class LogisticRegressionWidget(QWidget, Ui_Widget):
def __init__(self, plugin, parent=None):
QWidget.__init__(self, parent)
self.setupUi(self)
self.plugin = plugin
self.inputs = plugin.inputs
self.settings = QSettings("NextGIS", "MOLUSCE")
self.btnFitModel.clicked.connect(self.fitModel)
self.manageGui()
def manageGui(self):
self.spnNeighbourhood.setValue(self.settings.value("ui/LR/neighborhood", 1).toInt()[0])
def fitModel(self):
self.settings.setValue("ui/LR/neighborhood", self.spnNeighbourhood.value())
self.model = LR(ns=self.spnNeighbourhood.value())
self.model.setTrainingData(self.inputs["initial"],
self.inputs["factors"].values(),
self.inputs["final"],
mode=self.inputs["samplingMode"],
samples=self.plugin.spnSamplesCount.value()
)
self.model.train()
# populate table
self.showCoefficients()
self.inputs["model"] = self.model
def showCoefficients(self):
fm = self.model.getIntercept()
coef = self.model.getCoef()
self.tblCoefficients.clear()
self.tblCoefficients.setColumnCount(len(fm))
self.tblCoefficients.setRowCount(len(coef[0]) + 1)
for i in xrange(len(fm)):
item = QTableWidgetItem(unicode(fm[i]))
self.tblCoefficients.setItem(0, i, item)
for j in xrange(len(coef[i])):
item = QTableWidgetItem(unicode(coef[i][j]))
self.tblCoefficients.setItem(j + 1, i, item)
self.tblCoefficients.resizeRowsToContents()
self.tblCoefficients.resizeColumnsToContents()
def fitModel(self):
self.settings.setValue("ui/LR/neighborhood", self.spnNeighbourhood.value())
self.model = LR(ns=self.spnNeighbourhood.value())
self.model.setTrainingData(self.inputs["initial"],
self.inputs["factors"].values(),
self.inputs["final"],
mode=self.inputs["samplingMode"],
samples=self.plugin.spnSamplesCount.value()
)
self.model.train()
# populate table
self.showCoefficients()
self.inputs["model"] = self.model
def startFitModel(self):
if not utils.checkInputRasters(self.inputs):
QMessageBox.warning(self.plugin,
self.tr("Missed input data"),
self.tr("Initial or final raster is not set. Please specify input data and try again")
)
return
if not utils.checkFactors(self.inputs):
QMessageBox.warning(self.plugin,
self.tr("Missed input data"),
self.tr("Factors rasters is not set. Please specify them and try again")
)
return
if not utils.checkChangeMap(self.inputs):
QMessageBox.warning(self.plugin,
self.tr("Missed input data"),
self.tr("Change map raster is not set. Please create it try again")
)
return
self.settings.setValue("ui/LR/neighborhood", self.spnNeighbourhood.value())
self.plugin.logMessage(self.tr("Init LR model"))
model = LR(ns=self.spnNeighbourhood.value())
self.inputs["model"] = model
model.setMaxIter(self.spnMaxIterations.value())
model.setState(self.inputs["initial"])
model.setFactors(self.inputs["factors"].values())
model.setOutput(self.inputs["changeMap"])
model.setMode(self.inputs["samplingMode"],)
model.setSamples(self.plugin.spnSamplesCount.value())
self.plugin.logMessage(self.tr("Set training data"))
model.moveToThread(self.plugin.workThread)
self.plugin.workThread.started.connect(model.startTrain)
self.plugin.setProgressRange("Train LR model", 0)
model.finished.connect(self.__trainFinished)
model.errorReport.connect(self.plugin.logErrorReport)
model.finished.connect(self.plugin.workThread.quit)
self.plugin.workThread.start()
