public static void MeerKATFull()
{
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 frequencies = FitsIO.ReadFrequencies(@"freq.fits");
* var uvw = FitsIO.ReadUVW("uvw0.fits");
* var flags = FitsIO.ReadFlags("flags0.fits", uvw.GetLength(0), uvw.GetLength(1), frequencies.Length);
* double norm = 2.0;
* var visibilities = FitsIO.ReadVisibilities("vis0.fits", uvw.GetLength(0), uvw.GetLength(1), frequencies.Length, norm);
*/
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 = 1024;
int subgridsize = 16;
int kernelSize = 4;
//cell = image / grid
int max_nr_timesteps = 512;
double scaleArcSec = 2.5 / 3600.0 * PI / 180.0;
var watchTotal = new Stopwatch();
var watchForward = new Stopwatch();
var watchBackwards = new Stopwatch();
var watchDeconv = new Stopwatch();
watchTotal.Start();
var c = new GriddingConstants(visibilitiesCount, gridSize, subgridsize, kernelSize, max_nr_timesteps, (float)scaleArcSec, 1, 0.0f);
var metadata = Partitioner.CreatePartition(c, uvw, frequencies);
var psf = IDG.CalculatePSF(c, metadata, uvw, flags, frequencies);
FitsIO.Write(psf, "psf.fits");
var psfCut = CutImg(psf, 2);
FitsIO.Write(psfCut, "psfCut.fits");
var maxSidelobe = CommonDeprecated.PSF.CalcMaxSidelobe(psf);
var psfCorrelated = CommonDeprecated.PSF.CalculateFourierCorrelation(psfCut, c.GridSize, c.GridSize);
var xImage = new double[gridSize, gridSize];
var residualVis = visibilities;
var maxCycle = 2;
for (int cycle = 0; cycle < maxCycle; cycle++)
{
watchForward.Start();
var dirtyImage = IDG.ToImage(c, metadata, residualVis, uvw, frequencies);
watchForward.Stop();
FitsIO.Write(dirtyImage, "dirty" + cycle + ".fits");
watchDeconv.Start();
var sideLobe = maxSidelobe * GetMax(dirtyImage);
Console.WriteLine("sideLobeLevel: " + sideLobe);
var b = CommonDeprecated.Residuals.CalculateBMap(dirtyImage, psfCorrelated, psfCut.GetLength(0), psfCut.GetLength(1));
var lambda = 0.8;
var alpha = 0.05;
var currentLambda = Math.Max(1.0 / alpha * sideLobe, lambda);
var converged = SerialCDReference.DeconvolvePath(xImage, b, psfCut, currentLambda, 4.0, alpha, 5, 1000, 2e-5);
//var converged = GreedyCD2.Deconvolve(xImage, b, psfCut, currentLambda, alpha, 5000);
if (converged)
{
Console.WriteLine("-----------------------------CONVERGED!!!! with lambda " + currentLambda + "------------------------");
}
else
{
Console.WriteLine("-------------------------------not converged with lambda " + currentLambda + "----------------------");
}
watchDeconv.Stop();
FitsIO.Write(xImage, "xImage_" + cycle + ".fits");
watchBackwards.Start();
FFT.Shift(xImage);
var xGrid = FFT.Forward(xImage);
FFT.Shift(xImage);
var modelVis = IDG.DeGrid(c, metadata, xGrid, uvw, frequencies);
residualVis = Visibilities.Substract(visibilities, modelVis, flags);
watchBackwards.Stop();
}
watchBackwards.Stop();
watchTotal.Stop();
var timetable = "total elapsed: " + watchTotal.Elapsed;
timetable += "\n" + "idg forward elapsed: " + watchForward.Elapsed;
timetable += "\n" + "idg backwards elapsed: " + watchBackwards.Elapsed;
timetable += "\n" + "devonvolution: " + watchDeconv.Elapsed;
File.WriteAllText("watches_single.txt", timetable);
}
public static void DebugSimulatedMixed()
{
var frequencies = FitsIO.ReadFrequencies(@"C:\dev\GitHub\p9-data\small\fits\simulation_mixed\freq.fits");
var uvw = FitsIO.ReadUVW(@"C:\dev\GitHub\p9-data\small\fits\simulation_mixed\uvw.fits");
var flags = new bool[uvw.GetLength(0), uvw.GetLength(1), frequencies.Length]; //completely unflagged dataset
double norm = 2.0;
var visibilities = FitsIO.ReadVisibilities(@"C:\dev\GitHub\p9-data\small\fits\simulation_mixed\vis.fits", uvw.GetLength(0), uvw.GetLength(1), frequencies.Length, norm);
var visibilitiesCount = visibilities.Length;
int gridSize = 1024;
int subgridsize = 16;
int kernelSize = 4;
//cell = image / grid
int max_nr_timesteps = 512;
double scaleArcSec = 0.5 / 3600.0 * PI / 180.0;
var watchTotal = new Stopwatch();
var watchForward = new Stopwatch();
var watchBackwards = new Stopwatch();
var watchDeconv = new Stopwatch();
watchTotal.Start();
var c = new GriddingConstants(visibilitiesCount, gridSize, subgridsize, kernelSize, max_nr_timesteps, (float)scaleArcSec, 1, 0.0f);
var metadata = Partitioner.CreatePartition(c, uvw, frequencies);
var psf = IDG.CalculatePSF(c, metadata, uvw, flags, frequencies);
FitsIO.Write(psf, "psf.fits");
var psfCut = CutImg(psf, 2);
FitsIO.Write(psfCut, "psfCut.fits");
var maxSidelobe = CommonDeprecated.PSF.CalcMaxSidelobe(psf);
var xImage = new double[gridSize, gridSize];
var residualVis = visibilities;
var maxCycle = 10;
for (int cycle = 0; cycle < maxCycle; cycle++)
{
watchForward.Start();
var dirtyImage = IDG.ToImage(c, metadata, residualVis, uvw, frequencies);
watchForward.Stop();
FitsIO.Write(dirtyImage, "dirty" + cycle + ".fits");
watchDeconv.Start();
var sideLobe = maxSidelobe * GetMax(dirtyImage);
Console.WriteLine("sideLobeLevel: " + sideLobe);
var PsfCorrelation = CommonDeprecated.PSF.CalculateFourierCorrelation(psfCut, c.GridSize, c.GridSize);
var b = CommonDeprecated.Residuals.CalculateBMap(dirtyImage, PsfCorrelation, psfCut.GetLength(0), psfCut.GetLength(1));
var lambda = 100.0;
var alpha = 0.95;
var currentLambda = Math.Max(1.0 / alpha * sideLobe, lambda);
var converged = SerialCDReference.DeconvolvePath(xImage, b, psfCut, currentLambda, 5.0, alpha, 5, 6000, 1e-3);
//var converged = GreedyCD2.Deconvolve(xImage, b, psfCut, currentLambda, alpha, 5000);
if (converged)
{
Console.WriteLine("-----------------------------CONVERGED!!!! with lambda " + currentLambda + "------------------------");
}
else
{
Console.WriteLine("-------------------------------not converged with lambda " + currentLambda + "----------------------");
}
watchDeconv.Stop();
FitsIO.Write(xImage, "xImage_" + cycle + ".fits");
watchBackwards.Start();
FFT.Shift(xImage);
var xGrid = FFT.Forward(xImage);
FFT.Shift(xImage);
var modelVis = IDG.DeGrid(c, metadata, xGrid, uvw, frequencies);
residualVis = Visibilities.Substract(visibilities, modelVis, flags);
watchBackwards.Stop();
}
watchBackwards.Stop();
watchTotal.Stop();
var timetable = "total elapsed: " + watchTotal.Elapsed;
timetable += "\n" + "idg forward elapsed: " + watchForward.Elapsed;
timetable += "\n" + "idg backwards elapsed: " + watchBackwards.Elapsed;
timetable += "\n" + "devonvolution: " + watchDeconv.Elapsed;
File.WriteAllText("watches_single.txt", timetable);
}