绘制双子图含图例完整代码

import matplotlib.pyplot as plt

from matplotlib import ticker

import seaborn as sns

import pandas as pd

import numpy as np

plt.style.use('ggplot')

# fig, ax = plt.subplots(1,len(scenarios), figsize=(25,4.5))

# plt.show()

# colors = ["#468de4", 'orange', 'green', '#e44a44', 'purple']

colors = ['orange', 'purple']

data = {"Ave_reward":[], "Step":[]}

reward = []

# name = './tikick/{}_{}.csv'.format(file_name[i], aname)

name = ['PongNoFrameskip-v0_0_bcq.csv','PongNoFrameskip-v0_0_bcq_0.csv']

# f, (ax1, ax2) = plt.subplots(1, 2, sharey=True)

#************** below is the first figure ***************#

file = pd.read_csv(name[0])

for key in file:

if "avg_reward" in key:

reward.append(file[key].tolist())

plt_step = np.array(pd.read_csv(name[0])["step"].tolist())

plt_reward = np.array(reward)

data["Ave_reward"] = plt_reward.mean(0)

data["step"] = plt_step

ax = plt.subplot(121)

font_size = 10

x_step = plt_step.tolist()

y_mean = data["Ave_reward"].tolist()

y_max = plt_reward.max(0).tolist()

y_min = plt_reward.min(0).tolist()

 

# sns.lineplot(x_step, y_mean)

sns.lineplot(x_step, y_mean, ax=ax, legend=True, label = u'RCSCA_Net', lw=3, color=colors[0])

# plt.fill_between(x_step,y_max,y_min,facecolor="green",edgecolor="red",alpha=0.3)

num = plt.fill_between(x_step,y_max,y_min,alpha=0.2,label='bcq')

ax.set_title("BCQ", fontsize=font_size)

ax.spines['top'].set_visible(False)

ax.spines['right'].set_visible(False)

ax.set_xlabel('Time steps', fontdict={'size':20})

ax.tick_params(labelsize=font_size)

x_name = 'Average Return'

ax.set_ylabel(x_name, fontdict={'size':20})

 

plt.legend()

# fig.legend((num,), ('upper right',),'upper center',ncol=5)

# plt.legend(bbox_to_anchor=(-0.5, 1.40), ncol=2, labels='TiKick(ours)', \

# fontsize=22, frameon=True, facecolor='white', framealpha=1)

# ax.grid(True)

#************** below is the second figure ***************#

file = pd.read_csv(name[1])

for key in file:

if "avg_reward" in key:

reward.append(file[key].tolist())

plt_step = np.array(pd.read_csv(name[1])["step"].tolist())

plt_reward = np.array(reward)

data["Ave_reward"] = plt_reward.mean(0)

data["step"] = plt_step

ax = plt.subplot(121)

font_size = 10

x_step = plt_step.tolist()

y_mean = data["Ave_reward"].tolist()

y_max = plt_reward.max(0).tolist()

y_min = plt_reward.min(0).tolist()

 

# sns.lineplot(x_step, y_mean)

sns.lineplot(x_step, y_mean, ax=ax, legend=True, label = u'RCSCA_Net',lw=3, color=colors[1])

# plt.fill_between(x_step,y_max,y_min,facecolor="green",edgecolor="red",alpha=0.3)

num = plt.fill_between(x_step,y_max,y_min,alpha=0.2,label='bcq')

ax.set_title("bcq", fontsize=font_size)

ax.spines['top'].set_visible(False)

ax.spines['right'].set_visible(False)

ax.set_xlabel('Time steps', fontdict={'size':20})

ax.tick_params(labelsize=font_size)

x_name = 'Average Return'

# ax.set_ylabel(x_name, fontdict={'size':font_size})

 

# plt.legend()

# fig.legend((num,), ('upper right',),'upper center',ncol=5)

# plt.legend(bbox_to_anchor=(-0.5, 1.40), ncol=2, labels='TiKick(ours)', \

# fontsize=22, frameon=True, facecolor='white', framealpha=1)

ax.grid(True)

plt.show()

import pdb

pdb.set_trace()