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# Summary
Several of the most important figures up front.
### Model Violation 
The aggregate log-likelihood as a function of GST iterations''')
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ws.FitComparisonBarPlot(Ls, gssPerIter, mdlPerIter, 
                        effective_ds, objective, 'L')
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### Per-sequence Model Violation
And a histogram of the per-sequence goodness of fit values.''')
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k = -1 #iteration index
colorHistogramPlot = ws.ColorBoxPlot(
    objective, gssPerIter[k], effective_ds, mdlPerIter[k],
    linlg_pcntle=0.95, minProbClipForWeighting=mpc, typ='histogram')
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### Comparison of GST estimated gates to target gates: 
This table presents, for each of the gates, three different measures of distance or discrepancy from the GST estimate to the ideal target operation.  See text for more detail.''')
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ws.GatesVsTargetTable(mdl, target_model, cri)
