pygsti.report.construct_standard_report

pygsti.report.construct_standard_report#

construct_standard_report(results, title='auto', confidence_level=None, comm=None, ws=None, advanced_options=None, verbosity=1)#

Create a “standard” GST report, containing details about each estimate in results individually.

Parameters:

  • results (Results) – An object which represents the set of results from one or more GST estimation runs, typically obtained from running run_long_sequence_gst() or run_stdpractice_gst(), OR a dictionary of such objects, representing multiple GST runs to be compared (typically all with different data sets). The keys of this dictionary are used to label different data sets that are selectable in the report.

  • title (string, optional) – The title of the report. “auto” causes a random title to be generated (which you may or may not like).

  • confidence_level (int, optional) – If not None, then the confidence level (between 0 and 100) used in the computation of confidence regions/intervals. If None, no confidence regions or intervals are computed.

  • comm (mpi4py.MPI.Comm, optional) – When not None, an MPI communicator for distributing the computation across multiple processors.

  • ws (Workspace, optional) – The workspace used as a scratch space for performing the calculations and visualizations required for this report. If you’re creating multiple reports with similar tables, plots, etc., it may boost performance to use a single Workspace for all the report generation.

  • advanced_options (dict, optional) –

    A dictionary of advanced options for which the default values are usually are fine. Here are the possible keys of advanced_options:

    • linlogPercentilefloat, optional

      Specifies the colorscale transition point for any logL or chi2 color box plots. The lower (100 - linlogPercentile) percentile of the expected chi2 distribution is shown in a linear grayscale, and the top linlogPercentile is shown on a logarithmic colored scale.

    • nmthresholdfloat, optional

      The threshold, in units of standard deviations, that triggers the usage of non-Markovian error bars. If None, then non-Markovian error bars are never computed.

    • embed_figures: bool, optional

      Whether figures should be embedded in the generated report.

    • combine_robustbool, optional

      Whether robust estimates should automatically be combined with their non-robust counterpart when displayed in reports. (default is True).

    • idt_basis_dictstuple, optional

      Tuple of (prepDict,measDict) pauli-basis dictionaries, which map between 1-qubit Pauli basis strings (e.g. ‘-X’ or ‘Y’) and tuples of gate names (e.g. (‘Gx’,’Gx’)). If given, idle tomography will be performed on the ‘Gi’ gate and included in the report.

    • idt_idle_oplabelLabel, optional

      The label identifying the idle gate (for use with idle tomography).

    • skip_sectionstuple[str], optional

      Contains names of standard report sections that should be skipped in this particular report. Strings will be cast to lowercase, stripped of white space, and then mapped to omitted Section classes as follows

      {

      ‘summary’ : SummarySection, ‘goodness’ : GoodnessSection, ‘colorbox’ : GoodnessColorBoxPlotSection, ‘invariantgates’ : GaugeInvariantsGatesSection, ‘invariantgerms’ : GaugeInvariantsGermsSection, ‘variant’ : GaugeVariantSection, ‘variantraw’ : GaugeVariantsRawSection, ‘variantdecomp’ : GaugeVariantsDecompSection, ‘varianterrorgen’ : GaugeVariantsErrorGenSection, ‘input’ : InputSection, ‘meta’ : MetaSection, ‘help’ : HelpSection

      }

      A KeyError will be raised if skip_sections contains a string that is not in the keys of the above dict (after casting to lower case and stripping white space).

  • verbosity (int, optional) – How much detail to send to stdout.

Return type:

Report