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February 13, 2014 10:12
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| #!/usr/bin/env python | |
| import networkx as nx | |
| import matplotlib.pyplot as plt | |
| import math | |
| from random import random | |
| from numpy import arange | |
| N = 1000 | |
| K = 5 | |
| P = 0.05 | |
| # attractive force | |
| def f_a(d,k): | |
| return d*d/k | |
| # repulsive force | |
| def f_r(d,k): | |
| return k*k/d | |
| def fruchterman_reingold(G,iteration=50): | |
| W = 1 | |
| L = 1 | |
| area = W*L | |
| k = math.sqrt(area/nx.number_of_nodes(G)) | |
| # initial position | |
| for v in nx.nodes_iter(G): | |
| G.node[v]['x'] = W*random() | |
| G.node[v]['y'] = L*random() | |
| t = W/10 | |
| dt = t/(iteration+1) | |
| print("area:{0}".format(area)) | |
| print("k:{0}".format(k)) | |
| print("t:{0}, dt:{1}".format(t,dt)) | |
| for i in range(iteration): | |
| print("iter {0}".format(i)) | |
| pos = {} | |
| for v in G.nodes_iter(): | |
| pos[v] = [G.node[v]['x'],G.node[v]['y']] | |
| plt.close() | |
| plt.ylim([-0.1,1.1]) | |
| plt.xlim([-0.1,1.1]) | |
| plt.axis('off') | |
| nx.draw_networkx(G,pos=pos,node_size=10,width=0.1,with_labels=False) | |
| plt.savefig("fig/{0}.png".format(i)) | |
| # calculate repulsive forces | |
| for v in G.nodes_iter(): | |
| G.node[v]['dx'] = 0 | |
| G.node[v]['dy'] = 0 | |
| for u in G.nodes_iter(): | |
| if v != u: | |
| dx = G.node[v]['x'] - G.node[u]['x'] | |
| dy = G.node[v]['y'] - G.node[u]['y'] | |
| delta = math.sqrt(dx*dx+dy*dy) | |
| if delta != 0: | |
| d = f_r(delta,k)/delta | |
| G.node[v]['dx'] += dx*d | |
| G.node[v]['dy'] += dy*d | |
| # calculate attractive forces | |
| for v,u in G.edges_iter(): | |
| dx = G.node[v]['x'] - G.node[u]['x'] | |
| dy = G.node[v]['y'] - G.node[u]['y'] | |
| delta = math.sqrt(dx*dx+dy*dy) | |
| if delta != 0: | |
| d = f_a(delta,k)/delta | |
| ddx = dx*d | |
| ddy = dy*d | |
| G.node[v]['dx'] += -ddx | |
| G.node[u]['dx'] += +ddx | |
| G.node[v]['dy'] += -ddy | |
| G.node[u]['dy'] += +ddy | |
| # limit the maximum displacement to the temperature t | |
| # and then prevent from being displace outside frame | |
| for v in G.nodes_iter(): | |
| dx = G.node[v]['dx'] | |
| dy = G.node[v]['dy'] | |
| disp = math.sqrt(dx*dx+dy*dy) | |
| if disp != 0: | |
| cnt += 1 | |
| d = min(disp,t)/disp | |
| x = G.node[v]['x'] + dx*d | |
| y = G.node[v]['y'] + dy*d | |
| x = min(W,max(0,x)) - W/2 | |
| y = min(L,max(0,y)) - L/2 | |
| G.node[v]['x'] = min(math.sqrt(W*W/4-y*y),max(-math.sqrt(W*W/4-y*y),x)) + W/2 | |
| G.node[v]['y'] = min(math.sqrt(L*L/4-x*x),max(-math.sqrt(L*L/4-x*x),y)) + L/2 | |
| # cooling | |
| t -= dt | |
| pos = {} | |
| for v in G.nodes_iter(): | |
| pos[v] = [G.node[v]['x'],G.node[v]['y']] | |
| plt.close() | |
| plt.ylim([-0.1,1.1]) | |
| plt.xlim([-0.1,1.1]) | |
| plt.axis('off') | |
| nx.draw_networkx(G,pos=pos,node_size=10,width=0.1,with_labels=False) | |
| plt.savefig("fig/{0}.png".format(i+1)) | |
| return pos | |
| def main(): | |
| G = nx.watts_strogatz_graph(N,K,P) | |
| pos = fruchterman_reingold(G) | |
| plt.close() | |
| plt.ylim([-0.1,1.1]) | |
| plt.xlim([-0.1,1.1]) | |
| plt.axis('off') | |
| nx.draw_networkx(G,pos=nx.spring_layout(G),node_size=10,width=0.1,with_labels=False) | |
| plt.savefig("fig/orig.png") | |
| if __name__ == "__main__": | |
| main() |
replacing 'nodes_iter' with 'nodes' will work fine.
You can find solution from here:
https://stackoverflow.com/questions/33734836/graph-object-has-no-attribute-nodes-iter-in-networkx-module-python
@mmisono Hello. Great work. I have a quick question. Can I get a reference of line 94-95 code?
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Hi,
I am trying to run this in Python2.7. Any idea how to fix this error ? Appreciate your help.
Traceback (most recent call last): File ".\fruchterman-reingold.py", line 124, in <module> main() File ".\fruchterman-reingold.py", line 114, in main pos = fruchterman_reingold(G) File ".\fruchterman-reingold.py", line 28, in fruchterman_reingold for v in nx.nodes_iter(G): AttributeError: 'module' object has no attribute 'nodes_iter'Thanks,
V.