public static void DebugdWStack()
{
var frequencies = FitsIO.ReadFrequencies(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\freq.fits");
var uvw = FitsIO.ReadUVW(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\uvw0.fits");
var flags = FitsIO.ReadFlags(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\flags0.fits", uvw.GetLength(0), uvw.GetLength(1), frequencies.Length);
double norm = 2.0;
var visibilities = FitsIO.ReadVisibilities(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\vis0.fits", uvw.GetLength(0), uvw.GetLength(1), frequencies.Length, norm);
for (int i = 1; i < 8; i++)
{
var uvw0 = FitsIO.ReadUVW(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\uvw" + i + ".fits");
var flags0 = FitsIO.ReadFlags(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\flags" + i + ".fits", uvw0.GetLength(0), uvw0.GetLength(1), frequencies.Length);
var visibilities0 = FitsIO.ReadVisibilities(@"C:\dev\GitHub\p9-data\large\fits\meerkat_tiny\vis" + i + ".fits", uvw0.GetLength(0), uvw0.GetLength(1), frequencies.Length, norm);
uvw = FitsIO.Stitch(uvw, uvw0);
flags = FitsIO.Stitch(flags, flags0);
visibilities = FitsIO.Stitch(visibilities, visibilities0);
}
var maxW = 0.0;
for (int i = 0; i < uvw.GetLength(0); i++)
{
for (int j = 0; j < uvw.GetLength(1); j++)
{
maxW = Math.Max(maxW, Math.Abs(uvw[i, j, 2]));
}
}
maxW = Partitioner.MetersToLambda(maxW, frequencies[frequencies.Length - 1]);
var visCount2 = 0;
for (int i = 0; i < flags.GetLength(0); i++)
{
for (int j = 0; j < flags.GetLength(1); j++)
{
for (int k = 0; k < flags.GetLength(2); k++)
{
if (!flags[i, j, k])
{
visCount2++;
}
}
}
}
var visibilitiesCount = visCount2;
int gridSize = 4096;
int subgridsize = 16;
int kernelSize = 8;
int max_nr_timesteps = 1024;
double cellSize = 1.6 / 3600.0 * PI / 180.0;
int wLayerCount = 32;
double wStep = maxW / (wLayerCount);
var c = new GriddingConstants(visibilitiesCount, gridSize, subgridsize, kernelSize, max_nr_timesteps, (float)cellSize, wLayerCount, wStep);
var c2 = new GriddingConstants(visibilitiesCount, gridSize, subgridsize, kernelSize, max_nr_timesteps, (float)cellSize, 1, 0.0);
var metadata = Partitioner.CreatePartition(c, uvw, frequencies);
var psfVis = new Complex[uvw.GetLength(0), uvw.GetLength(1), frequencies.Length];
for (int i = 0; i < visibilities.GetLength(0); i++)
{
for (int j = 0; j < visibilities.GetLength(1); j++)
{
for (int k = 0; k < visibilities.GetLength(2); k++)
{
if (!flags[i, j, k])
{
psfVis[i, j, k] = new Complex(1.0, 0);
}
else
{
psfVis[i, j, k] = new Complex(0, 0);
}
}
}
}
var psfGrid = IDG.GridW(c, metadata, psfVis, uvw, frequencies);
var psf = FFT.WStackIFFTFloat(psfGrid, c.VisibilitiesCount);
FFT.Shift(psf);
FitsIO.Write(psf, "psfWStack.fits");
var totalSize = new Rectangle(0, 0, gridSize, gridSize);
var bMapCalculator = new PaddedConvolver(PSF.CalcPaddedFourierCorrelation(psf, totalSize), new Rectangle(0, 0, psf.GetLength(0), psf.GetLength(1)));
var fastCD = new FastSerialCD(totalSize, psf);
var lambda = 0.4f * fastCD.MaxLipschitz;
var alpha = 0.1f;
var xImage = new float[gridSize, gridSize];
var residualVis = visibilities;
for (int cycle = 0; cycle < 8; cycle++)
{
var dirtyGrid = IDG.GridW(c, metadata, residualVis, uvw, frequencies);
var dirty = FFT.WStackIFFTFloat(dirtyGrid, c.VisibilitiesCount);
FFT.Shift(dirty);
FitsIO.Write(dirty, "dirty_" + cycle + ".fits");
bMapCalculator.ConvolveInPlace(dirty);
FitsIO.Write(dirty, "bMap_" + cycle + ".fits");
var result = fastCD.Deconvolve(xImage, dirty, lambda, alpha, 10000, 1e-4f);
FitsIO.Write(xImage, "xImageGreedy" + cycle + ".fits");
FFT.Shift(xImage);
var xGrid = FFT.Forward(xImage);
FFT.Shift(xImage);
var modelVis = IDG.DeGridW(c, metadata, xGrid, uvw, frequencies);
var modelGrid = IDG.GridW(c, metadata, modelVis, uvw, frequencies);
var model = FFT.WStackIFFTFloat(modelGrid, c.VisibilitiesCount);
FFT.Shift(model);
FitsIO.Write(model, "model_" + cycle + ".fits");
residualVis = Visibilities.Substract(visibilities, modelVis, flags);
}
}