def showResults(self):
#restore .m file from archive
fileName = 'matlabua.m'
self.restoreFromArchive(fileName)
RawDataAnalyzer.plotUA(self.ensemble, self.outputs[0], fileName,
self.moments)
def showResults(self):
#restore .m file from archive
fileName = SensitivityAnalysis.outFileNames[self.subType]
self.restoreFromArchive(fileName)
cmd = SensitivityAnalysis.psuadeNames[self.subType]
RawDataAnalyzer.plotSA(self.ensemble, cmd, self.outputs[0], fileName)
def showResults(self):
#restore .m file from archive
fileName = ParameterScreening.outFileNames[self.subType]
self.restoreFromArchive(fileName)
cmd = ParameterScreening.getSubTypePsuadeName(self.subType)
RawDataAnalyzer.plotScreenInputs(self.ensemble, cmd, self.outputs[0],
fileName)
def analyze(self):
data = self.ensemble.getValidSamples()
Common.initFolder(RawDataAnalyzer.dname)
fname = Common.getLocalFileName(RawDataAnalyzer.dname, data.getModelName().split()[0], '.dat')
data.writeToPsuade(fname)
#perform UA
mfile = RawDataAnalyzer.performCA(fname, self.outputs[0])
#archive file
if mfile is not None:
self.archiveFile(mfile)
return mfile
def analyze(self):
data = self.ensemble.getValidSamples()
Common.initFolder(RawDataAnalyzer.dname)
fname = Common.getLocalFileName(RawDataAnalyzer.dname,
data.getModelName().split()[0], '.dat')
data.writeToPsuade(fname)
#perform screening
cmd = SensitivityAnalysis.psuadeNames[self.subType]
mfile = RawDataAnalyzer.performSA(fname, self.outputs[0], cmd)
#archive file
if mfile is not None:
self.archiveFile(mfile)
return mfile
def analyze(self):
data = self.ensemble.getValidSamples()
Common.initFolder(RawDataAnalyzer.dname)
fname = Common.getLocalFileName(RawDataAnalyzer.dname,
data.getModelName().split()[0], '.dat')
data.writeToPsuade(fname)
#perform screening
cmd = ParameterScreening.getSubTypePsuadeName(self.subType)
mfile = RawDataAnalyzer.screenInputs(fname, self.outputs[0], cmd)
if mfile is not None:
#archive file
self.archiveFile(mfile)
return mfile