In [1]:

    

%matplotlib inline


    

    




/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.
  warnings.warn(self.msg_depr % (key, alt_key))

In [72]:

    

import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt


    

In [74]:

    

sns.set(style='whitegrid')


    

In [55]:

    

df = pd.read_csv('Firing/2015-11-20_18-13-34', index_col='time', names= ['time', 'neuron', 'one'])


    

In [67]:

    

missEnergy = pd.read_csv('MissEnergy/2015-11-20_18-13-34', index_col='time', names= ['time', 'neuron', 'energy'])


    

In [68]:

    

missEnergy.head(10)


    

    
Out[68]:






  

    

      

      
neuron
      
energy
    
    

      
time
      

      

    
  
  

    

      
442
      
3033
      
0.00
    
    

      
442
      
6771
      
0.08
    
    

      
443
      
3033
      
0.00
    
    

      
444
      
3015
      
0.08
    
    

      
445
      
3015
      
0.08
    
    

      
445
      
3017
      
0.08
    
    

      
445
      
3038
      
0.08
    
    

      
446
      
3015
      
0.08
    
    

      
446
      
3031
      
0.08
    
    

      
446
      
6771
      
0.08
    
  

In [56]:

    

df.index = pd.to_datetime(df.index, unit='ms')


    

In [69]:

    

missEnergy.index = pd.to_datetime(missEnergy.index, unit='ms')


    

In [79]:

    

df.one.resample('10ms', how='sum').plot()


    

    
Out[79]:





<matplotlib.axes._subplots.AxesSubplot at 0x112c4cc50>






    

In [80]:

    

df.one.resample('1ms', how='sum').plot()


    

    
Out[80]:





<matplotlib.axes._subplots.AxesSubplot at 0x1137080d0>






    

In [81]:

    

(df.one.resample('10ms', how='sum').apply(np.log10) - df.one.resample('10ms', how='sum').shift(1).apply(np.log10)).plot()


    

    
Out[81]:





<matplotlib.axes._subplots.AxesSubplot at 0x1129c3a50>






    

In [78]:

    

ax = missEnergy.energy.resample('10ms', how='sum').plot(color='g', label='missing energy')
df.one.resample('10ms', how='sum').plot(ax=ax.twinx(), label='firing')
plt.legend()


    

    
Out[78]:





<matplotlib.legend.Legend at 0x1127ad450>






    

In [ ]: