#!/usr/bin/env python3
# Copyright 2026 Emile de Bruyn
# SPDX-License-Identifier: Apache-2.0

"""Reorder MotifBench's case summary before running its group-summary script."""
import argparse
import csv
import importlib.util
from pathlib import Path


def main():
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("work", type=Path, help="prepared MotifBench working directory")
    parser.add_argument("results", type=Path, help="evaluation output directory")
    args = parser.parse_args()
    with (args.work / "test_cases.csv").open(newline="") as handle:
        cases = list(csv.DictReader(handle))
    order = {f"{i:02d}_{row['pdb_id']}": i for i, row in enumerate(cases, 1)}
    with (args.results / "summary_by_problem.csv").open(newline="") as handle:
        reader = csv.DictReader(handle)
        fields, rows = reader.fieldnames, list(reader)
    if not rows:
        raise ValueError("the upstream summary contains no cases")
    names = [row["Problem"] for row in rows]
    if len(set(names)) != len(names) or any(name not in order for name in names):
        raise ValueError("summary contains duplicate or unknown case names")
    for row in rows:
        if int(row["Num_Evaluated"]) != 100:
            raise ValueError(f"{row['Problem']}: upstream score assumes 100 evaluated designs")
        cluster = args.results / row["Problem"] / "esm_successful_backbones/diversity_cluster.tsv"
        if int(row["Num_Solutions"]) > 0 and not cluster.is_file():
            raise FileNotFoundError(f"missing diversity clusters: {cluster}")
    ordered = args.results / "summary_by_problem_ordered.csv"
    overall = args.results / "overall_summary_ordered.csv"
    if ordered.exists() or overall.exists():
        raise FileExistsError("ordered summary output already exists")
    rows.sort(key=lambda row: order[row["Problem"]])
    with ordered.open("x", newline="") as handle:
        writer = csv.DictWriter(handle, fieldnames=fields)
        writer.writeheader()
        writer.writerows(rows)
    source = args.work / "scripts/write_overall_summary.py"
    module_spec = importlib.util.spec_from_file_location("motifbench_summary", source)
    if module_spec is None or module_spec.loader is None:
        raise ImportError(f"cannot load MotifBench summary module: {source}")
    module = importlib.util.module_from_spec(module_spec)
    module_spec.loader.exec_module(module)
    module.np.random.seed(0)
    module.main(str(args.work / "test_cases.csv"), str(ordered), str(overall))
    module.np.random.seed(0)
    for row in rows:
        cluster = module.diversity_cluster_path(str(args.results), row["Problem"])
        successes = module.load_successes_and_cluster(cluster)
        row["overall_score"] = module.MBScore_boostrap(successes)[0]
    with ordered.open("w", newline="") as handle:
        writer = csv.DictWriter(handle, fieldnames=fields + ["overall_score"])
        writer.writeheader()
        writer.writerows(rows)
    print(f"Summarized {len(rows)}/{len(cases)} cases in {ordered} and {overall}.")
    if len(rows) != len(cases):
        print("Warning: this is a partial benchmark summary, not a full BILBY-PRO score.")


if __name__ == "__main__":
    main()