In [1]:

    

import pandas as pd
import numpy as np

import pyaf.ForecastEngine as autof
import pyaf.Bench.TS_datasets as tsds

%matplotlib inline


    

In [ ]:

    




    

In [2]:

    

cac40_symbol = "^FCHI"
b = tsds.load_yahoo_stock_price(cac40_symbol)
df = b.mPastData


    

In [3]:

    

df.sample(4)


    

    
Out[3]:






  

    

      

      
^FCHI
      
Date
    
  
  

    

      
1121
      
4441.870117
      
2016-08-26
    
    

      
2
      
3237.689941
      
2012-04-11
    
    

      
85
      
3453.280029
      
2012-08-07
    
    

      
896
      
4688.700195
      
2015-10-12
    
  

In [4]:

    

df.info()


    

    




<class 'pandas.core.frame.DataFrame'>
RangeIndex: 1271 entries, 0 to 1270
Data columns (total 2 columns):
^FCHI    1271 non-null float64
Date     1271 non-null datetime64[ns]
dtypes: datetime64[ns](1), float64(1)
memory usage: 19.9 KB

In [5]:

    

lEngine = autof.cForecastEngine()
lEngine

H = 12;
# lEngine.mOptions.enable_slow_mode();
# lEngine.mOptions.mDebugPerformance = True;
lEngine.train(df , 'Date' , cac40_symbol, H);


    

In [6]:

    

lEngine.getModelInfo();


    

In [7]:

    

print(lEngine.mSignalDecomposition.mTrPerfDetails.head());


    

    




  Transformation                                              Model  \
0         _^FCHI    _^FCHI_Lag1Trend_residue_zeroCycle_residue_NoAR   
1         _^FCHI  _^FCHI_Lag1Trend_residue_bestCycle_byL2_residu...   
2   CumSum_^FCHI  CumSum_^FCHI_Lag1Trend_residue_zeroCycle_resid...   
3     Diff_^FCHI  Diff_^FCHI_Lag1Trend_residue_zeroCycle_residue...   
4  RelDiff_^FCHI  RelDiff_^FCHI_Lag1Trend_residue_zeroCycle_resi...   

   Complexity  FitCount       FitL2  FitMAPE  ForecastCount  ForecastL2  \
0          32      1007   51.404508   0.0092            252   47.507304   
1          40      1007   51.261535   0.0091            252   47.423443   
2          64      1007  113.635526   0.0101            252   47.507304   
3          64      1007   51.404508   0.0092            252   47.507304   
4          64      1007   51.404508   0.0092            252   47.507304   

   ForecastMAPE  TestCount     TestL2  TestMAPE  
0        0.0074         12  19.266754    0.0034  
1        0.0074         12  20.829463    0.0036  
2        0.0074         12  19.266754    0.0034  
3        0.0074         12  19.266754    0.0034  
4        0.0074         12  19.266754    0.0034  

In [8]:

    

lEngine.mSignalDecomposition.mBestModel.mTimeInfo.mResolution


    

    
Out[8]:





4

In [9]:

    

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)