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import matplotlib.pyplot as plt
import numpy as np
import gym
def plotLearning(x, scores, epsilons, filename, lines=None):
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("Game", 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.scatter(x, running_avg, color="C1")
#ax2.xaxis.tick_top()
ax2.axes.get_xaxis().set_visible(False)
ax2.yaxis.tick_right()
#ax2.set_xlabel('x label 2', color="C1")
ax2.set_ylabel('Score', color="C1")
#ax2.xaxis.set_label_position('top')
ax2.yaxis.set_label_position('right')
#ax2.tick_params(axis='x', colors="C1")
ax2.tick_params(axis='y', colors="C1")
if lines is not None:
for line in lines:
plt.axvline(x=line)
plt.savefig(filename)
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