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 [3]:

    

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


    

In [4]:

    

sns.set(style='whitegrid')


    

In [7]:

    

!ls -l ../../BrainPowerLogs/Firing/


    

    




total 64320
-rw-r--r--  1 jb  staff    691110 Dec  4 11:38 2015-12-04_11-37-27
-rw-r--r--  1 jb  staff  11186992 Dec  4 11:47 2015-12-04_11-38-02
-rw-r--r--  1 jb  staff   1462957 Dec  4 11:49 2015-12-04_11-47-39
-rw-r--r--  1 jb  staff   6050473 Dec  4 11:55 2015-12-04_11-50-37
-rw-r--r--  1 jb  staff   3704318 Dec  4 12:00 2015-12-04_11-55-21
-rw-r--r--  1 jb  staff   1706959 Dec  4 12:18 2015-12-04_12-17-03
-rw-r--r--  1 jb  staff   2159076 Dec  4 13:10 2015-12-04_13-06-59
-rw-r--r--  1 jb  staff    679687 Dec  4 13:12 2015-12-04_13-10-13
-rw-r--r--  1 jb  staff   1578582 Dec  4 13:17 2015-12-04_13-12-33
-rw-r--r--  1 jb  staff    295639 Dec  4 13:28 2015-12-04_13-28-10
-rw-r--r--  1 jb  staff    975524 Dec  4 13:29 2015-12-04_13-28-30
-rw-r--r--  1 jb  staff    604033 Dec  4 13:30 2015-12-04_13-29-50
-rw-r--r--  1 jb  staff    390486 Dec  4 13:30 2015-12-04_13-30-17
-rw-r--r--  1 jb  staff         0 Dec  4 13:30 2015-12-04_13-30-59
-rw-r--r--  1 jb  staff         0 Dec  4 13:31 2015-12-04_13-31-13
-rw-r--r--  1 jb  staff         0 Dec  4 13:33 2015-12-04_13-33-58
-rw-r--r--  1 jb  staff   1411538 Dec  4 13:37 2015-12-04_13-34-56

In [22]:

    

firing = pd.read_csv('../../BrainPowerLogs/Firing/2015-12-04_13-34-56', header=None, names=['time', 'neuron', 'one'])
firing.time = pd.to_timedelta(firing.time, unit='ms') + pd.to_datetime('2015-12-04 13:34:56')
firing.head()


    

    
Out[22]:






  

    

      

      
time
      
neuron
      
one
    
  
  

    

      
0
      
2015-12-04 13:34:56.050
      
2335
      
1
    
    

      
1
      
2015-12-04 13:34:56.050
      
6595
      
1
    
    

      
2
      
2015-12-04 13:34:56.050
      
6599
      
1
    
    

      
3
      
2015-12-04 13:34:56.051
      
2315
      
1
    
    

      
4
      
2015-12-04 13:34:56.054
      
6594
      
1
    
  

In [24]:

    

energy = pd.read_csv('../../BrainPowerLogs/Energy/2015-12-04_13-34-56', header=None, names=['time', 'available_pools', 'total_energy'])
energy.time = pd.to_timedelta(energy.time, unit='ms') + pd.to_datetime('2015-12-04 13:34:56')
energy.index = energy.time
energy.head()


    

    
Out[24]:






  

    

      

      
time
      
available_pools
      
total_energy
    
    

      
time
      

      

      

    
  
  

    

      
2015-12-04 13:34:56.004
      
2015-12-04 13:34:56.004
      
7520
      
7520
    
    

      
2015-12-04 13:34:56.005
      
2015-12-04 13:34:56.005
      
7520
      
7520
    
    

      
2015-12-04 13:34:56.006
      
2015-12-04 13:34:56.006
      
7520
      
7520
    
    

      
2015-12-04 13:34:56.007
      
2015-12-04 13:34:56.007
      
7520
      
7520
    
    

      
2015-12-04 13:34:56.008
      
2015-12-04 13:34:56.008
      
7520
      
7520
    
  

In [25]:

    

total_firing = firing.groupby('time').one.sum()


    

In [31]:

    

ax = total_firing.plot()


    

In [33]:

    

energy.total_energy.plot()


    

    
Out[33]:





<matplotlib.axes._subplots.AxesSubplot at 0x10f97c810>






    

In [53]:

    

plt.scatter(total_firing, energy.total_energy.ix[total_firing.index], alpha=0.2)
plt.ylabel('Remaining ATP immediately accessible to the neurons')
plt.xlabel('Number of firings')
plt.title('Phase diagram\nConvergence to the limit cycle')
plt.savefig('lotka-volterra-1.pdf')
plt.savefig('lotka-volterra-1.png')


    

In [51]:

    

plt.scatter(total_firing, energy.available_pools.ix[total_firing.index], alpha=0.2)
plt.ylabel('Number of non-empty pools')
plt.xlabel('Number of activations')
plt.title('Phase diagram\nConvergence to the limit cycle')
plt.savefig('lotka-volterra-2.pdf')
plt.savefig('lotka-volterra-2.png')


    

In [ ]: