In [1]:

    

%matplotlib inline


    

In [2]:

    

import networkx as nx
import numpy as np


t1 = np.array([[1,3,1,1],[3,1,1,1],[1,1,1,1],[1,1,1,1]])
g = nx.to_networkx_graph(t1)


    

    




Couldn't import dot_parser, loading of dot files will not be possible.

In [3]:

    

nx.draw(g)


    

In [4]:

    

t1


    

    
Out[4]:





array([[1, 3, 1, 1],
       [3, 1, 1, 1],
       [1, 1, 1, 1],
       [1, 1, 1, 1]])

In [5]:

    

g.add_node(4)
g.add_edge(1,4)


    

In [6]:

    

nx.draw(g)


    

In [7]:

    

m1 = nx.to_numpy_matrix(g)
print m1


    

    




[[ 1.  3.  1.  1.  0.]
 [ 3.  1.  1.  1.  1.]
 [ 1.  1.  1.  1.  0.]
 [ 1.  1.  1.  1.  0.]
 [ 0.  1.  0.  0.  0.]]

In [8]:

    

g.remove_node(3)


    

In [9]:

    

nx.draw(g)


    

In [10]:

    

nx.to_numpy_matrix(g)


    

    
Out[10]:





matrix([[ 1.,  3.,  1.,  0.],
        [ 3.,  1.,  1.,  1.],
        [ 1.,  1.,  1.,  0.],
        [ 0.,  1.,  0.,  0.]])

In [11]:

    

m2 = nx.to_numpy_matrix(g)


    

In [12]:

    

print m2


    

    




[[ 1.  3.  1.  0.]
 [ 3.  1.  1.  1.]
 [ 1.  1.  1.  0.]
 [ 0.  1.  0.  0.]]

In [14]:

    

import networkx.generators as nxg


    

In [30]:

    

nx.draw(nxg.random_lobster(20, 0.2, 0.3))


    

In [32]:

    

h1 = nx.star_graph(4)
nx.draw(h1)


    

In [34]:

    

h1m = nx.to_numpy_matrix(h1)


    

In [35]:

    

h1m[1,2] = 3


    

In [39]:

    

h2 = nx.from_numpy_matrix(h1m)


    

In [40]:

    

nx.draw(h2)


    

In [38]:

    

h1m[1,2] = 0


    

In [ ]: