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Merge branch 'beta'. To become version 0.9.3.
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Major updates are:
- RPE code updated and moved to a new sub-package, extras/rpe
- Adds support for qutrit reports & basis (but not a "good" basis yet)
- Fixes to logG-logT error generator so it's real (at least in cases of interest)
- comments carried through from data set files
- new meta-data tables at end of full and general reports.
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Erik Nielsen committed Feb 7, 2017
2 parents 0d057a1 + e08f414 commit 23470ec
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151 changes: 82 additions & 69 deletions jupyter_notebooks/Tutorials/00 Quick and easy GST.ipynb
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" Sum of Chi^2 = 1585.47 (1585 data params - 31 model params = expected mean of 1554; p-value = 0.283448)\n",
" Completed in 0.4s\n",
" 2*Delta(log(L)) = 1585.17\n",
" Iteration 7 took 0.5s\n",
" Iteration 7 took 0.4s\n",
" \n",
" Switching to ML objective (last iteration)\n",
" --- MLGST ---\n",
Expand All @@ -380,7 +380,7 @@
" 2*Delta(log(L)) = 1585.07\n",
" Final MLGST took 0.3s\n",
" \n",
"Iterative MLGST Total Time: 1.6s\n"
"Iterative MLGST Total Time: 1.5s\n"
]
}
],
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"text": [
" \n",
"--- Hessian Projector Optimization for gate CIs (L-BFGS-B) ---\n",
" 20s 0.0278965571\n",
" 25s 0.0276337997\n",
" 29s 0.0276079377\n",
" 34s 0.0275908344\n",
" 39s 0.0275853888\n",
" 43s 0.0275844496\n",
" 9s 0.0278965544\n",
" 13s 0.0276337987\n",
" 18s 0.0276079370\n",
" 22s 0.0275908338\n",
" 27s 0.0275853884\n",
" 32s 0.0275844490\n",
" The resulting min sqrt(sum(gateCIs**2)): 0.0275844\n",
"*** Generating tables ***\n",
" Iter 01 of 17 : Generating table: targetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 02 of 17 : Generating table: targetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 03 of 17 : Generating table: datasetOverviewTable (w/95% CIs) [0.0s]\n",
" Iter 04 of 17 : Generating table: bestGatesetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 05 of 17 : Generating table: bestGatesetSpamParametersTable (w/95% CIs) [0.0s]\n",
" Iter 06 of 17 : Generating table: bestGatesetGaugeOptParamsTable (w/95% CIs) [0.0s]\n",
" Iter 07 of 17 : Generating table: bestGatesetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 08 of 17 : Generating table: bestGatesetChoiTable (w/95% CIs) [0.2s]\n",
" Iter 09 of 17 : Generating table: bestGatesetDecompTable (w/95% CIs) [0.2s]\n",
" Iter 10 of 17 : Generating table: bestGatesetRotnAxisTable (w/95% CIs) [0.3s]\n",
" Iter 11 of 17 : Generating table: bestGatesetVsTargetTable (w/95% CIs) [1.3s]\n",
" Iter 12 of 17 : Generating table: bestGatesetErrorGenTable (w/95% CIs) [0.0s]\n",
" Iter 13 of 17 : Generating table: fiducialListTable (w/95% CIs) [0.0s]\n",
" Iter 14 of 17 : Generating table: prepStrListTable (w/95% CIs) [0.0s]\n",
" Iter 15 of 17 : Generating table: effectStrListTable (w/95% CIs) [0.0s]\n",
" Iter 16 of 17 : Generating table: germListTable (w/95% CIs) [0.0s]\n",
" Iter 17 of 17 : Generating table: progressTable (w/95% CIs) [0.2s]\n",
" Iter 01 of 19 : Generating table: targetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 02 of 19 : Generating table: targetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 03 of 19 : Generating table: datasetOverviewTable (w/95% CIs) [0.0s]\n",
" Iter 04 of 19 : Generating table: bestGatesetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 05 of 19 : Generating table: bestGatesetSpamParametersTable (w/95% CIs) [0.0s]\n",
" Iter 06 of 19 : Generating table: bestGatesetGaugeOptParamsTable (w/95% CIs) [0.0s]\n",
" Iter 07 of 19 : Generating table: bestGatesetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 08 of 19 : Generating table: bestGatesetChoiTable (w/95% CIs) [0.2s]\n",
" Iter 09 of 19 : Generating table: bestGatesetDecompTable (w/95% CIs) [0.2s]\n",
" Iter 10 of 19 : Generating table: bestGatesetRotnAxisTable (w/95% CIs) [0.3s]\n",
" Iter 11 of 19 : Generating table: bestGatesetVsTargetTable (w/95% CIs) [1.2s]\n",
" Iter 12 of 19 : Generating table: bestGatesetErrorGenTable (w/95% CIs) [0.0s]\n",
" Iter 13 of 19 : Generating table: metadataTable (w/95% CIs) Generating table: metadataTable [0.0s]\n",
" Iter 14 of 19 : Generating table: softwareEnvTable (w/95% CIs) Generating table: softwareEnvTable [0.2s]\n",
" Iter 15 of 19 : Generating table: fiducialListTable (w/95% CIs) [0.0s]\n",
" Iter 16 of 19 : Generating table: prepStrListTable (w/95% CIs) [0.0s]\n",
" Iter 17 of 19 : Generating table: effectStrListTable (w/95% CIs) [0.0s]\n",
" Iter 18 of 19 : Generating table: germListTable (w/95% CIs) [0.0s]\n",
" Iter 19 of 19 : Generating table: progressTable (w/95% CIs) [0.2s]\n",
"*** Generating plots ***\n",
"LogL plots (2): \n",
" Iter 1 of 3 : Generating figure: colorBoxPlotKeyPlot (w/95% CIs) Generating figure: colorBoxPlotKeyPlot [0.9s]\n",
" Iter 1 of 3 : Generating figure: colorBoxPlotKeyPlot (w/95% CIs) Generating figure: colorBoxPlotKeyPlot [0.8s]\n",
" Iter 2 of 3 : Generating figure: bestEstimateColorBoxPlot (w/95% CIs) Generating figure: bestEstimateColorBoxPlot [9.6s]\n",
" Iter 3 of 3 : Generating figure: invertedBestEstimateColorBoxPlot (w/95% CIs) Generating figure: invertedBestEstimateColorBoxPlot [9.4s]\n",
" Iter 3 of 3 : Generating figure: invertedBestEstimateColorBoxPlot (w/95% CIs) Generating figure: invertedBestEstimateColorBoxPlot [9.2s]\n",
"\n",
"*** Merging into template file ***\n",
"Latex file(s) successfully generated. Attempting to compile with pdflatex...\n",
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" Sum of Chi^2 = 1572.66 (1585 data params - 31 model params = expected mean of 1554; p-value = 0.364955)\n",
" Completed in 0.3s\n",
" 2*Delta(log(L)) = 1572.68\n",
" Iteration 7 took 0.3s\n",
" Iteration 7 took 0.4s\n",
" \n",
" Switching to ML objective (last iteration)\n",
" --- MLGST ---\n",
Expand All @@ -883,31 +885,33 @@
" 2*Delta(log(L)) = 1572.68\n",
" Final MLGST took 0.2s\n",
" \n",
"Iterative MLGST Total Time: 1.4s\n",
"Iterative MLGST Total Time: 1.3s\n",
" \n",
"--- Hessian Projector Optimization for gate CIs (L-BFGS-B) ---\n",
" 117s 0.0008805702\n",
" 121s 0.0008720898\n",
" 126s 0.0008712749\n",
" 9s 0.0008805701\n",
" 13s 0.0008720898\n",
" 18s 0.0008712748\n",
" The resulting min sqrt(sum(gateCIs**2)): 0.000871275\n",
"*** Generating tables ***\n",
" Iter 01 of 17 : Generating table: targetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 02 of 17 : Generating table: targetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 03 of 17 : Generating table: datasetOverviewTable (w/95% CIs) [0.0s]\n",
" Iter 04 of 17 : Generating table: bestGatesetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 05 of 17 : Generating table: bestGatesetSpamParametersTable (w/95% CIs) [0.0s]\n",
" Iter 06 of 17 : Generating table: bestGatesetGaugeOptParamsTable (w/95% CIs) [0.0s]\n",
" Iter 07 of 17 : Generating table: bestGatesetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 08 of 17 : Generating table: bestGatesetChoiTable (w/95% CIs) [0.2s]\n",
" Iter 09 of 17 : Generating table: bestGatesetDecompTable (w/95% CIs) [0.2s]\n",
" Iter 10 of 17 : Generating table: bestGatesetRotnAxisTable (w/95% CIs) [0.3s]\n",
" Iter 11 of 17 : Generating table: bestGatesetVsTargetTable (w/95% CIs) [1.2s]\n",
" Iter 12 of 17 : Generating table: bestGatesetErrorGenTable (w/95% CIs) [0.0s]\n",
" Iter 13 of 17 : Generating table: fiducialListTable (w/95% CIs) [0.0s]\n",
" Iter 14 of 17 : Generating table: prepStrListTable (w/95% CIs) [0.0s]\n",
" Iter 15 of 17 : Generating table: effectStrListTable (w/95% CIs) [0.0s]\n",
" Iter 16 of 17 : Generating table: germListTable (w/95% CIs) [0.0s]\n",
" Iter 17 of 17 : Generating table: progressTable (w/95% CIs) [0.2s]\n",
" Iter 01 of 19 : Generating table: targetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 02 of 19 : Generating table: targetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 03 of 19 : Generating table: datasetOverviewTable (w/95% CIs) [0.0s]\n",
" Iter 04 of 19 : Generating table: bestGatesetSpamTable (w/95% CIs) [0.0s]\n",
" Iter 05 of 19 : Generating table: bestGatesetSpamParametersTable (w/95% CIs) [0.0s]\n",
" Iter 06 of 19 : Generating table: bestGatesetGaugeOptParamsTable (w/95% CIs) [0.0s]\n",
" Iter 07 of 19 : Generating table: bestGatesetGatesTable (w/95% CIs) [0.0s]\n",
" Iter 08 of 19 : Generating table: bestGatesetChoiTable (w/95% CIs) [0.2s]\n",
" Iter 09 of 19 : Generating table: bestGatesetDecompTable (w/95% CIs) [0.2s]\n",
" Iter 10 of 19 : Generating table: bestGatesetRotnAxisTable (w/95% CIs) [0.3s]\n",
" Iter 11 of 19 : Generating table: bestGatesetVsTargetTable (w/95% CIs) [1.1s]\n",
" Iter 12 of 19 : Generating table: bestGatesetErrorGenTable (w/95% CIs) [0.0s]\n",
" Iter 13 of 19 : Generating table: metadataTable (w/95% CIs) Generating table: metadataTable [0.0s]\n",
" Iter 14 of 19 : Generating table: softwareEnvTable (w/95% CIs) Generating table: softwareEnvTable [0.0s]\n",
" Iter 15 of 19 : Generating table: fiducialListTable (w/95% CIs) [0.0s]\n",
" Iter 16 of 19 : Generating table: prepStrListTable (w/95% CIs) [0.0s]\n",
" Iter 17 of 19 : Generating table: effectStrListTable (w/95% CIs) [0.0s]\n",
" Iter 18 of 19 : Generating table: germListTable (w/95% CIs) [0.0s]\n",
" Iter 19 of 19 : Generating table: progressTable (w/95% CIs) [0.2s]\n",
"*** Generating plots ***\n",
"LogL plots (2): \n",
" Iter 1 of 3 : Generating figure: colorBoxPlotKeyPlot (w/95% CIs) Generating figure: colorBoxPlotKeyPlot [0.7s]\n",
Expand Down Expand Up @@ -959,21 +963,21 @@
"\n",
" .gatesets -- a dictionary of GateSet objects w/keys:\n",
" ---------------------------------------------------------\n",
" final estimate\n",
" target\n",
" final estimate\n",
" iteration estimates pre gauge opt\n",
" iteration estimates\n",
" seed\n",
" iteration estimates\n",
"\n",
" .gatestring_lists -- a dict of GateString lists w/keys:\n",
" ---------------------------------------------------------\n",
" effect fiducials\n",
" final\n",
" iteration\n",
" iteration delta\n",
" iteration\n",
" all\n",
" germs\n",
" prep fiducials\n",
" effect fiducials\n",
"\n",
" .tables -- a dict of ReportTable objects w/keys:\n",
" ---------------------------------------------------------\n",
Expand Down Expand Up @@ -1017,6 +1021,8 @@
" bestGatesetChoiEvalTable\n",
" hamiltonianProjectorTable\n",
" stochasticProjectorTable\n",
" metadataTable\n",
" softwareEnvTable\n",
"\n",
" .figures -- a dict of ReportFigure objects w/keys:\n",
" ---------------------------------------------------------\n",
Expand Down Expand Up @@ -1053,30 +1059,37 @@
" bestEstimatePolarGiEvalPlot\n",
" bestEstimatePolarGxEvalPlot\n",
" bestEstimatePolarGyEvalPlot\n",
" pauliProdHamiltonianDecompBoxesGi\n",
" pauliProdHamiltonianDecompBoxesGx\n",
" pauliProdHamiltonianDecompBoxesGy\n",
"\n",
" .parameters -- a dict of simulation parameters:\n",
" ---------------------------------------------------------\n",
" minProbClipForWeighting\n",
" defaultBasename\n",
" memLimit\n",
" distributeMethod\n",
" check\n",
" cptpPenaltyFactor\n",
" profiler\n",
" L,germ tuple base string dict\n",
" probClipInterval\n",
" max length list\n",
" linlogPercentile\n",
" objective\n",
" useFreqWeightedChiSq\n",
" starting point\n",
" maxIterations\n",
" defaultDirectory\n",
" gaugeOptParams\n",
" radius\n",
" minProbClipForWeighting\n",
" profile\n",
" objective\n",
" truncScheme\n",
" minProbClip\n",
" fiducial pairs\n",
" gaugeOptParams\n",
" depolarizeStart\n",
" profiler\n",
" defaultBasename\n",
" memLimit\n",
" linlogPercentile\n",
" nestedGateStringLists\n",
" contractStartToCPTP\n",
" tolerance\n",
" hessianProjection\n",
" max length list\n",
" distributeMethod\n",
" L,germ tuple base string dict\n",
" weights\n",
" minProbClip\n",
" probClipInterval\n",
"\n",
" .options -- a container of display options:\n",
" ---------------------------------------------------------\n",
Expand Down Expand Up @@ -1106,7 +1119,7 @@
},
{
"cell_type": "code",
"execution_count": 22,
"execution_count": null,
"metadata": {
"collapsed": true
},
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4 changes: 2 additions & 2 deletions jupyter_notebooks/Tutorials/01 GateSets.ipynb
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"\n",
"Probability of 'plus' spam label of gate string GxGx = 0.9049999999999999\n",
"Probability of 'minus' spam label of gate string GxGx = 0.09499999999999997\n",
"Probabilities as a dict = {'plus': 0.9049999999999999, 'minus': 0.09499999999999997}\n"
"Probabilities as a dict = {'minus': 0.09499999999999997, 'plus': 0.9049999999999999}\n"
]
}
],
Expand Down Expand Up @@ -507,7 +507,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": null,
"metadata": {
"collapsed": true
},
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4 changes: 2 additions & 2 deletions jupyter_notebooks/Tutorials/02 Gatestring lists.ipynb
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Expand Up @@ -415,8 +415,8 @@
"name": "stdout",
"output_type": "stream",
"text": [
"10 eLGST sets w/lengths <map object at 0x10a23aa90>\n",
"10 LSGST sets w/lengths <map object at 0x10a284588>\n",
"10 eLGST sets w/lengths <map object at 0x10a2329e8>\n",
"10 LSGST sets w/lengths <map object at 0x10a262f98>\n",
"\n",
"First 20 items for dataset generation in label : string format\n",
"{} : ()\n",
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24 changes: 12 additions & 12 deletions jupyter_notebooks/Tutorials/03 DataSets.ipynb
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Expand Up @@ -164,23 +164,23 @@
"output_type": "stream",
"text": [
"Dataset1:\n",
" Gx : {'minus': 85.0, 'plus': 15.0}\n",
"GxGy : {'minus': 55.0, 'plus': 45.0}\n",
"Gy : {'minus': 90.0, 'plus': 10.0}\n",
" Gx : {'plus': 15.0, 'minus': 85.0}\n",
"GxGy : {'plus': 45.0, 'minus': 55.0}\n",
"Gy : {'plus': 10.0, 'minus': 90.0}\n",
"\n",
"\n",
"Dataset2:\n",
" {} : {'minus': 100.0, 'plus': 0.0}\n",
"Gx : {'minus': 80.0, 'plus': 10.0}\n",
"GxGy : {'minus': 20.0, 'plus': 40.0}\n",
"GxGxGxGx : {'minus': 70.0, 'plus': 20.0}\n",
" {} : {'plus': 0.0, 'minus': 100.0}\n",
"Gx : {'plus': 10.0, 'minus': 80.0}\n",
"GxGy : {'plus': 40.0, 'minus': 20.0}\n",
"GxGxGxGx : {'plus': 20.0, 'minus': 70.0}\n",
"\n",
"\n",
"Dataset3 is too big to print, so here it is truncated to Dataset2's strings\n",
" {} : {'minus': 1000.0, 'plus': 0.0}\n",
"Gx : {'minus': 501.0, 'plus': 499.0}\n",
"GxGy : {'minus': 504.0, 'plus': 496.0}\n",
"GxGxGxGx : {'minus': 829.0, 'plus': 171.0}\n",
" {} : {'plus': 0.0, 'minus': 1000.0}\n",
"Gx : {'plus': 499.0, 'minus': 501.0}\n",
"GxGy : {'plus': 496.0, 'minus': 504.0}\n",
"GxGxGxGx : {'plus': 171.0, 'minus': 829.0}\n",
"\n",
"\n"
]
Expand Down Expand Up @@ -254,7 +254,7 @@
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"metadata": {
"collapsed": true
},
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