I am working with an NxN regular network and I want to plot its edge length distribution.
This is how I generate the network:
import networkx as nx
import matplotlib.pyplot as plt
N=30 #This can be changed
G=nx.grid_2d_graph(N,N)
pos = dict( (n, n) for n in G.nodes() )
labels = dict( ((i, j), i + (N-1-j) * N ) for i, j in G.nodes() )
nx.relabel_nodes(G,labels,False)
inds=labels.keys()
vals=labels.values()
inds.sort()
vals.sort()
pos2=dict(zip(vals,inds))
nx.draw_networkx(G, pos=pos2, with_labels=False, node_size = 15)
This is how I compute the edge length distribution:
def plot_edge_length_distribution(): #Euclidean distances from all nodes
lengths={}
for node in G.nodes():
neigh=nx.all_neighbors(G,node) #The connected neighbors of node n
for n in neigh:
lengths[node]=((pos2[n][1]-pos2[node][1])**2)+((pos2[n][0]-pos2[node][0])**2) #The square distance
items=sorted(lengths.items())
fig=plt.figure()
ax=fig.add_subplot(111)
ax.plot([k for (k,v) in items],[v/(num_edges) for (k,v) in items],'ks-')
ax.set_xscale("linear")
ax.set_yscale("linear")
plt.yticks(numpy.arange(0.94, 1.00, 0.02))
title_string=('Edge Length Distribution')
subtitle_string=('Lattice Network | '+str(N)+'x'+str(N)+' nodes')
plt.suptitle(title_string, y=0.99, fontsize=17)
plt.title(subtitle_string, fontsize=9)
plt.xlabel('Edge Length L')
plt.ylabel('p(L)')
ax.grid(True,which="both")
plt.show()
plot_edge_length_distribution()
This is what I obtain: there is something wrong as the dict lengths should contain only ones as values, due to the nature of the regular grid.
This is what I want: a plot telling me that length=1 has a probability p(l)=1 because the regular grid only features edges of length 1. What is wrong in my code?
items,[k for (k,v) in items]and[v/(num_edges) for (k,v) in items]. – Flooring