def __init__(self, op, lea1, nTimes=2):
Lea.__init__(self)
self._op = op
self._lea1 = lea1
self._nTimes = nTimes
if nTimes <= 0:
raise Lea.Error("times method requires a strictly positive integer")
def __init__(self,lea1,nTimes=2):
Lea.__init__(self)
self._lea1 = lea1
self._lea1Tuple = lea1.map(lambda v: (v,))
self._nTimes = nTimes
if nTimes <= 0:
raise Lea.Error("cprodTimes method requires a strictly positive integer")
def __init__(self,*iLeas):
Lea.__init__(self)
self._iLeas = tuple(iLeas)
# the following treatment is needed only if some clauses miss variables present
# in other clauses (e.g. CPT with context-specific independence)
# a rebalancing is needed if there are such missing variables and if these admit multiple
# values (total probability weight > 1)
aleaLeavesSet = frozenset(aleaLeaf for ilea in iLeas \
for aleaLeaf in ilea.getAleaLeavesSet() \
if aleaLeaf._count > 1 )
self._ctxClea = Clea(*aleaLeavesSet)
def __init__(self,lea1,condLea):
Lea.__init__(self)
self._lea1 = lea1
self._condLea = condLea
def __init__(self,*args):
Lea.__init__(self)
self._leaArgs = tuple(Lea.coerce(arg) for arg in args)
def __init__(self, *args):
Lea.__init__(self)
self._leaArgs = tuple(Lea.coerce(arg) for arg in args)
counts = tuple(leaArg.getAlea()._count for leaArg in self._leaArgs)
lcm = calcLCM(counts)
self._factors = tuple(lcm // count for count in counts)
def __init__(self,f,cleaArgs):
Lea.__init__(self)
self._f = f
self._cleaArgs = cleaArgs
def __init__(self,lea1,nbValues):
if nbValues <= 0:
raise Lea.Error("draw method requires a strictly positive integer")
Lea.__init__(self)
self._lea1 = lea1
self._nbValues = nbValues
