deltakit.decode.noise_sources.UniformMatchingNoise

class deltakit.decode.noise_sources.UniformMatchingNoise(basic_error_prob: float, edge_filter: Callable[[HyperMultiGraph], Sequence[EdgeT]] | None = None)

Bases: IndependentMatchingNoise

A noise model that defines noise over a single decoding graph, where all decoding edges are assigned a uniform weight and sampled randomly with given probability.

Methods

UniformMatchingNoise.as_exhaustive_sequential_model	Return the equivalent exhaustive model for this noise model.
UniformMatchingNoise.build_batch_error_generator	Given some representation of a code, return a generator of batches of errors for that code.
UniformMatchingNoise.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.
UniformMatchingNoise.empty_filter	Filter that does not change the input.
UniformMatchingNoise.error_generator	Given some representation of a code, return a generator of errors for that code.
UniformMatchingNoise.field_values	Return the values of data that characterises this noise model.
UniformMatchingNoise.get_rng	Return a numpy random number generator, using the member data seed.
UniformMatchingNoise.importance_sampling_decomposition	Expresses the independent error distribution as a statistical mixture of other error distributions.
UniformMatchingNoise.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.