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johns_algorithm.py
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191 lines (159 loc) · 6.88 KB
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from DPI import *
from copy import *
class Strongly_connected_components:
def DFS_scc(self, vertex, visited , stack):
#print("in DFS", vertex)
visited.add(vertex)
for v in vertex.adj_nodes:
#print("neighbor:" , v)
#print(v in visited)
if v in visited:
continue
self.DFS_scc(v, visited , stack)
#print("finishing vertex:" , vertex)
stack.append(vertex)
def reverse_graph(self, graph):
reversed_graph = SFGraph(dict())
for edge in graph.edge_list:
reversed_graph.add_edge( graph.nodes_name_map[edge.target].node_number , graph.nodes_name_map[edge.target].node_number , edge.weight )
return reversed_graph
def DFS_scc_reverse(self, vertex , visited , vertex_set):
visited.add(vertex)
vertex_set.add(vertex)
for v in vertex.adj_nodes:
if v in visited:
continue
self.DFS_scc_reverse(v , visited , vertex_set)
def scc(self, graph):
#print("in scc")
#for v in graph.vertex:
#print(type(v.node_number))
stack = []
visited = set()
for i in range(len(graph.vertex)):
if graph.vertex[i] in visited:
continue
self.DFS_scc( graph.vertex[i], visited, stack )
#print("visited:",visited)
#reversed_graph = copy(graph)
#print("before reverse:", graph)
reversed_graph = self.reverse_graph(graph)
#print("after reverse:", graph)
visited.clear()
result = []
#print("visited:",visited)
#print("stack:",stack)
while(len(stack)):
vertex = stack.pop()
if vertex in visited:
continue
cur_scc_set = set()
self.DFS_scc_reverse(vertex , visited , cur_scc_set)
result.append(cur_scc_set)
return result
class Cycle_finding:
def __init__(self):
#print("in finding init")
self.blocked_set = set()
self.blocked_map = defaultdict(set)
self.stack = list()
self.all_cycles = list()
pass
def create_subgraph(self, start_index , graph):
subgraph = SFGraph(dict())
#print(graph.edge_list)
for edge in graph.edge_list:
#print(type(edge.source), type(start_index))
if graph.nodes_name_map[edge.source].node_number >= start_index and graph.nodes_name_map[edge.target].node_number >= start_index:
subgraph.add_edge( graph.nodes_name_map[edge.source].node_number , graph.nodes_name_map[edge.target].node_number , edge.weight )
return subgraph
def get_least_index_scc(self, sccs , subgraph ):
import sys
min_index = sys.maxsize
min_vertex = None
min_scc = None
for scc in sccs:
if len(scc) == 1:
continue
for v in scc:
if v.node_number < min_index:
min_index, min_vertex , min_scc = v.node_number , v , scc
#print("min_index: ", min_index, "min_scc: ", min_scc)
if min_scc is None:
return -1 , min_vertex
graph_scc = SFGraph(dict())
new_scc = set()
for v in min_scc:
new_scc.add(subgraph.nodes_name_map[v.node_name])
min_scc = new_scc
for edge in subgraph.edge_list:
#print("in loop sub: ",subgraph.nodes_name_map[edge.source] , subgraph.nodes_name_map[edge.target], min_scc)
#print(subgraph.nodes_name_map[edge.source] in min_scc and subgraph.nodes_name_map[edge.target] in min_scc)
#print(type(min_scc))
if subgraph.nodes_name_map[edge.source] in min_scc and subgraph.nodes_name_map[edge.target] in min_scc:
graph_scc.add_edge( edge.source , edge.target , edge.weight )
#print("scc graph: ", graph_scc)
#print(min_vertex.node_name , graph_scc.nodes_name_map)
#print(min_vertex.node_name not in graph_scc.nodes_name_map)
#print("min_index: ", min_index, "min_scc: ", min_scc)
if min_vertex.node_name not in graph_scc.nodes_name_map:
return -1 , min_vertex
return min_index , min_vertex
def unblock(self, vertex):
#print("in unblock: unblocking ", vertex)
#print(self.blocked_set)
#print("unblock map for current node:")
#print(self.blocked_map[vertex])
if vertex not in self.blocked_set:
return
self.blocked_set.remove(vertex)
if len( self.blocked_map[vertex] ) > 0:
for v in self.blocked_map[vertex]:
self.unblock( v )
del self.blocked_map[ vertex ]
def find_cycles_in_scc(self, start_vertex, current_vertex):
self.stack.append(current_vertex)
self.blocked_set.add(current_vertex)
found_cycle = False
got_cycle = False
#print("at the beginning of algorithm, current_vertex: ",current_vertex)
for neighbor in current_vertex.adj_nodes:
if neighbor is start_vertex:
self.stack.append(start_vertex)
cycle = copy(self.stack)
cycle.reverse()
self.stack.pop()
self.all_cycles.append(cycle)
#print("find cycle")
found_cycle = True
elif neighbor not in self.blocked_set:
got_cycle = self.find_cycles_in_scc( start_vertex , neighbor )
found_cycle = (found_cycle or got_cycle)
if found_cycle:
self.unblock( current_vertex )
else:
for neighbor in current_vertex.adj_nodes:
self.blocked_map[neighbor].add( current_vertex )
self.stack.pop()
return found_cycle
def simple_cycles(self, graph):
start_index = 0
SCC = Strongly_connected_components()
#print("algorithm begins",len(graph.vertex))
while start_index <= len(graph.vertex):
#print("in loop , start index",start_index)
subGraph = self.create_subgraph(start_index , graph)
sccs = SCC.scc(subGraph)
#print("sccs: ", sccs)
#print("subgraph:" , subGraph)
maybe_least_index = self.get_least_index_scc(sccs , subGraph )
#print("least index: ", maybe_least_index)
if maybe_least_index[0] >= start_index:
least_vertex = maybe_least_index[1]
self.blocked_map.clear()
self.blocked_set.clear()
self.find_cycles_in_scc(least_vertex , least_vertex)
start_index = least_vertex.node_number + 1
else:
break
return self.all_cycles