exponential_moving_average_plot.py

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt


def smooth(scalars, weight): 
    last = scalars[0] 
    smoothed = list() 
    for point in scalars: 
        smoothed_val = last * weight + (1-weight)*point 
        smoothed.append(smoothed_val) 
        last = smoothed_val 
    return smoothed 

def plot(names, labels, title, weight):
    clrs = sns.color_palette("deep", len(labels))
    for i, name in enumerate(names):
        data = np.genfromtxt(name, delimiter=',')
        plt.plot(np.arange(len(data[1:, 2])), smooth(data[1:, 2], 0.0), alpha=0.2, color=clrs[i])
        plt.plot(np.arange(len(data[1:, 2])), smooth(data[1:, 2], weight), label=labels[i], color=clrs[i])

    plt.xlabel("Episodes")
    plt.ylabel("Cost")
    plt.legend()
    plt.title("Number of environment steps required to converge.")
    plt.show()