diff --git a/pattern_matching/main.py b/pattern_matching/main.py index 4807bb7..604794a 100644 --- a/pattern_matching/main.py +++ b/pattern_matching/main.py @@ -31,31 +31,34 @@ if __name__ == '__main__': """ The main function called when running from the command line. """ - nr_of_vertices = 50 - nr_of_diff_types_v = 10 - nr_of_edges = 150 - nr_of_diff_types_e = 10 + nr_of_vertices = 10 + nr_of_diff_types_v = 0 + nr_of_edges = 20 + nr_of_diff_types_e = 0 dv = [random.randint(0, nr_of_diff_types_v) for _ in range(nr_of_vertices)] - # dv = np.random.random_integers(0, nr_of_diff_types_v, nr_of_vertices) de = [random.randint(0, nr_of_diff_types_e) for _ in range(nr_of_edges)] - # de = np.random.random_integers(0, nr_of_diff_types_e, nr_of_edges) dc_inc = [random.randint(0, nr_of_vertices-1) for _ in range(nr_of_edges)] - # dc_inc = np.random.random_integers(0, nr_of_vertices-1, nr_of_edges) dc_out = [random.randint(0, nr_of_vertices-1) for _ in range(nr_of_edges)] - # dc_out = np.random.random_integers(0, nr_of_vertices-1, nr_of_edges) # override random graph by copy pasting output from terminal - dv = [ 10,5,4,0,8,6,8,0,4,8,5,5,7,0,10,0,5,6,10,4,0,3,0,8,2,7,5,8,1,0,2,10,0,0,1,6,8,4,7,6,4,2,10,10,6,4,6,0,2,7 ] - de = [ 8,10,8,1,6,7,4,3,5,2,0,0,9,6,0,3,8,3,2,7,2,3,10,8,10,8,10,2,5,5,10,6,7,5,1,2,1,2,2,3,7,7,2,1,7,2,9,10,8,1,9,4,1,3,1,1,8,2,2,9,10,9,1,9,4,10,10,10,9,3,5,3,6,6,9,1,2,6,3,2,4,10,9,6,5,6,2,4,3,2,4,10,6,2,8,8,0,5,1,7,3,4,3,8,7,3,0,8,3,3,8,5,10,5,9,3,1,10,3,2,6,3,10,0,5,10,9,10,0,1,4,7,10,3,1,9,1,2,3,7,4,3,7,8,8,4,5,10,1,4 ] - dc_inc = [ 0,25,18,47,22,25,16,45,38,25,5,45,15,44,17,46,6,17,35,8,16,29,48,47,25,34,4,20,24,1,47,44,8,25,32,3,16,6,33,21,6,13,41,10,17,25,21,33,31,30,5,4,45,26,16,42,12,25,29,3,32,30,14,26,11,13,7,13,3,43,43,22,48,37,20,28,15,40,19,33,43,16,49,36,11,25,9,42,3,22,16,40,42,44,27,30,1,18,10,35,19,6,9,43,37,38,45,19,41,14,37,45,0,31,29,31,24,20,44,46,8,45,43,3,38,38,35,12,19,45,7,34,20,28,12,17,45,17,35,49,20,21,49,1,35,38,38,36,33,30 ] - dc_out = [ 9,2,49,49,37,33,16,21,5,46,4,15,9,6,14,22,16,33,23,21,15,31,37,23,47,3,30,26,35,9,29,21,39,32,22,43,5,9,41,30,31,30,37,33,31,34,23,22,34,26,44,36,38,33,48,5,9,34,13,7,48,41,43,26,26,7,12,6,12,28,22,8,29,22,24,27,16,4,31,41,32,15,19,20,38,0,26,18,43,46,40,17,29,14,34,14,32,17,32,47,16,45,7,4,35,22,42,11,38,2,0,29,4,38,17,44,9,23,5,10,31,17,1,11,16,5,37,27,35,32,45,16,18,1,14,4,42,24,43,31,21,38,6,34,39,46,20,1,38,47 ] + # dv = [ 10,5,4,0,8,6,8,0,4,8,5,5,7,0,10,0,5,6,10,4,0,3,0,8,2,7,5,8,1,0,2,10,0,0,1,6,8,4,7,6,4,2,10,10,6,4,6,0,2,7 ] + # de = [ 8,10,8,1,6,7,4,3,5,2,0,0,9,6,0,3,8,3,2,7,2,3,10,8,10,8,10,2,5,5,10,6,7,5,1,2,1,2,2,3,7,7,2,1,7,2,9,10,8,1,9,4,1,3,1,1,8,2,2,9,10,9,1,9,4,10,10,10,9,3,5,3,6,6,9,1,2,6,3,2,4,10,9,6,5,6,2,4,3,2,4,10,6,2,8,8,0,5,1,7,3,4,3,8,7,3,0,8,3,3,8,5,10,5,9,3,1,10,3,2,6,3,10,0,5,10,9,10,0,1,4,7,10,3,1,9,1,2,3,7,4,3,7,8,8,4,5,10,1,4 ] + # dc_inc = [ 0,25,18,47,22,25,16,45,38,25,5,45,15,44,17,46,6,17,35,8,16,29,48,47,25,34,4,20,24,1,47,44,8,25,32,3,16,6,33,21,6,13,41,10,17,25,21,33,31,30,5,4,45,26,16,42,12,25,29,3,32,30,14,26,11,13,7,13,3,43,43,22,48,37,20,28,15,40,19,33,43,16,49,36,11,25,9,42,3,22,16,40,42,44,27,30,1,18,10,35,19,6,9,43,37,38,45,19,41,14,37,45,0,31,29,31,24,20,44,46,8,45,43,3,38,38,35,12,19,45,7,34,20,28,12,17,45,17,35,49,20,21,49,1,35,38,38,36,33,30 ] + # dc_out = [ 9,2,49,49,37,33,16,21,5,46,4,15,9,6,14,22,16,33,23,21,15,31,37,23,47,3,30,26,35,9,29,21,39,32,22,43,5,9,41,30,31,30,37,33,31,34,23,22,34,26,44,36,38,33,48,5,9,34,13,7,48,41,43,26,26,7,12,6,12,28,22,8,29,22,24,27,16,4,31,41,32,15,19,20,38,0,26,18,43,46,40,17,29,14,34,14,32,17,32,47,16,45,7,4,35,22,42,11,38,2,0,29,4,38,17,44,9,23,5,10,31,17,1,11,16,5,37,27,35,32,45,16,18,1,14,4,42,24,43,31,21,38,6,34,39,46,20,1,38,47 ] + + dv = [0, 1, 0, 1, 0] + de = [0, 0, 0] + dc_inc = [0, 2, 4] + dc_out = [1, 3, 3] gg = GraphGenerator(dv, de, dc_inc, dc_out, debug) graph = gg.getRandomGraph() - pattern = gg.getRandomPattern(5, 15, debug=debug) + print(graph.vertices) + pattern = gg.getRandomPattern(3, 15, debug=debug) + print(pattern.vertices) # override random pattern by copy pasting output from terminal to create # pattern, paste it in the createConstantPattern function in the generator.py @@ -70,10 +73,12 @@ if __name__ == '__main__': #PM = PatternMatching('SP') # PM = PatternMatching('Ullmann') PM = PatternMatching('VF2') - v,e = PM.match(pattern, graph) + matches = PM.match(pattern, graph) + print("found", len(matches), "matches:", matches) # regenerate graph, to show matched pattern - graphToDot.printGraph('randomGraph.dot', graph, v, e) + for i, (v,e) in enumerate(matches): + graphToDot.printGraph(f'randomGraph-{i}.dot', graph, v, e) if debug: print(len(v)) diff --git a/pattern_matching/patternMatching.py b/pattern_matching/patternMatching.py index 77e2c98..149a001 100644 --- a/pattern_matching/patternMatching.py +++ b/pattern_matching/patternMatching.py @@ -36,6 +36,7 @@ class PatternMatching(object): self.result = None self.previous = [] self.optimize = optimize + self.results = [] def match(self, pattern, graph): """ @@ -68,6 +69,7 @@ class PatternMatching(object): self.bound_vertices = {} self.bound_edges = {} self.result = None + self.results = [] return result @@ -845,7 +847,21 @@ class PatternMatching(object): """ # all candidate pair (n, m) represent graph x pattern + candidate = frozenset(itertools.chain( + ((i, j) for i,j in VF2_obj.mapping.items()), + # ((self.reverseMapH[i], self.reverseMapP[j]) for i,j in VF2_obj.mapping.items()), + [(h[n],p[m])], + )) + + if candidate in self.alreadyVisited: + # print(self.indent*" ", "candidate:", candidate) + # for match in self.alreadyVisited.get(index_M, []): + # if match == candidate: + return False # already visited this (partial) match -> skip + + if feasibilityTest(H, P, h, p, VF2_obj, n, m): + print(self.indent*" ","adding to match:", n, "->", m) # adapt VF2_obj VF2_obj.core_graph[n] = True VF2_obj.core_pattern[m] = True @@ -855,17 +871,30 @@ class PatternMatching(object): addOutNeighbours(P[m], VF2_obj.N_out_pattern, index_M) addIncNeighbours(P, m, VF2_obj.N_inc_pattern, index_M) - if findM(H, P, h, p, VF2_obj, index_M + 1): - return True + if index_M > 0: + # remember our partial match (shallow copy) so we don't visit it again + self.alreadyVisited.add(frozenset([ (i, j) for i,j in VF2_obj.mapping.items()])) + # self.alreadyVisited.setdefault(index_M, set()).add(frozenset([ (self.reverseMapH[i], self.reverseMapP[j]) for i,j in VF2_obj.mapping.items()])) + # print(self.alreadyVisited) - # else, cleanup, adapt VF2_obj - VF2_obj.core_graph[n] = False - VF2_obj.core_pattern[m] = False - del VF2_obj.mapping[h[n]] - delNeighbours(VF2_obj.N_out_graph, index_M) - delNeighbours(VF2_obj.N_inc_graph, index_M) - delNeighbours(VF2_obj.N_out_pattern, index_M) - delNeighbours(VF2_obj.N_inc_pattern, index_M) + self.indent += 1 + if findM(H, P, h, p, VF2_obj, index_M + 1): + # return True + print(self.indent*" ","found match", len(self.results), ", continuing...") + self.indent -= 1 + + if True: + # else: + print(self.indent*" ","backtracking... remove", n, "->", m) + + # else, backtrack, adapt VF2_obj + VF2_obj.core_graph[n] = False + VF2_obj.core_pattern[m] = False + del VF2_obj.mapping[h[n]] + delNeighbours(VF2_obj.N_out_graph, index_M) + delNeighbours(VF2_obj.N_inc_graph, index_M) + delNeighbours(VF2_obj.N_out_pattern, index_M) + delNeighbours(VF2_obj.N_inc_pattern, index_M) return False @@ -879,12 +908,15 @@ class PatternMatching(object): # skip graph vertices that are not in VF2_obj.N_out_graph # (or already matched) if N_graph[n] == -1 or VF2_obj.core_graph[n]: + # print(self.indent*" "," skipping") continue + print(self.indent*" "," n:", n) for m in range(0, len(N_pattern)): # skip graph vertices that are not in VF2_obj.N_out_pattern # (or already matched) if N_pattern[m] == -1 or VF2_obj.core_pattern[m]: continue + print(self.indent*" "," m:", m) if matchPhase(H, P, h, p, index_M, VF2_obj, n, m): return True @@ -899,35 +931,48 @@ class PatternMatching(object): # skip vertices that are connected to the graph # (or already matched) if not (VF2_obj.N_out_graph[n] == -1 and VF2_obj.N_inc_graph[n] == -1) or VF2_obj.core_graph[n]: + # print(self.indent*" "," skipping") continue + print(" n:", n) for m in range(0, len(VF2_obj.N_out_pattern)): # skip vertices that are connected to the graph # (or already matched) if not (VF2_obj.N_out_pattern[m] == -1 and VF2_obj.N_inc_pattern[m] == -1) or VF2_obj.core_pattern[m]: + # print(self.indent*" "," skipping") continue + print(self.indent*" "," m:", m) if matchPhase(H, P, h, p, index_M, VF2_obj, n, m): return True return False + print(self.indent*" ","index_M:", index_M) + # We are at the end, we found an candidate. if index_M == len(p): + print(self.indent*" ","end...") bound_graph_vertices = {} for vertex_bound, _ in VF2_obj.mapping.items(): bound_graph_vertices.setdefault(vertex_bound.type, set()).add(vertex_bound) self.result = self.matchNaive(vertices=bound_graph_vertices, edges=self.graph.edges) + if self.result != None: + self.results.append(self.result) return self.result != None - # try the candidates is the preffered order - # first try the adjacent vertices connected via the outgoing edges. - if preferred(H, P, h, p, index_M, VF2_obj, VF2_obj.N_out_graph, VF2_obj.N_out_pattern): - return True + if index_M > 0: + # try the candidates is the preffered order + # first try the adjacent vertices connected via the outgoing edges. + print(self.indent*" ","preferred L1") + if preferred(H, P, h, p, index_M, VF2_obj, VF2_obj.N_out_graph, VF2_obj.N_out_pattern): + return True - # then try the adjacent vertices connected via the incoming edges. - if preferred(H, P, h, p, index_M, VF2_obj, VF2_obj.N_inc_graph, VF2_obj.N_inc_pattern): - return True + print(self.indent*" ","preferred L2") + # then try the adjacent vertices connected via the incoming edges. + if preferred(H, P, h, p, index_M, VF2_obj, VF2_obj.N_inc_graph, VF2_obj.N_inc_pattern): + return True + print(self.indent*" ","leastPreferred") # and lastly, try the vertices not connected to the currently matched vertices if leastPreferred(H, P, h, p, index_M, VF2_obj): return True @@ -937,11 +982,23 @@ class PatternMatching(object): # create adjecency matrix of the graph H, h = self.createAdjacencyMatrixMap(self.graph) + print("adjacency:", H) + print("h:", len(h)) # create adjecency matrix of the pattern P, p = self.createAdjacencyMatrixMap(self.pattern) VF2_obj = VF2_Obj(len(h), len(p)) + self.indent = 0 + + # Only for debugging: + self.reverseMapH = { h[i] : i for i in range(len(h))} + self.reverseMapP = { p[i] : i for i in range(len(p))} + + # Set of partial matches already explored - prevents us from producing the same match multiple times + # Encoded as a mapping from match size to the partial match + self.alreadyVisited = set() + findM(H, P, h, p, VF2_obj) - return self.result \ No newline at end of file + # return self.results \ No newline at end of file diff --git a/pattern_matching/run.sh b/pattern_matching/run.sh index 08e7247..57f1e58 100755 --- a/pattern_matching/run.sh +++ b/pattern_matching/run.sh @@ -1,8 +1,11 @@ #!/bin/sh +rm *.svg +rm *.dot python main.py -dot randomGraph.dot -Tsvg > randomGraph.svg -dot randomPattern.dot -Tsvg > randomPattern.svg +# dot randomGraph.dot -Tsvg > randomGraph.svg +for filename in randomGraph-*.dot; do + dot $filename -Tsvg > $filename.svg +done -firefox randomGraph.svg -firefox randomPattern.svg \ No newline at end of file +firefox *.svg