def testVarGenFuncs(iterGen):
valuesIter = msuite.getParamValuesIter(varDict, iterGen)
print "Value tuples:\n%s" % list(valuesIter)
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
print "Indices into vars list:\n%s" % list(indicesIter)
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
varNameDicts = msuite.getVariantNameDicts(varDict, indicesIter)
print "Dictionary of var names:values :\n%s" % varNameDicts
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
varPathDicts = msuite.getVariantParamPathDicts(varDict, indicesIter)
print "Dictionary of var paths:values :\n%s" % varPathDicts
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
subPaths = msuite.getTextParamValsSubdirs(varDict, indicesIter)
print "Sub-paths (textual):\n%s" % subPaths
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
cmdLineOvers = msuite.getVariantCmdLineOverrides(varDict, indicesIter)
print "Cmd-line strings:\n%s" % cmdLineOvers
print "subDirs, strs:"
subDirsAndCmdLines = zip(subPaths, cmdLineOvers)
for subDir, cmdLineStr in subDirsAndCmdLines:
print " %s: '%s'" % (subDir, cmdLineStr)
print "Indexes and results of a certain parameter"
gravRunIs = msuite.getVarRunIs('gravity', varDict, varNameDicts)
print "Run Indices of variant 'gravity':\n%s" % gravRunIs
surfValsMap = msuite.getOtherParamValsByVarRunIs(gravRunIs, varNameDicts,
'surfShape')
print "Run Indices of variant 'surfShape' sorted by 'gravity':\n%s" \
% (surfValsMap)
def testVarGenFuncs(iterGen):
valuesIter = msuite.getParamValuesIter(varDict, iterGen)
print "Value tuples:\n%s" % list(valuesIter)
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
print "Indices into vars list:\n%s" % list(indicesIter)
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
varNameDicts = msuite.getVariantNameDicts(varDict, indicesIter)
print "Dictionary of var names:values :\n%s" % varNameDicts
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
varPathDicts = msuite.getVariantParamPathDicts(varDict, indicesIter)
print "Dictionary of var paths:values :\n%s" % varPathDicts
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
subPaths = msuite.getTextParamValsSubdirs(varDict, indicesIter)
print "Sub-paths (textual):\n%s" % subPaths
indicesIter = msuite.getVariantIndicesIter(varDict, iterGen)
cmdLineOvers = msuite.getVariantCmdLineOverrides(varDict, indicesIter)
print "Cmd-line strings:\n%s" % cmdLineOvers
print "subDirs, strs:"
subDirsAndCmdLines = zip(subPaths, cmdLineOvers)
for subDir, cmdLineStr in subDirsAndCmdLines:
print " %s: '%s'" % (subDir, cmdLineStr)
print "Indexes and results of a certain parameter"
gravRunIs = msuite.getVarRunIs('gravity', varDict, varNameDicts)
print "Run Indices of variant 'gravity':\n%s" % gravRunIs
surfValsMap = msuite.getOtherParamValsByVarRunIs(gravRunIs, varNameDicts,
'surfShape')
print "Run Indices of variant 'surfShape' sorted by 'gravity':\n%s" \
% (surfValsMap)
def modelImagesDisplay(mSuite, rGen, level, imgPerRow=1):
imageInfos = mSuite.modelImagesToDisplay
elements = []
if mSuite.iterGen is not None:
inIter = msuite.getVariantIndicesIter(mSuite.modelVariants,
mSuite.iterGen)
varNameDicts = msuite.getVariantNameDicts(mSuite.modelVariants, inIter)
for runI, imagesPerRun in enumerate(imageInfos):
#Allow runs with no images (may not be interesting).
if len(imagesPerRun) == 0:
continue
mRun = mSuite.runs[runI]
elements.append(
rGen.getHeaderEl("Run %d: %s" % (runI, mSuite.runs[runI].name),
level))
# TODO: optional info to provide with each run.
#if mSuite.iterGen is not None:
# elements.append(rGen.getHeaderEl("%s" % varNameDicts[runI],
# style=ParaStyle))
# Put the images in a table
nRows = int(math.ceil(len(imagesPerRun) / float(imgPerRow)))
data = [[] for rowI in range(nRows)]
rowI = 0
for ii, imgInfo in enumerate(imagesPerRun):
hdrText = "Timestep %d:" % (imgInfo[0])
if imgInfo[1] != "": hdrText += " (%s)" % imgInfo[1]
imgFName = os.path.join(mRun.basePath, mRun.outputPath,
'window.%.5d.png' % imgInfo[0])
# Set possible thumbnail size - can reduce file size if many
# images are being used.
tScale = 1 / float(imgPerRow) * 100
# Set display size on page
img = PIL.Image.open(imgFName)
initWidth, initHeight = img.size
ratio = initHeight / float(initWidth)
newWidth = int(
math.floor((rGen.PAGE_WIDTH * .9) / float(imgPerRow)))
newHeight = int(math.floor(newWidth * ratio))
data[rowI].append(
rGen.getImageEls(imgFName,
width=newWidth,
height=newHeight,
tScale=tScale,
hdrText=hdrText))
if (ii + 1) % imgPerRow == 0: rowI += 1
table = rGen.getTableEl(data)
elements.append(table)
result = elements
return result
def modelImagesDisplay(mSuite, rGen, level, imgPerRow=1):
imageInfos = mSuite.modelImagesToDisplay
elements = []
if mSuite.iterGen is not None:
inIter = msuite.getVariantIndicesIter(mSuite.modelVariants,
mSuite.iterGen)
varNameDicts = msuite.getVariantNameDicts(mSuite.modelVariants, inIter)
for runI, imagesPerRun in enumerate(imageInfos):
#Allow runs with no images (may not be interesting).
if len(imagesPerRun) == 0:
continue
mRun = mSuite.runs[runI]
elements.append(rGen.getHeaderEl("Run %d: %s" % (runI,
mSuite.runs[runI].name), level))
# TODO: optional info to provide with each run.
#if mSuite.iterGen is not None:
# elements.append(rGen.getHeaderEl("%s" % varNameDicts[runI],
# style=ParaStyle))
# Put the images in a table
nRows = int(math.ceil(len(imagesPerRun)/float(imgPerRow)))
data = [[] for rowI in range(nRows)]
rowI = 0
for ii, imgInfo in enumerate(imagesPerRun):
hdrText = "Timestep %d:" % (imgInfo[0])
if imgInfo[1] != "": hdrText += " (%s)" % imgInfo[1]
imgFName = os.path.join(mRun.basePath, mRun.outputPath,
'window.%.5d.png' % imgInfo[0])
# Set possible thumbnail size - can reduce file size if many
# images are being used.
tScale = 1/float(imgPerRow) * 100
# Set display size on page
img = PIL.Image.open(imgFName)
initWidth, initHeight = img.size
ratio = initHeight / float(initWidth)
newWidth = int(math.floor((rGen.PAGE_WIDTH*.9) / float(imgPerRow)))
newHeight = int(math.floor(newWidth * ratio))
data[rowI].append(rGen.getImageEls(imgFName, width=newWidth,
height=newHeight, tScale=tScale, hdrText=hdrText))
if (ii+1) % imgPerRow == 0: rowI += 1
table = rGen.getTableEl(data)
elements.append(table)
result = elements
return result
def reportResults(mSuite, mResults):
indicesIter = msuite.getVariantIndicesIter(mSuite.modelVariants,
mSuite.iterGen)
varNameDicts = msuite.getVariantNameDicts(mSuite.modelVariants, indicesIter)
for resI, mRes in enumerate(mResults):
print "Post-process result %d: with" % resI,
print ", ".join(["%s=%g" % item for item in varNameDicts[resI].iteritems()])
mRes.readFrequentOutput()
mRes.freqOutput.plotOverTime('Vrms', depName='Time',
path=mRes.outputPath)
maxVal, maxTimeStep = mRes.freqOutput.getMax('Vrms')
maxTime = mRes.freqOutput.getValueAtStep('Time', maxTimeStep)
print "\tMaximum value of Vrms was %f, at time %.2f" % (maxVal, maxTime)
modelplots.plotOverAllRuns(mResults, 'Vrms', depName='Time',
path=mSuite.outputPathBase)
mSuite.analysisImages = [
'Vrms-multiRunTimeSeries.png']
mSuite.modelImagesToDisplay = [[] for runI in range(len(mSuite.runs))]
for runI, mRun in enumerate(mSuite.runs):
mRes = mResults[runI]
fStep = mRes.freqOutput.finalStep()
fTime = mRes.freqOutput.getValueAtStep('Time', fStep)
dEvery = mRun.simParams.dumpevery
lastImgStep = fStep / dEvery * dEvery
vrmsMax, vrmsPeakStep = mRes.freqOutput.getMax('Vrms')
vrmsMaxTime = mRes.freqOutput.getValueAtStep('Time', vrmsPeakStep)
vrmsPeakImgStep = mRun.simParams.nearestDumpStep(fStep, vrmsPeakStep)
vrmsPeakImgTime = mRes.freqOutput.getValueAtStep('Time',
vrmsPeakImgStep)
mSuite.modelImagesToDisplay[runI] = [
(0, "initial"),
(vrmsPeakImgStep, "t=%f, near VRMS peak %g (at t=%g)" %\
(vrmsPeakImgTime, vrmsMax, vrmsMaxTime)),
(mRun.simParams.nearestDumpStep(fStep, fStep*.5), "1/2"),
(mRun.simParams.nearestDumpStep(fStep, fStep*.75), "3/4"),
(lastImgStep, "final state (t=%f)" % fTime)]
for rGen in getGenerators(["RST", "ReportLab"], mSuite.outputPathBase):
sReps.makeSuiteReport(mSuite, mResults, rGen,
os.path.join(mSuite.outputPathBase, "%s-report.%s" %\
("RayTaySuite-examples", rGen.stdExt)), imgPerRow=3)
def getStatus(self, resultsSet):
"""After a suite of runs created by :meth:".genSuite"
has been run, when this method is passed the results of the suite
(as a list of :class:`credo.modelresult.ModelResult`), it must decide
and return the status of the test (as a :class:`.SysTestResult`).
It also needs to save this status to :attr:`.testStatus`.
By default, this simply gets each :class:`~.TestComponent` registered
for the system test do check its status, all must pass for a total
pass.
.. note:: if using this default method, then sub-classes need to
have defined `failMsg` and `passMsg` attributes to use.
"""
# If using this defaul
if not (hasattr(self, 'passMsg') and hasattr(self, 'failMsg')):
raise AttributeError("Please define 'passMsg' and 'failMsg'"\
" attributes of your SysTest class to use the defualt"\
" getStatus method.")
if len(resultsSet) != len(self.testComps):
raise ValueError("Model results passed in to getStatus must"\
" be same length array as number of testComponents specified"\
" (lens are %d and %d, respectively)" %\
(len(resultsSet), len(self.testComps)))
self.checkModelResultsValid(resultsSet)
runPassed = [None for res in resultsSet]
self.tcResults = [{} for res in resultsSet]
#TODO: cleanup in future when iterator/generator interface improved
if self.mSuite.iterGen is not None:
inIter = msuite.getVariantIndicesIter(self.mSuite.modelVariants,
self.mSuite.iterGen)
varDicts = msuite.getVariantNameDicts(self.mSuite.modelVariants,
inIter)
for runI, modelResult in enumerate(resultsSet):
if len(self.testComps[runI]) > 0:
print("Testing single-run T.C.s for model result %d" % (runI))
if self.mSuite.iterGen is not None:
print("(var-generated, with variants applied of:\n%s)"\
% varDicts[runI])
for tcName, tComp in list(self.testComps[runI].items()):
tcResult = tComp.check(modelResult)
self.tcResults[runI][tcName] = tcResult
runPassed[runI] = all(self.tcResults[runI].values())
if len(self.testComps[runI]) > 0:
if runPassed[runI]:
print("All single run test components for"\
" run %d passed." % runI)
else:
#Do not break - we want to do all checks for sys tests
print("at least one single run test component for"\
" run %d failed." % runI)
self.allsrPassed = all(runPassed)
#Now do the Multi-run test components
if len(self.multiRunTestComps) > 0:
print("Testing multi-run test components:")
self.mrtcResults = {}
for tcName, mrtComp in list(self.multiRunTestComps.items()):
tcResult = mrtComp.check(resultsSet)
self.mrtcResults[tcName] = tcResult
self.allmrPassed = all(self.mrtcResults.values())
if len(self.multiRunTestComps) > 0:
if self.allmrPassed:
print("All multi-run test components passed.")
else:
print("at least one multi-run test component failed.")
if self.allsrPassed and self.allmrPassed:
self.testStatus = CREDO_PASS(self.passMsg)
else:
self.testStatus = CREDO_FAIL(self.failMsg)
return self.testStatus
def customReporting(sciBTest, mResults):
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
stress = {}
recDeviatoricStress = {}
recDeviatoricStressTCs = {}
recDeviatoricStressRes = {}
stressTCs = {}
stressRes = {}
for fComp in ["XX", "XY", "YY"]:
recDeviatoricStressTCs[fComp], recDeviatoricStressRes[fComp] = sciBTest.getTCRes(\
"recoveredDeviatoricStress-%s" % fComp)
stressTCs[fComp], stressRes[fComp] = sciBTest.getTCRes(\
"Stress-%s" % fComp)
recDeviatoricStress[fComp] = [tc.actualVal for tc in recDeviatoricStressTCs[fComp]]
stress[fComp] = [tc.actualVal for tc in stressTCs[fComp]]
inIter = msuite.getVariantIndicesIter(sciBTest.mSuite.modelVariants,
iterStrategy)
varDicts = msuite.getVariantNameDicts(sciBTest.mSuite.modelVariants,
inIter)
for resI, mRes in enumerate(mResults):
print "Post-process result %d" % (resI),
print "with variants applied of:"
print varDicts[resI]
print "Value of recDeviatoricStress(%s) is (%s)\n stress(%s) is (%s)." %\
(", ".join(fCompMap),
", ".join(["%g" % recDeviatoricStress[c][resI] for c in fCompMap]),
", ".join(fCompMap),
", ".join(["%g" % stress[c][resI] for c in fCompMap]))
# TO DO:
#plotDeviatoricStressVsAnalytic(maxStressXX, maxStressYY, maxStressXY,
# minStressXX, minStressYY, minStressXY,
# {"DeviatoricStress_XX":recDeviatoricStress['XX']}, {"DeviatoricStress_YY":recDeviatoricStress['YY']},
# {"DeviatoricStress_XY":recDeviatoricStress['XY']},
# {"Stress_XX":stressXX}, {"Stress_YY":stressYY}, {"Stress_XY":stressXY})
#plt.savefig(os.path.join(mSuite.outputPathBase,
# "RecoveredDeviatoricStressAndStressValues.png"),
# dpi=None, facecolor='w', edgecolor='w',
# orientation='portrait', papertype=None, format=None,
# transparent=False)
# Save to a CSV file.
observables = {'recovered DeviatoricStress XX': recDeviatoricStress['XX'],
'recovered DeviatoricStress XX Passed': recDeviatoricStressRes['XX'],
'recovered DeviatoricStress YY': recDeviatoricStress['YY'],
'recovered DeviatoricStress YY Passed': recDeviatoricStressRes['YY'],
'recovered DeviatoricStress XY': recDeviatoricStress['XY'],
'recovered DeviatoricStress XY Passed': recDeviatoricStressRes['XY'],
'stress XX': stress['XX'],
'stress XX Passed': stressRes['XX'],
'stress YY': stress['YY'],
'stress YY Passed': stressRes['YY'],
'stress XY': stress['XY'],
'stress XY Passed': stressRes['XY']}
msuite.writeInputsOutputsToCSV(sciBTest.mSuite, observables,
"OrthotropicTestStressValues.csv")
sciBTest.mSuite.analysisImages = None
sciBTest.mSuite.modelImagesToDisplay = None
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)))
