Can the package NetworkX be used to draw complex network with weights given by a distribution, for example a power law? Then can I write a code to draw the weight distribution or strength distribution, or even further to draw the weighted average nearest neighbours degree of a node? then coloring each class of similar degrees, or similar strenghs, etc.
I have a large data of a complex network consisting of about 300 nodes, and data about individual egdes' weights. What is the best way to draw such a network?
Edges in networkx can use the special attribute 'weight' which can be used in a number of algorithms requiring weighted edges. You can use networkx drawing commands to take these weights into account (e.g., by the spring force in a spring embedded visualisation). Something like:
>>> import networkx as nx
>>> import matplotlib.pyplot as plt
>>> G = nx.Graph()
>>> # add nodes, edges, etc.
...
>>> nx.draw_spring(G)
>>> plt.show()