| """Example: Compute per-family and per-source statistics.""" |
| import json |
| import numpy as np |
| from collections import Counter |
|
|
| with open("dataset/entries_final_v3.json") as f: |
| entries = json.load(f) |
|
|
| |
| families = Counter(f for e in entries for f in e.get("families", ["unknown"])) |
| print("Family Distribution:") |
| for fam, count in families.most_common(): |
| pct = 100 * count / len(entries) |
| print(f" {fam:25s}: {count:>7,} ({pct:.1f}%)") |
|
|
| |
| print("\nFE Distribution by Source:") |
| for src in ["mp", "oqmd", "jarvis"]: |
| subset = [e for e in entries if e.get("source") == src] |
| fe_vals = [e.get("formation_energy_per_atom", 0) for e in subset |
| if e.get("formation_energy_per_atom") is not None] |
| print(f" {src:8s}: mean={np.mean(fe_vals):.3f} " |
| f"median={np.median(fe_vals):.3f} " |
| f"std={np.std(fe_vals):.3f} " |
| f"N={len(fe_vals):,}") |
|
|
| |
| print("\nProperty Coverage:") |
| for prop in ["formation_energy_per_atom", "energy_above_hull", "band_gap"]: |
| present = sum(1 for e in entries if e.get(prop) is not None) |
| print(f" {prop:35s}: {present:>7,} / {len(entries):,} " |
| f"({100*present/len(entries):.1f}%)") |
|
|
