private static ReconstructionInfo ReconstructGradientApprox(Data input, float[,] fullPsf, string folder, int cutFactor, int maxMajor, string dirtyPrefix, string xImagePrefix, StreamWriter writer, double objectiveCutoff, float epsilon)
{
var info = new ReconstructionInfo();
var psfCut = PSF.Cut(fullPsf, cutFactor);
var maxSidelobe = PSF.CalcMaxSidelobe(fullPsf, cutFactor);
var totalSize = new Rectangle(0, 0, input.c.GridSize, input.c.GridSize);
var psfBMap = psfCut;
var bMapCalculator = new PaddedConvolver(PSF.CalcPaddedFourierCorrelation(psfBMap, totalSize), new Rectangle(0, 0, psfBMap.GetLength(0), psfBMap.GetLength(1)));
var bMapCalculator2 = new PaddedConvolver(PSF.CalcPaddedFourierCorrelation(fullPsf, totalSize), new Rectangle(0, 0, fullPsf.GetLength(0), fullPsf.GetLength(1)));
var fastCD = new FastSerialCD(totalSize, psfCut);
var fastCD2 = new FastSerialCD(totalSize, psfCut);
fastCD2.ResetLipschitzMap(fullPsf);
FitsIO.Write(psfCut, folder + cutFactor + "psf.fits");
var lambda = LAMBDA_GLOBAL * fastCD.MaxLipschitz;
var lambdaTrue = (float)(LAMBDA_GLOBAL * PSF.CalcMaxLipschitz(fullPsf));
var xImage = new float[input.c.GridSize, input.c.GridSize];
var residualVis = input.visibilities;
DeconvolutionResult lastResult = null;
var firstTimeConverged = false;
var lastLambda = 0.0f;
for (int cycle = 0; cycle < maxMajor; cycle++)
{
Console.WriteLine("cycle " + cycle);
var dirtyGrid = IDG.GridW(input.c, input.metadata, residualVis, input.uvw, input.frequencies);
var dirtyImage = FFT.WStackIFFTFloat(dirtyGrid, input.c.VisibilitiesCount);
FFT.Shift(dirtyImage);
FitsIO.Write(dirtyImage, folder + dirtyPrefix + cycle + ".fits");
//calc data and reg penalty
var dataPenalty = Residuals.CalcPenalty(dirtyImage);
var regPenalty = ElasticNet.CalcPenalty(xImage, lambdaTrue, alpha);
var regPenaltyCurrent = ElasticNet.CalcPenalty(xImage, lambda, alpha);
info.lastDataPenalty = dataPenalty;
info.lastRegPenalty = regPenalty;
var maxDirty = Residuals.GetMax(dirtyImage);
var bMap = bMapCalculator.Convolve(dirtyImage);
FitsIO.Write(bMap, folder + dirtyPrefix + "bmap_" + cycle + ".fits");
var maxB = Residuals.GetMax(bMap);
var correctionFactor = Math.Max(maxB / (maxDirty * fastCD.MaxLipschitz), 1.0f);
var currentSideLobe = maxB * maxSidelobe * correctionFactor;
var currentLambda = Math.Max(currentSideLobe / alpha, lambda);
writer.Write(cycle + ";" + currentLambda + ";" + currentSideLobe + ";" + ";" + fastCD2.GetAbsMaxDiff(xImage, bMap, lambdaTrue, alpha) + ";" + dataPenalty + ";" + regPenalty + ";" + regPenaltyCurrent + ";");;
writer.Flush();
//check wether we can minimize the objective further with the current psf
var objectiveReached = (dataPenalty + regPenalty) < objectiveCutoff;
var minimumReached = (lastResult != null && lastResult.Converged && fastCD2.GetAbsMaxDiff(xImage, dirtyImage, lambdaTrue, alpha) < MAJOR_EPSILON && currentLambda == lambda);
if (lambda == lastLambda & !firstTimeConverged)
{
firstTimeConverged = true;
minimumReached = false;
}
if (!objectiveReached & !minimumReached)
{
//writer.Write(firstTimeConverged + ";");
//writer.Flush();
info.totalDeconv.Start();
if (!firstTimeConverged)
{
lastResult = fastCD.Deconvolve(xImage, bMap, currentLambda, alpha, 30000, epsilon);
}
else
{
bMap = bMapCalculator2.Convolve(dirtyImage);
//FitsIO.Write(bMap, folder + dirtyPrefix + "bmap_" + cycle + "_full.fits");
maxB = Residuals.GetMax(bMap);
correctionFactor = Math.Max(maxB / (maxDirty * fastCD2.MaxLipschitz), 1.0f);
currentSideLobe = maxB * maxSidelobe * correctionFactor;
currentLambda = Math.Max(currentSideLobe / alpha, lambdaTrue);
info.totalDeconv.Start();
lastResult = fastCD.Deconvolve(xImage, bMap, currentLambda, alpha, 30000, epsilon);
info.totalDeconv.Stop();
}
info.totalDeconv.Stop();
FitsIO.Write(xImage, folder + xImagePrefix + cycle + ".fits");
writer.Write(lastResult.Converged + ";" + lastResult.IterationCount + ";" + lastResult.ElapsedTime.TotalSeconds + "\n");
writer.Flush();
FFT.Shift(xImage);
var xGrid = FFT.Forward(xImage);
FFT.Shift(xImage);
var modelVis = IDG.DeGridW(input.c, input.metadata, xGrid, input.uvw, input.frequencies);
residualVis = Visibilities.Substract(input.visibilities, modelVis, input.flags);
}
else
{
writer.Write(false + ";0;0\n");
writer.Flush();
break;
}
lastLambda = currentLambda;
}
bMapCalculator.Dispose();
bMapCalculator2.Dispose();
return(info);
}
private static void ReconstructSerial(MeasurementData input, GriddingConstants c, float[,] fullPsf, string folder, string file, int processorCount)
{
var totalWatch = new Stopwatch();
var currentWatch = new Stopwatch();
var totalSize = new Rectangle(0, 0, c.GridSize, c.GridSize);
var psfCut = PSF.Cut(fullPsf, CUT_FACTOR_SERIAL);
var maxSidelobe = PSF.CalcMaxSidelobe(fullPsf, CUT_FACTOR_SERIAL);
var fastCD = new FastSerialCD(totalSize, psfCut, processorCount);
var metadata = Partitioner.CreatePartition(c, input.UVW, input.Frequencies);
var writer = new StreamWriter(folder + "/" + file + ".txt");
var psfBMap = psfCut;
using (var bMapCalculator = new PaddedConvolver(PSF.CalcPaddedFourierCorrelation(psfBMap, totalSize), new Rectangle(0, 0, psfBMap.GetLength(0), psfBMap.GetLength(1))))
using (var bMapCalculator2 = new PaddedConvolver(PSF.CalcPaddedFourierCorrelation(fullPsf, totalSize), new Rectangle(0, 0, fullPsf.GetLength(0), fullPsf.GetLength(1))))
{
var currentBMapCalculator = bMapCalculator;
var maxLipschitz = PSF.CalcMaxLipschitz(psfCut);
var lambda = (float)(LAMBDA * maxLipschitz);
var lambdaTrue = (float)(LAMBDA * PSF.CalcMaxLipschitz(fullPsf));
var alpha = ALPHA;
var switchedToOtherPsf = false;
var xImage = new float[c.GridSize, c.GridSize];
var residualVis = input.Visibilities;
DeconvolutionResult lastResult = null;
for (int cycle = 0; cycle < 6; cycle++)
{
Console.WriteLine("cycle " + cycle);
var dirtyGrid = IDG.GridW(c, metadata, residualVis, input.UVW, input.Frequencies);
var dirtyImage = FFT.WStackIFFTFloat(dirtyGrid, c.VisibilitiesCount);
FFT.Shift(dirtyImage);
FitsIO.Write(dirtyImage, folder + "/dirty" + cycle + ".fits");
currentWatch.Restart();
totalWatch.Start();
var maxDirty = Residuals.GetMax(dirtyImage);
var bMap = bMapCalculator.Convolve(dirtyImage);
var maxB = Residuals.GetMax(bMap);
var correctionFactor = Math.Max(maxB / (maxDirty * fastCD.MaxLipschitz), 1.0f);
var currentSideLobe = maxB * maxSidelobe * correctionFactor;
var currentLambda = Math.Max(currentSideLobe / alpha, lambda);
var objective = Residuals.CalcPenalty(dirtyImage) + ElasticNet.CalcPenalty(xImage, lambdaTrue, alpha);
var absMax = fastCD.GetAbsMaxDiff(xImage, bMap, lambdaTrue, alpha);
if (absMax >= MAJOR_STOP)
{
lastResult = fastCD.Deconvolve(xImage, bMap, currentLambda, alpha, 30000, 1e-5f);
}
if (lambda == currentLambda & !switchedToOtherPsf)
{
currentBMapCalculator = bMapCalculator2;
lambda = lambdaTrue;
switchedToOtherPsf = true;
}
currentWatch.Stop();
totalWatch.Stop();
writer.WriteLine(cycle + ";" + currentLambda + ";" + objective + ";" + absMax + ";" + lastResult.IterationCount + ";" + totalWatch.Elapsed.TotalSeconds + ";" + currentWatch.Elapsed.TotalSeconds);
writer.Flush();
if (absMax < MAJOR_STOP)
{
break;
}
FFT.Shift(xImage);
var xGrid = FFT.Forward(xImage);
FFT.Shift(xImage);
var modelVis = IDG.DeGridW(c, metadata, xGrid, input.UVW, input.Frequencies);
residualVis = Visibilities.Substract(input.Visibilities, modelVis, input.Flags);
}
}
}
