void ChangeResolutionAction::IncreaseTime(TimeFrequencyData &originalData, const TimeFrequencyData &changedData, bool restoreImage, bool restoreMask)
{
if(restoreImage)
{
size_t imageCount = originalData.ImageCount();
if(imageCount != changedData.ImageCount())
throw std::runtime_error("When restoring resolution in change resolution action, original data and changed data do not have the same number of images");
for(size_t i=0;i<imageCount;++i)
{
Image2DCPtr image = changedData.GetImage(i);
Image2DPtr newImage(new Image2D(image->EnlargeHorizontally(_timeDecreaseFactor, originalData.ImageWidth())));
originalData.SetImage(i, newImage);
}
}
if(restoreMask)
{
originalData.SetMask(changedData);
size_t maskCount = originalData.MaskCount();
for(size_t i=0;i<maskCount;++i)
{
Mask2DCPtr mask = changedData.GetMask(i);
Mask2DPtr newMask = Mask2D::CreateUnsetMaskPtr(originalData.ImageWidth(), originalData.ImageHeight());
newMask->EnlargeHorizontallyAndSet(*mask, _timeDecreaseFactor);
originalData.SetMask(i, newMask);
}
}
}
void RFIGuiController::plotMeanSpectrum(bool weight)
{
if(IsImageLoaded())
{
std::string title = weight ? "Sum spectrum" : "Mean spectrum";
Plot2D &plot = _plotManager->NewPlot2D(title);
TimeFrequencyData data = ActiveData();
Mask2DCPtr mask =
Mask2D::CreateSetMaskPtr<false>(data.ImageWidth(), data.ImageHeight());
Plot2DPointSet &beforeSet = plot.StartLine("Without flagging");
if(weight)
RFIPlots::MakeMeanSpectrumPlot<true>(beforeSet, data, mask, MetaData());
else
RFIPlots::MakeMeanSpectrumPlot<false>(beforeSet, data, mask, MetaData());
mask = Mask2D::CreateCopy(data.GetSingleMask());
if(!mask->AllFalse())
{
Plot2DPointSet &afterSet = plot.StartLine("Flagged");
if(weight)
RFIPlots::MakeMeanSpectrumPlot<true>(afterSet, data, mask, MetaData());
else
RFIPlots::MakeMeanSpectrumPlot<false>(afterSet, data, mask, MetaData());
}
_plotManager->Update();
}
}
void RFIGuiController::OpenTestSet(unsigned index, bool gaussianTestSets)
{
unsigned width = 1024*16, height = 1024;
if(IsImageLoaded())
{
TimeFrequencyData activeData = ActiveData();
width = activeData.ImageWidth();
height = activeData.ImageHeight();
}
Mask2DPtr rfi = Mask2D::CreateSetMaskPtr<false>(width, height);
Image2DPtr testSetReal(MitigationTester::CreateTestSet(index, rfi, width, height, gaussianTestSets));
Image2DPtr testSetImaginary(MitigationTester::CreateTestSet(2, rfi, width, height, gaussianTestSets));
TimeFrequencyData data(SinglePolarisation, testSetReal, testSetImaginary);
data.SetGlobalMask(rfi);
_rfiGuiWindow.GetTimeFrequencyWidget().SetNewData(data, MetaData());
_rfiGuiWindow.GetTimeFrequencyWidget().Update();
}
void UVImager::Image(const TimeFrequencyData &data, TimeFrequencyMetaDataCPtr metaData, unsigned frequencyIndex)
{
if(_uvReal == 0)
Empty();
Image2DCPtr
real = data.GetRealPart(),
imaginary = data.GetImaginaryPart();
Mask2DCPtr
flags = data.GetSingleMask();
for(unsigned i=0;i<data.ImageWidth();++i) {
switch(_imageKind) {
case Homogeneous:
if(flags->Value(i, frequencyIndex)==0.0L) {
num_t
vr = real->Value(i, frequencyIndex),
vi = imaginary->Value(i, frequencyIndex);
if(std::isfinite(vr) && std::isfinite(vi))
{
num_t u,v;
GetUVPosition(u, v, i, frequencyIndex, metaData);
SetUVValue(u, v, vr, vi, 1.0);
SetUVValue(-u, -v, vr, -vi, 1.0);
}
}
break;
case Flagging:
if((flags->Value(i, frequencyIndex)!=0.0L && !_invertFlagging) ||
(flags->Value(i, frequencyIndex)==0.0L && _invertFlagging)) {
num_t u,v;
GetUVPosition(u, v, i, frequencyIndex, metaData);
SetUVValue(u, v, 1, 0, 1.0);
SetUVValue(-u, -v, 1, 0, 1.0);
}
break;
}
}
}
void CalibratePassbandAction::calibrate(TimeFrequencyData& data) const
{
const size_t height = data.ImageHeight();
std::vector<num_t> stddev(_steps);
for(size_t step=0; step!=_steps; ++step)
{
const size_t startY = step*height/_steps, endY = (step+1)*height/_steps;
std::vector<num_t> dataVector((1+endY-startY) * data.ImageWidth() * data.ImageCount());
std::vector<num_t>::iterator vecIter = dataVector.begin();
const Mask2DCPtr maskPtr = data.GetSingleMask();
const Mask2D &mask = *maskPtr;
for(size_t i=0; i!=data.ImageCount(); ++i)
{
const Image2D &image = *data.GetImage(i);
for(size_t y=startY; y!=endY; ++y)
{
const num_t *inputPtr = image.ValuePtr(0, y);
const bool *maskPtr = mask.ValuePtr(0, y);
for(size_t x=0; x!=image.Width(); ++x)
{
if(!*maskPtr && std::isfinite(*inputPtr))
{
*vecIter = *inputPtr;
++vecIter;
}
++inputPtr;
++maskPtr;
}
}
}
dataVector.resize(vecIter - dataVector.begin());
num_t mean;
ThresholdTools::WinsorizedMeanAndStdDev<num_t>(dataVector, mean, stddev[step]);
}
for(size_t i=0; i!=data.ImageCount(); ++i)
{
const Image2D &image = *data.GetImage(i);
Image2D *destImage = Image2D::CreateUnsetImage(image.Width(), image.Height());
for(size_t step=0; step!=_steps; ++step)
{
const size_t startY = step*height/_steps, endY = (step+1)*height/_steps;
float correctionFactor;
if(stddev[step] == 0.0)
correctionFactor = 0.0;
else
correctionFactor = 1.0 / stddev[step];
const __m128 corrFact4 = _mm_set_ps(correctionFactor, correctionFactor, correctionFactor, correctionFactor);
for(size_t y=startY; y!=endY; ++y)
{
const float *inputPtr = image.ValuePtr(0, y);
float *destPtr = destImage->ValuePtr(0, y);
for(size_t x=0;x<image.Width();x+=4)
{
_mm_store_ps(destPtr, _mm_mul_ps(corrFact4, _mm_load_ps(inputPtr)));
inputPtr += 4;
destPtr += 4;
}
}
}
data.SetImage(i, Image2DPtr(destImage));
}
}