class SetupComparisonConfidence(formSetupComparisonConfidence,baseSetupComparisonConfidence):
""" dernière étape de définition d'une analyse de type comparison ou confidence
"""
def __init__(self,analysis,parent=None):
super(SetupComparisonConfidence,self).__init__(parent)
self.parent=parent
self.parents = Parents(self.parent)
self.analysis = analysis
self.scNumList = []
self.dico_values = {}
self.createWidgets()
self.ui.verticalLayout_2.setAlignment(Qt.AlignHCenter)
self.ui.verticalLayout_2.setAlignment(Qt.AlignTop)
self.restoreAnalysisValues()
self.parents.updateDoc(self)
def createWidgets(self):
self.ui=self
self.ui.setupUi(self)
self.deInterValuesW = []
self.lrInterValuesW = []
self.ui.projectNameEdit.setText(self.parents.dir)
self.ui.gridLayout.setAlignment(Qt.AlignTop)
self.ui.posteriorDistributionFrame.hide()
QObject.connect(self.ui.exitButton,SIGNAL("clicked()"),self.exit)
QObject.connect(self.ui.okButton,SIGNAL("clicked()"),self.validate)
QObject.connect(self.ui.redefButton,SIGNAL("clicked()"),self.redefineScenarios)
QObject.connect(self.ui.numRegCombo,SIGNAL("currentIndexChanged(QString)"),self.updateInterValues)
QObject.connect(self.ui.deEdit,SIGNAL("textChanged(QString)"),self.updateInterValues)
QObject.connect(self.ui.lrEdit,SIGNAL("textChanged(QString)"),self.updateInterValues)
QObject.connect(self.ui.posteriorDistributionSampleSizeEdit,SIGNAL("textChanged(QString)"),self.updateInterValues)
QObject.connect(self.ui.logisticRegressioncheckBox,SIGNAL("stateChanged(int)"),self.updateInterValues)
if "confidence" in self.analysis.category :
self.ui.label.setText("Confidence in scenario choice")
self.setScenarios([self.analysis.chosenSc])
self.setCandidateScenarios(self.analysis.candidateScList)
self.setRecordValues(self.analysis.candidateScList)
self.ui.redefButton.hide()
self.ui.numRegCombo.clear()
self.ui.numRegCombo.addItem("0")
self.ui.numRegCombo.addItem("1")
#self.ui.notdsEdit.setText("500")
self.ui.intermediateValuesFrame.hide()
if self.analysis.category == "confidence_posterior_global" :
self.ui.posteriorDistributionFrame.show()
self.ui.notdsLabel.setText(self.ui.notdsLabel.text().replace("[TO-REPLACE]", "pseudo-observed"))
self.ui.scenarioProbaExplainLabel.setText(self.ui.scenarioProbaExplainLabel.text().replace("[TO-REPLACE]", "pseudo-observed"))
else: # assume self.analysis.category == "compare"
self.ui.logisticRegressioncheckBox.setChecked(True)
self.ui.logisticRegressioncheckBox.hide()
self.ui.notdsEdit.hide()
self.ui.notdsLabel.hide()
self.ui.candidateLabel.hide()
self.setScenarios([self.analysis.chosenSc])
self.setCandidateScenarios(self.analysis.candidateScList)
self.setRecordValues(self.analysis.candidateScList)
self.ui.notdsLabel.setText(self.ui.notdsLabel.text().replace("[TO-REPLACE]", "observed"))
self.ui.scenarioProbaExplainLabel.setText(self.ui.scenarioProbaExplainLabel.text().replace("[TO-REPLACE]", "observed"))
self.ui.numRegCombo.setCurrentIndex(1)
self.ui.deEdit.setText("500")
self.ui.analysisNameLabel.setText(self.analysis.name)
def updateInterValues(self,numstr):
if self.ui.logisticRegressioncheckBox.isChecked() :
self.lrEdit.setEnabled(True)
if "confidence" in self.analysis.category :
self.ui.numRegCombo.setCurrentIndex(self.ui.numRegCombo.findText("1"))
else :
self.lrEdit.setDisabled(True)
if "confidence" in self.analysis.category :
self.ui.numRegCombo.setCurrentIndex(self.ui.numRegCombo.findText("0"))
for w in self.lrInterValuesW:
w.hide()
self.ui.lrValLayout.removeWidget(w)
for w in self.deInterValuesW:
w.hide()
self.ui.deValLayout.removeWidget(w)
self.lrInterValuesW = []
self.deInterValuesW = []
try:
#de = int(self.ui.deEdit.text())
lr = int(self.ui.lrEdit.text())
numreg = int(self.ui.numRegCombo.currentText())
if numreg == 0:
self.ui.lrValuesFrame.setDisabled(True)
self.ui.lrEdit.setDisabled(True)
self.analysis.logreg = False
else :
self.ui.lrValuesFrame.setDisabled(False)
self.ui.lrEdit.setDisabled(False)
self.analysis.logreg = True
#dedec = de/numreg
lrdec = lr/numreg
for i in range(numreg):
lrlab = QLabel(str(lr))
#delab = QLabel(str(de))
self.lrInterValuesW.append(lrlab)
#self.deInterValuesW.append(delab)
self.ui.lrValLayout.addWidget(lrlab)
#self.ui.deValLayout.addWidget(delab)
#de -= dedec
lr -= lrdec
except Exception as e:
print e
def restoreAnalysisValues(self):
if self.analysis.computationParameters != "":
cp = self.analysis.computationParameters
self.ui.cnosdEdit.setText(cp.split('n:')[1].split(';')[0])
self.ui.deEdit.setText(cp.split('d:')[1].split(';')[0])
numreg = cp.split('m:')[1].split(';')[0]
self.ui.numRegCombo.setCurrentIndex(self.ui.numRegCombo.findText(numreg))
if numreg in [1, "1"] :
self.ui.logisticRegressioncheckBox.setChecked(True)
else :
self.ui.logisticRegressioncheckBox.setChecked(False)
self.ui.lrEdit.setText(cp.split('l:')[1].split(';')[0])
if "confidence" in self.analysis.category :
if self.analysis.category == "confidence_posterior_global":
if "z:" in cp :
self.ui.posteriorDistributionSampleSizeEdit.setText(cp.split('z:')[1].split(';')[0])
if "c:" in cp :
self.ui.notdsEdit.setText(cp.split('c:')[1].split(';')[0])
elif self.analysis.category == "confidence_prior_global":
if "b:" in cp :
self.ui.notdsEdit.setText(cp.split('b:')[1].split(';')[0])
elif self.analysis.category in ["confidence_prior_specific", "confidence"]:
if "t:" in cp :
self.ui.notdsEdit.setText(cp.split('t:')[1].split(';')[0])
def checkAll(self):
problems = ""
try:
if "confidence" in self.analysis.category :
notds = int(self.ui.notdsEdit.text())
if self.analysis.category == "confidence_posterior_global":
linearRegrassion = int(self.ui.posteriorDistributionSampleSizeEdit.text())
lr = int(self.ui.lrEdit.text())
de = int(self.ui.deEdit.text())
cnosd = int(self.ui.cnosdEdit.text())
except Exception as e:
problems += "Only non-empty integer values are accepted\n"
if problems == "":
return True
else:
output.notify(self,"value problem",problems)
return False
def validate(self):
""" defini les computation parameters de l'analyse et ajoute celle-ci au projet
"""
analysis_in_edition = (self.analysis.computationParameters != "")
self.analysis.candidateScList = self.scNumList
self.majDicoValues()
chosen_scs_txt = ""
for cs in self.scNumList:
chosen_scs_txt+="%s,"%str(cs)
chosen_scs_txt = chosen_scs_txt[:-1]
if self.checkAll():
if self.analysis.category == "compare":
self.analysis.computationParameters = "s:%s;n:%s;d:%s;l:%s;m:%s;f:%s"%(chosen_scs_txt,self.dico_values['choNumberOfsimData'],self.dico_values['de'],self.dico_values['lr'],self.dico_values['numReg'],self.analysis.fda)
elif "confidence" in self.analysis.category : # == "confidence":
# FIXED :
# "/home/dehneg/diyabc/src-JMC-C++/general"
# -p "/media/psf/Home/VMshare/example_2_microsat_sequence_data_complexe_scenarios_ghost_pop_project_2013_7_9-1/"
# -f "s:1,2;r:1;n:203900;m:1;d:501;l:2039;t:509;f:0;h:t2=25500.0 t1=5005.0 ra=0.5 NS1=25500.0 N1=25500.0 N2=25500.0
# N3=5005.0 NS2=25500.0 ta=5005.0;u:g1(0.00055 2 0.2 2 5.005e-06 2)*g2(0.00055 2 0.2 2 5.005e-06 2)*g3(0.00055
# 2 0.2 2 5.005e-06 2)*g4(5.5e-09 2 10.025 2)*g5(5.05e-08 2 10.025 2)"
# -i fixed
# -g 509
# -m
# -t 1
#PRIOR
#"/home/dehneg/diyabc/src-JMC-C++/general"
# -p "/media/psf/Home/VMshare/example_2_microsat_sequence_data_complexe_scenarios_ghost_pop_project_2013_7_9-1/"
# -f "s:1,2;r:1;n:203900;m:1;d:501;l:2039;t:509;f:0;h:t2=UN[1000,50000.0,0.0,0.0] t1=UN[10.0,10000.0,0.0,0.0] ra=UN[0.001,0.999,0.0,0.0]
# NS1=UN[1000,50000.0,0.0,0.0] N1=UN[1000,50000.0,0.0,0.0] N2=UN[1000,50000.0,0.0,0.0] N3=UN[10,10000.0,0.0,0.0]
# NS2=UN[1000,50000.0,0.0,0.0] ta=UN[10.0,10000.0,0.0,0.0] ta>t1 t2>ta;u:g1(UN[1.00E-004,1.00E-3,0.0005,2]
# GA[1.00E-005,1.00E-002,Mean_u,2] UN[1.00E-001,3.00E-001,0.22,2] GA[1.00E-002,9.00E-001,Mean_P,2]
# LU[1.00E-008,1.00E-005,1.00E-007,2] GA[1.00E-009,1.00E-004,Mean_u_SNI,2])*g2(UN[1.00E-004,1.00E-3,0.0005,2]
# GA[1.00E-005,1.00E-002,Mean_u,2] UN[1.00E-001,3.00E-001,0.22,2] GA[1.00E-002,9.00E-001,Mean_P,2]
# LU[1.00E-008,1.00E-005,1.00E-007,2] GA[1.00E-009,1.00E-004,Mean_u_SNI,2])*g3(UN[1.00E-004,1.00E-3,0.0005,2]
# GA[1.00E-005,1.00E-002,Mean_u,2] UN[1.00E-001,3.00E-001,0.22,2] GA[1.00E-002,9.00E-001,Mean_P,2]
# LU[1.00E-008,1.00E-005,1.00E-007,2]
# GA[1.00E-009,1.00E-004,Mean_u_SNI,2])*g4(UN[1.00E-9,1.00E-8,5E-9,2] GA[1.00E-10,1.00E-7,Mean_u,2] UN[0.050,20,10,2]
# GA[0.050,20,Mean_k1,2] UN[0.050,20,10,2] GA[0.050,20,Mean_k2,2])*g5(UN[1.00E-9,1.00E-7,5E-9,2] GA[1.00E-9,1.00E-6,Mean_u,2]
# UN[0.050,20,10,2] GA[0.050,20,Mean_k1,2] UN[0.050,20,10,2] GA[0.050,20,Mean_k2,2])"
# -i prior
# -g 509 -m -t 1
candListTxt = ""
for cs in self.analysis.candidateScList:
candListTxt+="%s,"%str(cs)
candListTxt = candListTxt[:-1]
strparam = ""
strparam += "n:%s;"%self.dico_values['choNumberOfsimData']
strparam += "m:%s;"%self.dico_values['numReg']
strparam += "d:%s;"%self.dico_values['de']
strparam += "f:%s;"%self.analysis.fda
if self.analysis.category == "confidence_posterior_global":
strparam += "z:%s;" % self.dico_values['linearRegression']
strparam += "l:%s;" % self.dico_values['lr']
strparam += "c:%s;"%self.dico_values['notds']
strparam += ""
elif self.analysis.category == "confidence_prior_global":
strparam += "l:%s;"%self.dico_values['lr']
strparam += "b:%s;"%self.dico_values['notds']
elif self.analysis.category == "confidence_prior_specific":
strparam += "s:%s;"%candListTxt
strparam += "r:%s;"%self.analysis.chosenSc
strparam += "l:%s;"%self.dico_values['lr']
strparam += "t:%s;"%self.dico_values['notds']
if self.analysis.drawn is 'posterior':
strparam += "po;z:%s;a:%s"% (self.dico_values['posteriorNumDataSets'], self.dico_values['posteriorSimNumDataSets'])
else :
strparam += "h:"
if self.analysis.drawn:
for paramname in self.analysis.histParamsDrawn.keys():
l = self.analysis.histParamsDrawn[paramname]
strparam += "%s="%paramname
strparam += "%s[%s,%s,%s,%s] "%(l[1],l[2],l[3],l[4],l[5])
for ctxt in self.analysis.condTxtList:
strparam += "%s "%ctxt
else:
for paramname in self.analysis.histParamsFixed.keys():
l = self.analysis.histParamsFixed[paramname]
strparam += "%s="%paramname
strparam += "%s "%l[1]
strparam = strparam[:-1]
if self.analysis.drawn:
mutmod = self.analysis.mutationModelDrawn
else:
mutmod = self.analysis.mutationModelFixed
if len(mutmod)>0:
strparam += ";u:"
if type(mutmod[0]) == type(u'plop'):
for ind,gr in enumerate(mutmod):
strparam += "g%s("%(ind+1)
strgr = gr.strip()
strgr = strgr.split('\n')
for j,elem in enumerate(strgr):
if elem.split()[0] != "MODEL":
to_add = strgr[j].split()[1]
strparam += "%s "%to_add
# virer le dernier espace
strparam = strparam[:-1]
strparam += ")*"
else:
for ind,gr in enumerate(mutmod):
strparam += "g%s("%(ind+1)
for num in gr:
strparam += "%s "%num
# virer le dernier espace
strparam = strparam[:-1]
strparam += ")*"
# virer le dernier '-'
strparam = strparam[:-1]
self.analysis.computationParameters = strparam
if not analysis_in_edition:
self.parents.addAnalysis(self.analysis)
self.exit()
def setRecordValues(self,scList):
if scList in [None, False, [None], [False]] or len(scList) == 0 :
scList = [x for x in range(1,self.parents.nb_sc+1)]
sumRec = 0
for i in scList:
sumRec+=self.parents.readNbRecordsOfScenario(int(i))
self.ui.cnosdEdit.setText(str(sumRec))
# total number of simulated data default
self.ui.totNumSimLabel.setText(str(sumRec))
# logistic regression default
onePc = sumRec / 100
if onePc < 1000:
if sumRec < 1000:
onePc = sumRec
else:
onePc = 1000
self.ui.lrEdit.setText(str(onePc))
# posteriorDistributionSampleSize default
#onePcScn = (sumRec / 100 ) / len(scList)
#self.ui.posteriorDistributionSampleSizeEdit.setText(str(onePcScn))
def setCandidateScenarios(self,scList):
""" ecrit la liste des scenarios candidats
"""
if scList in [None, False, [None], [False]] or len(scList) == 0 :
txt = ""
else :
plur= ""
if len(scList)>1:
plur = "s"
lstxt=""
self.scNumList = []
for i in scList:
lstxt+="%s, "%i
self.scNumList.append(i)
lstxt = lstxt[:-2]
txt = "Candidate scenario%s : %s"%(plur,lstxt)
self.ui.candidateLabel.setText(txt)
def setScenarios(self,scList):
""" ecrit la liste des scenarios à comparer
"""
if scList in [None, False, [None], [False]] or len(scList) == 0 :
txt = ""
else :
plur= ""
if len(scList)>1:
plur = "s"
lstxt=""
self.scNumList = []
for i in scList:
lstxt+="%s, "%i
self.scNumList.append(i)
lstxt = lstxt[:-2]
txt = "Chosen scenario%s : %s"%(plur,lstxt)
self.ui.scenariosLabel.setText(txt)
def redefineScenarios(self):
""" retourne au choix des scenarios en lui redonnant moi même comme next_widget
"""
compFrame = self
genSel = GenericScenarioSelection(len(self.parents.hist_model_win.scList),"Select the scenarios that you wish to compare",compFrame,"Comparison of scenarios",2,self.analysis,self.parent)
self.ui.parents.analysisStack.addWidget(genSel)
self.ui.parents.analysisStack.removeWidget(self)
self.ui.parents.analysisStack.setCurrentWidget(genSel)
def majDicoValues(self):
self.dico_values["choNumberOfsimData"] = str(self.ui.cnosdEdit.text())
self.dico_values["de"] = str(self.ui.deEdit.text())
self.dico_values["linearRegression"] = str(self.ui.posteriorDistributionSampleSizeEdit.text())
self.dico_values["lr"] = str(self.ui.lrEdit.text())
self.dico_values["numReg"] = str(self.ui.numRegCombo.currentText())
self.dico_values["notds"] = str(self.ui.notdsEdit.text())
#look for posteriorDataSetNumberEdit in BiasNConfidenceScenarioSelection
for child in self.ui.parents.analysisStack.children():
try :
self.dico_values['posteriorNumDataSets'] = child.posteriorDataSetNumberEdit.text()
except AttributeError as e :
pass
try :
self.dico_values['posteriorSimNumDataSets'] = child.posteriorSimulatedDataSetNumberEdit.text()
except AttributeError as e :
pass
def exit(self):
## reactivation des onglets
self.ui.parents.analysisStack.removeWidget(self)
self.ui.parents.analysisStack.setCurrentIndex(0)
class BiasNConfidenceScenarioSelection(formBiasScenarioSelection,baseBiasScenarioSelection):
""" Selection du scenario dans la cadre d'une analyse de type bias ou confidence
"""
def __init__(self,nb_sc,analysis,parent=None):
super(BiasNConfidenceScenarioSelection,self).__init__(parent)
self.parent=parent
self.parents = Parents(self.parent)
self.analysis = analysis
self.nb_sc = nb_sc
self.checklist = []
self.radiolist = []
self.createWidgets()
self.putChoices()
self.ui.verticalLayout_3.setAlignment(Qt.AlignHCenter)
self.ui.verticalLayout_3.setAlignment(Qt.AlignTop)
self.ui.verticalLayout_2.setAlignment(Qt.AlignHCenter)
self.ui.verticalLayout_2.setAlignment(Qt.AlignTop)
self.ui.verticalLayout.setAlignment(Qt.AlignHCenter)
self.ui.verticalLayout.setAlignment(Qt.AlignTop)
self.restoreAnalysisValues()
def createWidgets(self):
self.ui=self
self.ui.setupUi(self)
QObject.connect(self.ui.exitButton,SIGNAL("clicked()"),self.exit)
QObject.connect(self.ui.okButton,SIGNAL("clicked()"),self.validate)
QObject.connect(self.ui.fixedRadio,SIGNAL("clicked()"),self.checkParameterValues)
QObject.connect(self.ui.drawnPriorRadio,SIGNAL("clicked()"),self.checkParameterValues)
QObject.connect(self.ui.drawnPosteriorRadio,SIGNAL("clicked()"),self.checkParameterValues)
if self.analysis.category == "bias":
self.ui.analysisTypeLabel.setText("Bias and mean square error")
else:
self.ui.analysisTypeLabel.setText("Confidence in scenario choice")
self.ui.projectDirEdit.setText(self.parents.dir)
self.ui.analysisNameLabel.setText(self.analysis.name)
# hide posterior option
if self.analysis.category != "bias":
self.ui.drawnPosteriorRadio.hide()
self.checkParameterValues()
def restoreAnalysisValues(self):
if self.analysis.chosenSc != None:
self.radiolist[self.analysis.chosenSc - 1].setChecked(True)
if self.analysis.category == "confidence_prior_specific":
for i in range(self.nb_sc):
num = i+1
check = self.checklist[i]
check.setChecked(len(self.analysis.candidateScList) == 0 or num in self.analysis.candidateScList)
if self.analysis.drawn != None:
if self.analysis.drawn is False :
self.ui.fixedRadio.setChecked(True)
# in legacy analysis, drawn can be set to True for prior :
elif self.analysis.drawn is True :
self.ui.drawnPriorRadio.setChecked(True)
else :
self.ui.drawnPriorRadio.setChecked('prior' in self.analysis.drawn)
self.ui.drawnPosteriorRadio.setChecked('posterior' in self.analysis.drawn)
cp = self.analysis.computationParameters
posteriorDataSetNumber = ""
try:
posteriorDataSetNumber = cp.split('z:')[1].split(';')[0]
except IndexError:
pass
posteriorSimulatedDataSetNumber = ""
try:
posteriorSimulatedDataSetNumber = cp.split('a:')[1].split(';')[0]
except IndexError:
pass
self.ui.posteriorDataSetNumberEdit.setText(posteriorDataSetNumber)
self.ui.posteriorSimulatedDataSetNumberEdit.setText(posteriorSimulatedDataSetNumber)
self.checkParameterValues(reset=False)
def checkParameterValues(self, reset=True):
self.ui.posteriorDataSetNumberFrame.hide()
if self.analysis.category == "confidence_prior_specific" and self.ui.drawnPosteriorRadio.isChecked():
nbRecordsSelectedScenario = self.parents.readNbRecordsOfScenario(int(self.getSelectedScenario()))
self.ui.maxPosteriorDataSetNumberLabel.setText("max = %s"%nbRecordsSelectedScenario)
if str(self.ui.posteriorSimulatedDataSetNumberEdit.text()) is '' :
self.ui.posteriorSimulatedDataSetNumberEdit.setText(str(nbRecordsSelectedScenario))
elif int(str(self.ui.posteriorSimulatedDataSetNumberEdit.text())) > nbRecordsSelectedScenario :
self.ui.posteriorSimulatedDataSetNumberEdit.setText(str(nbRecordsSelectedScenario))
if reset or str(self.ui.posteriorDataSetNumberEdit.text()) is '' :
self.ui.posteriorDataSetNumberEdit.setText(str(nbRecordsSelectedScenario/100))
self.ui.posteriorDataSetNumberFrame.show()
def validate(self):
""" passe à l'étape suivante de la définition de l'analyse
"""
# pour confidence et bias, on a selectionné un scenario
self.analysis.chosenSc = self.getSelectedScenario()
if self.ui.fixedRadio.isChecked():
self.analysis.drawn = False
elif self.ui.drawnPriorRadio.isChecked():
self.analysis.drawn = 'prior'
elif self.ui.drawnPosteriorRadio.isChecked():
self.analysis.drawn = 'posterior'
if self.analysis.category == "confidence_prior_specific":
try :
if int(str(self.ui.posteriorSimulatedDataSetNumberEdit.text())) > self.parents.readNbRecordsOfScenario(int(self.analysis.chosenSc)) \
or int(str(self.ui.posteriorSimulatedDataSetNumberEdit.text())) <= 0 :
raise
except :
QMessageBox.information(self,"Number error","Total number of simulated data considered for local regression should be a positive number and inferior to the number of records of the scenario %s : %s" \
%(self.analysis.chosenSc, self.parents.readNbRecordsOfScenario(int(self.analysis.chosenSc)) ))
return 0
try :
if int(str(self.ui.posteriorDataSetNumberEdit.text())) > int(str(self.ui.posteriorSimulatedDataSetNumberEdit.text())) \
or int(str(self.ui.posteriorDataSetNumberEdit.text())) <= 0 :
raise
except :
QMessageBox.information(self,"Number error","Number of datasets for local linear regression (simulate data closest to observed) should be a positive number and inferior to the number of records of the scenario %s : %s" \
%(self.analysis.chosenSc, str(self.ui.posteriorSimulatedDataSetNumberEdit.text()) ))
return 0
# le cas du confidence, les sc à afficher dans le hist model sont ceux selectionnés
if self.analysis.category == "confidence_prior_specific":
if len(self.getListSelectedScenarios()) >= 2:
# pour confidence on a du selectionner au moins deux scenarios
self.analysis.candidateScList = self.getListSelectedScenarios()
if self.ui.fixedRadio.isChecked():
next_widget = HistFixed(self.analysis,self.parent)
# prior
else:
next_widget = HistDrawn(self.analysis,self.parent)
else:
QMessageBox.information(self,"Selection error","At least %s scenarios have to be selected"%2)
return 0
# le cas du bias, un sc à afficher, celui du radio button
else:
# en fonction de fixed ou drawn, l'écran suivant présente un objet différent
if self.ui.fixedRadio.isChecked():
next_widget = HistFixed(self.analysis,self.parent)
elif self.ui.drawnPosteriorRadio.isChecked():
next_widget = SetupEstimationBias(self.analysis,self.parent)
else:
next_widget = HistDrawn(self.analysis,self.parent)
self.ui.parents.analysisStack.addWidget(next_widget)
self.ui.parents.analysisStack.removeWidget(self)
self.ui.parents.analysisStack.setCurrentWidget(next_widget)
# skip group loci selection for microsat and seqs analysis
# if self.ui.drawnPosteriorRadio.isChecked() and not self.parents.isSnp() :
# next_widget.validate()
self.parents.updateDoc(next_widget)
def getSelectedScenario(self):
""" retourne le numero du scenario choisi
"""
for i,r in enumerate(self.radiolist):
if r.isChecked():
return i+1
def getListSelectedScenarios(self):
""" retourne la liste des scenarios choisis
"""
res = []
for i,ch in enumerate(self.checklist):
if ch.isChecked():
res.append(i+1)
return res
def putChoices(self):
""" met les choix de scenario en place
"""
for i in range(self.nb_sc):
num = i+1
radio = QRadioButton("Scenario %s"%num,self)
self.radiolist.append(radio)
self.ui.verticalLayout_4.addWidget(radio)
QObject.connect(radio,SIGNAL("clicked()"),self.checkParameterValues)
self.radiolist[0].setChecked(True)
if self.analysis.category == "confidence_prior_specific":
for i in range(self.nb_sc):
num = i+1
check = QCheckBox("Scenario %s"%num,self)
self.checklist.append(check)
self.ui.verticalLayout_6.addWidget(check)
else:
self.ui.candidateScenariosLabel.hide()
self.ui.candidateScenariosTipLabel.hide()
self.ui.frame_3.hide()
def exit(self):
## reactivation des onglets
self.ui.parents.analysisStack.removeWidget(self)
self.ui.parents.analysisStack.setCurrentIndex(0)
