def customReporting(sciBTest, mResults):
# This gets called immediately post the models being run.
# First set up overall analysis images
modelplots.plotOverAllRuns(mResults, 'Vrms', depName='Time',
path=sciBTest.outputPathBase)
import plotCpuTimesAllRuns as plotCpus
plotCpus.plotAllRuns(sciBTest.outputPathBase)
sciBTest.mSuite.analysisImages = ["Vrms-multiRunTimeSeries.png",
'cpuTimePerStep.png']
# Now specific per-run images
fStep = mResults[0].freqOutput.finalStep()
dEvery = sciBTest.mSuite.runs[0].simParams.dumpevery
lastImgStep = fStep / dEvery * dEvery
vrmsPeakTime = sciBTest.testComps[0]['VRMS of first diapir'].actualTime
vrmsPeakStep = mResults[0].freqOutput.getClosest('Time', vrmsPeakTime)[1]
vrmsPeakImgStep = int(round(vrmsPeakStep / float(dEvery))) * dEvery
vrmsPeakImgStep = min([vrmsPeakImgStep, lastImgStep])
# Create an empty list of images to display
sciBTest.mSuite.modelImagesToDisplay = [[] for runI in \
range(len(sciBTest.mSuite.runs))]
# Choose which model timestep images to display:- note that here we're
# programmatically choosing to show the Peak VRMS timestep.
sciBTest.mSuite.modelImagesToDisplay[0] = [
(10, "initial state"),
(120, ""),
(vrmsPeakImgStep, "near first VRMS peak at t=%f" % vrmsPeakTime),
(lastImgStep, "")]
# Here we just ask the CREDO reporting API to get Report Generators for
# PDF (ReportLab) and RST (Restructured Text) output, and create a
# standard science benchmark report.
for rGen in getGenerators(["RST", "ReportLab"], sciBTest.outputPathBase):
sReps.makeSciBenchReport(sciBTest, mResults, rGen,
os.path.join(sciBTest.outputPathBase, "%s-report.%s" %\
(sciBTest.testName, rGen.stdExt)), imgPerRow=2)
def customReport_VRMS_Nusselt(sciBTest, mResults):
# Some custom output generation and analysis
vrmsTCs, vrmsResults = sciBTest.getTCRes("VRMS vs Blankenbach")
nusseltTCs, nusseltResults = sciBTest.getTCRes("Nusselt vs Blankenbach")
vrmsActuals = [tc.actualVal for tc in vrmsTCs]
nusseltActuals = [tc.actualVal for tc in nusseltTCs]
# TODO: useful if below values available on modelResults automatically.
for mRes in mResults: mRes.readFrequentOutput()
nSteps = [mRes.freqOutput.finalStep() for mRes in mResults]
# Plotting / CSV writing
thermalConvPostProc.plotResultsVsBlankenbach(BBRa,
BBVrmsMin, BBVrmsMax,
BBNusseltMin, BBNusseltMax,
{"UW Actual":vrmsActuals}, {"UW Actual":nusseltActuals},
os.path.join(sciBTest.outputPathBase, "VrmsAndNusseltValues.png"))
observables = {'Vrms':vrmsActuals, 'Vrms Passed':vrmsResults,
'Nusselt':nusseltActuals, 'Nusselt Passed':nusseltResults,
'nSteps':nSteps}
msuite.writeInputsOutputsToCSV(sciBTest.mSuite, observables,
"thermalDimBMResults.csv")
modelplots.plotOverAllRuns(mResults, 'Nusselt',
path=sciBTest.outputPathBase)
modelplots.plotOverAllRuns(mResults, 'Vrms',
path=sciBTest.outputPathBase)
#TODO: modularise the below
import plotCpuTimesAllRuns as plotCpus
plotCpus.plotAllRuns(sciBTest.outputPathBase)
sciBTest.mSuite.analysisImages = [
'VrmsAndNusseltValues.png',
'Nusselt-multiRunTimeSeries.png',
'Vrms-multiRunTimeSeries.png',
'cpuTimePerStep.png']
sciBTest.mSuite.modelImagesToDisplay = [[] for runI in \
range(len(sciBTest.mSuite.runs))]
lastImgSteps = []
for finalStep, mRun in zip(nSteps, sciBTest.mSuite.runs):
simParams = mRun.getSimParams()
lastImgSteps.append(simParams.nearestDumpStep(finalStep, finalStep))
sciBTest.mSuite.modelImagesToDisplay[0] = [
(0, ""),
(700, ""),
(lastImgSteps[0], "")]
sciBTest.mSuite.modelImagesToDisplay[1] = [
(0, ""),
(800, ""),
(lastImgSteps[1], "")]
sciBTest.mSuite.modelImagesToDisplay[2] = [
(0, ""),
(400, ""),
(lastImgSteps[2], "")]
for rGen in getGenerators(["RST", "ReportLab"], sciBTest.outputPathBase):
sReps.makeSciBenchReport(sciBTest, mResults, rGen,
os.path.join(sciBTest.outputPathBase, "%s-report.%s" %\
(sciBTest.testName, rGen.stdExt)), imgPerRow=3)
def customReport_VRMS(sciBTest, mResults):
for mRes in mResults: mRes.readFrequentOutput()
# Some custom output generation and analysis
fSteps = [mResult.freqOutput.finalStep() for mResult in mResults]
vrmsTCs, vrmsResults = sciBTest.getTCRes("VRMS Max")
vrmsActuals = [tc.actualVal for tc in vrmsTCs]
# Now specific per-run images
dEvery = sciBTest.mSuite.runs[0].simParams.dumpevery
lastImgSteps = [fStep / dEvery * dEvery for fStep in fSteps]
# find the timestep
vrmsPeakTimes = [tc.actualTime for tc in vrmsTCs]
vrmsPeakSteps = [mRes.freqOutput.getClosest('Time', peakTime)[1] for mRes, peakTime in\
zip(mResults, vrmsPeakTimes) ]
# TODO: useful if below values available on modelResults automatically.
# Plotting
modelplots.plotOverAllRuns(mResults, 'Vrms', depName='Time',
path=sciBTest.outputPathBase)
modelplots.plotOverAllRuns(mResults, 'Entrainment',
path=sciBTest.outputPathBase, depName='Time')
#TODO: modularise the below
import plotCpuTimesAllRuns as plotCpus
plotCpus.plotAllRuns(sciBTest.outputPathBase)
sciBTest.mSuite.analysisImages = [
'Vrms-multiRunTimeSeries.png',
'Entrainment-multiRunTimeSeries.png',
'cpuTimePerStep.png']
sciBTest.mSuite.modelImagesToDisplay = [[] for runI in \
range(len(sciBTest.mSuite.runs))]
lastImgSteps = []
vrmsPeakImgSteps = []
for runI, mRun in enumerate(sciBTest.mSuite.runs):
finalStep = fSteps[runI]
simParams = mRun.getSimParams()
lastImgSteps.append(simParams.nearestDumpStep(finalStep, finalStep))
vrmsPeakImgSteps.append(simParams.nearestDumpStep(vrmsPeakSteps[runI],
finalStep))
for resI, mResult in enumerate(mResults):
simParams = sciBTest.mSuite.runs[resI].getSimParams()
qtrStep = simParams.nearestDumpStep(fSteps[resI]//4, fSteps[resI])
halfStep = simParams.nearestDumpStep(fSteps[resI]//2, fSteps[resI])
qtrTime = mResult.freqOutput.getValueAtStep("Time", qtrStep)
halfTime = mResult.freqOutput.getValueAtStep("Time", halfStep)
sciBTest.mSuite.modelImagesToDisplay[resI] = [
(0, ""),
(vrmsPeakImgSteps[resI], "VRMS Peak, t=%f" % vrmsPeakTimes[resI]),
(qtrStep, "t=%f" % qtrTime),
(halfStep, "t=%f" % halfTime),
(lastImgSteps[resI], "Final, t=%f" % (stopTime))]
for rGen in getGenerators(["RST", "ReportLab"], sciBTest.outputPathBase):
sReps.makeSciBenchReport(sciBTest, mResults, rGen,
os.path.join(sciBTest.outputPathBase, "%s-report.%s" %\
(sciBTest.testName, rGen.stdExt)), imgPerRow=3)
