In [1]:

    

import pickle as pkl
import pandas as pd

%matplotlib inline


    

In [2]:

    

! echo $PATH


    

    




/home/ericmjl/anaconda3/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/games:/usr/local/texlive/2015/bin/x86_64-linux:/home/ericmjl/pypy3/bin:/home/ericmjl/pypy/bin

In [3]:

    

! pypy3 simulation.py


    

    




n_hosts: 400, time:1.9110538959503174

In [4]:

    

! python simulation.py


    

    




n_hosts: 400, time:8.817363500595093

In [5]:

    

with open('results/simulation.pkl', 'rb') as f:
    results = pkl.load(f)


    

In [6]:

    

data = pd.DataFrame(results)


    

In [7]:

    

data.columns


    

    
Out[7]:





Index(['n_blue_immune', 'n_blue_virus', 'n_contacts', 'n_immune', 'n_infected',
       'n_mixed', 'n_original', 'n_red_immune', 'n_red_virus', 'n_uninfected'],
      dtype='object')

In [8]:

    

# Plot hosts
data[['n_blue_immune', 'n_red_immune', 'n_immune']].plot()


    

    
Out[8]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f5aee193cc0>






    

In [9]:

    

# Plot viruses.
data[['n_blue_virus', 'n_red_virus', 'n_mixed']].plot()


    

    
Out[9]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f5af5071358>






    

In [10]:

    

data[['n_contacts']].plot()


    

    
Out[10]:





<matplotlib.axes._subplots.AxesSubplot at 0x7f5af509f710>






    

In [ ]: