def generateSamples(data,
selectedInputs,
selectedOutputs,
numSamples=None,
sampleMethod=-1):
psuadeDataFile = os.getcwd() + os.path.sep + 'psuadeData'
if os.path.exists(psuadeDataFile):
os.remove(psuadeDataFile)
# Create new SampleData object with only selected inputs and outputs
newModel = Model()
inputNames = numpy.array(data.getInputNames())
newModel.setInputNames(inputNames[selectedInputs])
outputNames = numpy.array(data.getOutputNames())
newModel.setOutputNames(outputNames[selectedOutputs])
newModel.setInputMins(data.getInputMins()[selectedInputs])
newModel.setInputMaxs(data.getInputMaxs()[selectedInputs])
newModel.setDriverName(data.getDriverName())
if data.getInputDefaults() is not None:
newModel.setInputDefaults(data.getInputDefaults()[selectedInputs])
returnData = SampleData(newModel)
if numSamples:
returnData.setNumSamples(numSamples)
else:
returnData.setNumSamples(data.getNumSamples())
if sampleMethod >= 0:
returnData.setSampleMethod(sampleMethod)
else:
returnData.setSampleMethod(data.getSampleMethod())
if returnData.getSampleMethod(
) == SamplingMethods.METIS and os.path.exists('psuadeMetisInfo'):
os.remove('psuadeMetisInfo')
distributions = data.getInputDistributions()
pdfconvert = False
for dist in distributions:
distType = dist.getDistributionType()
if returnData.getSampleMethod(
) != SamplingMethods.MC and distType not in [
Distribution.SAMPLE, Distribution.UNIFORM
]:
pdfconvert = True
returnData.setInputDistributions(distributions)
curDir = os.getcwd()
if platform.system() == 'Windows':
import win32api
curDir = win32api.GetShortPathName(curDir)
psuadeInFile = curDir + os.sep + 'psuade.in'
if pdfconvert:
# omit non-uniform and non-sample PDF info from input file
ExperimentalDesign.createPsuadeInFile(returnData,
psuadeInFile,
includePDF=False)
else:
ExperimentalDesign.createPsuadeInFile(returnData,
psuadeInFile,
includePDF=True)
out, error = Common.invokePsuade(psuadeInFile)
if os.path.exists(psuadeDataFile):
showerr = True
data = LocalExecutionModule.readSampleFromPsuadeFile(
psuadeDataFile)
if pdfconvert:
os.remove(psuadeDataFile)
tmpfile = os.getcwd() + os.path.sep + 'tmp'
y = 1
# add back in the full PDF info
RSAnalyzer.writeRSdata(tmpfile,
y,
data,
inputPDF=distributions)
# write script to PDF conversion
f = tempfile.SpooledTemporaryFile()
if platform.system() == 'Windows':
import win32api
tmpfile = win32api.GetShortPathName(tmpfile)
f.write(('load %s\n' % tmpfile).encode())
f.write(b'pdfconvert\n')
f.write(('write %s\n' % psuadeDataFile).encode())
nOutputs = returnData.getNumOutputs()
if nOutputs > 1:
f.write(b'n\n') # write all outputs
f.write(b'quit\n')
f.seek(0)
out, error = Common.invokePsuade(f)
f.close()
if os.path.exists(psuadeDataFile):
data = LocalExecutionModule.readSampleFromPsuadeFile(
psuadeDataFile)
showerr = False
else:
showerr = False
if showerr:
error = 'ExperimentalDesign: %s does not exist.' % psuadeDataFile
Common.showError(error, out)
return None
else:
return data
def generateSamples(self):
# self.setModal(False)
# Gather all info into SampleData object
if isinstance(self.model, Model):
model = copy.deepcopy(self.model)
# runData = SampleData(self.model)
else:
model = copy.deepcopy(self.model.model)
# runData = copy.deepcopy(self.model)
# Gather distributions from distribution table
types = []
modelTypes = self.model.getInputTypes()
defaults = []
modelDefaults = self.model.getInputDefaults()
mins = []
modelMins = self.model.getInputMins()
maxs = []
modelMaxs = self.model.getInputMaxs()
dists = []
selectedInputs = []
# Set sampling scheme to selected or monte carlo if adaptive
if self.chooseSchemeRadio.isChecked():
scheme = self.schemesList.currentItem().text()
else:
scheme = "Monte Carlo"
# First get parameters for the model
row = 0
for inputNum in range(self.model.getNumInputs()):
if modelTypes[inputNum] == Model.VARIABLE:
# Type
combobox = self.distTable.cellWidget(row, 1)
if combobox is None:
text = self.distTable.item(row, 1).text()
else:
text = combobox.currentText()
if text == "Fixed":
value = Model.FIXED
else:
value = Model.VARIABLE
types.append(value)
if value == Model.VARIABLE:
selectedInputs.append(inputNum)
# Defaults
item = self.distTable.item(row, 2)
if item is None or len(item.text()) == 0:
defaults.append(None)
else:
defaults.append(float(item.text()))
# Mins
item = self.distTable.item(row, 3)
mins.append(float(item.text()))
# Maxs
item = self.distTable.item(row, 4)
maxs.append(float(item.text()))
row += 1
else: # Fixed
types.append(Model.FIXED)
defaults.append(modelDefaults[inputNum])
mins.append(modelMins[inputNum])
maxs.append(modelMaxs[inputNum])
# Update model
model.setInputTypes(types)
model.setInputDefaults(defaults)
model.setInputMins(mins)
model.setInputMaxs(maxs)
# Create SampleData object
runData = SampleData(model, self.session)
runData.setModelName(
self.session.flowsheet.results.incrimentSetName("UQ_Ensemble"))
runData.setFromFile(False)
# Now get distributions for the SampleData object
numSampleFromFile = 0
row = 0
for inputNum in range(self.model.getNumInputs()):
if modelTypes[inputNum] == Model.VARIABLE:
# Only collect those that are not fixed to generate inputs
combobox = self.distTable.cellWidget(row, 5)
dist = combobox.currentIndex()
# Check non-uniform distribution and non-Monte Carlo scheme
if (
False
): # dist != Distribution.UNIFORM and SamplingMethods.getEnumValue(scheme) != SamplingMethods.MC:
msgbox = QMessageBox()
msgbox.setWindowTitle("UQ/Opt GUI Warning")
msgbox.setText(
"Non-Uniform distributions are not compatible with any "
+
"sampling scheme other than Monte Carlo! Please change "
+
"all distributions back to uniform or select Monte Carlo "
+ "sampling scheme.")
msgbox.setIcon(QMessageBox.Warning)
msgbox.exec_()
return
if dist == Distribution.SAMPLE:
numSampleFromFile += 1
dists += [self.distTable.getDistribution(row)]
row += 1
else: # Fixed
dist = Distribution(Distribution.UNIFORM)
dists = dists + [dist]
runData.setInputDistributions(dists)
numSamples = int(self.numSamplesBox.value())
runData.setNumSamples(numSamples)
runData.setSampleMethod(scheme)
# Check number of samples
scheme = runData.getSampleMethod()
newNumSamples = SamplingMethods.validateSampleSize(
scheme, len(selectedInputs), numSamples)
if scheme == SamplingMethods.LSA:
if newNumSamples != numSamples:
msgbox = QMessageBox()
msgbox.setWindowTitle("UQ/Opt GUI Warning")
msgbox.setText(
"%s scheme with %d variable inputs requires %d samples! Do you want to proceed?"
% (
SamplingMethods.getPsuadeName(scheme),
len(selectedInputs),
newNumSamples,
))
msgbox.setIcon(QMessageBox.Question)
msgbox.setStandardButtons(QMessageBox.Yes | QMessageBox.No)
msgbox.setDefaultButton(QMessageBox.Yes)
response = msgbox.exec_()
if response == QMessageBox.Yes:
runData.setNumSamples(newNumSamples)
else:
return
elif scheme == SamplingMethods.MOAT or scheme == SamplingMethods.GMOAT:
if type(newNumSamples) is tuple:
msgbox = QMessageBox()
msgbox.setWindowTitle("UQ/Opt GUI Warning")
msgbox.setText(
"%s scheme with %d variable inputs cannot have %d samples! How do you want to proceed?"
% (
SamplingMethods.getFullName(scheme),
len(selectedInputs),
numSamples,
))
msgbox.setIcon(QMessageBox.Question)
firstValButton = msgbox.addButton(
"Change to %d samples" % newNumSamples[0],
QMessageBox.AcceptRole)
secondValButton = msgbox.addButton(
"Change to %d samples" % newNumSamples[1],
QMessageBox.AcceptRole)
cancelButton = msgbox.addButton(QMessageBox.Cancel)
msgbox.exec_()
if msgbox.clickedButton() == firstValButton:
runData.setNumSamples(int(newNumSamples[0]))
elif msgbox.clickedButton() == secondValButton:
runData.setNumSamples(int(newNumSamples[1]))
else:
return
# Visual indications of processing
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
self.generateStatusText.setText("Generating...")
self.generateStatusText.repaint()
# Generate samples for the variable inputs
selectedRunData = ExperimentalDesign.generateSamples(
runData, selectedInputs, self.model.getSelectedOutputs())
if selectedRunData is None:
QApplication.restoreOverrideCursor()
self.generateStatusText.setText("")
return
selectedInputData = selectedRunData.getInputData()
# Add fixed inputs back in
## print runData.getNumSamples()
fullInputData = [0] * runData.getNumSamples()
for row in range(runData.getNumSamples()):
rowData = []
selectedIndex = 0
for col in range(runData.getNumInputs()):
if col in selectedInputs:
rowData.append(selectedInputData[row][selectedIndex])
selectedIndex = selectedIndex + 1
else:
rowData.append(defaults[col])
fullInputData[row] = rowData
runData.setInputData(fullInputData)
runData.setRunState([0] * runData.getNumSamples())
self.runData = runData
# Handle archive of METIS file
if self.runData.getSampleMethod() == SamplingMethods.METIS:
if self.currentArchiveData is not None:
# Common.removeArchive(self.currentArchive)
self.currentArchiveData.removeArchiveFolder()
pass
# Common.archiveFile('psuadeMetisInfo', self.runData.getID())
self.runData.archiveFile("psuadeMetisInfo")
self.currentArchiveData = self.runData
# Restore cursor
QApplication.restoreOverrideCursor()
self.generateStatusText.setText("Done!")
self.samplesGenerated = True
self.previewButton.setEnabled(True)
self.doneButton.setEnabled(True)
