annotate RandomGraph.py @ 36:305cc03c2750
Chapter 5.5, exercise 6, #3: compute WS clustering coefficient
and characteristic length on a BA model graph.
| author |
Brian Neal <bgneal@gmail.com> |
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Thu, 10 Jan 2013 19:24:02 -0600 |
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950a34c7e26b |
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bgneal@6
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1 """This module contains the RandomGraph class.
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2
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3 """
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4 import random
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5 import itertools
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6
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7 from Graph import Graph, Edge
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8
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9
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10 class RandomGraph(Graph):
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11 """A RandomGraph is a Graph that adds a method to generate random edges."""
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12
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13 def add_random_edges(self, p=0.5):
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14 """This method first removes all edges, then adds edges at random such
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15 that the probability is p that there is an edge between any two nodes.
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16
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17 p must be a float between 0 and 1, inclusive.
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18
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19 """
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20 self.remove_all_edges()
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21
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22 # For each combination of 2 vertices, create an edge between them if we
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23 # select a random number [0.0, 1.0) that is less than p.
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24 for v, w in itertools.combinations(self.iterkeys(), 2):
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25 if random.random() <= p:
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26 self.add_edge(Edge(v, w))
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27
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28
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29 if __name__ == '__main__':
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30 import string
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31 import sys
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32 from Graph import Vertex
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33 from GraphWorld import GraphWorld, CircleLayout
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34
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35 def main(script_name, n=10, p=0.5):
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36
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37 n = int(n)
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38 p = float(p)
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39
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40 labels = string.ascii_lowercase + string.ascii_uppercase
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41 vs = [Vertex(c) for c in labels[:n]]
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42
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43 g = RandomGraph(vs)
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44 g.add_random_edges(p)
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45 layout = CircleLayout(g)
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46
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47 gw = GraphWorld()
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48 gw.show_graph(g, layout)
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49 gw.mainloop()
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50
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51 main(*sys.argv)
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52
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