File size: 6,743 Bytes
df32294 | 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 | """Phase 8: Metadata Audit — completeness, consistency, correctness."""
import json, time
from pathlib import Path
from collections import Counter
import numpy as np
OUT = Path("scripts/audit_reports")
DATASET = "dataset/entries_final_v3.json"
AUDIT_DIR = Path.cwd() if Path.cwd().name == "Scandium-Dataset" else Path("/home/shamique/Scandium Labs SSB/Scandium-Dataset")
severity_counts = {"CRITICAL": 0, "HIGH": 0, "MEDIUM": 0, "LOW": 0, "PASS": 0}
findings = []
def finding(severity, phase, check, status, detail):
severity_counts[severity] += 1
findings.append({"severity": severity, "phase": phase, "check": check, "status": status, "detail": str(detail)[:200]})
s = "🔴" if severity == "CRITICAL" else "🟠" if severity == "HIGH" else "🟡" if severity == "MEDIUM" else "🔵" if severity == "LOW" else "✅"
print(f" {s} [{severity:8s}] {check}: {str(detail)[:120]}")
REQUIRED_FIELDS = ["source_id", "formula", "elements", "source",
"space_group", "volume", "density", "structure_json",
"quality_score", "quality_sub_scores", "quality_flags",
"tier", "provenance", "nsites", "band_gap", "formation_energy_per_atom",
"families"]
def main():
print("=" * 60)
print(" PHASE 8: METADATA AUDIT")
print("=" * 60)
with open(AUDIT_DIR / DATASET) as f:
entries = json.load(f)
N = len(entries)
# Field completeness
print(f"\n--- Field Completeness ---")
field_missing = Counter()
for field in REQUIRED_FIELDS:
for e in entries:
if field not in e or e[field] is None:
field_missing[field] += 1
for field, count in sorted(field_missing.items()):
bad = count > 0
sev = "PASS"
if bad and count > N * 0.01:
sev = "HIGH" if count > N * 0.1 else "MEDIUM"
elif bad and count > 10:
sev = "LOW"
elif bad:
sev = "PASS"
finding(sev, "completeness", f"missing_{field}", f"{count:,} ({100*count/N:.1f}%)", "")
# Check tier distribution
print(f"\n--- Tier Distribution ---")
tier_counts = Counter(e.get("tier") for e in entries)
for tier, cnt in sorted(tier_counts.items()):
print(f" {tier:12s}: {cnt:>7,}")
if tier_counts.get("raw") is None:
finding("LOW", "tiers", "no_raw_tier", "raw tier missing from frozen set", "")
# Source distribution
print(f"\n--- Source Distribution ---")
src_counts = Counter(e.get("source") for e in entries)
for src, cnt in sorted(src_counts.items()):
print(f" {src:8s}: {cnt:>7,} ({100*cnt/N:.1f}%)")
# Family distribution
print(f"\n--- Family Distribution ---")
family_counts = Counter()
for e in entries:
for fam in e.get("families", []):
family_counts[fam] += 1
for fam, cnt in sorted(family_counts.most_common(20)):
print(f" {fam:20s}: {cnt:>7,}")
# Provenance completeness
print(f"\n--- Provenance ---")
prov_fields = 0
for e in entries:
if e.get("provenance"):
prov_fields += 1
print(f" Entries with provenance: {prov_fields:,} ({100*prov_fields/N:.1f}%)")
if prov_fields < N:
finding("HIGH", "provenance", "missing_provenance",
f"{N - prov_fields:,} entries ({100*(N-prov_fields)/N:.1f}%) missing", "")
else:
finding("PASS", "provenance", "all_have_provenance", "", "")
# Check duplicate_group metadata
dg_cnt = sum(1 for e in entries if e.get("duplicate_group") is not None)
print(f"\n Entries with duplicate_group: {dg_cnt:,} ({100*dg_cnt/N:.1f}%)")
# Check that all entries have structure_json
no_struct = sum(1 for e in entries if not e.get("structure_json"))
if no_struct > 0:
finding("CRITICAL", "structure", "missing_structure",
f"{no_struct:,} ({100*no_struct/N:.1f}%)", "")
else:
finding("PASS", "structure", "all_have_structure", "", "")
# Check structured_formula parity
sf_missing = sum(1 for e in entries if not e.get("structured_formula"))
if sf_missing > 0:
finding("MEDIUM", "metadata", "missing_structured_formula",
f"{sf_missing:,} entries", "")
# ID format consistency
print(f"\n--- ID Consistency ---")
id_formats = Counter()
for e in entries:
mid = e.get("source_id", "")
if mid.startswith("mp-"):
id_formats["mp-"] += 1
elif mid.startswith("oqmd-"):
id_formats["oqmd-"] += 1
elif mid.startswith("jv-") or mid.startswith("jarvis-"):
id_formats["jarvis"] += 1
else:
id_formats["other"] += 1
for fmt, cnt in sorted(id_formats.items()):
print(f" {fmt:12s}: {cnt:>7,}")
if id_formats.get("other", 0) > 0:
finding("MEDIUM", "metadata", "nonstandard_ids",
f"{id_formats['other']:,} nonstandard IDs", "")
# Quality flags staleness (OQMD space_group flag vs actual space_group)
stale_flags = 0
for e in entries:
if e.get("source") == "oqmd" and e.get("space_group") is not None:
flags = e.get("quality_flags", [])
if "missing_spacegroup" in flags:
stale_flags += 1
if stale_flags > 100:
finding("MEDIUM", "metadata", "stale_quality_flags",
f"{stale_flags:,} OQMD entries flagged missing_spacegroup but SG now populated", "flags need recalculation")
elif stale_flags > 0:
finding("LOW", "metadata", "stale_quality_flags", f"{stale_flags} entries", "")
else:
finding("PASS", "metadata", "flags_current", "", "")
# Summary
print(f"\n{'=' * 60}")
print(f" PHASE 8 SUMMARY")
print(f" CRITICAL: {severity_counts['CRITICAL']}")
print(f" HIGH: {severity_counts['HIGH']}")
print(f" MEDIUM: {severity_counts['MEDIUM']}")
print(f" LOW: {severity_counts['LOW']}")
print(f" PASS: {severity_counts['PASS']}")
print(f"{'=' * 60}")
report = {
"phase": "Phase 8: Metadata Audit",
"timestamp": time.strftime("%Y-%m-%d %H:%M:%S"),
"field_completeness": dict(field_missing),
"tier_distribution": dict(tier_counts),
"source_distribution": dict(src_counts),
"family_distribution": dict(family_counts),
"id_formats": dict(id_formats),
"stale_quality_flags": stale_flags,
"findings": findings,
"summary": dict(severity_counts),
}
with open(OUT / "phase8_metadata_audit.json", "w") as f:
json.dump(report, f, indent=2)
print(f"\n Report: {OUT / 'phase8_metadata_audit.json'}")
if __name__ == "__main__":
main()
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