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); } } }