add some codes

codes/ddpg/plot.py

@@ -0,0 +1,47 @@
+#!/usr/bin/env python
+# coding=utf-8
+'''
+@Author: John
+@Email: johnjim0816@gmail.com
+@Date: 2020-06-11 16:30:09
+@LastEditor: John
+@LastEditTime: 2020-06-12 11:34:52
+@Discription: 
+@Environment: python 3.7.7
+'''
+import matplotlib.pyplot as plt
+import pandas as pd
+import seaborn as sns; sns.set()
+import numpy as np
+import os 
+
+# def plot(item,ylabel='rewards'):
+#     plt.figure()
+#     plt.plot(np.arange(len(item)), item)
+#     plt.title(ylabel+' of DDPG') 
+#     plt.ylabel(ylabel)
+#     plt.xlabel('episodes')
+#     plt.savefig(os.path.dirname(__file__)+"/result/"+ylabel+".png")
+#     plt.show()
+
+def plot(item,ylabel='rewards'):
+    df = pd.DataFrame(dict(time=np.arange(500),
+                       value=np.random.randn(500).cumsum()))
+    g = sns.relplot(x="time", y="value", kind="line", data=df)
+    g.fig.autofmt_xdate()
+    # time = range(len(item))
+    # sns.set(style="darkgrid", font_scale=1.5)
+    # sns.lineplot(time=time, data=item, color="r", condition="behavior_cloning")
+    # # sns.tsplot(time=time, data=x2, color="b", condition="dagger")
+    # plt.ylabel("Reward")
+    # plt.xlabel("Iteration Number")
+    # plt.title("Imitation Learning")
+
+    plt.show()
+if __name__ == "__main__":
+
+    output_path = os.path.dirname(__file__)+"/result/"
+    rewards=np.load(output_path+"rewards.npy", )
+    moving_average_rewards=np.load(output_path+"moving_average_rewards.npy",)
+    plot(rewards)
+    plot(moving_average_rewards,ylabel='moving_average_rewards')