pygsti.protocols.vb

Volumetric Benchmarking Protocol objects

Classes

BenchmarkingDesign(depths, circuit_lists, ...)	Experiment design that holds benchmarking data.
ByDepthDesign(depths, circuit_lists[, ...])	Experiment design that holds circuits organized by depth.
ByDepthSummaryStatistics([depths, ...])	A protocol that computes summary statistics for data organized into by-depth circuit lists. :param depths: A sequence of the depths to compute summary statistics for or the special "all" value which means "all the depths in the data". If data being processed does not contain a given value in depths, it is just ignored. :type depths: list or "all", optional :param statistics_to_compute: A sequence of the statistic names to compute. Allowed names are: 'success_counts', 'total_counts', 'hamming_distance_counts', 'success_probabilities', 'polarization', 'adjusted_success_probabilities', 'two_q_gate_count', 'depth', 'idealout', 'circuit_index', and 'width'. :type statistics_to_compute: tuple, optional :param names_to_compute: A sequence of user-defined names for the statistics in statistics_to_compute. If None, then the statistic names themselves are used. These names are the column names produced by calling to_dataframe on this protocol's results, so can be useful to name the computed statistics differently from the statistic name itself to distinguish it from the same statistic run on other data, when you want to combine data frames generated from multiple ProtocolData objects. :type names_to_compute: tuple, optional :param custom_data_src: An alternate source of the data counts used to compute the desired summary statistics. Currently this can only be a SuccessFailModel. :type custom_data_src: SuccessFailModel, optional :param name: The name of this protocol, also used to (by default) name the results produced by this protocol. If None, the class name will be used. :type name: str, optional.
PeriodicMirrorCircuitDesign(pspec, depths, ...)	Experiment design for periodic mirror-circuit benchmarking.
SummaryStatistics(name)	A protocol that can construct "summary" quantities from raw data.
SummaryStatisticsResults(data, protocol_instance)	Summary statistics computed for a set of data.