def to_dict(self):
data = super().to_dict()
data["name"] = self.name
data["type"] = data.pop("type")
data["spectral_model"] = self.spectral_model.to_dict()
data["parameters"] = Parameters([self.rotation, self.tmax]).to_dict()
if self.apply_irf != self._apply_irf_default:
data["apply_irf"] = self.apply_irf
return data
def parameters(self):
return Parameters([self.a, self.y]) + self.m1.parameters
def __init__(self, m1, a=1, y=99):
self.m1 = m1
a = Parameter("a", a)
y = Parameter("y", y)
self.default_parameters = Parameters([a, y])
super().__init__(a=a, y=y)
def parameters(self):
return Parameters([self.norm
]) + self.m1.parameters + self.m2.parameters
def parameters(self):
return (Parameters([self.rotation, self.tmax]) +
self.spectral_model.parameters)
def parameters(self):
return (Parameters([self.rotation, self.tmax, self.bias]) +
self._intrinsic_spectral_model.parameters +
self._ebl.parameters)