow.parquet as pq
from dataset_store import _encode_value, _decode_value
ssb_col = table.column("ssb_screening").to_pylist()
for table_row in updated_rows:
# Find the corresponding index in all_* arrays
sid = _decode_value(table.column("source_id")[table_row].as_py())
if sid in sid_to_idx:
ssb_col[table_row] = _encode_value(all_ssb[sid_to_idx[sid]])
table = table.set_column(
table.schema.get_field_index("ssb_screening"), "ssb_screening",
pa.chunked_array([pa.array(ssb_col)])
)
pq.write_table(table, PARQUET_PATH, compression="zstd")
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--workers", type=int, default=max(1, cpu_count() - 1))
parser.add_argument("--batch-size", type=int, default=5000)
parser.add_argument("--max-sites", type=int, default=60)
args = parser.parse_args()
print(f"Parallel BVSE processor | workers={args.workers} batch={args.batch_size} max_sites={args.max_sites}")
print(f"Loading Parquet...")
import pyarrow.parquet as pq
t0 = time.time()
table = pq.read_table(PARQUET_PATH)
# Decode columns
from dataset_store import _decode_value, _encode_value
all_sids = []
all_structs = []
all_mobiles = []
all_ssb = []
all_rows = []
for i in range(table.num_rows):
sid = _decode_value(table.column("source_id")[i].as_py())
mobile = _decode_value(table.column("mobile_ion")[i].as_py())
nsites_raw = table.column("nsites")[i].as_py()
nsites = int(_decode_value(nsites_raw)) if nsites_raw else 999
struct_raw = table.column("structure_json")[i].as_py()
struct = _decode_value(struct_raw) if struct_raw else None
ssb_raw = table.column("ssb_screening")[i].as_py()
ssb = _decode_value(ssb_raw) if ssb_raw else {}
if mobile in ("Li", "Na") and struct and nsites <= args.max_sites:
all_sids.append(sid)
all_structs.append(struct)
all_mobiles.append(mobile)
all_ssb.append(ssb)
all_rows.append(i)
print(f" {len(all_sids):,} Li/Na entries (≤{args.max_sites} sites) loaded in {time.time()-t0:.1f}s")
# Build lookup: source_id -> index in all_* arrays
sid_to_idx = {sid: i for i, sid in enumerate(all_sids)}
all_table_rows = all_rows # table row indices for each entry
updated_rows = set()
# Load checkpoint
completed_sids = set()
if CHECKPOINT_PATH.exists():
with open(CHECKPOINT_PATH) as f:
completed_sids = set(json.load(f))
print(f" Resuming from checkpoint: {len(completed_sids):,} already computed")
# Build worklist (skip already done)
worklist = []
for idx in range(len(all_sids)):
if all_sids[idx] not in completed_sids:
worklist.append((all_sids[idx], all_structs[idx], all_mobiles[idx]))
print(f" Remaining: {len(worklist):,} entries")
if not worklist:
print(" All entries already processed.")
return
# Process in batches
total_processed = len(completed_sids)
total_ok = 0
total_skip = 0
total_err = 0
barriers = []
class_counts = defaultdict(int)
batch_num = 0
checkpoint_counter = 0
CHECKPOINT_EVERY_N_BATCHES = 50 # checkpoint every 50 batches (every ~2500 entries at batch=50)
pool = Pool(processes=args.workers)
t_start = time.time()
while worklist:
batch = worklist[:args.batch_size]
worklist = worklist[args.batch_size:]
print(f" Batch {batch_num}: {len(batch)} entries, {len(worklist)} remaining...", flush=True)
results = pool.map(process_one, batch)
# Apply results
for r in results:
sid = r["sid"]
if sid in sid_to_idx:
idx = sid_to_idx[sid]
ssb = all_ssb[idx]
if r["barrier"] is not None:
ssb["bvse_migration_barrier_eV"] = r["barrier"]
ssb["bvse_mobility_class"] = r["cls"]
ssb["bvse_percolation_dimensionality"] = r["dim"]
barriers.append(r["barrier"])
class_counts[r["cls"]] += 1
total_ok += 1
elif r["skip"]:
total_skip += 1
else:
total_err += 1
completed_sids.add(sid)
updated_rows.add(all_table_rows[idx])
total_processed += len(batch)
batch_num += 1
# Periodic checkpoint to Parquet
checkpoint_counter += 1
if checkpoint_counter >= CHECKPOINT_EVERY_N_BATCHES or not worklist:
_write_checkpoint(table, updated_rows, all_ssb, sid_to_idx, all_table_rows)
# Save completed SIDs for resume
with open(CHECKPOINT_PATH, "w") as f:
json.dump(list(completed_sids), f)
rate = total_processed / (time.time() - t_start)
eta = len(worklist) / rate if rate > 0 and worklist else 0
print(f" CHECKPOINT: {total_processed:,} done, {len(worklist):,} remain, "
f"{rate:.1f} ent/s, ETA {eta/3600:.1f}h", flush=True)
checkpoint_counter = 0
pool.close()
pool.join()
elapsed = time.time() - t_start
print(f"\n{'=' * 60}")
print(f" BVSE COMPLETE")
print(f" Processed: {total_processed:,}")
print(f" Barriers computed: {total_ok}")
print(f" Skipped: {total_skip}")
print(f" Errors: {total_err}")
print(f" Time: {elapsed/60:.1f} min ({total_processed/elapsed:.1f} ent/s)")
print(f"{'=' * 60}")
if __name__ == "__main__":
main()
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