| from pathlib import Path | |
| import argparse | |
| import numpy as np | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--input", help="input filename", type=str, nargs="+") | |
| parser.add_argument("--output", help="output result file", default=None) | |
| args = parser.parse_args() | |
| scores = {} | |
| for path in args.input: | |
| with open(path, "r") as reader: | |
| for line in reader.readlines(): | |
| metric, score = line.strip().split(": ") | |
| score = float(score) | |
| if metric not in scores: | |
| scores[metric] = [] | |
| scores[metric].append(score) | |
| if len(scores) == 0: | |
| print("No experiment directory found, wrong path?") | |
| exit(1) | |
| with open(args.output, "w") as writer: | |
| print("Average results: ", file=writer) | |
| for metric, score in scores.items(): | |
| score = np.array(score) | |
| mean = np.mean(score) | |
| std = np.std(score) | |
| print(f"{metric}: {mean:.3f} (±{std:.3f})", file=writer) | |
| print("", file=writer) | |
| print("Best results: ", file=writer) | |
| for metric, score in scores.items(): | |
| score = np.max(score) | |
| print(f"{metric}: {score:.3f}", file=writer) | |