differentiable_game/plot.py at master · rnilva/differentiable_game · GitHub

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from typing import List
import matplotlib.pyplot as plt
import pandas as pd
import argparse


def plot_keys(data: pd.DataFrame, keys: List[str]):
    for key in keys:
        plt.plot(data[key], label=key)
    plt.legend()


if __name__ == "__main__":

    parser = argparse.ArgumentParser()
    parser.add_argument('path')
    args = parser.parse_args();


    # rows = []

    # with open('test.csv', newline='') as f:
    #     reader = csv.reader(f, delimiter=',')
    #     read_header = True
    #     for row in reader:
    #         if read_header:
    #             header = row
    #             read_header = False
    #         else:
    #             rows.append(row)

    data = pd.read_csv(args.path, delimiter=', ')

    # print(data)

    print(data.keys())

    keys_to_plot = [
        'rollout/win_rate',
        'eval/win_rate_c1',
        'eval/win_rate_c2',
        'rollout/draw_rate',
    ]

    # # data['eval/win_rate_c1'].plot()
    # plt.plot(data['eval/win_rate_c1'])
    # plt.plot(data['eval/win_rate_c2'])
    # plt.plot(data['rollout/draw_rate'])
    # plt.plot(data['train/entropy_loss'])
    # plt.legend()

    plt.figure(1, figsize=[15, 15])
    plt.subplot(411)
    plot_keys(data, keys_to_plot)
    plt.subplot(412)
    plot_keys(data, ['train/loss'])
    plt.subplot(413)
    plot_keys(data, ['train/entropy_loss'])
    plt.subplot(414)
    plot_keys(data, ['rollout/avg_basic_preference'])
    plt.savefig('test.png')