rxmc.ias_pn_model.IsobaricAnalogPNXSModel#

class rxmc.ias_pn_model.IsobaricAnalogPNXSModel(U_p_coulomb: Callable[[float, tuple], complex], U_p_central: Callable[[float, tuple], complex], U_p_spin_orbit: Callable[[float, tuple], complex], U_n_central: Callable[[float, tuple], complex], U_n_spin_orbit: Callable[[float, tuple], complex], calculate_params: Callable[[Workspace, tuple], tuple], params: list = [], model_name: str = None)[source]#

Bases: PhysicalModel

A model that predicts the (p,n) IAS differential xs for a given reaction. This model requires five interaction potentials: - Proton Coulomb potential: U_p_coulomb - Proton central potential: U_p_central - Proton spin-orbit potential: U_p_spin_orbit - Neutron central potential: U_n_central - Neutron spin-orbit potential: U_n_spin_orbit

Each potential takes in an arbitrary tuple of params, which are calculated from the model parameters via the calculate_params function.

The calculate_params function should have the signature: (ws: jitr.xs.quasielastic_pn.Workspace, *params: tuple) -> tuple and return a tuple of five elements, each being a tuple of parameters to be passed to the corresponding potential function in the order listed above.

__init__(U_p_coulomb: Callable[[float, tuple], complex], U_p_central: Callable[[float, tuple], complex], U_p_spin_orbit: Callable[[float, tuple], complex], U_n_central: Callable[[float, tuple], complex], U_n_spin_orbit: Callable[[float, tuple], complex], calculate_params: Callable[[Workspace, tuple], tuple], params: list = [], model_name: str = None)[source]#
Parameters:

  • U_p_coulomb (callable) – f(r, args) -> complex — proton Coulomb potential.

  • U_p_central (callable) – f(r, args) -> complex — proton central potential.

  • U_p_spin_orbit (callable) – f(r, args) -> complex — proton spin-orbit potential.

  • U_n_central (callable) – f(r, args) -> complex — neutron central potential.

  • U_n_spin_orbit (callable) – f(r, args) -> complex — neutron spin-orbit potential.

  • calculate_params (callable) – f(workspace, *params) -> (args_p_coulomb, args_p_central, args_p_spin_orbit, args_n_central, args_n_spin_orbit) mapping model parameters to the argument tuples expected by each potential callable.

  • params (list of Parameter, optional) – Parameters of the model. Defaults to [].

  • model_name (str, optional) – Human-readable model name. Defaults to "IsobaricAnalogPNXSModel".

Methods

__init__(U_p_coulomb, U_p_central, ...[, ...])

evaluate(observation, *params)

Evaluate the model on the constraint angular grid.

visualizable_model_prediction(observation, ...)

Evaluate the model on the visualisation angular grid.
evaluate(observation: IsobaricAnalogPNObservation, *params: tuple) → ndarray[source]#

Evaluate the model on the constraint angular grid.

Parameters:

  • observation (IsobaricAnalogPNObservation) – Observation containing the pre-built workspace.

  • *params (float) – Physical-model parameter values, consumed by calculate_params.

Returns:

np.ndarray – Predicted (p,n) IAS differential cross section in b/sr on observation.constraint_workspace.angles.

visualizable_model_prediction(observation: IsobaricAnalogPNObservation, *params: tuple) → ndarray[source]#

Evaluate the model on the visualisation angular grid.

Parameters:

  • observation (IsobaricAnalogPNObservation) – Observation containing the pre-built workspace.

  • *params (float) – Physical-model parameter values, consumed by calculate_params.

Returns:

np.ndarray – Predicted (p,n) IAS differential cross section in b/sr on observation.visualization_workspace.angles.