FundusShift / code /fsbench /audit.py
le-dang1haha's picture
Metadata, audit, EDA and pipeline code
70f9003 verified
Raw History Blame Contribute Delete
4.31 kB
"""Step 4: leakage audit + count tables -> audit_report.md. Exit code 1 if any leakage check fails.
python -m fsbench.audit --bench data/bench
"""
import argparse
import sys
from pathlib import Path
import pandas as pd
from .common import CLASSES
USED = ["train", "val", "cal", "test", "test_ood", "test_openset"]
def _md(df):
df = df.reset_index()
head = "| " + " | ".join(map(str, df.columns)) + " |"
sep = "|" + "---|" * len(df.columns)
return "\n".join([head, sep] + ["| " + " | ".join(map(str, r)) + " |" for r in df.itertuples(index=False)])
def main(argv=None):
ap = argparse.ArgumentParser()
ap.add_argument("--bench", required=True)
a = ap.parse_args(argv)
bench = Path(a.bench)
s = pd.read_csv(bench / "splits.csv", dtype=str, keep_default_na=False)
u = s[s.split.isin(USED)]
pairs = pd.read_csv(bench / "near_duplicates.csv", dtype=str, keep_default_na=False)
split_of = dict(zip(s.image_id, s.split))
checks = []
def check(name, bad):
checks.append((name, len(bad) == 0, len(bad)))
return bad
# held-out splits are never trained on, so test / test_ood / test_openset count as one side for leakage
u = u.assign(leak_key=u.split.where(~u.split.str.startswith("test"), "held_out"))
split_of = {i: (k if k != "held_out" else "held_out") for i, k in zip(u.image_id, u.leak_key)}
check("leakage group in >1 split", u.groupby("group_id").leak_key.nunique().loc[lambda x: x > 1])
check("identical file (SHA-256) in >1 split", u[u.sha256 != ""].groupby("sha256").leak_key.nunique().loc[lambda x: x > 1])
pp = u[u.patient_id != ""].groupby(["source", "patient_id"]).leak_key.nunique()
check("patient in >1 split", pp[pp > 1])
xp = pairs[[x in split_of and y in split_of and split_of[x] != split_of[y]
for x, y in zip(pairs.image_id_a, pairs.image_id_b)]]
check("near-duplicate pair across splits", xp)
fam = u.assign(side=u.split.str.startswith("test")).groupby("family").side.nunique()
check("acquisition family on both dev and test side", fam[fam > 1])
dev_src, test_src = set(u.source[u.split.isin(["train", "val", "cal"])]), set(u.source[u.split.str.startswith("test")])
check("source on both dev and test side", sorted(dev_src & test_src))
check("cal image without cal_A/cal_B", u[(u.split == "cal") & (u.cal_subset == "")])
classes = [c for c in [*CLASSES, "OPENSET"] if c in set(u.label)]
by_split = pd.crosstab(u.split, u.label).reindex(index=USED, columns=classes, fill_value=0)
by_split["total"] = by_split.sum(axis=1)
by_src = pd.crosstab([u.source, u.split], u.label).reindex(columns=classes, fill_value=0)
ncls = (by_src.groupby(level=0).sum() > 0).sum(axis=1).value_counts().sort_index()
cal = pd.crosstab(u.cal_subset[u.split == "cal"], u.label[u.split == "cal"]).reindex(columns=classes, fill_value=0)
unused = s[s.split == "unused"].unused_reason.value_counts().rename("images")
dr = u[u.dr_grade != ""]
dr_tab = pd.crosstab(dr.split, dr.dr_grade) if len(dr) else pd.DataFrame()
lines = ["# FundusShift — audit report", "",
f"Inventory rows: {len(s)} | used in protocol: {len(u)} | unused: {len(s) - len(u)} | "
f"sources used: {u.source.nunique()}", "", "## Leakage checks", "",
"| check | result | violations |", "|---|---|---|"]
lines += [f"| {n} | {'PASS' if ok else 'FAIL'} | {k} |" for n, ok, k in checks]
lines += ["", "## Images per split and class", "", _md(by_split),
"", "## Calibration halves", "", _md(cal),
"", "## Mapped classes per source (count of sources)", "", _md(ncls.rename("sources").rename_axis("n_classes")),
"", "## Source x split x class", "", _md(by_src),
"", "## Unused images by reason", "", _md(unused.rename_axis("reason"))]
if len(dr_tab):
lines += ["", "## Secondary task: ICDR DR grade per split", "", _md(dr_tab)]
(bench / "audit_report.md").write_text("\n".join(lines) + "\n")
for n, ok, k in checks:
print(f"{'PASS' if ok else 'FAIL'} {n} ({k})")
print(f"\n{by_split.to_string()}\n\nreport -> {bench / 'audit_report.md'}")
sys.exit(0 if all(ok for _, ok, _ in checks) else 1)
if __name__ == "__main__":
main()