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 __init__(self,
model,
session,
viewOnly=False,
returnDataSignal=None,
parent=None):
super(SimSetup, self).__init__(parent)
self.setupUi(self)
self.viewOnly = viewOnly
self.returnDataSignal = returnDataSignal
self.sampleFileSet = (
set()
) # Contains which inputs are of the distribution "Sample from File"
self.fsDataBrowser = dataBrowserFrame(session, self)
self.dataViewWidget.setLayout(QStackedLayout(self.dataViewWidget))
self.dataViewWidget.layout().addWidget(self.fsDataBrowser)
self.fsDataBrowser.refreshContents()
self.fileLoaded = False
self.samplesGenerated = False
self.currentArchiveData = None
self.model = model
self.session = session
if isinstance(model, Model):
data = SampleData(model)
dists = []
for i in range(model.getNumInputs()):
dists = dists + ["U"]
data.setInputDistributions(dists)
else:
data = model
self.currentArchiveData = data
self.ignoreDistributionCheck = False
if model.getRunType() == Model.EMULATOR:
self.flowsheetDataRadio.setHidden(True)
if viewOnly:
self.loadSamplesRadio.setEnabled(False)
self.flowsheetDataRadio.setEnabled(False)
self.loadSamplesRadio.clicked.connect(self.setPage)
self.flowsheetDataRadio.clicked.connect(self.setPage)
self.chooseSchemeRadio.clicked.connect(self.setPage)
self.setPage()
self.browseButton.clicked.connect(self.loadSampleFile)
# self.cancelButton.clicked.connect(self.reject)
self.cancelButton.clicked.connect(self.cancel)
self.previewButton.clicked.connect(self.preview)
self.previewButton.setEnabled(False)
# self.doneButton.clicked.connect(self.accept)
self.doneButton.clicked.connect(self.doneClicked)
self.doneButton.setEnabled(False)
if viewOnly:
self.cancelButton.setText("OK")
self.doneButton.setHidden(True)
self.samplingTabs.setTabEnabled(1, False)
# Make sure appropriate option is visible
# self.chooseSchemeRadio.setChecked(True)
# self.showChooseSchemePage()
if not isinstance(model, Model):
if model.getInputData() is not None:
self.previewButton.setEnabled(True)
if not viewOnly:
self.doneButton.setEnabled(True)
self.runData = model
# Make sure distribution tab is showing
self.samplingTabs.setCurrentIndex(0)
self.samplingTabs.currentChanged[int].connect(self.checkDists)
# Set up distributions table
self.distTable.init(model, InputPriorTable.SIMSETUP, viewOnly=viewOnly)
self.allFixedButton.clicked.connect(self.makeAllFixed)
self.allVariableButton.clicked.connect(self.makeAllVariable)
if viewOnly or model.getRunType() == Model.EMULATOR:
self.allFixedButton.setHidden(True)
self.allVariableButton.setHidden(True)
# Set up sampling schemes tab
self.generateSamplesButton.setEnabled(False)
self.generateStatusText.setText("")
self.allSchemesRadio.setChecked(True)
foundLibs = LocalExecutionModule.getPsuadeInstalledModules()
foundMETIS = foundLibs["METIS"]
self.schemesList.clear()
self.schemesList.addItems(SamplingMethods.fullNames[:-2]
) # Leave out GMETIS and FULL Factorial
if not foundMETIS:
item = self.schemesList.item(SamplingMethods.METIS)
text = item.text()
item.setText(text + " (Not installed)")
flags = item.flags()
item.setFlags(flags & ~Qt.ItemIsEnabled)
if isinstance(model, SampleData):
self.schemesList.setCurrentRow(model.getSampleMethod())
self.generateSamplesButton.setEnabled(True)
# Change lists of schemes displayed
self.allSchemesRadio.toggled.connect(self.showAllSchemes)
self.paramScreenRadio.toggled.connect(self.showParamScreenSchemes)
self.adaptiveRefineRadio.toggled.connect(
self.showAdaptiveRefineSchemes)
self.otherRadio.toggled.connect(self.showOtherSchemes)
self.schemesList.currentItemChanged.connect(
self.handleGenerateSamplesButton)
self.generateSamplesButton.clicked.connect(self.generateSamples)
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)
class SimSetup(_SimSetup, _SimSetupUI):
SCHEME_PAGE_INDEX = 0
LOAD_PAGE_INDEX = 1
FLOWSHEET_PAGE_INDEX = 2
def __init__(self,
model,
session,
viewOnly=False,
returnDataSignal=None,
parent=None):
super(SimSetup, self).__init__(parent)
self.setupUi(self)
self.viewOnly = viewOnly
self.returnDataSignal = returnDataSignal
self.sampleFileSet = (
set()
) # Contains which inputs are of the distribution "Sample from File"
self.fsDataBrowser = dataBrowserFrame(session, self)
self.dataViewWidget.setLayout(QStackedLayout(self.dataViewWidget))
self.dataViewWidget.layout().addWidget(self.fsDataBrowser)
self.fsDataBrowser.refreshContents()
self.fileLoaded = False
self.samplesGenerated = False
self.currentArchiveData = None
self.model = model
self.session = session
if isinstance(model, Model):
data = SampleData(model)
dists = []
for i in range(model.getNumInputs()):
dists = dists + ["U"]
data.setInputDistributions(dists)
else:
data = model
self.currentArchiveData = data
self.ignoreDistributionCheck = False
if model.getRunType() == Model.EMULATOR:
self.flowsheetDataRadio.setHidden(True)
if viewOnly:
self.loadSamplesRadio.setEnabled(False)
self.flowsheetDataRadio.setEnabled(False)
self.loadSamplesRadio.clicked.connect(self.setPage)
self.flowsheetDataRadio.clicked.connect(self.setPage)
self.chooseSchemeRadio.clicked.connect(self.setPage)
self.setPage()
self.browseButton.clicked.connect(self.loadSampleFile)
# self.cancelButton.clicked.connect(self.reject)
self.cancelButton.clicked.connect(self.cancel)
self.previewButton.clicked.connect(self.preview)
self.previewButton.setEnabled(False)
# self.doneButton.clicked.connect(self.accept)
self.doneButton.clicked.connect(self.doneClicked)
self.doneButton.setEnabled(False)
if viewOnly:
self.cancelButton.setText("OK")
self.doneButton.setHidden(True)
self.samplingTabs.setTabEnabled(1, False)
# Make sure appropriate option is visible
# self.chooseSchemeRadio.setChecked(True)
# self.showChooseSchemePage()
if not isinstance(model, Model):
if model.getInputData() is not None:
self.previewButton.setEnabled(True)
if not viewOnly:
self.doneButton.setEnabled(True)
self.runData = model
# Make sure distribution tab is showing
self.samplingTabs.setCurrentIndex(0)
self.samplingTabs.currentChanged[int].connect(self.checkDists)
# Set up distributions table
self.distTable.init(model, InputPriorTable.SIMSETUP, viewOnly=viewOnly)
self.allFixedButton.clicked.connect(self.makeAllFixed)
self.allVariableButton.clicked.connect(self.makeAllVariable)
if viewOnly or model.getRunType() == Model.EMULATOR:
self.allFixedButton.setHidden(True)
self.allVariableButton.setHidden(True)
# Set up sampling schemes tab
self.generateSamplesButton.setEnabled(False)
self.generateStatusText.setText("")
self.allSchemesRadio.setChecked(True)
foundLibs = LocalExecutionModule.getPsuadeInstalledModules()
foundMETIS = foundLibs["METIS"]
self.schemesList.clear()
self.schemesList.addItems(SamplingMethods.fullNames[:-2]
) # Leave out GMETIS and FULL Factorial
if not foundMETIS:
item = self.schemesList.item(SamplingMethods.METIS)
text = item.text()
item.setText(text + " (Not installed)")
flags = item.flags()
item.setFlags(flags & ~Qt.ItemIsEnabled)
if isinstance(model, SampleData):
self.schemesList.setCurrentRow(model.getSampleMethod())
self.generateSamplesButton.setEnabled(True)
# Change lists of schemes displayed
self.allSchemesRadio.toggled.connect(self.showAllSchemes)
self.paramScreenRadio.toggled.connect(self.showParamScreenSchemes)
self.adaptiveRefineRadio.toggled.connect(
self.showAdaptiveRefineSchemes)
self.otherRadio.toggled.connect(self.showOtherSchemes)
self.schemesList.currentItemChanged.connect(
self.handleGenerateSamplesButton)
self.generateSamplesButton.clicked.connect(self.generateSamples)
def cancel(self):
self.reject()
def doneClicked(self):
if self.returnDataSignal:
self.returnDataSignal.emit(self.getData())
self.accept()
def setPage(self):
"""
Change the page view
"""
if self.chooseSchemeRadio.isChecked():
self.samplePages.setCurrentIndex(self.SCHEME_PAGE_INDEX)
self.previewButton.setEnabled(self.samplesGenerated)
self.doneButton.setEnabled(self.samplesGenerated)
elif self.flowsheetDataRadio.isChecked():
self.samplePages.setCurrentIndex(self.FLOWSHEET_PAGE_INDEX)
self.previewButton.setEnabled(False)
self.doneButton.setEnabled(True)
elif self.loadSamplesRadio.isChecked():
self.samplePages.setCurrentIndex(self.LOAD_PAGE_INDEX)
self.previewButton.setEnabled(self.fileLoaded)
self.doneButton.setEnabled(self.fileLoaded)
else:
# I think this is impossible
raise Exception("No generate samples radio button checked")
#### Load samples methods
def loadSampleFile(self):
if platform.system() == "Windows":
allFiles = "*.*"
else:
allFiles = "*"
sampleFile, _ = QFileDialog.getOpenFileName(
self,
"Load Sample file",
"",
"Psuade Files (*.dat *.psuade *.filtered);;Psuade Simple File (*.smp);;CSV (Comma delimited) (*.csv);;All files (%s)"
% allFiles,
)
if not sampleFile: # Cancelled
return
fromSimpleFile = False
try:
if sampleFile.endswith(".csv"):
data = LocalExecutionModule.readSampleFromCsvFile(
sampleFile, False)
inputNames = data.getInputNames()
if len(inputNames[0]) == 0:
fromSimpleFile = True
else:
data = LocalExecutionModule.readSampleFromPsuadeFile(
sampleFile)
inputData = data.getInputData()
numSamples = data.getNumSamples()
numInputs = data.getNumInputs()
numLoadVariableInputs = data.getInputTypes().count(Model.VARIABLE)
except:
import traceback
traceback.print_exc()
try:
(
inputData,
_,
numInputs,
_,
) = LocalExecutionModule.readDataFromSimpleFile(sampleFile)
numSamples = inputData.shape[0]
numLoadVariableInputs = numInputs
fromSimpleFile = True
except:
QMessageBox.critical(
self,
"Incorrect format",
"File does not have the correct format! Please consult the users manual about the format.",
)
return
# Check compatibility with model.
# For now, we just check number of inputs ok.
modelInputTypes = self.model.getInputTypes()
numModelVariableInputs = modelInputTypes.count(Model.VARIABLE)
compatible = True
if fromSimpleFile and numLoadVariableInputs != numModelVariableInputs:
prompt = (
"This file does not have the same number of variable inputs (%d) as the setup model (%d)!"
% (numLoadVariableInputs, numModelVariableInputs))
compatible = False
elif not fromSimpleFile: # Check if input names match
if numLoadVariableInputs < numModelVariableInputs:
prompt = (
"This file does not have as many variable inputs (%d) as the setup model (%d)!"
% (numLoadVariableInputs, numModelVariableInputs))
compatible = False
else:
loadInputNames = data.getInputNames()
loadInputTypes = data.getInputTypes()
loadVariableNames = set([
loadInputNames[modelIndex]
for modelIndex in range(len(loadInputNames))
if loadInputTypes[modelIndex] == Model.VARIABLE
])
modelInputNames = self.model.getInputNames()
modelVariableNames = set([
modelInputNames[modelIndex]
for modelIndex in range(len(modelInputNames))
if modelInputTypes[modelIndex] == Model.VARIABLE
])
if not loadVariableNames <= modelVariableNames:
compatible = False
prompt = "This file does not have the same variable names as the setup model!"
if not compatible:
QMessageBox.warning(self, self.tr("UQ GUI"), self.tr(prompt),
QMessageBox.Ok, QMessageBox.Ok)
return
# UI indications of success
self.sampleFileNameEdit.setText(sampleFile)
self.fileLoaded = True
self.previewButton.setEnabled(True)
self.doneButton.setEnabled(True)
# Create loadData object
self.loadData = SampleData(self.model)
self.loadData.setFromFile(False)
if fromSimpleFile:
self.loadData.setSampleMethod(SamplingMethods.MC)
else:
self.loadData.setSampleMethod(data.getSampleMethod())
self.loadData.setNumSamples(numSamples)
resultData = numpy.zeros([numSamples, self.model.getNumInputs()])
modelDefaults = self.model.getInputDefaults()
loadIndex = 0
if fromSimpleFile:
for modelIndex, modelInType in enumerate(modelInputTypes):
if modelInType == Model.FIXED:
resultData[:, modelIndex] = [modelDefaults[modelIndex]
] * numSamples
else:
inDataCol = inputData[:, loadIndex]
resultData[:, modelIndex] = inDataCol
loadIndex += 1
else: # full file
# Create mapping between model names and load names
loadDefaults = self.loadData.getInputDefaults()
for modelIndex, (modelInName, modelInType) in enumerate(
zip(modelInputNames, modelInputTypes)):
if modelInName in loadInputNames:
loadIndex = loadInputNames.index(modelInName)
if modelInType == Model.FIXED:
if modelInName in loadInputNames:
value = loadDefaults[loadIndex]
else:
value = modelDefaults[modelIndex]
resultData[:, modelIndex] = [value] * numSamples
else: # Variable
if modelInName not in loadInputNames:
resultData[:,
modelIndex] = [modelDefaults[modelIndex]
] * numSamples
elif loadInputTypes[loadIndex] == Model.FIXED:
resultData[:, modelIndex] = [loadDefaults[loadIndex]
] * numSamples
else:
inDataCol = inputData[:, loadIndex]
resultData[:, modelIndex] = inDataCol
self.loadData.setInputDistributions(data.getInputDistributions())
dists = []
for modelIndex in range(self.model.getNumInputs()):
d = Distribution(Distribution.SAMPLE)
d.setParameterValues(sampleFile, modelIndex + 1)
dists.append(d)
self.loadData.setInputDistributions(dists)
self.loadData.setInputData(resultData)
self.loadData.setRunState([False] * numSamples)
def makeAllFixed(self):
# self.setAllTypeButtons(Model.FIXED)
self.distTable.makeAllFixed()
def makeAllVariable(self):
# self.setAllTypeButtons(Model.VARIABLE)
self.distTable.makeAllVariable()
def checkDists(self, tabIndex):
if tabIndex == 0 or self.ignoreDistributionCheck:
self.ignoreDistributionCheck = False
return
showMessage = False
if self.distTable.getNumVariables() == 0:
showMessage = True
message = "All inputs are fixed! One needs to be variable."
else:
valid, error = self.distTable.checkValidInputs()
if not valid:
showMessage = True
message = (
"Distribution settings not correct or entirely filled out! %s"
% error)
else:
rowsToWarnAboutMass = []
for row in range(self.distTable.rowCount()):
for col in [3, 4]:
item = self.distTable.item(row, col)
if col == 3:
minVal = float(item.text())
else:
maxVal = float(item.text())
#### Get distribution parameters
for col in [6, 7]:
cellTable = self.distTable.cellWidget(row, col)
if isinstance(cellTable, QComboBox):
continue
item = None
if cellTable is not None:
item = cellTable.item(0, 1)
if item is not None and item.text():
if col == 6:
distParam1 = float(item.text())
else:
distParam2 = float(item.text())
else:
if col == 6:
distParam1 = None
else:
distParam2 = None
#### Check mass and warn if below 50%
# Only collect those that are not fixed to generate inputs
combobox = self.distTable.cellWidget(row, 5)
dist = combobox.currentIndex()
# Create file for psuade input
if dist not in [Distribution.UNIFORM, Distribution.SAMPLE]:
f = tempfile.SpooledTemporaryFile()
for i in range(2):
f.write(b"cdf_lookup\n")
distNum = dist
if dist == Distribution.BETA:
distNum = 4
elif dist == Distribution.WEIBULL:
distNum = 5
elif dist == Distribution.GAMMA:
distNum = 6
elif dist == Distribution.EXPONENTIAL:
distNum = 7
f.write(b"%d\n" %
distNum) # Number of distribution
f.write(b"%f\n" % distParam1) # Parameter 1
if distParam2 is not None:
f.write(b"%f\n" % distParam2) # Parameter 2
if i == 0:
val = minVal
else:
val = maxVal
f.write(b"%f\n" % val) # Min or max value
f.write(b"quit\n")
f.seek(0)
# invoke psuade
psuadePath = LocalExecutionModule.getPsuadePath()
if psuadePath is None:
return
p = subprocess.Popen(
psuadePath,
stdin=f,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
shell=True,
)
f.close()
# process error
out, error = p.communicate()
if error:
Common.showError(error, out)
return None
# parse output
lines = out.splitlines()
vals = []
for line in lines:
if "Cumulative probability = " in line.decode(
"utf-8"):
words = line.split()
vals.append(float(words[-1]))
mass = vals[1] - vals[0]
if mass < 0.5:
rowsToWarnAboutMass.append(row)
if len(rowsToWarnAboutMass) > 0:
self.samplingTabs.setCurrentIndex(0)
for row in rowsToWarnAboutMass:
msgbox = QMessageBox()
msgbox.setWindowTitle("UQ/Opt GUI Warning")
msgbox.setText(
"Regarding input " +
self.model.getInputNames()[row] +
": Min/max range is narrow for its distribution. "
+
"This could cause sample generation to take more time. Continue?"
)
msgbox.setIcon(QMessageBox.Warning)
msgbox.setStandardButtons(QMessageBox.Yes
| QMessageBox.No)
msgbox.setDefaultButton(QMessageBox.Yes)
ret = msgbox.exec_()
if ret != QMessageBox.Yes:
self.distTable.selectRow(row)
return
self.ignoreDistributionCheck = True
self.samplingTabs.setCurrentIndex(1)
if showMessage:
self.samplingTabs.setCurrentIndex(0)
msgbox = QMessageBox()
msgbox.setWindowTitle("UQ/Opt GUI Warning")
msgbox.setText(message)
msgbox.setIcon(QMessageBox.Warning)
msgbox.exec_()
return
### Sampling schemes methods
def showAllSchemes(self):
if self.chooseSchemeRadio.isChecked():
foundLibs = LocalExecutionModule.getPsuadeInstalledModules()
foundMETIS = foundLibs["METIS"]
self.schemesList.clear()
self.schemesList.addItems(
SamplingMethods.fullNames[:-2]) # Remove GMETIS
if not foundMETIS:
item = self.schemesList.item(SamplingMethods.METIS)
text = item.text()
item.setText(text + " (Not installed)")
flags = item.flags()
item.setFlags(flags & ~Qt.ItemIsEnabled)
def showParamScreenSchemes(self):
if self.paramScreenRadio.isChecked():
self.schemesList.clear()
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.MOAT))
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.GMOAT))
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.LSA))
def showAdaptiveRefineSchemes(self):
if self.adaptiveRefineRadio.isChecked():
foundLibs = LocalExecutionModule.getPsuadeInstalledModules()
foundMETIS = foundLibs["METIS"]
self.schemesList.clear()
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.METIS))
if not foundMETIS:
item = self.schemesList.item(0)
text = item.text()
item.setText(text + " (Not installed)")
flags = item.flags()
item.setFlags(flags & ~Qt.ItemIsEnabled)
def showOtherSchemes(self):
if self.otherRadio.isChecked():
self.schemesList.clear()
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.MC))
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.LPTAU))
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.LH))
self.schemesList.addItem(
SamplingMethods.getFullName(SamplingMethods.OA))
def handleGenerateSamplesButton(self):
self.generateSamplesButton.setEnabled(
self.schemesList.currentRow() != -1)
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)
### Preview button
def preview(self):
if self.loadSamplesRadio.isChecked():
previewData = self.loadData
else:
previewData = self.runData
# self.setModal(False)
dialog = Preview(previewData, self)
# dialog.exec_()
dialog.show()
# self.setModal(True)
### Return data
def getData(self):
if self.loadSamplesRadio.isChecked():
returnData = self.loadData
elif self.flowsheetDataRadio.isChecked():
self.session.flowsheet.results.exportPSUADE("temp/psuadeData2.tmp")
returnData = LocalExecutionModule.readSampleFromPsuadeFile(
"temp/psuadeData2.tmp")
else:
returnData = self.runData
return returnData
def loadSampleFile(self):
if platform.system() == "Windows":
allFiles = "*.*"
else:
allFiles = "*"
sampleFile, _ = QFileDialog.getOpenFileName(
self,
"Load Sample file",
"",
"Psuade Files (*.dat *.psuade *.filtered);;Psuade Simple File (*.smp);;CSV (Comma delimited) (*.csv);;All files (%s)"
% allFiles,
)
if not sampleFile: # Cancelled
return
fromSimpleFile = False
try:
if sampleFile.endswith(".csv"):
data = LocalExecutionModule.readSampleFromCsvFile(
sampleFile, False)
inputNames = data.getInputNames()
if len(inputNames[0]) == 0:
fromSimpleFile = True
else:
data = LocalExecutionModule.readSampleFromPsuadeFile(
sampleFile)
inputData = data.getInputData()
numSamples = data.getNumSamples()
numInputs = data.getNumInputs()
numLoadVariableInputs = data.getInputTypes().count(Model.VARIABLE)
except:
import traceback
traceback.print_exc()
try:
(
inputData,
_,
numInputs,
_,
) = LocalExecutionModule.readDataFromSimpleFile(sampleFile)
numSamples = inputData.shape[0]
numLoadVariableInputs = numInputs
fromSimpleFile = True
except:
QMessageBox.critical(
self,
"Incorrect format",
"File does not have the correct format! Please consult the users manual about the format.",
)
return
# Check compatibility with model.
# For now, we just check number of inputs ok.
modelInputTypes = self.model.getInputTypes()
numModelVariableInputs = modelInputTypes.count(Model.VARIABLE)
compatible = True
if fromSimpleFile and numLoadVariableInputs != numModelVariableInputs:
prompt = (
"This file does not have the same number of variable inputs (%d) as the setup model (%d)!"
% (numLoadVariableInputs, numModelVariableInputs))
compatible = False
elif not fromSimpleFile: # Check if input names match
if numLoadVariableInputs < numModelVariableInputs:
prompt = (
"This file does not have as many variable inputs (%d) as the setup model (%d)!"
% (numLoadVariableInputs, numModelVariableInputs))
compatible = False
else:
loadInputNames = data.getInputNames()
loadInputTypes = data.getInputTypes()
loadVariableNames = set([
loadInputNames[modelIndex]
for modelIndex in range(len(loadInputNames))
if loadInputTypes[modelIndex] == Model.VARIABLE
])
modelInputNames = self.model.getInputNames()
modelVariableNames = set([
modelInputNames[modelIndex]
for modelIndex in range(len(modelInputNames))
if modelInputTypes[modelIndex] == Model.VARIABLE
])
if not loadVariableNames <= modelVariableNames:
compatible = False
prompt = "This file does not have the same variable names as the setup model!"
if not compatible:
QMessageBox.warning(self, self.tr("UQ GUI"), self.tr(prompt),
QMessageBox.Ok, QMessageBox.Ok)
return
# UI indications of success
self.sampleFileNameEdit.setText(sampleFile)
self.fileLoaded = True
self.previewButton.setEnabled(True)
self.doneButton.setEnabled(True)
# Create loadData object
self.loadData = SampleData(self.model)
self.loadData.setFromFile(False)
if fromSimpleFile:
self.loadData.setSampleMethod(SamplingMethods.MC)
else:
self.loadData.setSampleMethod(data.getSampleMethod())
self.loadData.setNumSamples(numSamples)
resultData = numpy.zeros([numSamples, self.model.getNumInputs()])
modelDefaults = self.model.getInputDefaults()
loadIndex = 0
if fromSimpleFile:
for modelIndex, modelInType in enumerate(modelInputTypes):
if modelInType == Model.FIXED:
resultData[:, modelIndex] = [modelDefaults[modelIndex]
] * numSamples
else:
inDataCol = inputData[:, loadIndex]
resultData[:, modelIndex] = inDataCol
loadIndex += 1
else: # full file
# Create mapping between model names and load names
loadDefaults = self.loadData.getInputDefaults()
for modelIndex, (modelInName, modelInType) in enumerate(
zip(modelInputNames, modelInputTypes)):
if modelInName in loadInputNames:
loadIndex = loadInputNames.index(modelInName)
if modelInType == Model.FIXED:
if modelInName in loadInputNames:
value = loadDefaults[loadIndex]
else:
value = modelDefaults[modelIndex]
resultData[:, modelIndex] = [value] * numSamples
else: # Variable
if modelInName not in loadInputNames:
resultData[:,
modelIndex] = [modelDefaults[modelIndex]
] * numSamples
elif loadInputTypes[loadIndex] == Model.FIXED:
resultData[:, modelIndex] = [loadDefaults[loadIndex]
] * numSamples
else:
inDataCol = inputData[:, loadIndex]
resultData[:, modelIndex] = inDataCol
self.loadData.setInputDistributions(data.getInputDistributions())
dists = []
for modelIndex in range(self.model.getNumInputs()):
d = Distribution(Distribution.SAMPLE)
d.setParameterValues(sampleFile, modelIndex + 1)
dists.append(d)
self.loadData.setInputDistributions(dists)
self.loadData.setInputData(resultData)
self.loadData.setRunState([False] * numSamples)
def writeOUUdata(outfile, outputs, constraints, derivatives, data, xtable,
**kwargs):
# Charles TODO: Handle y is now a list of inputs
# Charles TODO: Handle derivatives
# defaults
rseed = None
driver = data.getDriverName()
if driver is None:
driver = 'NONE'
optdriver = data.getOptDriverName()
if optdriver is None:
optdriver = 'NONE'
ensoptdriver = data.getEnsembleOptDriverName()
if ensoptdriver is None:
ensoptdriver = 'NONE'
auxdriver = data.getAuxDriverName()
if auxdriver is None:
auxdriver = 'NONE'
inputLB = None
inputUB = None
inputDefaults = None
distributions = None
init_input = None
# process keyworded arguments
for key in kwargs:
k = key.lower()
if k == 'randseed':
rseed = kwargs[key]
elif k == 'driver':
driver = kwargs[key]
elif k == 'optdriver':
optdriver = kwargs[key]
elif k == 'ensoptdriver':
ensoptdriver = kwargs[key]
elif k == 'auxdriver':
auxdriver = kwargs[key]
elif k == 'inputlowerbounds':
inputLB = kwargs[key]
elif k == 'inputupperbounds':
inputUB = kwargs[key]
elif k == 'inputpdf':
distributions = kwargs[key]
elif k == 'init_input':
init_input = kwargs[key]
inputTypes = data.getInputTypes()
nInputs = data.getNumInputs()
inputNames = data.getInputNames()
variableInputIndices = []
for e in xtable:
if e['type'] != u'Fixed':
variableInputIndices.append(inputNames.index(e['name']))
nVariableInputs = len(variableInputIndices)
nOutputs = len(outputs)
nSamples = num_fmin = 1 # number of random restarts
nConstraints = constraints.count(True)
nDerivatives = derivatives.count(True)
totalOutputs = nOutputs + nConstraints + nDerivatives
f = open(outfile, 'w')
if init_input:
f.write('PSUADE_IO\n')
f.write('%d %d %d\n' % (nVariableInputs, totalOutputs, nSamples))
f.write("1 0\n") # assume initial point has not been run
for x in init_input:
f.write(' % .16e\n' % x)
for i in xrange(totalOutputs):
f.write(' 9.9999999999999997e+34\n')
f.write("PSUADE_IO\n")
# TO DO: merge with RSAnalyzer.writeRSdata()
f.write('PSUADE\n')
# ... input ...
numFixed = nInputs - nVariableInputs
f.write('INPUT\n')
if numFixed > 0:
f.write(' num_fixed %d\n' % numFixed)
f.write(' dimension = %d\n' % nVariableInputs)
if inputLB is None:
inputLB = data.getInputMins()
if inputUB is None:
inputUB = data.getInputMaxs()
if inputDefaults is None:
inputDefaults = data.getInputDefaults()
indices = range(nInputs)
variableIndex = 1
fixedIndex = 1
for i, name, inType, lb, ub, default in zip(indices, inputNames, \
inputTypes, inputLB, inputUB, inputDefaults):
if i in variableInputIndices: #inType == Model.VARIABLE:
f.write(' variable %d %s = % .16e % .16e\n' % \
(variableIndex, name, lb, ub))
variableIndex = variableIndex + 1
else:
f.write(' fixed %d %s = % .16e\n' %
(fixedIndex, name, default))
fixedIndex = fixedIndex + 1
# inject discrete variables in psuade
opttypes = []
cnt = 0
for e in xtable:
cnt = cnt + 1
t = e['type']
if t == u'Opt: Primary Discrete (Z1d)':
opttypes.append(cnt)
nn = len(opttypes)
for ii in range(nn):
jj = opttypes[ii]
f.write(' discrete %d\n' % (jj))
if distributions is None:
distributions = SampleData.getInputDistributions(data)
for i, inType, dist in zip(indices, inputTypes, distributions):
if i in variableInputIndices: #inType == Model.VARIABLE:
distType = dist.getDistributionType()
distParams = dist.getParameterValues()
if distType != Distribution.UNIFORM:
f.write(' PDF %d %c' % (i+1, \
Distribution.getPsuadeName(distType)))
if distType == Distribution.SAMPLE:
error = 'OUU: In function writeOUUdata(), '
error = error + 'SAMPLE distribution is not supported.'
Common.showError(error)
return None
else:
if distParams[0] is not None:
f.write(' % .16e' % distParams[0])
if distParams[1] is not None:
f.write(' % .16e' % distParams[1])
f.write('\n')
f.write('END\n')
# ... output ...
outActive = nOutputs
nConstrs = 0
nDerivs = 0
for ii in range(len(constraints)):
if constraints[ii]:
outActive = outActive + 1
nConstrs = nConstrs + 1
for ii in range(len(derivatives)):
if derivatives[ii]:
outActive = outActive + 1
nDerivs = nDerivs + 1
if (nOutputs != 1):
error = 'OUU: In function writeOUUdata(), '
error = error + 'multi-objective optimization not supported.'
Common.showError(error)
return None
else:
if ((nConstrs > 0) and (nDerivs > 0)):
error = 'OUU: In function writeOUUdata(), '
error = error + 'LBFGS does not support inequality constraints.'
Common.showError(error)
return None
elif ((nDerivs > 0) and (nDerivs != nVariableInputs)):
error = 'OUU: In function writeOUUdata(), '
error = error + 'Number of derivatives not correct'
Common.showError(error)
return None
f.write('OUTPUT\n')
f.write(' dimension = %d\n' % (outActive))
outputNames = SampleData.getOutputNames(data)
for ii in range(nOutputs):
ind = outputs[ii]
f.write(' variable %d %s\n' % (ii + 1, outputNames[ind - 1]))
print(' variable %d %s\n' % (ii + 1, outputNames[ind - 1]))
outActive = nOutputs + 1
for ii in range(len(constraints)):
if constraints[ii]:
f.write(' variable %d %s\n' % (outActive, outputNames[ii]))
print(' variable %d %s\n' % (outActive, outputNames[ii]))
outActive = outActive + 1
for ii in range(len(derivatives)):
if derivatives[ii]:
f.write(' variable %d %s\n' % (outActive, outputNames[ii]))
print(' variable %d %s\n' % (outActive, outputNames[ii]))
outActive = outActive + 1
f.write('END\n')
# ... method ...
f.write('METHOD\n')
f.write(' sampling = MC\n') # OUU uses this to create
f.write(' num_samples = 1\n') # initial guess
if rseed is not None:
f.write('random_seed = %d\n' % rseed) # random seed
f.write('END\n')
# ... application ...
f.write('APPLICATION\n')
if platform.system() == 'Windows':
import win32api
if driver != 'NONE' and driver != 'PSUADE_LOCAL':
driver = win32api.GetShortPathName(driver)
if optdriver != 'NONE' and optdriver != 'PSUADE_LOCAL':
optdriver = win32api.GetShortPathName(optdriver)
if ensoptdriver != 'NONE' and ensoptdriver != 'PSUADE_LOCAL':
ensoptdriver = win32api.GetShortPathName(ensoptdriver)
if auxdriver != 'NONE' and auxdriver != 'PSUADE_LOCAL':
auxdriver = win32api.GetShortPathName(auxdriver)
f.write(' driver = %s\n' % driver)
f.write(' opt_driver = %s\n' % optdriver)
f.write(' ensemble_opt_driver = %s\n' % ensoptdriver)
f.write(' aux_opt_driver = %s\n' % auxdriver)
f.write(' launch_interval = 0\n')
f.write('END\n')
# ... analysis ...
f.write('ANALYSIS\n')
if (nDerivs > 0):
f.write(' optimization method = ouu_lbfgs\n')
else:
f.write(' optimization method = ouu\n')
f.write(' optimization num_local_minima = 1\n')
f.write(' optimization max_feval = 1000000\n')
f.write(' optimization fmin = 0.0\n')
f.write(' optimization tolerance = 1.000000e-06\n')
f.write(' optimization num_fmin = %d\n' % num_fmin)
f.write(' optimization print_level = 3\n')
#f.write(' analyzer output_id = %d\n' % y)
f.write(' analyzer output_id = 1\n')
f.write(' opt_expert\n')
f.write(' printlevel 0\n')
f.write('END\n')
f.write('END\n')
f.close()
return outfile
