| import pyarrow.parquet as pq, pyarrow.compute as pc, glob, os, numpy as np, pandas as pd, sys |
| W=sys.argv[1] |
| S=os.path.expanduser("~/.cache/huggingface/hub/datasets--LeMaterial--LeMat-Bulk/snapshots/0dc17eea904b860ad7288141e9870f67f8e6bb2c/compatible_pbe") |
| dfs=[] |
| for f in sorted(glob.glob(S+"/*.parquet")): |
| t=pq.read_table(f,columns=["immutable_id","nsites","elements","chemical_formula_reduced","energy","last_modified","functional","cross_compatibility","forces","stress_tensor","lattice_vectors"]) |
| d=t.select(["immutable_id","nsites","chemical_formula_reduced","energy","last_modified","functional","cross_compatibility"]).to_pandas() |
| d["elements"]=[",".join(sorted(e)) for e in t.column("elements").to_pylist()] |
| fr=t.column("forces").to_pylist() |
| d["fmax"]=[float(np.linalg.norm(np.asarray(x),axis=1).max()) if x else np.nan for x in fr] |
| st=t.column("stress_tensor").to_pylist() |
| d["p_kbar"]=[float(-np.trace(np.asarray(x))/3) if x is not None and len(x)==3 else np.nan for x in st] |
| lv=t.column("lattice_vectors").to_pylist() |
| d["vol"]=[abs(np.linalg.det(np.asarray(x))) for x in lv] |
| d["shard"]=os.path.basename(f) |
| dfs.append(d); print(f, len(d), flush=True) |
| df=pd.concat(dfs,ignore_index=True) |
| df["src"]=df.immutable_id.str.extract(r"^([a-z]+)")[0] |
| df.to_parquet(W+"/lemat_meta.parquet") |
| print(df.src.value_counts()); print(df.functional.value_counts(), df.cross_compatibility.value_counts()) |
|
|
