conservative-bayesian-public/make_tightness_plots.py at main · saifh-github/conservative-bayesian-public · GitHub

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import os
import glob
import gzip
import pickle
import argparse
from utils import plotting
from omegaconf import OmegaConf
from termcolor import colored

parser = argparse.ArgumentParser()
parser.add_argument("--timestamp", default="latest")
parser.add_argument("--device", default="auto", help="Device to use: 'cpu', 'cuda', 'mps', or 'auto'")
parser.add_argument("--config", default="configs/config.yaml", help="Path to config file")


def get_latest(directory="results/tightness"):
    pattern = os.path.join(directory, "*")
    subdirs = [d for d in glob.glob(pattern) if os.path.isdir(d)]

    latest_time = 0
    latest_dir = None

    for subdir in subdirs:
        files = glob.glob(os.path.join(subdir, "*"))
        if files:
            latest_file = max(files, key=os.path.getmtime)
            mod_time = os.path.getmtime(latest_file)
            if mod_time > latest_time:
                latest_time = mod_time
                latest_dir = subdir

    return latest_dir


def main(args):
    plot_config = None
    if args.config and os.path.exists(args.config):
        cfg = OmegaConf.load(args.config)
        plot_config = plotting.PlotConfig.from_config(cfg)

    if args.timestamp == "latest":
        results_dir = get_latest()
    else:
        results_dir = os.path.join("results/tightness", args.timestamp)

    path = os.path.join(results_dir, "results.pkl.gz")

    with gzip.open(path, "rb") as f:
        results = pickle.load(f)
    print(colored(f"📂 Loaded {path}", "green"))
    print(colored("🔑 Available keys in results:", "cyan"), results.keys())
    ex_time = results["execution_time"]
    print(
        colored(f"⏱️  Execution time: {round(ex_time)} seconds, or {round(ex_time/60)} minutes, or {round(ex_time/3600, ndigits=3)} hours for {results['args'].n_episodes} episodes", "yellow")
    )

    save_path = os.path.join(results_dir, "overestimation.pdf")
    plotting.plot_overestimation(
        results, plot_error_bars=False, save_path=save_path, save_format="pdf", plot_config=plot_config
    )
    print(colored(f"📊 Plot saved to {save_path}", "green"))

    save_path = os.path.join(results_dir, "overestimation_error.pdf")
    plotting.plot_overestimation(
        results, plot_error_bars=True, save_path=save_path, save_format="pdf", plot_config=plot_config
    )
    print(colored(f"📊 Plot saved to {save_path}", "green"))

    save_path = os.path.join(results_dir, "harm_estimates.pdf")
    plotting.box_plot(
        results, save_path=save_path, save_format="pdf", plot_config=plot_config
    )
    print(colored(f"📊 Plot saved to {save_path}", "green"))


if __name__ == "__main__":
    args = parser.parse_args()
    main(args)