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98 lines
3.3 KiB
Python
98 lines
3.3 KiB
Python
def strongly_connected_components(graph):
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"""
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Tarjan's Algorithm (named for its discoverer, Robert Tarjan) is a
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graph theory algorithm for finding the strongly connected
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components of a graph.
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Based on: http://en.wikipedia.org/wiki/Tarjan%27s_strongly_connected_components_algorithm
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@author: Dries Verdegem, some minor edits by Martin Thoma
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@source: http://www.logarithmic.net/pfh/blog/01208083168
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"""
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index_counter = 0
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stack = []
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lowlinks = {}
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index = {}
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result = []
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def strongconnect(node, index_counter):
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print("Start with node: %s###########################" % node)
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# set the depth index for this node to the smallest unused index
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print("lowlinks:\t%s" % lowlinks)
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print("index:\t%s" % index)
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print("stack:\t%s" % stack)
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index[node] = index_counter
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lowlinks[node] = index_counter
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index_counter += 1
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stack.append(node)
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# Consider successors of `node`
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try:
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successors = graph[node]
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except:
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successors = []
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# Depth first search
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for successor in successors:
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# Does the current node point to a node that was already
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# visited?
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if successor not in lowlinks:
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print("successor not in lowlinks: %s -> %s (node, successor)" %
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(node, successor))
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# Successor has not yet been visited; recurse on it
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strongconnect(successor, index_counter)
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lowlinks[node] = min(lowlinks[node], lowlinks[successor])
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elif successor in stack:
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# else:
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print("successor in stack: %s -> %s" % (node, successor))
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# the successor is in the stack and hence in the
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# current strongly connected component (SCC)
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lowlinks[node] = min(lowlinks[node], index[successor])
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else:
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print("This happens sometimes. node: %s, successor: %s" %
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(node, successor))
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print("Lowlinks: %s" % lowlinks)
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print("stack: %s" % stack)
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# If `node` is a root node, pop the stack and generate an SCC
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if lowlinks[node] == index[node]:
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print("Got root node: %s (index/lowlink: %i)" %
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(node, lowlinks[node]))
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connected_component = []
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while True:
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successor = stack.pop()
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print("pop: %s" % successor)
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connected_component.append(successor)
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if successor == node:
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break
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component = tuple(connected_component)
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# storing the result
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result.append(component)
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else:
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print("Node: %s, lowlink: %i, index: %i" %
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(node, lowlinks[node], index[node]))
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for node in graph:
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if node not in lowlinks:
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strongconnect(node, index_counter)
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return result
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graph = {'a': ['b'],
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'b': ['c'],
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'c': ['d', 'e'],
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'd': ['a', 'e', 'h'],
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'e': ['c', 'f'],
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'f': ['g', 'i'],
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'g': ['h', 'f'],
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'h': ['j'],
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'i': ['g', 'f'],
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'j': ['i'],
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'k': [],
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'h': []}
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print strongly_connected_components(graph)
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