pygsti.extras.rb.benchmarker
Encapsulates RB results and dataset objects
Module Contents
Classes
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- class pygsti.extras.rb.benchmarker.Benchmarker(specs, ds=None, summary_data=None, predicted_summary_data=None, dstype='standard', success_outcome='success', success_key='target', dscomparator=None)
Bases:
object
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dstype : (‘success-fail’, ‘standard’)
specs: dictionary of (name, RBSpec) key-value pairs. The names are arbitrary
- select_volumetric_benchmark_regions(depths, boundary, widths='all', datatype='success_probabilities', statistic='mean', merit='aboveboundary', specs=None, aggregate=True, passnum=None, rescaler='auto')
- volumetric_benchmark_data(depths, widths='all', datatype='success_probabilities', statistic='mean', specs=None, aggregate=True, rescaler='auto')
- flattened_data(specs=None, aggregate=True)
- test_pass_stability(formatdata=False, verbosity=1)
- generate_success_or_fail_dataset(overwrite=False)
- summary_data(datatype, specindex, qubits=None)
- create_summary_data(predictions=None, verbosity=2, auxtypes=None)
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- analyze(specindices=None, analysis='adjusted', bootstraps=200, verbosity=1)
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todo: this partly ignores specindices
- filter_experiments(numqubits=None, containqubits=None, onqubits=None, sampler=None, two_qubit_gate_prob=None, prefilter=None, benchmarktype=None)
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