def allPatterns(cls, motif, k):
"""
Return all k-patterns from a given vertex set
"""
if (motif, k) in cls.allPatternLookup:
patterns = cls.allPatternLookup[(motif, k)]
else:
patterns = []
# iterate over power set of vertices
vertexSet = motif.nodes
for v_set in xpowerset(vertexSet):
# iterate over all possible boundary sizes
for boundarySize in range(min([k, len(v_set)]) + 1):
# iterate over all possible boundaries
for boundary in itertools.combinations(
v_set, boundarySize):
# iterate over all possible boundary mappings
for mapping in itertools.permutations(
range(k), boundarySize):
d = dict(zip(boundary, mapping))
kp = cls(v_set, d, motif)
if kp.isSeparator():
patterns.append(kp)
cls.separatorLookup[(kp.vertices, kp.boundary,
motif)] = kp
cls.allPatternLookup[(motif, k)] = patterns
return iter(patterns)
def allPatterns(cls, motif, k):
"""
Return all k-patterns from a given vertex set
"""
if (motif, k) in cls.allPatternLookup:
patterns = cls.allPatternLookup[(motif, k)]
else:
patterns = []
# iterate over power set of vertices
vertexSet = motif.nodes
for v_set in xpowerset(vertexSet):
# iterate over all possible boundary sizes
for boundarySize in range(min([k, len(v_set)])+1):
# iterate over all possible boundaries
for boundary in itertools.combinations(v_set,
boundarySize):
# iterate over all possible boundary mappings
for mapping in itertools.permutations(range(k),
boundarySize):
d = dict(zip(boundary, mapping))
kp = cls(v_set, d, motif)
if kp.isSeparator():
patterns.append(kp)
cls.separatorLookup[(kp.vertices, kp.boundary,
motif)] = kp
cls.allPatternLookup[(motif, k)] = patterns
return iter(patterns)
def allCompatible(self):
"""
Generator of all patterns that are compatible for joining with this
pattern
"""
v_set = self.graph.nodes
for otherVertices in xpowerset(v_set - self.vertices):
pattern2 = self.__class__(set(otherVertices) | self.boundaryVertices, self.boundary, self.graph)
if pattern2.isSeparator():
yield pattern2
def allCompatible(self):
"""
Generator of all patterns that are compatible for joining with this
pattern
"""
v_set = self.graph.nodes
for otherVertices in xpowerset(v_set - self.vertices):
pattern2 = self.__class__(
set(otherVertices) | self.boundaryVertices, self.boundary,
self.graph)
if pattern2.isSeparator():
yield pattern2
def inverseJoin(self):
"""Generator of all pattern pairs whose joins give this pattern"""
# Create set of vertices not on the boundary
nonBoundaryVertices = self.vertices - self.boundaryVertices
# Iterate over all divisions of boundary vertices into 2 sets
for v_list in xpowerset(nonBoundaryVertices):
v_set = set(v_list)
# print "Inverse join: " + str(v_set)
pattern2 = self.__class__(v_set | self.boundaryVertices, self.boundary, self.graph)
pattern3 = self.__class__(self.vertices - v_set, self.boundary, self.graph)
if pattern2.isSeparator() and pattern3.isSeparator():
yield (pattern2, pattern3)
def inverseJoin(self, mem_motif=None):
"""Generator of all pattern pairs whose joins give this pattern"""
# Create set of vertices not on the boundary
nonBoundaryVertices = self.vertices - self.boundaryVertices
# Iterate over all divisions of boundary vertices into 2 sets
for v_list in xpowerset(nonBoundaryVertices):
v_set = set(v_list)
# print "Inverse join: " + str(v_set)
pattern2 = self.__class__(v_set | self.boundaryVertices,
self.boundary, self.graph)
pattern3 = self.__class__(self.vertices - v_set, self.boundary,
self.graph)
if pattern2.isSeparator() and pattern3.isSeparator():
yield (pattern2, pattern3)
def allPatterns(cls, graph, k):
"""Return all k-patterns from a given vertex set"""
# iterate over power set of vertices
vertexSet = graph.nodes
for v_set in xpowerset(vertexSet):
# iterate over all possible boundary sizes
for boundarySize in range(min([k, len(v_set)]) + 1):
# iterate over all possible boundaries
for boundary in itertools.combinations(v_set, boundarySize):
# iterate over all possible boundary mappings
for mapping in itertools.permutations(range(k), boundarySize):
d = dict(zip(boundary, mapping))
kp = cls(v_set, d, graph)
if kp.isSeparator():
yield kp
def allPatterns(cls, graph, k):
"""Return all k-patterns from a given vertex set"""
# iterate over power set of vertices
vertexSet = graph.nodes
for v_set in xpowerset(vertexSet):
# iterate over all possible boundary sizes
for boundarySize in range(min([k, len(v_set)]) + 1):
# iterate over all possible boundaries
for boundary in itertools.combinations(v_set, boundarySize):
# iterate over all possible boundary mappings
for mapping in itertools.permutations(
range(k), boundarySize):
d = dict(zip(boundary, mapping))
kp = cls(v_set, d, graph)
if kp.isSeparator():
yield kp
def allPatterns(cls, graph, k):
"""Return all k-patterns from a given vertex set"""
# print [(i, len(j)) for i, j in cls.allPatternLookup.iteritems()]
if (graph, k) in cls.allPatternLookup:
patterns = cls.allPatternLookup[(graph, k)]
else:
patterns = []
# iterate over power set of vertices
vertexSet = graph.nodes
for v_set in xpowerset(vertexSet):
# iterate over all possible boundary sizes
for boundarySize in range(min([k, len(v_set)])+1):
# iterate over all possible boundaries
for boundary in itertools.combinations(v_set,
boundarySize):
# iterate over all possible boundary mappings
for mapping in itertools.permutations(range(k),
boundarySize):
d = dict(zip(boundary, mapping))
kp = cls(v_set, d, graph)
if kp.isSeparator():
patterns.append(kp)
cls.allPatternLookup[(graph, k)] = patterns
return iter(patterns)
