Array<T>::Array(int length, int start_index) : m_start_index(0)
{
setStartIndex(start_index);
setLength(length);
for (int i = 0; i < m_length; i++)
m_array[i] = T();
}
void AutocorrelatorProcessor::setOutputType(autocorrelator_output::type& newVal)
{
realAutocorrelator.setOutputType(newVal);
complexAutocorrelator.setOutputType(newVal);
output=newVal;
setStartIndex();
setSubsize();
}
void Plot::updatePlot ()
{
qDebug() << "Plot::updatePlot";
_plotSettings.endPos = g_symbol->bars();
_plotSettings.startPos = getStartPosition();
setStartIndex(_plotSettings.startPos);
}
void GopathBrowser::currentEditorChanged(LiteApi::IEditor* editor)
{
if (!m_syncEditor->isChecked()) {
return;
}
if (editor && !editor->filePath().isEmpty()) {
QModelIndex index = m_model->findPath(editor->filePath());
if (index.isValid()) {
m_pathTree->setCurrentIndex(index);
m_pathTree->scrollTo(index,QAbstractItemView::EnsureVisible);
if (m_syncProject->isChecked()) {
setStartIndex(index.parent());
}
}
}
}
AutocorrelatorProcessor::AutocorrelatorProcessor(std::vector<float>& outReal, std::vector<std::complex<float> >& outComplex, size_t correlationSz, long overlap, size_t numAverages, autocorrelator_output::type outType, bool zeroMean, bool zeroCenter):
realOut(outReal),
complexOut(outComplex),
realAutocorrelator(outReal,correlationSz, overlap, numAverages, outType, zeroMean, zeroCenter),
complexAutocorrelator(outComplex,correlationSz, overlap, numAverages, outType, zeroMean, zeroCenter),
isComplex(false),
output(outType),
correlationSize(correlationSz),
inputOverlap(overlap)
{
//exponential averaging technique doesn't decimate output frames
//we may change this later
params.outputFramesPerInputFrame=1;
setSubsize();
setConsumeLen();
setStartIndex();
}
void Plot::setBarSpacing (int d)
{
_plotSettings.spacing = d;
setStartIndex(_plotSettings.startPos);
}
void GopathBrowser::setActivate()
{
setStartIndex(m_contextIndex);
}
