Tutorial - Marques-Pita Canalization

In [1]:

    

%load_ext autoreload
%autoreload 2
%matplotlib inline


    

In [3]:

    

import networkx as nx
import pandas as pd
#pd.set_option('display.unicode.east_asian_width', False)
#pd.set_option('display.unicode.ambiguous_as_wide', False)
pd.set_option('display.width',200)
import cana
from cana.datasets.bio import MARQUESPITA
from cana.drawing.canalizing_map import draw_canalizing_map_graphviz
import matplotlib.pylab as plt
from IPython.display import Image, display


    

In [4]:

    

Image(url="http://journals.plos.org/plosone/article/figure/image?size=large&id=info:doi/10.1371/journal.pone.0055946.g005",width=350)


    

    
Out[4]:

In [6]:

    

net = MARQUESPITA()
print(net)


    

    




<BNetwork(Name='Marques-Pita & Rocha', N=7, Nodes=['One', 'Two', 'Three', 'Four', 'Five', 'Six', 'Seven'])>

In [5]:

    

n = MARQUESPITA().nodes[6]
print( n.outputs)
print( n)
print( 'k_r: %.2f - %.2f' % (n.input_redundancy(mode='node',bound='upper',norm=False), n.input_redundancy(mode='node',bound='lower',norm=False)))
print( 'k_e: %.2f - %.2f' % (n.effective_connectivity(mode='node',bound='upper',norm=False), n.effective_connectivity(mode='node',bound='lower',norm=False)))
print('k_s: %.2f - %.2f' % (n.input_symmetry(mode='node',bound='upper',norm=False), n.input_symmetry(mode='node',bound='lower',norm=False)))
print()

print('k_r: %s (upper)' % n.input_redundancy(mode='input',bound='upper'))
print( 'k_e: %s (upper)' % n.input_redundancy(mode='input',bound='upper'))
print() 
dfLUT, dfPI, dfTW = n.look_up_table(), n.schemata_look_up_table(type='pi'), n.schemata_look_up_table(type='ts')
print( display(pd.concat({'Original LUT':dfLUT,'PI Schema':dfPI,'TW Schema':dfTW}, axis=1).fillna('-')))


    

    




[0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
<BNode(name='Seven', k=6, inputs=[One,Two,Three,Four,Five,Six], state=0, outputs='[0,0,0,0...0,0,0,0]' constant=False)>
k_r: 4.25 - 3.97
k_e: 1.75 - 2.03
k_s: 4.19 - 2.55

k_r: [0.9375, 0.5625, 0.5625, 0.9375, 0.9375, 0.9375] (upper)
k_e: [0.9375, 0.5625, 0.5625, 0.9375, 0.9375, 0.9375] (upper)







    








  

    

      

      
Original LUT
      
PI Schema
      
TW Schema
    
    

      

      
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0
      
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100001
      
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None

In [15]:

    

Image(url="http://journals.plos.org/plosone/article/figure/image?size=large&id=10.1371/journal.pone.0055946.g010",width=350)


    

    
Out[15]:

In [8]:

    

draw_canalizing_map_graphviz(n.canalizing_map())


    

    
Out[8]:

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