In [1]:

    

import numpy as np
import pandas as pd
from emulator.main import Account


    

In [2]:

    

A = Account()


    

In [3]:

    

actions = np.random.randint(0,3, size=(32))


    

In [4]:

    

rewrads_list = []
for i in actions:
    r,n,d = A.step(i)
    rewrads_list.append(r)


    

In [5]:

    

GAMMA = 0.9
R_list = []
R = 0
for i in rewrads_list[::-1]:
    R = i + GAMMA * R
    R_list.append(R)
R_list.reverse()


    

In [6]:

    

tmp = pd.DataFrame()
tmp['reward'] = rewrads_list
tmp['discount'] = R_list


    

In [7]:

    

tmp


    

    
Out[7]:







  

    

      

      
reward
      
discount
    
  
  

    

      
0
      
0.006588
      
-0.011630
    
    

      
1
      
-0.009998
      
-0.020242
    
    

      
2
      
-0.000981
      
-0.011382
    
    

      
3
      
-0.003235
      
-0.011556
    
    

      
4
      
-0.001571
      
-0.009246
    
    

      
5
      
-0.003855
      
-0.008527
    
    

      
6
      
0.002484
      
-0.005191
    
    

      
7
      
0.000000
      
-0.008528
    
    

      
8
      
0.004114
      
-0.009475
    
    

      
9
      
0.000672
      
-0.015099
    
    

      
10
      
0.001422
      
-0.017523
    
    

      
11
      
-0.006369
      
-0.021049
    
    

      
12
      
0.000362
      
-0.016311
    
    

      
13
      
-0.009769
      
-0.018525
    
    

      
14
      
0.000150
      
-0.009730
    
    

      
15
      
-0.003153
      
-0.010978
    
    

      
16
      
-0.001789
      
-0.008694
    
    

      
17
      
-0.003495
      
-0.007672
    
    

      
18
      
-0.008901
      
-0.004641
    
    

      
19
      
0.009744
      
0.004733
    
    

      
20
      
0.003367
      
-0.005568
    
    

      
21
      
0.001658
      
-0.009927
    
    

      
22
      
0.000683
      
-0.012872
    
    

      
23
      
-0.003734
      
-0.015061
    
    

      
24
      
0.001064
      
-0.012586
    
    

      
25
      
-0.001857
      
-0.015167
    
    

      
26
      
-0.002752
      
-0.014789
    
    

      
27
      
-0.004749
      
-0.013374
    
    

      
28
      
-0.006626
      
-0.009584
    
    

      
29
      
-0.000160
      
-0.003286
    
    

      
30
      
0.000511
      
-0.003474
    
    

      
31
      
-0.004427
      
-0.004427
    
  

In [ ]: