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()
