"""Run read_idf_file across the corpus and report per-channel accuracy vs sidecars."""
from __future__ import annotations
import sys
from pathlib import Path

REPO = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(REPO))

from micromate.idf_file import read_idf_file
from analysis_idf.recon import load_sidecar_samples


def sidecar_path(idfw: Path) -> Path:
    return idfw.parent / "TXT" / f"{idfw.name}.txt"


def main():
    root = REPO / "tests/fixtures/THORDATA_example"
    files = [f for f in root.rglob("*.IDFW") if not str(f).endswith(".CDB")]
    files.sort()
    GEO_LSB = 0.0003

    n_ok = n_skip = 0
    overall = {"Tran": [], "Vert": [], "Long": []}

    for f in files:
        try:
            res = read_idf_file(f)
        except Exception:
            n_skip += 1
            continue
        sc_path = sidecar_path(f)
        if not sc_path.exists():
            n_skip += 1
            continue
        try:
            sc = load_sidecar_samples(sc_path)
        except Exception:
            n_skip += 1
            continue

        per_file = {}
        for ch in ("Tran", "Vert", "Long"):
            sc_counts = [int(round(v / GEO_LSB)) for v in sc[ch]]
            dec = res.samples.get(ch, [])
            n = min(len(sc_counts), len(dec))
            if n == 0:
                per_file[ch] = 0.0
                continue
            exact = sum(1 for i in range(n) if sc_counts[i] == dec[i])
            pct = 100.0 * exact / n
            per_file[ch] = pct
            overall[ch].append(pct)
        n_ok += 1

    print(f"Processed {n_ok} files (skipped {n_skip})")
    print("Per-channel exact-match % (mean / min / max):")
    for ch, vals in overall.items():
        if vals:
            avg = sum(vals) / len(vals)
            print(f"  {ch}: mean={avg:.2f}%  min={min(vals):.2f}%  max={max(vals):.2f}%  n={len(vals)}")


if __name__ == "__main__":
    main()