pygsti.protocols.freeformsim.ModelFreeformSimulator

class ModelFreeformSimulator(models)

Bases: FreeformDataSimulator

A base class for data simulators that utilize models (probably most of them!).

Holds a dictionary of models and provides basic functionality for computing probabilities, final states, and process matrices corresponding to circuits which make implementing compute_freeform_data() easier.

Parameters:

models (dict) – A dictionary whose keys are string labels and values are Model objects, specifying the models used to compute “simulated” data.

Methods

__init__(models)
apply(df)	Apply this data simulator to a data frame having a Circuit column.
apply_fn(series)
compute_circuit_probabilities(model, circuit)
compute_final_state(model, circuit[, ...])
compute_final_states(circuit[, ...])
compute_freeform_data(circuit)	Computes the simulated free-form data for a single circuit.
compute_probabilities(circuit[, ...])
compute_process_matrices(circuit[, ...])
compute_process_matrix(model, circuit[, ...])
run(edesign[, memlimit, comm])	Run this data simulator on an experiment design.

apply(df)

Apply this data simulator to a data frame having a Circuit column.

Parameters:

df (pandas.DataFrame) – The data frame to apply to.

Return type:

pandas.DataFrame

compute_freeform_data(circuit)

Computes the simulated free-form data for a single circuit.

Parameters:

circuit (Circuit) – The circuit to compute data for.

Return type:

dict

run(edesign, memlimit=None, comm=None)

Run this data simulator on an experiment design.

Parameters:

• edesign (ExperimentDesign) – The input experiment design.

• memlimit (int, optional) – A rough per-processor memory limit in bytes.

• comm (mpi4py.MPI.Comm, optional) – When not None, an MPI communicator used to run this data simulator in parallel.

Return type:

ProtocolData