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Pattern matching: return all the matches (instead of the first one found)

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This commit is contained in:
Joeri Exelmans 2024-09-03 11:41:07 +02:00
parent a7148d455b
commit 7ece331efb
3 changed files with 102 additions and 37 deletions
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93
pattern_matching/patternMatching.py
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@ -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
# return self.results