utils.py

import numpy as np
import matplotlib.pyplot as plt


def plot_learning_curve(scores, epsilons, filename="output.png", lines=None):
    x = [i + 1 for i in range(len(scores))]
    fig = plt.figure()
    ax = fig.add_subplot(111, label="1")
    ax2 = fig.add_subplot(111, label="2", frame_on=False)

    ax.plot(x, epsilons, color="C0")
    ax.set_xlabel("Training Steps", color="C0")
    ax.set_ylabel("Epsilon", color="C0")
    ax.tick_params(axis="x", colors="C0")
    ax.tick_params(axis="y", colors="C0")

    N = len(scores)
    running_avg = np.empty(N)
    for t in range(N):
        running_avg[t] = np.mean(scores[max(0, t - 20) : (t + 1)])

    ax2.plot(x, running_avg, color="C1")
    ax2.axes.get_xaxis().set_visible(False)
    ax2.yaxis.tick_right()
    ax2.set_ylabel("Score", color="C1")
    ax2.yaxis.set_label_position("right")
    ax2.tick_params(axis="y", colors="C1")

    if lines is not None:
        for line in lines:
            plt.axvline(x=line)

    plt.show()
    plt.savefig(filename)