def __init__(
self,
value=0,
vmin=0,
vmax=1,
vdflt=0,
# vector=dict(),
ipvname=None,
opvname=None,
unit="",
vst="user",
vdesc="",
tags=[],
dtype=float,
dist=Distribution(Distribution.UNIFORM),
):
"""
Initialize the variable list
Args:
value: variable value
vmin: min value
vmax: max value
vdflt: default value
unit: string description of units of measure
vst: A sring description of a group for the variable {"user", "sinter"}
vdesc: A sentence or so describing the variable
tags: List of string tags for the variable
dtype: type of data {float, int, str, object}
dist: distribution type for UQ
"""
self.dtype = dtype
value = value
if vmin is None:
vmin = value
if vmax is None:
vmax = value
if vdflt is None:
vdflt = value
self.min = vmin # maximum value
self.max = vmax # minimum value
self.default = vdflt # default value
self.unit = unit # units of measure
self.set = vst # variable set name user or sinter so I know if
# user added it or from sinter configuration file
self.desc = vdesc # variable description
self.scaled = 0.0 # scaled value for the variable
self.scaling = "None" # type of variable scaling
self.minScaled = 0.0 # scaled minimum
self.maxScaled = 0.0 # scaled maximum
self.tags = tags # set of tags for use in heat integration or
# other searching and sorting
self.con = False # true if the input is set through connection
self.setValue(value) # value of the variable
# self.setVector(vector) # dictionary for vector variables
self.setType(dtype)
self.setname(ipvname, opvname)
self.dist = copy.copy(dist)
def createPsuadeInFile(data, filename, includePDF=True):
outf = open(filename, 'w')
outf.write('PSUADE\n')
#Write inputs
outf.write('INPUT\n')
outf.write(' dimension = %d\n' % data.getNumInputs())
names = data.getInputNames()
mins = data.getInputMins()
maxs = data.getInputMaxs()
indices = list(range(data.getNumInputs()))
for i, name, minimum, maximum in zip(indices, names, mins, maxs):
outf.write(' variable %d %s = %e %e\n' %
(i + 1, name, minimum, maximum))
distributions = data.getInputDistributions()
for i, dist in zip(indices, distributions):
distType = dist.getDistributionType()
distParams = dist.getParameterValues()
if distType == Distribution.SAMPLE:
outf.write(' PDF %d %c' %
(i + 1, Distribution.getPsuadeName(distType)))
if distParams[0] is not None:
filename = distParams[0]
if platform.system() == 'Windows':
import win32api
filename = win32api.GetShortPathName(filename)
outf.write(' %s' % filename)
if distParams[1] is not None:
outf.write(' %d' % distParams[1])
outf.write('\n')
elif includePDF: # write out PDF info for all non-uniform PDF types
if distType != Distribution.UNIFORM:
outf.write(' PDF %d %c' %
(i + 1, Distribution.getPsuadeName(distType)))
if distParams[0] is not None:
outf.write(' %e' % distParams[0])
if distParams[1] is not None:
outf.write(' %e' % distParams[1])
outf.write('\n')
outf.write('END\n')
#Write outputs
outf.write('OUTPUT\n')
if data.getNumOutputs() == 0:
outf.write(' dimension = 1\n')
names = ['ghostOuput']
indices = list(range(1))
for i, name in zip(indices, names):
outf.write(' variable %d %s\n' % (i + 1, name))
else:
outf.write(' dimension = %d\n' % data.getNumOutputs())
names = data.getOutputNames()
indices = list(range(data.getNumOutputs()))
for i, name in zip(indices, names):
outf.write(' variable %d %s\n' % (i + 1, name))
outf.write('END\n')
#Write Method
outf.write('METHOD\n')
outf.write(' sampling = %s\n' %
SamplingMethods.getPsuadeName(data.getSampleMethod()))
outf.write(' num_samples = %d\n' % data.getNumSamples())
if data.getSampleMethod() != SamplingMethods.GMOAT:
outf.write(' randomize\n')
outf.write('END\n')
#Write Application
outf.write('APPLICATION\n')
driverString = data.getDriverName()
if driverString is None:
driverString = 'NONE'
elif platform.system() == 'Windows':
if os.path.exists(driverString):
import win32api
driverString = win32api.GetShortPathName(driverString)
else:
driverString = 'NONE'
driverString = 'NONE'
outf.write(' driver = %s\n' % driverString)
outf.write(' save_frequency = 1\n')
outf.write('END\n')
#Write Analysis
outf.write('ANALYSIS\n')
outf.write(' diagnostics 2\n')
outf.write('END\n')
outf.write('END\n')
outf.close()
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)
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 updateInputVariables(self):
'''
Update the input variables table from the node contents
'''
table = self.inputVarTable
vars = self.node.inVars
table.clearContents()
table.setRowCount(len(vars))
row = 0
for name in sorted(vars.keys(), key=lambda s: s.lower()):
var = vars[name]
if var.con == 1:
bgColor = QColor(255, 255, 200)
elif var.con ==2:
bgColor = QColor(255, 220, 230)
else:
bgColor = QColor(255, 255, 255)
gh.setTableItem(table, row, self.ivCols["Name"], name,
bgColor=bgColor, editable=False)
gh.setTableItem(table, row,
self.ivCols["Value"],
var.value,
jsonEnc = True,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Default"],
var.default,
jsonEnc = True,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Min"],
var.min,
jsonEnc = True,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Max"],
var.max,
jsonEnc = True,
bgColor = bgColor)
gh.setTableItem(table,
row, self.ivCols["Tags"],
var.tags,
jsonEnc = True,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Unit"],
var.unit,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Type"],
pullDown= ["float", "int", "str"],
text=var.typeStr(),
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Description"],
var.desc,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Distribution"],
Distribution.getFullName(var.dist.type),
pullDown=Distribution.fullNames,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Param 1"],
var.dist.firstParamValue,
jsonEnc = True,
bgColor = bgColor)
gh.setTableItem(table, row,
self.ivCols["Param 2"],
var.dist.secondParamValue,
jsonEnc = True,
bgColor = bgColor)
row += 1
table.resizeColumnsToContents()
self.inputVarTable.setSelectionMode(
QAbstractItemView.ExtendedSelection)
self.inputVarTable.setSelectionBehavior(
QAbstractItemView.SelectRows)
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
def __init__(self, info, parent=None):
super(AnalysisInfoDialog, self).__init__(parent)
self.setWindowTitle('Analysis Additional Info')
self.resize(400, 400)
self.gridLayout = QGridLayout(self)
self.table = QTableWidget()
self.table.setRowCount(len(list(info.keys())))
self.table.setColumnCount(1)
boldFont = QFont()
boldFont.setWeight(75)
boldFont.setBold(True)
totalHeight = 20
totalWidth = 50
row = 0
for key in list(info.keys()):
if key in ('xprior', 'xtable', 'ytable', 'obsTable'):
continue
#item = QTableWidgetItem(key)
#self.table.setItem(row, 0, item)
if isinstance(info[key], (list, tuple)):
strings = []
for strItem in info[key]:
if isinstance(strItem, dict):
ks = list(strItem.keys())
for k in ks:
if strItem[k] is None:
del strItem[k]
strings.append(str(strItem))
item = QTableWidgetItem('\n'.join(strings))
else:
item = QTableWidgetItem(str(info[key]))
self.table.setItem(row, 0, item)
row += 1
if row > 0:
label = QLabel('Additional Info')
label.setFont(boldFont)
self.gridLayout.addWidget(label)
self.gridLayout.addWidget(self.table)
self.table.horizontalHeader().setHidden(True)
self.table.setRowCount(row)
self.table.setVerticalHeaderLabels([key for key in list(info.keys()) if key not in ('xprior', 'xtable', 'ytable', 'obsTable')])
#self.table.verticalHeader().setHidden(True)
self.table.setWordWrap(True)
self.table.resizeColumnsToContents()
self.table.resizeRowsToContents()
self.show() # Needed for headers to be correctly sized
width = 2 + self.table.verticalHeader().width() + self.table.columnWidth(0)
if self.table.verticalScrollBar().isVisible():
width += self.table.verticalScrollBar().width()
self.table.setMinimumWidth(width)
maxHeight = 3
for i in range(row):
maxHeight += self.table.rowHeight(i)
self.table.setMinimumHeight(maxHeight)
totalHeight += maxHeight + 20
if width + 20 > totalWidth:
totalWidth = width + 20
# Show table
for key in info:
if key in ('xprior', 'xtable', 'ytable', 'obsTable'):
#self.resize(800, 400)
values = info[key]
for d in values:
if d is not None and 'type' in d and d['type'] == 'Design':
keys = list(d.keys())
for k in keys:
if k not in ('name', 'type'):
del d[k]
if key == 'ytable':
labelString = 'Outputs'
elif key == 'obsTable':
labelString = 'Experiments'
else:
labelString = 'Inputs'
label = QLabel(labelString)
label.setFont(boldFont)
self.gridLayout.addWidget(label)
table = QTableWidget()
self.gridLayout.addWidget(table)
table.setRowCount(len([1 for i in range(len(values)) if values[i] is not None]))
# column headers
if key == 'obsTable':
inputInfo = info['xtable']
designVars = []
for d in inputInfo:
if 'type' in d and d['type'] == 'Design':
designVars.append(d['name'])
columnHeaders = [name + ' Value' for name in designVars]
outputInfo = info['ytable']
outputVars = [d['name'] for d in outputInfo if d is not None]
for out in outputVars:
columnHeaders.append(out + ' Mean')
columnHeaders.append(out + ' Std Dev')
table.setColumnCount(len(columnHeaders))
table.setHorizontalHeaderLabels(columnHeaders)
table.setVerticalHeaderLabels(['Experiment ' + str(num) for num in range(1, len(values) + 1)])
else:
columnSet = set()
if key == 'ytable':
valuesKeys = ['name', 'rsIndex', 'legendreOrder', 'marsBases', 'marsInteractions',
'userRegressionFile']
columnHeaders = ['Output Name', 'RS Type', 'Legendre Order', 'MARS # Basis Functions',
'MARS Deg. of Interaction', 'User Regression File']
else: #xprior, xtable
valuesKeys = ['name', 'type', 'value', 'pdf', 'param1', 'param2', 'min', 'max']
columnHeaders = ['Input Name', 'Type', 'Fixed Value', 'PDF', 'PDF Param 1', 'PDF Param 2', 'Min', 'Max']
for d in values:
if d is not None:
d2 = copy.deepcopy(d)
for key in d2:
if d2[key] is None:
del d[key]
columnSet = columnSet.union(set(d.keys()))
table.setColumnCount(len(columnSet))
usedColumns = []
usedHeaders = []
columnIndices = {}
for i, (valuesKey, header) in enumerate(zip(valuesKeys, columnHeaders)):
if valuesKey in columnSet:
usedColumns.append(valuesKey)
usedHeaders.append(header)
columnIndices[valuesKey] = i
table.setHorizontalHeaderLabels(usedHeaders)
table.verticalHeader().setHidden(True)
table.setWordWrap(True)
r = 0
for i in range(len(values)):
if key == 'obsTable':
for c, string in enumerate(values[r][1:]):
item = QTableWidgetItem(string)
table.setItem(r, c, item)
r += 1
elif values[r] is not None:
for c, colName in enumerate(usedColumns):
if colName in values[r]:
if colName == 'pdf':
string = Distribution.getFullName(values[r][colName])
elif colName == 'rsIndex':
string = ResponseSurfaces.getFullName(values[r][colName])
else:
string = str(values[r][colName])
item = QTableWidgetItem(string)
table.setItem(r, c, item)
r += 1
table.resizeColumnsToContents()
QtCore.QCoreApplication.processEvents()
width = 2
if key == 'obsTable':
width += table.verticalHeader().width()
for i in range(table.columnCount()):
width += table.columnWidth(i)
if table.verticalScrollBar().isVisible():
width += table.verticalScrollBar().width()
if width > 800:
width = 800
table.setMinimumWidth(width)
maxHeight = 3 + table.horizontalHeader().height()
for i in range(table.rowCount()):
maxHeight += table.rowHeight(i)
maxHeight = min([maxHeight, 400])
table.setMinimumHeight(maxHeight)
totalHeight += maxHeight + 20
if width + 20 > totalWidth:
totalWidth = width + 20
self.okButton = QPushButton(self)
self.okButton.setText('OK')
self.okButton.clicked.connect(self.close)
self.gridLayout.addWidget(self.okButton)
self.show()
self.resize(totalWidth, totalHeight)
def __init__(self, info, parent=None):
super(AnalysisInfoDialog, self).__init__(parent)
self.setWindowTitle("Analysis Additional Info")
self.resize(400, 400)
self.gridLayout = QGridLayout(self)
self.table = QTableWidget()
self.table.setRowCount(len(list(info.keys())))
self.table.setColumnCount(1)
boldFont = QFont()
boldFont.setWeight(75)
boldFont.setBold(True)
totalHeight = 20
totalWidth = 50
row = 0
for key in list(info.keys()):
if key in ("xprior", "xtable", "ytable", "obsTable"):
continue
# item = QTableWidgetItem(key)
# self.table.setItem(row, 0, item)
if isinstance(info[key], (list, tuple)):
strings = []
for strItem in info[key]:
if isinstance(strItem, dict):
ks = list(strItem.keys())
for k in ks:
if strItem[k] is None:
del strItem[k]
strings.append(str(strItem))
item = QTableWidgetItem("\n".join(strings))
else:
item = QTableWidgetItem(str(info[key]))
self.table.setItem(row, 0, item)
row += 1
if row > 0:
label = QLabel("Additional Info")
label.setFont(boldFont)
self.gridLayout.addWidget(label)
self.gridLayout.addWidget(self.table)
self.table.horizontalHeader().setHidden(True)
self.table.setRowCount(row)
self.table.setVerticalHeaderLabels(
[
key
for key in list(info.keys())
if key not in ("xprior", "xtable", "ytable", "obsTable")
]
)
# self.table.verticalHeader().setHidden(True)
self.table.setWordWrap(True)
self.table.resizeColumnsToContents()
self.table.resizeRowsToContents()
self.show() # Needed for headers to be correctly sized
width = 2 + self.table.verticalHeader().width() + self.table.columnWidth(0)
if self.table.verticalScrollBar().isVisible():
width += self.table.verticalScrollBar().width()
self.table.setMinimumWidth(width)
maxHeight = 3
for i in range(row):
maxHeight += self.table.rowHeight(i)
self.table.setMinimumHeight(maxHeight)
totalHeight += maxHeight + 20
if width + 20 > totalWidth:
totalWidth = width + 20
# Show table
for key in info:
if key in ("xprior", "xtable", "ytable", "obsTable"):
# self.resize(800, 400)
values = info[key]
for d in values:
if d is not None and "type" in d and d["type"] == "Design":
keys = list(d.keys())
for k in keys:
if k not in ("name", "type"):
del d[k]
if key == "ytable":
labelString = "Outputs"
elif key == "obsTable":
labelString = "Experiments"
else:
labelString = "Inputs"
label = QLabel(labelString)
label.setFont(boldFont)
self.gridLayout.addWidget(label)
table = QTableWidget()
self.gridLayout.addWidget(table)
table.setRowCount(
len([1 for i in range(len(values)) if values[i] is not None])
)
# column headers
if key == "obsTable":
inputInfo = info["xtable"]
designVars = []
for d in inputInfo:
if "type" in d and d["type"] == "Design":
designVars.append(d["name"])
columnHeaders = [name + " Value" for name in designVars]
outputInfo = info["ytable"]
outputVars = [d["name"] for d in outputInfo if d is not None]
for out in outputVars:
columnHeaders.append(out + " Mean")
columnHeaders.append(out + " Std Dev")
table.setColumnCount(len(columnHeaders))
table.setHorizontalHeaderLabels(columnHeaders)
table.setVerticalHeaderLabels(
["Experiment " + str(num) for num in range(1, len(values) + 1)]
)
else:
columnSet = set()
if key == "ytable":
valuesKeys = [
"name",
"rsIndex",
"legendreOrder",
"marsBases",
"marsInteractions",
"userRegressionFile",
]
columnHeaders = [
"Output Name",
"RS Type",
"Legendre Order",
"MARS # Basis Functions",
"MARS Deg. of Interaction",
"User Regression File",
]
else: # xprior, xtable
valuesKeys = [
"name",
"type",
"value",
"pdf",
"param1",
"param2",
"min",
"max",
]
columnHeaders = [
"Input Name",
"Type",
"Fixed Value",
"PDF",
"PDF Param 1",
"PDF Param 2",
"Min",
"Max",
]
for d in values:
if d is not None:
d2 = copy.deepcopy(d)
for key in d2:
if d2[key] is None:
del d[key]
columnSet = columnSet.union(set(d.keys()))
table.setColumnCount(len(columnSet))
usedColumns = []
usedHeaders = []
columnIndices = {}
for i, (valuesKey, header) in enumerate(
zip(valuesKeys, columnHeaders)
):
if valuesKey in columnSet:
usedColumns.append(valuesKey)
usedHeaders.append(header)
columnIndices[valuesKey] = i
table.setHorizontalHeaderLabels(usedHeaders)
table.verticalHeader().setHidden(True)
table.setWordWrap(True)
r = 0
for i in range(len(values)):
if key == "obsTable":
for c, string in enumerate(values[r][1:]):
item = QTableWidgetItem(string)
table.setItem(r, c, item)
r += 1
elif values[r] is not None:
for c, colName in enumerate(usedColumns):
if colName in values[r]:
if colName == "pdf":
string = Distribution.getFullName(
values[r][colName]
)
elif colName == "rsIndex":
string = ResponseSurfaces.getFullName(
values[r][colName]
)
else:
string = str(values[r][colName])
item = QTableWidgetItem(string)
table.setItem(r, c, item)
r += 1
table.resizeColumnsToContents()
QtCore.QCoreApplication.processEvents()
width = 2
if key == "obsTable":
width += table.verticalHeader().width()
for i in range(table.columnCount()):
width += table.columnWidth(i)
if table.verticalScrollBar().isVisible():
width += table.verticalScrollBar().width()
if width > 800:
width = 800
table.setMinimumWidth(width)
maxHeight = 3 + table.horizontalHeader().height()
for i in range(table.rowCount()):
maxHeight += table.rowHeight(i)
maxHeight = min([maxHeight, 400])
table.setMinimumHeight(maxHeight)
totalHeight += maxHeight + 20
if width + 20 > totalWidth:
totalWidth = width + 20
self.okButton = QPushButton(self)
self.okButton.setText("OK")
self.okButton.clicked.connect(self.close)
self.gridLayout.addWidget(self.okButton)
self.show()
self.resize(totalWidth, totalHeight)