deltakit.decode.noise_sources.MonteCarloNoise

class deltakit.decode.noise_sources.MonteCarloNoise

Bases: _NoiseModel[CodeT, ErrorT]

Abstract class to manage the production of non-terminating independent noise generators.

Methods

MonteCarloNoise.as_exhaustive_sequential_model	Return the equivalent exhaustive model for this noise model.
MonteCarloNoise.build_batch_error_generator	Given some representation of a code, return a generator of batches of errors for that code.
MonteCarloNoise.build_split_batch_error_generators	Given some representation of a code, return num_splits number of batch generators of errors for that code and the respective sizes for those generators.
MonteCarloNoise.error_generator	Given some representation of a code, return a generator of errors for that code.
MonteCarloNoise.field_values	Return the values of data that characterises this noise model.
MonteCarloNoise.get_rng	Return a numpy random number generator, using the member data seed.
MonteCarloNoise.importance_sampling_decomposition	Expresses the independent error distribution as a statistical mixture of other error distributions.
MonteCarloNoise.split_error_generator	Given some representation of a code, return num_splits number of generators of errors for that code and the respective sizes for those generators.