def plot_episode_red(df, E): #, center_line, inner_border, outer_border):
fig = plt.figure(1, figsize=(trkSizeX/5, trkSizeY/5))
ax = fig.add_subplot(211)
ax.set_aspect(aspect=1)
pu.print_border(ax, track, color="WhiteSmoke") # center_line, inner_border, outer_border)
episode_data = df[df['episode'] == E]
for row in episode_data.iterrows():
x1,y1,action,reward = row[1]['x'], row[1]['y'], row[1]['action'], row[1]['reward']
car_x2, car_y2 = x1 - 0.02, y1
plt.plot([x1, car_x2], [y1, car_y2], 'r.')
def plot_episode_color(df, E): #, center_line, inner_border, outer_border):
fig = plt.figure(1, figsize=(trkSizeX/5, trkSizeY/5))
ax = fig.add_subplot(211)
ax.set_aspect(aspect=1)
pu.print_border(ax, track, color="WhiteSmoke") # center_line, inner_border, outer_border)
episode_data = df[df['episode'] == E]
for row in episode_data.iterrows():
x1,y1,action,reward = row[1]['x'], row[1]['y'], row[1]['action'], row[1]['reward']
actidx = int(action)
action_color = asl[int(action)].color
action_s = (asl[int(action)].throttle / maxThrottle)**2 * 50 # tune the size of the dots
#print(action_color)
#plt.scatter([x1, car_x2], [y1, car_y2], color=action_color, s=action_s, alpha=0.65)
plt.scatter(x1, y1, color=action_color, s=action_s, alpha=0.75)