owliftcurve.py

orange源码 数据挖掘技术

        #load settings
        self.loadSettings()

        # temp variables
        self.dres = None
        self.classifierColor = None
        self.numberOfClasses  = 0
        self.targetClass = None
        self.numberOfClassifiers = 0
        self.numberOfIterations = 0
        self.graphs = []
        self.maxp = 1000
        self.defaultPerfLinePValues = []

        # performance analysis (temporary values
        self.FPcost = 500.0
        self.FNcost = 500.0
        self.pvalue = 50.0 ##0.400

        # list of values (remember for each class)
        self.FPcostList = []
        self.FNcostList = []
        self.pvalueList = []

        # GUI
        self.grid.expand(3, 3)
        self.graphsGridLayoutQGL = QGridLayout(self.mainArea)
        # save each ROC graph in separate file
        self.connect(self.graphButton, SIGNAL("clicked()"), self.saveToFile)

        ## general tab
        self.tabs = QTabWidget(self.controlArea, 'tabWidget')
        self.generalTab = QVGroupBox(self)

        ## target class
        self.classCombo = OWGUI.comboBox(self.generalTab, self, 'targetClass', box='Target Class', items=[], callback=self.target)
        self.classCombo.setMaximumSize(150, 20)

        ## classifiers selection (classifiersQLB)
        self.classifiersQVGB = QVGroupBox(self.generalTab)
        self.classifiersQVGB.setTitle("Classifiers")
        self.classifiersQLB = QListBox(self.classifiersQVGB)
        self.classifiersQLB.setSelectionMode(QListBox.Multi)
        self.connect(self.classifiersQLB, SIGNAL("selectionChanged()"), self.classifiersSelectionChange)
        self.unselectAllClassifiersQLB = QPushButton("(Un)select all", self.classifiersQVGB)
        self.connect(self.unselectAllClassifiersQLB, SIGNAL("clicked()"), self.SUAclassifiersQLB)

        # show Lift Curve convex hull
        OWGUI.checkBox(self.generalTab, self, 'ShowConvexHull', 'Show Lift Convex Hull', tooltip='', callback=self.setShowConvexHull)
        self.tabs.insertTab(self.generalTab, "General")
        

        # performance analysis
        self.performanceTab = QVGroupBox(self)
        self.performanceTabCosts = QVGroupBox(self.performanceTab)
        OWGUI.checkBox(self.performanceTabCosts, self, 'EnablePerformance', 'Show Cost Function', tooltip='', callback=self.setShowPerformanceAnalysis)

        ## FP and FN cost ranges
        mincost = 1; maxcost = 1000; stepcost = 5;
        self.maxpsum = 100; self.minp = 1; self.maxp = self.maxpsum - self.minp ## need it also in self.pvaluesUpdated
        stepp = 1.0

        OWGUI.hSlider(self.performanceTabCosts, self, 'FPcost', box='FP Cost', minValue=mincost, maxValue=maxcost, step=stepcost, callback=self.costsChanged, ticks=50)
        OWGUI.hSlider(self.performanceTabCosts, self, 'FNcost', box='FN Cost', minValue=mincost, maxValue=maxcost, step=stepcost, callback=self.costsChanged, ticks=50)
        OWGUI.hSlider(self.performanceTabCosts, self, 'pvalue', box='p(cl) [%]', minValue=self.minp, maxValue=self.maxp, step=stepp, callback=self.pvaluesUpdated, ticks=5, labelFormat="%2.1f")
        OWGUI.button(self.performanceTabCosts, self, 'Default p(cl)', self.setDefaultPValues) ## reset p values to default

        ## test set selection (testSetsQLB)
        self.testSetsQVGB = QVGroupBox(self.performanceTab)
        self.testSetsQVGB.setTitle("Test sets")
        self.testSetsQLB = QListBox(self.testSetsQVGB)
        self.testSetsQLB.setSelectionMode(QListBox.Multi)
        self.connect(self.testSetsQLB, SIGNAL("selectionChanged()"), self.testSetsSelectionChange)
        self.unselectAllTestSetsQLB = QPushButton("(Un)select all", self.testSetsQVGB)
        self.connect(self.unselectAllTestSetsQLB, SIGNAL("clicked()"), self.SUAtestSetsQLB)
        self.tabs.insertTab(self.performanceTab, "Analysis")

        # settings tab
        self.settingsTab = QVGroupBox(self)
        OWGUI.hSlider(self.settingsTab, self, 'PointWidth', box='Point Width', minValue=3, maxValue=5, step=9, callback=self.setPointWidth, ticks=1)
        OWGUI.hSlider(self.settingsTab, self, 'CurveWidth', box='Lift Curve Width', minValue=1, maxValue=5, step=1, callback=self.setCurveWidth, ticks=1)
        OWGUI.hSlider(self.settingsTab, self, 'ConvexHullCurveWidth', box='Lift Curve Convex Hull', minValue=2, maxValue=9, step=1, callback=self.setConvexHullCurveWidth, ticks=1)
        OWGUI.checkBox(self.settingsTab, self, 'ShowDiagonal', 'Show Diagonal', tooltip='', callback=self.setShowDiagonal)
        self.tabs.insertTab(self.settingsTab, "Settings")

        self.resize(800, 600)

    def calcAllClassGraphs(self):
        for (cl, g) in enumerate(self.graphs):
            g.setNumberOfClassifiersIterationsAndClassifierColors(self.dres.classifierNames, self.numberOfIterations, self.classifierColor)
            g.setTestSetData(self.dresSplitByIterations, cl)
            g.setShowConvexHull(self.ShowConvexHull)
            g.setShowPerformanceLine(self.EnablePerformance)

            ## user settings
            g.setPointWidth(self.PointWidth)
            g.setCurveWidth(self.CurveWidth)
            g.setShowDiagonal(self.ShowDiagonal)
            g.setConvexHullCurveWidth(self.ConvexHullCurveWidth)
            g.setHullColor(QColor(self.HullColor))

    def results(self, dres):
        self.FPcostList = []
        self.FNcostList = []
        self.pvalueList = []

        if not dres:
            self.targetClass = None
            self.classCombo.clear()
            self.removeGraphs()
            self.testSetsQLB.clear()
            return
        self.dres = dres

        self.classifiersQLB.clear()
        self.testSetsQLB.clear()
        self.removeGraphs()
        self.classCombo.clear()

        self.defaultPerfLinePValues = []
        if self.dres <> None:
            ## classQLB
            self.numberOfClasses = len(self.dres.classValues)
            self.graphs = []

            for i in range(self.numberOfClasses):
                self.FPcostList.append( 500)
                self.FNcostList.append( 500)
                graph = singleClassLiftCurveGraph(self.mainArea, "", "Predicted Class: " + self.dres.classValues[i])
                self.graphs.append( graph )
                self.classCombo.insertItem(self.dres.classValues[i])

            ## classifiersQLB
            self.classifierColor = []
            self.numberOfClassifiers = self.dres.numberOfLearners
            if self.numberOfClassifiers > 1:
                allCforHSV = self.numberOfClassifiers - 1
            else:
                allCforHSV = self.numberOfClassifiers
            for i in range(self.numberOfClassifiers):
                newColor = QColor()
                newColor.setHsv(i*255/allCforHSV, 255, 255)
                self.classifierColor.append( newColor )

            ## testSetsQLB
            self.dresSplitByIterations = orngStat.splitByIterations(self.dres)
            self.numberOfIterations = len(self.dresSplitByIterations)

            self.calcAllClassGraphs()

            ## classifiersQLB
            for i in range(self.numberOfClassifiers):
                newColor = self.classifierColor[i]
                self.classifiersQLB.insertItem(ColorPixmap(newColor), self.dres.classifierNames[i])
            self.classifiersQLB.selectAll(1)

            ## testSetsQLB
            self.testSetsQLB.insertStrList([str(i) for i in range(self.numberOfIterations)])
            self.testSetsQLB.selectAll(1)

            ## calculate default pvalues
            reminder = self.maxp
            for f in orngStat.classProbabilitiesFromRes(self.dres):
                v = int(round(f * self.maxp))
                reminder -= v
                if reminder < 0:
                    v = v+reminder
                self.defaultPerfLinePValues.append(v)
                self.pvalueList.append( v)

            self.targetClass = 0 ## select first target
            self.target()
        else:
            self.classifierColor = None
        self.performanceTabCosts.setEnabled(1)
        self.setDefaultPValues()

if __name__ == "__main__":
    a = QApplication(sys.argv)
    owdm = OWLiftCurve()
    a.setMainWidget(owdm)
    owdm.show()
    a.exec_loop()