def WeightedSumSq(weights, inputs=None, *args, **kwargs):
weights = stdvector(weights)
if inputs is None:
inputs = weights
elif isinstance(inputs[0], str):
inputs = stdvector(inputs)
else:
inputs = OutputDescriptors(inputs)
return R.GNA.GNAObjectTemplates.WeightedSumSqT(
context.current_precision())(weights, inputs, *args, **kwargs)
def Dummy(shape, name, varnames=None, *args, **kwargs):
if varnames:
return R.GNA.GNAObjectTemplates.DummyT(context.current_precision())(
shape, name, stdvector(varnames), *args, **kwargs)
return R.GNA.GNAObjectTemplates.DummyT(context.current_precision())(
shape, name, *args, **kwargs)
def OscProb3(*args, **kwargs):
"""OscProb3 wrapper
Aguments:
Neutrino from,
Neutrino to,
std::string l_name="L",
bool modecos=true,
std::vector<std::string> dmnames={}
"""
if len(args) >= 5:
args = list(args)
args[4] = stdvector(args[4])
return R.GNA.GNAObjectTemplates.OscProb3T(context.current_precision())(
*args, **kwargs)
def OutputDescriptors(outputs):
descriptors = []
odescr = R.OutputDescriptorT(context.current_precision(),
context.current_precision())
ohandle = R.TransformationTypes.OutputHandleT(context.current_precision())
singleoutput = R.SingleOutputT(context.current_precision())
for output in outputs:
if isinstance(output, odescr):
append = output
elif isinstance(output, ohandle):
append = odescr(output)
elif isinstance(output, singleoutput):
append = odescr(output.single())
else:
raise Exception('Expect OutputHandle or SingleOutput object')
descriptors.append(append)
return stdvector(
descriptors, 'OutputDescriptorT<%s,%s>' %
(context.current_precision(), context.current_precision()))
def VarProduct(varnames, *args, **kwargs):
return R.GNA.GNAObjectTemplates.VarProductT(context.current_precision())(
stdvector(varnames), *args, **kwargs)
def VarArrayPreallocated(vars, *args, **kwargs):
cls = R.GNA.GNAObjectTemplates.VarArrayPreallocatedT(
context.current_precision())
ret = cls(stdvector(vars), *args, **kwargs)
return ret
def VarArray(vars, *args, **kwargs):
cls = R.GNA.GNAObjectTemplates.VarArrayT(context.current_precision())
ret = cls(stdvector(vars), *args, **kwargs)
ret.transformations.front().updateTypes()
return ret
def EnergyResolution(weights, *args, **kwargs):
return R.EnergyResolution(stdvector(weights), *args, **kwargs)
def PolyRatio(nominator=[], denominator=[], *args, **kwargs):
nominator = stdvector(nominator, 'string')
denominator = stdvector(denominator, 'string')
return R.GNA.GNAObjectTemplates.PolyRatioT(context.current_precision())(
nominator, denominator, *args, **kwargs)