As noted in Tutorial 00, pygsti can provide many reports or presentation slides.
In this tutorial, we look at how to customize some of the output of pygsti's report generating module.
#Import the GST module -- you probably want this at the beginning of every notebook
import pygsti
import json
Creating reports is a method of the pygsti.report.Results object. Below, we create such an object, and then initialize it with the appropriate fiducials, germs, maximum lengths, etc.
It's important to note that the pygsti.report.Results object requires an argument to indicate which objective function you wish to score the estimate using. It's recommended that, if you ran MC2GST, you use the "chi2" argument, while if you ran MLGST, you use "logL". Otherwise, you will score your estimate based on an objective function you weren't optimizing over, so your scores may be rather weird!
Creating reports is a method of the pygsti.report.Results object. Below, we create such an object, and then initialize it with the appropriate fiducials, germs, maximum lengths, etc.
It's important to note that the pygsti.report.Results object requires an argument to indicate which objective function you wish to score the estimate using. It's recommended that, if you ran MC2GST, you use the "chi2" argument, while if you ran MLGST, you use "logL". Otherwise, you will score your estimate based on an objective function you weren't optimizing over, so your scores may be rather weird!
First, we'll make smaller reports that don't contain any confidence intervals for the estimates, nor any appendices.
NOTE: In order for you to create PowerPoint files, you'll have to have python-pptx installed on your system.
# Follow Algorithm tutorial to generate LSGST gatesets
gs_target = pygsti.io.load_gateset("tutorial_files/Example_Gateset.txt")
gs_target.set_basis("gm",2)
ds = pygsti.io.load_dataset("tutorial_files/Example_Dataset.txt", cache=True)
fiducialList = pygsti.io.load_gatestring_list("tutorial_files/Example_FiducialList.txt")
#Run LGST to get an initial estimate for the gates in gs_target based on the data in ds
specs = pygsti.construction.build_spam_specs(fiducialGateStrings=fiducialList)
gs_lgst = pygsti.do_lgst(ds, specs, targetGateset=gs_target, svdTruncateTo=4, verbosity=1)
#Gauge optimize the result to match the target gateset
gs_lgst_after_gauge_opt = pygsti.optimize_gauge(gs_lgst, "target", targetGateset=gs_target)
#Contract the result to CPTP
gs_clgst = pygsti.contract(gs_lgst_after_gauge_opt, "CPTP")
#Get lists of gate strings for successive iterations of MC2GST to use
specs = pygsti.construction.build_spam_specs(fiducialGateStrings=fiducialList)
germList = pygsti.io.load_gatestring_list("tutorial_files/Example_GermsList.txt")
maxLengthList = json.load(open("tutorial_files/Example_maxLengths.json","r"))
lsgstListOfLists = [ pygsti.io.load_gatestring_list("tutorial_files/Example_LSGSTlist%d.txt" % l) for l in maxLengthList]
gs_lsgst_list = pygsti.do_iterative_mc2gst(ds, gs_clgst, lsgstListOfLists, verbosity=2,
minProbClipForWeighting=1e-6, probClipInterval=(-1e6,1e6),
returnAll=True )
go_gatesets = [ pygsti.optimize_gauge(gs, "target", targetGateset=gs_target, gateWeight=1, spamWeight=0.001) for gs in gs_lsgst_list]
res = pygsti.report.Results()
res.init_Ls_and_germs("chi2", gs_target, ds, gs_clgst, maxLengthList, germList,
go_gatesets, lsgstListOfLists, fiducialList, fiducialList,
pygsti.construction.repeat_with_max_length, False)
#Make smaller reports (no confidence intervals or appendicies)
res.create_full_report_pdf(filename="tutorial_files/Example_reportB.pdf", verbosity=2, confidenceLevel=None,
debugAidsAppendix=False, gaugeOptAppendix=False,
pixelPlotAppendix=False, whackamoleAppendix=False)
res.create_brief_report_pdf(filename="tutorial_files/Example_briefB.pdf", verbosity=2, confidenceLevel=None)
res.create_presentation_pdf(filename="tutorial_files/Example_slidesB.pdf", verbosity=2, confidenceLevel=None,
debugAidsAppendix=False, pixelPlotAppendix=False, whackamoleAppendix=False)
res.create_presentation_ppt(filename="tutorial_files/Example_slidesB.ppt", verbosity=2, confidenceLevel=None,
debugAidsAppendix=False, pixelPlotAppendix=False, whackamoleAppendix=False)
res.create_full_report_pdf(filename="tutorial_files/Example_report.pdf", verbosity=2, confidenceLevel=95,
debugAidsAppendix=True, gaugeOptAppendix=True,
pixelPlotAppendix=True, whackamoleAppendix=True)
res.create_brief_report_pdf(filename="tutorial_files/Example_brief.pdf", verbosity=2, confidenceLevel=95)
res.create_presentation_pdf(filename="tutorial_files/Example_slides.pdf", verbosity=2, confidenceLevel=95,
debugAidsAppendix=True, pixelPlotAppendix=True, whackamoleAppendix=True)
res.create_presentation_ppt(filename="tutorial_files/Example_slides.ppt", verbosity=2, confidenceLevel=95,
debugAidsAppendix=True, pixelPlotAppendix=True, whackamoleAppendix=True)
import pygsti.report.latex as LU
reload(LU)
LU.latex_value(1.2e30,2)