void PlotDataFitFunction::calculate() {
if (!pData_)
return;
if (fittingValues_.column >= 0) {
fitData();
}
else {
PlotFunction* newPlotData;
newPlotData = new PlotFunction();
newPlotData->getPlotExpression().setExpressionName(expressionNameInput_.get());
newPlotData->setExpressionLength(static_cast<PlotFunction::ExpressionDescriptionLengthType>(expressionText_.getValue()),
maxLength_.get(),selfDescription_.get());
PlotFunction* oldData;
oldData = pDataOut_;
pDataOut_ = newPlotData;
setOutPortData();
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
oldData->getPlotExpression().deletePlotExpressionNodes();
delete oldData;
}
}
void CanvasRenderer::resizeCanvas(tgt::ivec2 newsize) {
if (!tgt::hand(tgt::greaterThanEqual(newsize, tgt::ivec2(canvasSize_.getMinValue()))) && tgt::hand(tgt::lessThanEqual(newsize, canvasSize_.getMaxValue()))) {
LWARNING("Invalid canvas dimensions: " << newsize << ". Ignoring.");
}
if (!canvas_)
return;
if (getProcessorWidget() && getProcessorWidget()->getSize() != newsize) {
if (getProcessorWidget()->isVisible()) {
getProcessorWidget()->setSize(newsize.x, newsize.y);
}
newsize = getProcessorWidget()->getSize();
}
if (newsize != inport_.getSize()) {
canvas_->getGLFocus();
glViewport(0, 0, static_cast<GLint>(newsize.x), static_cast<GLint>(newsize.y));
inport_.requestSize(newsize);
}
canvasSize_.set(newsize);
}
void PlotDataFitFunction::fitData() {
if (fittingValues_.regressionType == FunctionLibrary::LINEAR)
linearRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::SQRT)
sqrtRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::SIMPLESPLINE)
simpleSplineRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::CONSTANTSPLINE)
constantSpline(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::BSPLINE)
bSplineRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::CUBICSPLINE)
cubicSplineRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::SQUARE)
squareRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::CUBIC)
cubicRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::POLYNOMIAL)
multiRegression(fittingValues_.dimension,fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::LOGARITHMIC)
logarithmicRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::POWER)
powerRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::EXPONENTIAL)
exponentialRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::SIN)
sinRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::COS)
cosRegression(fittingValues_.column);
else if (fittingValues_.regressionType == FunctionLibrary::INTERPOLATION)
interpolRegression(fittingValues_.column);
else {
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
}
}
void PlotFunctionDiscret::process() {
tgtAssert(isInitialized(), "not initialized");
if (inPort_.hasData() && inPort_.hasChanged()) {
readData();
calculate();
}
else if (!inPort_.hasData()){
pData_ = 0;
PlotData* oldPlotData;
oldPlotData = pDataOut_;
pDataOut_ = new PlotData(0,0);
setOutPortData();
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
delete oldPlotData;
}
else if (inPort_.hasData() && !inPort_.hasChanged()) {
calculate();
}
else if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
}
void PlotDataMerge::calculate() {
tgtAssert(isInitialized(), "not initialized");
PlotData* oldData;
oldData = pDataOut_;
if (pFirstData_ && !pSecondData_)
pDataOut_ = new PlotData(*pFirstData_);
else if (!pFirstData_ && pSecondData_)
pDataOut_ = new PlotData(*pSecondData_);
else if (!pFirstData_ && !pSecondData_)
pDataOut_ = 0;
else {
pDataOut_ = new PlotData(1,5);
if (ignoreColumnLabel_.get())
pFirstData_->mergeWith(*pSecondData_,*pDataOut_,PlotData::IGNORECOLUMNLABELS);
else
pFirstData_->mergeWith(*pSecondData_,*pDataOut_);
}
setOutPortData();
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
delete oldData;
}
void OntologyClassificationProcessor::updateView() {
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
}
void PlotDataFitFunction::updateView() {
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
}
void CanvasRenderer::boolPropertyChanged() {
if(getProcessorWidget())
getProcessorWidget()->updateFromProcessor();
}
void PlotDataMerge::updateView() {
if (getProcessorWidget()){
getProcessorWidget()->updateFromProcessor();
}
}
