In [11]:

    

#https://github.com/jamesrobertlloyd/gpss-research/tree/master/data/tsdl
#https://cran.r-project.org/web/packages/rdatamarket/
#https://datamarket.com/data/list/?q=cat:ecc%20provider:tsdl

import pandas as pd
import numpy as np
import scipy.io


import pyaf.ForecastEngine as autof

%matplotlib inline  

url = "http://github.com/jamesrobertlloyd/gpss-research/blob/master/data/tsdl/ibm-common-stock-closing-prices-.mat?raw=true"

import requests
response = requests.get(url)
with open("ibm.mat", "wb") as file:
    file.write(response.content)
    file.close();

mat = scipy.io.loadmat("ibm.mat")


    

In [12]:

    

df = pd.DataFrame()
df['Date'] = mat['X'].T[0]
df['Signal'] = mat['y'].T[0]
df.head()


    

    
Out[12]:






  

    

      

      
Date
      
Signal
    
  
  

    

      
0
      
1961.375342
      
460.0
    
    

      
1
      
1961.378082
      
457.0
    
    

      
2
      
1961.380822
      
452.0
    
    

      
3
      
1961.389041
      
459.0
    
    

      
4
      
1961.391781
      
462.0
    
  

In [20]:

    

lEngine = autof.cForecastEngine()
lEngine.train(df, 'Date' , 'Signal' , 7)
lEngine


    

    
Out[20]:





<pyaf.ForecastEngine.cForecastEngine at 0x7ff040c67c18>

In [21]:

    

#lEngine.getModelInfo()
#lEngine.mSignalDecomposition.mTrPerfDetails


    

In [22]:

    

lEngine.standrdPlots()


    

    




/usr/lib/python3/dist-packages/matplotlib/__init__.py:1403: UserWarning:  This call to matplotlib.use() has no effect
because the backend has already been chosen;
matplotlib.use() must be called *before* pylab, matplotlib.pyplot,
or matplotlib.backends is imported for the first time.

  warnings.warn(_use_error_msg)






    













    













    













    













    

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