#!/usr/bin/env python3 """Stats for actuator/valve-like outputs (Type 3).""" import argparse import csv import gzip import json from pathlib import Path from typing import Dict, List def parse_args(): base_dir = Path(__file__).resolve().parent parser = argparse.ArgumentParser(description="Actuator/valve stats.") parser.add_argument("--generated", default=str(base_dir / "results" / "generated.csv")) parser.add_argument("--reference", default=str(base_dir / "config.json")) parser.add_argument("--features", default="", help="comma-separated list") parser.add_argument("--config", default=str(base_dir / "config.json")) parser.add_argument("--out", default=str(base_dir / "results" / "actuator_stats.json")) parser.add_argument("--max-rows", type=int, default=200000) return parser.parse_args() def resolve_reference_glob(ref_arg: str) -> str: ref_path = Path(ref_arg) if ref_path.suffix == ".json": cfg = json.loads(ref_path.read_text(encoding="utf-8")) data_glob = cfg.get("data_glob") or cfg.get("data_path") or "" if not data_glob: raise SystemExit("reference config has no data_glob/data_path") combined = ref_path.parent / data_glob if "*" in str(combined) or "?" in str(combined): return str(combined) return str(combined.resolve()) return str(ref_path) def read_series(path: Path, cols: List[str], max_rows: int) -> Dict[str, List[float]]: vals = {c: [] for c in cols} opener = gzip.open if str(path).endswith(".gz") else open with opener(path, "rt", newline="") as fh: reader = csv.DictReader(fh) for i, row in enumerate(reader): for c in cols: try: vals[c].append(float(row[c])) except Exception: pass if max_rows > 0 and i + 1 >= max_rows: break return vals def spike_stats(series: List[float]): if not series: return { "unique_ratio": None, "top1_mass": None, "top3_mass": None, "median_dwell": None, } n = len(series) # discretize by rounding rounded = [round(v, 2) for v in series] counts = {} for v in rounded: counts[v] = counts.get(v, 0) + 1 unique_ratio = len(counts) / n top = sorted(counts.values(), reverse=True) top1_mass = top[0] / n if top else None top3_mass = sum(top[:3]) / n if len(top) >= 3 else top1_mass # dwell length dwells = [] current = rounded[0] dwell = 1 for v in rounded[1:]: if v == current: dwell += 1 else: dwells.append(dwell) current = v dwell = 1 dwells.append(dwell) dwells.sort() median_dwell = dwells[len(dwells) // 2] if dwells else None return { "unique_ratio": unique_ratio, "top1_mass": top1_mass, "top3_mass": top3_mass, "median_dwell": median_dwell, } def main(): args = parse_args() features = [f.strip() for f in args.features.split(",") if f.strip()] if not features and Path(args.config).exists(): cfg = json.loads(Path(args.config).read_text(encoding="utf-8")) features = cfg.get("type3_features", []) or [] if not features: raise SystemExit("no features specified for actuator_stats") gen_vals = read_series(Path(args.generated), features, args.max_rows) ref_glob = resolve_reference_glob(args.reference) ref_paths = sorted(Path(ref_glob).parent.glob(Path(ref_glob).name)) if not ref_paths: raise SystemExit(f"no reference files matched: {ref_glob}") real_vals = {c: [] for c in features} for p in ref_paths: vals = read_series(p, features, args.max_rows) for c in features: real_vals[c].extend(vals[c]) out = {"features": features, "generated": {}, "reference": {}} for c in features: out["generated"][c] = spike_stats(gen_vals[c]) out["reference"][c] = spike_stats(real_vals[c]) out_path = Path(args.out) out_path.parent.mkdir(parents=True, exist_ok=True) out_path.write_text(json.dumps(out, indent=2), encoding="utf-8") print("wrote", out_path) if __name__ == "__main__": main()