def __init__(self, solver, n, incrset1, incrset2):
"""Creates an incremental set of all pairs frozetset([c1, c2]) from incrset1 and incrset2 respectively,
that are connected with N variables, according to solver"""
# defining variables
self._solver = solver
self._incrset1 = incrset1
self._incrset2 = incrset2
self._n = n
# map from objects to sets of pairs
self._map = {}
# super init
IncrementalSet.__init__(self, [incrset1, incrset2])
def __init__(self, solver, n, incrset1, incrset2):
"""Creates an incremental set of all pairs frozetset([c1, c2]) from incrset1 and incrset2 respectively,
that are connected with N variables, according to solver"""
# defining variables
self._solver = solver
self._incrset1 = incrset1
self._incrset2 = incrset2
self._n = n
# map from objects to sets of pairs
self._map = {}
# super init
IncrementalSet.__init__(self, [incrset1, incrset2])
def __init__(self, pattern, solver):
self._solver = solver
# convert pattern to a set of tuples
listoftuples = []
for clusterpattern in pattern:
(kind, clustername, pointnames) = clusterpattern
listoftuples.append(tuple([kind, clustername, tuple(pointnames)]))
setoftuples = frozenset(listoftuples)
self._pattern = setoftuples
# create sub-sets for correct type of input clusters
self._subs = []
# NOTE: we cannot use source like this to link it to a pattern, because sources may be equal!
self._source2pattern = {}
for clusterpattern in self._pattern:
(kind, clustername, pointnames) = clusterpattern
sub = KindFilter(kind, len(pointnames), self._solver.top_level())
self._subs.append(sub)
# NOTE: we cannot use source like this to link it to a pattern, because sources may be equal!
self._source2pattern[sub] = [clusterpattern]
print "creating", sub, "for", self._source2pattern[sub]
#rof
# create sub-sets for all pairs of clusters
listoftuples = list(setoftuples)
l = len(listoftuples)
for i in range(l):
for j in range(i + 1, l):
cp1 = listoftuples[i]
cp2 = listoftuples[j]
(kind1, clustername1, pointnames1) = cp1
(kind2, clustername2, pointnames2) = cp2
shared = set(pointnames1).intersection(set(pointnames2))
n = len(shared)
if n > 0:
kindfilter1 = KindFilter(kind1, len(pointnames1),
self._solver.top_level())
kindfilter2 = KindFilter(kind2, len(pointnames2),
self._solver.top_level())
sub = NConnectedPairs(solver, n, kindfilter1, kindfilter2)
self._subs.append(sub)
# NOTE: we cannot use source like this to link it to a pattern, because sources may be equal!
self._source2pattern[sub] = [cp1, cp2]
print "creating", sub, "for", self._source2pattern[sub]
IncrementalSet.__init__(self, self._subs)
def __init__(self, kind, minpoints, incrset):
kind2class = {}
kind2class["rigid"]=Rigid
kind2class["hog"]=Hedgehog
kind2class["balloon"]=Balloon
kind2class["distance"]=Rigid
kind2class["point"]=Rigid
kind2maxpoints = {}
kind2maxpoints["rigid"]=0
kind2maxpoints["hog"]=0
kind2maxpoints["balloon"]=0
kind2maxpoints["distance"]=2
kind2maxpoints["point"]=1
self._kind = kind
self._classobj = kind2class[kind]
self._maxpoints = kind2maxpoints[kind]
self._input = incrset
self._minpoints = minpoints
IncrementalSet.__init__(self,[incrset])
def __init__(self, kind, minpoints, incrset):
kind2class = {}
kind2class["rigid"] = Rigid
kind2class["hog"] = Hedgehog
kind2class["balloon"] = Balloon
kind2class["distance"] = Rigid
kind2class["point"] = Rigid
kind2maxpoints = {}
kind2maxpoints["rigid"] = 0
kind2maxpoints["hog"] = 0
kind2maxpoints["balloon"] = 0
kind2maxpoints["distance"] = 2
kind2maxpoints["point"] = 1
self._kind = kind
self._classobj = kind2class[kind]
self._maxpoints = kind2maxpoints[kind]
self._input = incrset
self._minpoints = minpoints
IncrementalSet.__init__(self, [incrset])
def __init__(self, pattern, solver):
self._solver = solver
# convert pattern to a set of tuples
listoftuples = []
for clusterpattern in pattern:
(kind, clustername, pointnames) = clusterpattern
listoftuples.append(tuple([kind, clustername, tuple(pointnames)]))
setoftuples = frozenset(listoftuples)
self._pattern = setoftuples
# create sub-sets for correct type of input clusters
self._subs = []
# NOTE: we cannot use source like this to link it to a pattern, because sources may be equal!
self._source2pattern = {}
for clusterpattern in self._pattern:
(kind, clustername, pointnames) = clusterpattern
sub = KindFilter(kind, len(pointnames),self._solver.top_level())
self._subs.append(sub)
# NOTE: we cannot use source like this to link it to a pattern, because sources may be equal!
self._source2pattern[sub]=[clusterpattern]
print "creating",sub,"for",self._source2pattern[sub]
#rof
# create sub-sets for all pairs of clusters
listoftuples = list(setoftuples)
l = len(listoftuples)
for i in range(l):
for j in range(i+1,l):
cp1 = listoftuples[i]
cp2 = listoftuples[j]
(kind1, clustername1, pointnames1) = cp1
(kind2, clustername2, pointnames2) = cp2
shared = set(pointnames1).intersection(set(pointnames2))
n = len(shared)
if n > 0:
kindfilter1 = KindFilter(kind1, len(pointnames1),self._solver.top_level())
kindfilter2 = KindFilter(kind2, len(pointnames2),self._solver.top_level())
sub = NConnectedPairs(solver, n, kindfilter1,kindfilter2)
self._subs.append(sub)
# NOTE: we cannot use source like this to link it to a pattern, because sources may be equal!
self._source2pattern[sub]=[cp1,cp2]
print "creating",sub,"for",self._source2pattern[sub]
IncrementalSet.__init__(self, self._subs)
