def helper(self, *args, **kwargs): if any(needsSampling(arg) for arg in itertools.chain(args, kwargs.values())): return VectorMethodDistribution(method, self, args, kwargs) elif any(needsLazyEvaluation(arg) for arg in itertools.chain(args, kwargs.values())): # see analogous comment in distributionFunction return makeDelayedFunctionCall(helper, (self,) + args, kwargs) else: return method(self, *args, **kwargs)
def handler2(self, *args):
if needsSampling(self):
return VectorOperatorDistribution(op, self, args)
elif any(needsSampling(arg) for arg in args):
return VectorMethodDistribution(method, self, args, {})
elif any(needsLazyEvaluation(arg) for arg in args):
# see analogous comment in distributionFunction
return makeDelayedFunctionCall(handler2, args, {})
else:
return method(self, *args)
def helper(*args):
if needsSampling(instance):
return VectorOperatorDistribution(op, instance, args)
elif any(needsSampling(arg) for arg in args):
return VectorMethodDistribution(method, instance, args, {})
elif any(needsLazyEvaluation(arg) for arg in args):
# see analogous comment in distributionFunction
return makeDelayedFunctionCall(helper, args, {})
else:
return wrapped(*args)
def helper(*args, **kwargs):
args = tuple(toDistribution(arg) for arg in args)
kwargs = { name: toDistribution(arg) for name, arg in kwargs.items() }
if any(needsSampling(arg) for arg in itertools.chain(args, kwargs.values())):
return MethodDistribution(method, instance, args, kwargs)
elif any(needsLazyEvaluation(arg)
for arg in itertools.chain(args, kwargs.values())):
# see analogous comment in distributionFunction
return makeDelayedFunctionCall(helper, args, kwargs)
else:
return wrapped(*args, **kwargs)
def helper(*args, **kwargs):
args = tuple(toDistribution(arg) for arg in args)
kwargs = { name: toDistribution(arg) for name, arg in kwargs.items() }
if any(needsSampling(arg) for arg in itertools.chain(args, kwargs.values())):
return FunctionDistribution(wrapped, args, kwargs, support, valueType)
elif any(needsLazyEvaluation(arg)
for arg in itertools.chain(args, kwargs.values())):
# recursively call this helper (not the original function), since the
# delayed arguments may evaluate to distributions, in which case we'll
# have to make a FunctionDistribution
return makeDelayedFunctionCall(helper, args, kwargs)
else:
return wrapped(*args, **kwargs)
