pygsti.report.focused_mc2gst_gatesets¶
-
pygsti.report.
focused_mc2gst_gatesets
(gateStrings, dataset, specs, startGateset, minProbClipForWeighting=0.0001, probClipInterval=(-1000000.0, 1000000.0), verbosity=0)¶ Constructs a dictionary with keys == gate strings and values == Focused-LSGST GateSets.
Parameters: - gateStrings (list of GateString or tuple objects) – The gate strings to estimate using LSGST. The elements of this list are the keys of the returned dictionary.
- dataset (DataSet) – The data to use for all LGST and LSGST estimates.
- specs (2-tuple) – A (prepSpecs,effectSpecs) tuple usually generated by calling build_spam_specs(...)
- startGateset (GateSet) – The gate set to seed LSGST with. Often times obtained via LGST.
- minProbClipForWeighting (float, optional) – defines the clipping interval for the statistical weight used within the chi^2 function (see chi2fn).
- probClipInterval (2-tuple, optional) – (min,max) to clip probabilities to within GateSet probability computation routines (see GateSet.bulk_fill_probs)
- verbosity (int, optional) – Verbosity value to send to do_mc2gst(...) call.
Returns: A dictionary that relates each gate string of gateStrings to a GateSet containing the LSGST estimate of that gate string stored under the gate label “GsigmaLbl”.
Return type: dict