In [1]:

    

import pandas as pd
import numpy as np
%matplotlib inline


    

In [2]:

    

train = np.load("../train_data/normal.npy")
train


    

    
Out[2]:





array([[  0.00000000e+00,   1.25333234e-01],
       [  1.25333234e-01,   2.48689887e-01],
       [  2.48689887e-01,   3.68124553e-01],
       ..., 
       [ -3.68124553e-01,  -2.48689887e-01],
       [ -2.48689887e-01,  -1.25333234e-01],
       [ -1.25333234e-01,   3.92877345e-15]])

In [3]:

    

initial = np.load("initial.npy")
initial


    

    
Out[3]:





array([  0.00000000e+00,   1.25333234e-01,   2.48689887e-01,
         3.68124553e-01,   4.81753674e-01,   5.87785252e-01,
         6.84547106e-01,   7.70513243e-01,   8.44327926e-01,
         9.04827052e-01,   9.51056516e-01,   9.82287251e-01,
         9.98026728e-01,   9.98026728e-01,   9.82287251e-01,
         9.51056516e-01,   9.04827052e-01,   8.44327926e-01,
         7.70513243e-01,   6.84547106e-01,   5.87785252e-01,
         4.81753674e-01,   3.68124553e-01,   2.48689887e-01,
         1.25333234e-01,  -3.21624530e-16,  -1.25333234e-01,
        -2.48689887e-01,  -3.68124553e-01,  -4.81753674e-01,
        -5.87785252e-01,  -6.84547106e-01,  -7.70513243e-01,
        -8.44327926e-01,  -9.04827052e-01,  -9.51056516e-01,
        -9.82287251e-01,  -9.98026728e-01,  -9.98026728e-01,
        -9.82287251e-01,  -9.51056516e-01,  -9.04827052e-01,
        -8.44327926e-01,  -7.70513243e-01,  -6.84547106e-01,
        -5.87785252e-01,  -4.81753674e-01,  -3.68124553e-01,
        -2.48689887e-01,  -1.25333234e-01])

In [4]:

    

output = np.load("output.npy")
output


    

    
Out[4]:





array([ 0.01816994,  0.16730818,  0.32001099,  0.46868694,  0.60363388,
        0.71590197,  0.80050695,  0.85753089,  0.89054608,  0.90424329,
        0.90291858,  0.88995934,  0.86784983,  0.83833361,  0.80258352,
        0.76133496,  0.7149784 ,  0.66362107,  0.6071251 ,  0.54513144,
        0.4770776 ,  0.40222058,  0.31968117,  0.22853443,  0.12798166,
        0.01764446, -0.10199758, -0.22907224, -0.35987493, -0.48886338,
       -0.60940671, -0.71522009, -0.80185318, -0.8674556 , -0.91254377,
       -0.93914878, -0.94990599, -0.94741786, -0.93392909, -0.91122663,
       -0.88065338, -0.8431673 , -0.79940832, -0.74975729, -0.69437957,
       -0.63326204, -0.56623876, -0.49301687, -0.41320774, -0.32637736,
       -0.23213467, -0.13028058, -0.02104703,  0.09456092,  0.21436191,
        0.33468249,  0.45041138,  0.55571097,  0.64534527,  0.71602499,
        0.7669732 ,  0.79947579,  0.81591392,  0.81890619,  0.81081355,
        0.79355299,  0.76857781,  0.73692465,  0.69927394,  0.65600336,
        0.60722834,  0.55283052,  0.49247906,  0.42565149,  0.35166508,
        0.2697356 ,  0.17908922,  0.07916024, -0.03009382, -0.14776012,
       -0.27150109, -0.39726391, -0.51947784, -0.63193619, -0.72915244,
       -0.80755985, -0.86596382, -0.90517151, -0.92719078, -0.93445933,
       -0.92932796, -0.91380644, -0.88948905, -0.85757124, -0.81890178,
       -0.77403903, -0.7233032 , -0.66681433, -0.60452402, -0.53624094])

In [5]:

    

train_df = pd.DataFrame(train[:len(initial) + len(output), 0], columns=["train"])
initial_df = pd.DataFrame(initial, columns=["initial"])
output_df = pd.DataFrame(output, columns=["output"], index=range(len(initial), len(initial) + len(output)))
merged = pd.concat([train_df, initial_df, output_df])
merged.plot(style=["-", "-", "k--"], figsize=(15, 5), grid=True)


    

    
Out[5]:





<matplotlib.axes._subplots.AxesSubplot at 0x10c4426a0>






    

In [ ]: