xopto.mcbase.mcrun module

class RunMinPacketsBase(min_packets: float, batch_size: int, selection: slice)

Bases: object

Object for running MC simulations until the desired number of packets is collected by the selected detector.

Parameters

• min_packets (int) – Minimum required number of packets.

• min_weight (float) – Minimum weight that needs to be collected by the detector.

• batch_size (int) – Number of packets to launch in a single simulation.

property batch_size: int

Number of packets processed / launched in one simulation run / batch.

property min_packets: int

The minimum number of packets that needs to be collected by the selected detector.

property n: int

The number of packets that were launched during the last call to the run() method.

process_batch(result: tuple) → Tuple[float, int, tuple]

Implement this method in a subclass. Return True if the batch is complete.

Parameters

result (tuple) – Result as returned by the Monte Carlo simulation.

Returns

• total_weight (float) – The total accumulated weight.

• num_packets (int) – The total number of packets accumulated after processing this batch.

• result (tuple) – Simulation result ready for the next Monte Carlo simulation.

run(mc_obj: xopto.mcbase.mcobject.McObject, min_packets: Optional[int] = None, out: Optional[tuple] = None, *args, **kwargs) → tuple

Repeat simulations in batches until the required minimum weight is collected by the selected detector and optionally the minimum number of packets is launched.

Parameters

• mc_obj (mcobject.McObject) – Simulator instance.

• min_packets (int) – Optional minimum number of packets to launch and simulate. If None (default), there is no restriction on te minimum number of packets that need to be simulated.

• out (tuple) – Output from the previous run of the simulator.

• *args (tuple) – Positional arguments passed to the simulator.

• **kwargs (dict) – Keyword arguments passed to the simulator.

Returns

result – Accumulated results as returned by the Mont Carlo simulator instance.

Return type

tuple

property selection: int

A slice / region or index of the detector that is used to compute the collected weight. If None (default), the entire detector contributes to the total weight.

property weight: float

The weight collected by the detector during the last call to the run() method.

class RunMinWeightBase(min_weight: float, batch_size: int, selection: Optional[slice] = None)

Bases: object

Base class for running MC simulations until the desired weight is collected by the selected detector.

Parameters

• min_weight (float) – Minimum weight that needs to be collected by the detector.

• batch_size (int) – Number of packets to launch in a single simulation.

property batch_size: int

Number of packets processed / launched in one simulation run / batch.

property min_weight: int

The minimum total weight that needs to be collected by the selected detector.

property n: int

The number of packets that were launched during the last call to the run() method.

process_batch(result: tuple) → Tuple[float, int, tuple]

Implement this method in a subclass. :param result: Result as returned by the Monte Carlo simulation. :type result: tuple

Returns

• total_weight (float) – The total accumulated weight.

• num_packets (int) – The total number of packets accumulated after processing this batch.

• result (tuple) – Simulation result ready for the next Monte Carlo simulation.

run(mc_obj: xopto.mcbase.mcobject.McObject, min_packets: Optional[int] = None, out: Optional[tuple] = None, *args, **kwargs) → tuple

Repeat simulations in batches until the required minimum weight is collected by the selected detector and optionally the minimum number of packets is launched.

Parameters

• mc_obj (mcobject.McObject) – Simulator instance.

• min_packets (int) – Optional minimum number of packets to launch and simulate. If None (default), there is no restriction on te minimum number of packets that need to be simulated.

• out (tuple) – Output from the previous run of the simulator.

• *args (tuple) – Positional arguments passed to the simulator.

• **kwargs (dict) – Keyword arguments passed to the simulator.

Returns

result – Accumulated results as returned by the Mont Carlo simulator instance.

Return type

tuple

property selection: int

A slice / region or index of the detector that is used to compute the collected weight. If None (default), the entire detector contributes to the total weight.

property weight: float

The weight collected by the detector during the last call to the run() method.