app/graph/generators.py
author Sverre Rabbelier <srabbelier@gmail.com>
Thu, 27 Nov 2008 21:57:24 +0000
changeset 597 66088092f849
parent 594 06c2228e39cb
permissions -rw-r--r--
Proper working implementation of a cycle detection algorithm, that returns the cycles (rather than printing them) by constructing the path between the two nodes that were found to be cyclic. Patch by: Sverre Rabbelier

# Copyright (c) 2007-2008 Pedro Matiello <pmatiello@gmail.com>
#                         Zsolt Haraszti <zsolt@drawwell.net>
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation
# files (the "Software"), to deal in the Software without
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# copies of the Software, and to permit persons to whom the
# Software is furnished to do so, subject to the following
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# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.

# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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"""
Random graph generators for python-graph.

@sort: generate
"""


# Imports
import graph as classes
from random import randint


# Generator

def generate(graph, num_nodes, num_edges, weight_range=(1, 1)):
	"""
	Add nodes and random edges to the graph.
	
	@type  graph: graph
	@param graph: Graph.
	
	@type  num_nodes: number
	@param num_nodes: Number of nodes.
	
	@type  num_edges: number
	@param num_edges: Number of edges.

	@type  weight_range: tuple
	@param weight_range: tuple of two integers as lower and upper limits on randomly generated
	weights (uniform distribution).
	"""
	# Discover if graph is directed or not
 	directed = (type(graph) == classes.digraph)

	# Nodes first
	nodes = xrange(num_nodes)
	graph.add_nodes(nodes)
	
	# Build a list of all possible edges
	edges = []
        edges_append = edges.append
	for x in nodes:
		for y in nodes:
			if ((directed and x != y) or (x > y)):
				edges_append((x, y))
	
	# Randomize the list
	for i in xrange(len(edges)):
		r = randint(0, len(edges)-1)
		edges[i], edges[r] = edges[r], edges[i]
	
		# Add edges to the graph
		min_wt = min(weight_range)
		max_wt = max(weight_range)
	for i in xrange(num_edges):
		each = edges[i]
		graph.add_edge(each[0], each[1], wt = randint(min_wt, max_wt))