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64 lines
1.9 KiB
Python
64 lines
1.9 KiB
Python
"""
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Aggregate results from any experiment into a flat CSV.
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Usage:
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python analysis/aggregate.py --results_dir results/2d/ --out results/2d/summary.csv
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python analysis/aggregate.py --results_dir results/ --recursive --out results/all.csv
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"""
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import argparse, glob, json, os
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import pandas as pd
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SCALAR_KEYS = [
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"experiment", "run_name", "mixing", "encoder", "mode", "source_dist",
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"seed", "N", "lamb", "rho", "lr", "steps", "batch_size", "n_layers", "hidden",
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"r2_zx", "r2_xz", "r2_zh", "r2_hz",
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"orth_err", "orth_err_normalized",
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"epsilon", "delta", "D_bound", "approx_bound",
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"procrustes_mse", "L_h", "trace_cov",
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"final_align", "final_sigreg", "final_whiten", "final_loss",
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]
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def load_results(results_dir, recursive=False):
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pattern = os.path.join(results_dir, "**/*.json") if recursive else os.path.join(results_dir, "*.json")
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files = sorted(glob.glob(pattern, recursive=recursive))
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print(f"Found {len(files)} .json files")
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rows = []
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for path in files:
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try:
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with open(path) as f:
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r = json.load(f)
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row = {k: r.get(k) for k in SCALAR_KEYS}
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row["file"] = os.path.relpath(path, results_dir)
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rows.append(row)
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except Exception as e:
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print(f" SKIP {path}: {e}")
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return pd.DataFrame(rows)
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def main():
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p = argparse.ArgumentParser()
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p.add_argument("--results_dir", type=str, required=True)
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p.add_argument("--out", type=str, default=None)
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p.add_argument("--recursive", action="store_true")
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args = p.parse_args()
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df = load_results(args.results_dir, recursive=args.recursive)
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if len(df) == 0:
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print("No results found.")
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return
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print(f"\n{len(df)} runs loaded")
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print(df.to_string(index=False))
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out = args.out or os.path.join(args.results_dir, "summary.csv")
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df.to_csv(out, index=False)
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print(f"\nSaved {out}")
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if __name__ == "__main__":
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main()
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