In [234]:

    

drive_path = 'c:/'
import numpy as np
import pandas as pd
import os
import sys
import matplotlib.pyplot as plt
%matplotlib
%pylab inline
from scipy.stats import ks_2samp
from scipy.stats import anderson_ksamp
from scipy.stats import kruskal
from scipy.stats import variation
from scipy import signal
import seaborn as sns


    

    




Using matplotlib backend: Qt4Agg

In [239]:

    

from scipy import signal


    

In [235]:

    

names=['Plane','Time','Elapsed (ms)']
names.extend([col for col in df.columns if 'G PMT' in col])
df=pd.read_table('C:\\Users\Annie\Desktop\\160621_1_Notepad\\2.txt',skiprows=4)
df=df.loc[df.Plane != 0,df.columns.isin(names)]
df.head()


    

    
Out[235]:






  

    

      

      
Plane
      
Time
      
Elapsed (ms)
      
G PMT (1)
      
G PMT (2)
      
G PMT (3)
      
G PMT (4)
      
G PMT (5)
      
G PMT (6)
      
G PMT (7)
      
G PMT (8)
      
G PMT (9)
      
G PMT (10)
      
G PMT (11)
      
G PMT (12)
      
G PMT (13)
      
G PMT (14)
    
  
  

    

      
1
      
1
      
09:55:25
      
165
      
1310.932
      
1134.720
      
1375.670
      
1759.653
      
1726.413
      
1024.716
      
820.900
      
1111.946
      
850.824
      
690.523
      
2888.812
      
764.946
      
1377.105
      
1268.311
    
    

      
2
      
2
      
09:55:25
      
330
      
1269.739
      
1100.187
      
1414.522
      
1802.143
      
1775.746
      
985.765
      
773.489
      
1101.351
      
871.412
      
698.963
      
2761.536
      
710.986
      
1401.905
      
1207.291
    
    

      
3
      
3
      
09:55:25
      
495
      
1275.511
      
1053.187
      
1321.687
      
1760.020
      
1610.571
      
979.481
      
795.878
      
1069.486
      
849.294
      
664.826
      
2788.232
      
715.243
      
1337.552
      
1220.000
    
    

      
4
      
4
      
09:55:25
      
660
      
1243.943
      
1109.853
      
1318.626
      
1748.939
      
1621.190
      
975.444
      
779.278
      
1100.586
      
847.941
      
653.679
      
2823.928
      
716.027
      
1364.914
      
1209.783
    
    

      
5
      
5
      
09:55:25
      
825
      
1258.489
      
1077.080
      
1357.252
      
1671.061
      
1602.476
      
976.198
      
799.433
      
1059.919
      
856.162
      
705.092
      
2733.957
      
737.365
      
1381.657
      
1207.126
    
  

In [236]:

    

odf=df[[col for col in df.columns if 'G PMT' in col]]
odf.head()


    

    
Out[236]:






  

    

      

      
G PMT (1)
      
G PMT (2)
      
G PMT (3)
      
G PMT (4)
      
G PMT (5)
      
G PMT (6)
      
G PMT (7)
      
G PMT (8)
      
G PMT (9)
      
G PMT (10)
      
G PMT (11)
      
G PMT (12)
      
G PMT (13)
      
G PMT (14)
    
  
  

    

      
1
      
1310.932
      
1134.720
      
1375.670
      
1759.653
      
1726.413
      
1024.716
      
820.900
      
1111.946
      
850.824
      
690.523
      
2888.812
      
764.946
      
1377.105
      
1268.311
    
    

      
2
      
1269.739
      
1100.187
      
1414.522
      
1802.143
      
1775.746
      
985.765
      
773.489
      
1101.351
      
871.412
      
698.963
      
2761.536
      
710.986
      
1401.905
      
1207.291
    
    

      
3
      
1275.511
      
1053.187
      
1321.687
      
1760.020
      
1610.571
      
979.481
      
795.878
      
1069.486
      
849.294
      
664.826
      
2788.232
      
715.243
      
1337.552
      
1220.000
    
    

      
4
      
1243.943
      
1109.853
      
1318.626
      
1748.939
      
1621.190
      
975.444
      
779.278
      
1100.586
      
847.941
      
653.679
      
2823.928
      
716.027
      
1364.914
      
1209.783
    
    

      
5
      
1258.489
      
1077.080
      
1357.252
      
1671.061
      
1602.476
      
976.198
      
799.433
      
1059.919
      
856.162
      
705.092
      
2733.957
      
737.365
      
1381.657
      
1207.126
    
  

In [237]:

    

plt.figure();
plt.plot(df[[col for col in df.columns if 'G PMT' in col]]);


    

In [245]:

    

detrend(odf);


    

In [246]:

    

plt.figure();
plt.plot(odf_dt);


    

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In [133]:

    

import thunder as td


    

In [147]:

    

td.series.fromexample('fish')


    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-147-0b939e41979f> in <module>()
----> 1 td.series.fromexample('fish')

C:\Users\Annie\Anaconda2\lib\site-packages\thunder\series\readers.pyc in fromexample(name, engine)
    436             if not key.name.endswith('/'):
    437                 key.get_contents_to_filename(os.path.join(d, key.name))
--> 438         data = frombinary(os.path.join(d, 'series', name), engine=engine)
    439 
    440         if spark and isinstance(engine, spark):

C:\Users\Annie\Anaconda2\lib\site-packages\thunder\series\readers.pyc in frombinary(path, ext, conf, dtype, shape, skip, index, labels, engine, credentials)
    290         Credentials for remote storage (e.g. S3) in the form {access: ***, secret: ***}
    291     """
--> 292     shape, dtype = _binaryconfig(path, conf, dtype, shape, credentials)
    293 
    294     from thunder.readers import normalize_scheme, get_parallel_reader

C:\Users\Annie\Anaconda2\lib\site-packages\thunder\series\readers.pyc in _binaryconfig(path, conf, dtype, shape, credentials)
    363 
    364     if 'dtype' not in params.keys():
--> 365         raise ValueError('dtype not specified either in conf.json or as argument')
    366 
    367     if 'shape' not in params.keys():

ValueError: dtype not specified either in conf.json or as argument

In [143]:

    




    

    




---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-143-31372f3aef9c> in <module>()
----> 1 td.series.fromexample('iris')

C:\Users\Annie\Anaconda2\lib\site-packages\thunder\series\readers.pyc in fromexample(name, engine)
    436             if not key.name.endswith('/'):
    437                 key.get_contents_to_filename(os.path.join(d, key.name))
--> 438         data = frombinary(os.path.join(d, 'series', name), engine=engine)
    439 
    440         if spark and isinstance(engine, spark):

C:\Users\Annie\Anaconda2\lib\site-packages\thunder\series\readers.pyc in frombinary(path, ext, conf, dtype, shape, skip, index, labels, engine, credentials)
    290         Credentials for remote storage (e.g. S3) in the form {access: ***, secret: ***}
    291     """
--> 292     shape, dtype = _binaryconfig(path, conf, dtype, shape, credentials)
    293 
    294     from thunder.readers import normalize_scheme, get_parallel_reader

C:\Users\Annie\Anaconda2\lib\site-packages\thunder\series\readers.pyc in _binaryconfig(path, conf, dtype, shape, credentials)
    363 
    364     if 'dtype' not in params.keys():
--> 365         raise ValueError('dtype not specified either in conf.json or as argument')
    366 
    367     if 'shape' not in params.keys():

ValueError: dtype not specified either in conf.json or as argument

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