public MainWindow()
{
try
{
Options.DeviceCount = GPU.GetDeviceCount();
if (Options.DeviceCount <= 0)
throw new Exception();
}
catch (Exception)
{
MessageBox.Show("No CUDA devices found, shutting down.");
Close();
}
GPU.MemoryChanged += () => Options.UpdateGPUStats();
DataContext = Options;
Options.PropertyChanged += Options_PropertyChanged;
Closing += MainWindow_Closing;
InitializeComponent();
DisableWhenRunning = new List<UIElement>
{
GridOptionsIO,
GridOptionsPreprocessing,
GridOptionsParticles,
GridOptionsCTF,
GridOptionsMovement,
GridOptionsGrids,
GridOptionsPostprocessing
};
if (File.Exists("Previous.settings"))
Options.Load("Previous.settings");
for (int i = 0; i < GPU.GetDeviceCount(); i++)
{
GPU.SetDevice(i);
Console.WriteLine($"Device {i}:");
Console.WriteLine($"Free memory: {GPU.GetFreeMemory(i)} MB");
Console.WriteLine($"Total memory: {GPU.GetTotalMemory(i)} MB");
}
GPU.SetDevice(0);
Options.UpdateGPUStats();
// Create mockup
{
float2[] SplinePoints = { new float2(0f, 0f), new float2(1f / 3f, 1f)};//, new float2(2f / 3f, 0f)};//, new float2(1f, 1f) };
Cubic1D ReferenceSpline = new Cubic1D(SplinePoints);
Cubic1DShort ShortSpline = Cubic1DShort.GetInterpolator(SplinePoints);
for (float i = -1f; i < 2f; i += 0.01f)
{
float Reference = ReferenceSpline.Interp(i);
float Test = ShortSpline.Interp(i);
if (Math.Abs(Reference - Test) > 1e-6f)
throw new Exception();
}
Random Rnd = new Random(123);
int3 GridDim = new int3(1, 1, 1);
float[] GridValues = new float[GridDim.Elements()];
for (int i = 0; i < GridValues.Length; i++)
GridValues[i] = (float)Rnd.NextDouble();
CubicGrid CGrid = new CubicGrid(GridDim, GridValues);
float[] Managed = CGrid.GetInterpolated(new int3(16, 16, 16), new float3(0, 0, 0));
float[] Native = CGrid.GetInterpolatedNative(new int3(16, 16, 16), new float3(0, 0, 0));
for (int i = 0; i < Managed.Length; i++)
if (Math.Abs(Managed[i] - Native[i]) > 1e-6f)
throw new Exception();
Matrix3 A = new Matrix3(1, 2, 3, 4, 5, 6, 7, 8, 9);
Matrix3 B = new Matrix3(11, 12, 13, 14, 15, 16, 17, 18, 19);
Matrix3 C = A * B;
// Euler matrix
{
Matrix3 E = Matrix3.Euler(0 * Helper.ToRad, 20 * Helper.ToRad, 0 * Helper.ToRad);
float3 EE = Matrix3.EulerFromMatrix(E.Transposed()) * Helper.ToDeg;
float3 Transformed = E * new float3(1, 0, 0);
Transformed.Y = 0;
}
//float3[] HealpixAngles = Helper.GetHealpixAngles(3, "D4");
// Deconvolve reconstructions using a separate CTF
//{
// for (int i = 1; i <= 24; i++)
// {
// Image Map = StageDataLoad.LoadMap($"F:\\stefanribo\\vlion\\warped_{i}.mrc", new int2(1, 1), 0, typeof(float));
// Image MapFT = Map.AsFFT(true);
// Map.Dispose();
// Image CTF = StageDataLoad.LoadMap($"F:\\stefanribo\\vlion\\warped_ctf_{i}.mrc", new int2(1, 1), 0, typeof(float));
// foreach (var slice in CTF.GetHost(Intent.ReadWrite))
// for (int s = 0; s < slice.Length; s++)
// slice[s] = Math.Max(1e-3f, slice[s]);
// MapFT.Divide(CTF);
// Map = MapFT.AsIFFT(true);
// MapFT.Dispose();
// Map.WriteMRC($"F:\\stefanribo\\vlion\\warped_deconv_{i}.mrc");
// Map.Dispose();
// }
//}
//{
// Image SumFT = new Image(new int3(220, 220, 220), true, true);
// Image SumWeights = new Image(new int3(220, 220, 220), true);
// int read = 0;
// foreach (var tomoPath in Directory.EnumerateFiles("F:\\stefanribo\\oridata\\particles", "tomo*.mrc"))
// {
// FileInfo Info = new FileInfo(tomoPath);
// Image Tomo = StageDataLoad.LoadMap(tomoPath, new int2(1, 1), 0, typeof(float));
// Image TomoFT = Tomo.AsFFT(true);
// Tomo.Dispose();
// Image TomoWeights = StageDataLoad.LoadMap("F:\\stefanribo\\oridata\\particlectf\\" + Info.Name, new int2(1, 1), 0, typeof(float));
// TomoFT.Multiply(TomoWeights);
// TomoWeights.Multiply(TomoWeights);
// SumFT.Add(TomoFT);
// SumWeights.Add(TomoWeights);
// TomoFT.Dispose();
// TomoWeights.Dispose();
// Debug.WriteLine(read++);
// }
// foreach (var slice in SumWeights.GetHost(Intent.ReadWrite))
// {
// for (int i = 0; i < slice.Length; i++)
// {
// slice[i] = Math.Max(1e-3f, slice[i]);
// }
// }
// SumFT.Divide(SumWeights);
// Image Sum = SumFT.AsIFFT(true);
// Sum.WriteMRC("F:\\stefanribo\\oridata\\particles\\weightedaverage.mrc");
// SumFT.Dispose();
// SumWeights.Dispose();
// Sum.Dispose();
//}
//{
// Image Subtrahend = StageDataLoad.LoadMap("E:\\martinsried\\stefan\\membranebound\\vlion\\relion_subtrahend.mrc", new int2(1, 1), 0, typeof(float));
// Image SubtrahendFT = Subtrahend.AsFFT(true);
// int read = 0;
// foreach (var tomoPath in Directory.EnumerateFiles("E:\\martinsried\\stefan\\membranebound\\oridata\\particles", "tomo*.mrc"))
// {
// FileInfo Info = new FileInfo(tomoPath);
// Image Tomo = StageDataLoad.LoadMap(tomoPath, new int2(1, 1), 0, typeof(float));
// Image TomoFT = Tomo.AsFFT(true);
// Tomo.Dispose();
// Image TomoWeights = StageDataLoad.LoadMap("E:\\martinsried\\stefan\\membranebound\\oridata\\particlectf\\" + Info.Name, new int2(1, 1), 0, typeof(float));
// Image SubtrahendFTMult = new Image(SubtrahendFT.GetDevice(Intent.Read), SubtrahendFT.Dims, true, true);
// SubtrahendFTMult.Multiply(TomoWeights);
// TomoFT.Subtract(SubtrahendFTMult);
// Tomo = TomoFT.AsIFFT(true);
// Tomo.WriteMRC("D:\\stefanribo\\particles\\" + Info.Name);
// Tomo.Dispose();
// TomoFT.Dispose();
// SubtrahendFTMult.Dispose();
// TomoWeights.Dispose();
// Debug.WriteLine(read++);
// }
//}
//{
// Image SubtRef1 = StageDataLoad.LoadMap("E:\\martinsried\\stefan\\membranebound\\vlion\\warp_subtrahend.mrc", new int2(1, 1), 0, typeof(float));
// Projector Subt = new Projector(SubtRef1, 2);
// SubtRef1.Dispose();
// Image ProjFT = Subt.Project(new int2(220, 220), new[] { new float3(0, 0, 0) }, 110);
// Image Proj = ProjFT.AsIFFT();
// Proj.RemapFromFT();
// Proj.WriteMRC("d_testproj.mrc");
//}
// Projector
/*{
Image MapForProjector = StageDataLoad.LoadMap("E:\\youwei\\run36_half1_class001_unfil.mrc", new int2(1, 1), 0, typeof (float));
Projector Proj = new Projector(MapForProjector, 2);
Image Projected = Proj.Project(new int2(240, 240), new[] { new float3(0, 0, 0) }, 120);
Projected = Projected.AsIFFT();
Projected.RemapFromFT();
Projected.WriteMRC("d_projected.mrc");
}*/
// Backprojector
/*{
Image Dot = new Image(new int3(32, 32, 360));
for (int a = 0; a < 360; a++)
Dot.GetHost(Intent.Write)[a][0] = 1;
Dot = Dot.AsFFT();
Dot.AsAmplitudes().WriteMRC("d_dot.mrc");
Image DotWeights = new Image(new int3(32, 32, 360), true);
for (int a = 0; a < 360; a++)
for (int i = 0; i < DotWeights.ElementsSliceReal; i++)
DotWeights.GetHost(Intent.Write)[a][i] = 1;
float3[] Angles = new float3[360];
for (int a = 0; a < 360; a++)
Angles[a] = new float3(0, a * Helper.ToRad * 0.05f, 0);
Projector Proj = new Projector(new int3(32, 32, 32), 2);
Proj.BackProject(Dot, DotWeights, Angles);
Proj.Weights.WriteMRC("d_weights.mrc");
//Image Re = Proj.Data.AsImaginary();
//Re.WriteMRC("d_projdata.mrc");
Image Rec = Proj.Reconstruct(true);
Rec.WriteMRC("d_rec.mrc");
}*/
//Star Models = new Star("D:\\rado27\\Refine3D\\run1_ct5_it005_half1_model.star", "data_model_group_2");
//Debug.WriteLine(Models.GetRow(0)[0]);
/*Image Volume = StageDataLoad.LoadMap("F:\\carragher20s\\ref256.mrc", new int2(1, 1), 0, typeof (float));
Image VolumePadded = Volume.AsPadded(new int3(512, 512, 512));
VolumePadded.WriteMRC("d_padded.mrc");
Volume.Dispose();
VolumePadded.RemapToFT(true);
Image VolumeFT = VolumePadded.AsFFT(true);
VolumePadded.Dispose();
Image VolumeProjFT = VolumeFT.AsProjections(new[] { new float3(Helper.ToRad * 0, Helper.ToRad * 0, Helper.ToRad * 0) }, new int2(256, 256), 2f);
Image VolumeProj = VolumeProjFT.AsIFFT();
VolumeProjFT.Dispose();
VolumeProj.RemapFromFT();
VolumeProj.WriteMRC("d_proj.mrc");
VolumeProj.Dispose();*/
/*Options.Movies.Add(new Movie(@"D:\Dev\warp\May19_21.44.54.mrc"));
Options.Movies.Add(new Movie(@"D:\Dev\warp\May19_21.49.06.mrc"));
Options.Movies.Add(new Movie(@"D:\Dev\warp\May19_21.50.48.mrc"));
Options.Movies.Add(new Movie(@"D:\Dev\warp\May19_21.52.16.mrc"));
Options.Movies.Add(new Movie(@"D:\Dev\warp\May19_21.53.43.mrc"));
CTFDisplay.PS2D = new BitmapImage();*/
/*float2[] SimCoords = new float2[512 * 512];
for (int y = 0; y < 512; y++)
for (int x = 0; x < 512; x++)
{
int xcoord = x - 512, ycoord = y - 512;
SimCoords[y * 512 + x] = new float2((float) Math.Sqrt(xcoord * xcoord + ycoord * ycoord),
(float) Math.Atan2(ycoord, xcoord));
}
float[] Sim2D = new CTF {Defocus = -2M}.Get2D(SimCoords, 512, true);
byte[] Sim2DBytes = new byte[Sim2D.Length];
for (int i = 0; i < 512 * 512; i++)
Sim2DBytes[i] = (byte) (Sim2D[i] * 255f);
BitmapSource Sim2DSource = BitmapSource.Create(512, 512, 96, 96, PixelFormats.Indexed8, BitmapPalettes.Gray256, Sim2DBytes, 512);
CTFDisplay.Simulated2D = Sim2DSource;*/
/*float2[] PointsPS1D = new float2[512];
for (int i = 0; i < PointsPS1D.Length; i++)
PointsPS1D[i] = new float2(i, (float) Math.Exp(-i / 300f));
CTFDisplay.PS1D = PointsPS1D;
float[] SimCTF = new CTF { Defocus = -2M }.Get1D(512, true);
float2[] PointsSim1D = new float2[SimCTF.Length];
for (int i = 0; i < SimCTF.Length; i++)
PointsSim1D[i] = new float2(i, SimCTF[i] * (float)Math.Exp(-i / 100f) + (float)Math.Exp(-i / 300f));
CTFDisplay.Simulated1D = PointsSim1D;*/
/*CubicGrid Grid = new CubicGrid(new int3(5, 5, 5), 0, 0, Dimension.X);
Grid.Values[2, 2, 2] = 1f;
float[] Data = new float[11 * 11 * 11];
int i = 0;
for (float z = 0f; z < 1.05f; z += 0.1f)
for (float y = 0f; y < 1.05f; y += 0.1f)
for (float x = 0f; x < 1.05f; x += 0.1f)
Data[i++] = Grid.GetInterpolated(new float3(x, y, z));
Image DataImage = new Image(Data, new int3(11, 11, 11));
DataImage.WriteMRC("bla.mrc");
Image GPUImage = new Image(DataImage.GetDevice(Intent.Read), new int3(11, 11, 11));
GPUImage.WriteMRC("gpu.mrc");*/
/*CubicGrid WiggleGrid = new CubicGrid(new int3(2, 2, 1));
float[][] WiggleWeights = WiggleGrid.GetWiggleWeights(new int3(3, 3, 1));*/
}
}
public static void FitCTF(float2[] data, float[] simulation, float[] zeros, float[] peaks, out Cubic1D background, out Cubic1D scale)
{
if (zeros.Length < 2 || peaks.Length < 1)
{
background = new Cubic1D(new[] { new float2(0, 0), new float2(1, 0) });
scale = new Cubic1D(new[] { new float2(0, 1), new float2(1, 1) });
return;
}
float MinX = MathHelper.Min(data.Select(p => p.X)), MaxX = MathHelper.Max(data.Select(p => p.X)), ScaleX = 1f / (MaxX - MinX);
peaks = peaks.Where(v => v >= MinX && v <= MaxX).Where((v, i) => i % 1 == 0).ToArray();
zeros = zeros.Where(v => v >= MinX && v <= MaxX).Where((v, i) => i % 1 == 0).ToArray();
List <float2> Peaks = new List <float2>(), Zeros = new List <float2>();
foreach (var zero in zeros)
{
int Pos = (int)((zero - MinX) * ScaleX * data.Length);
int First = Math.Max(0, Pos - 1);
int Last = Math.Min(data.Length - 1, Pos + 1);
float MinVal = data[First].Y;
for (int i = First; i < Last; i++)
{
MinVal = Math.Min(MinVal, data[i].Y);
}
Zeros.Add(new float2(zero, MinVal));
}
float[] Background = (new Cubic1D(Zeros.ToArray())).Interp(data.Select(v => v.X).ToArray());
float2[] DataSubtracted = Helper.ArrayOfFunction(i => new float2(data[i].X, data[i].Y - Background[i]), Background.Length);
for (int z = 0; z < Zeros.Count; z++)
{
float2 Zero = Zeros[z];
int Pos = (int)((Zero.X - MinX) * ScaleX * DataSubtracted.Length);
int First = Math.Max(0, Pos - 1);
int Last = Math.Min(DataSubtracted.Length, Pos + 1);
float MinVal = DataSubtracted[First].Y;
for (int i = First; i < Last; i++)
{
MinVal = Math.Min(MinVal, DataSubtracted[i].Y);
}
Zeros[z] = new float2(Zero.X, Zero.Y + MinVal);
}
Background = (new Cubic1D(Zeros.ToArray())).Interp(data.Select(v => v.X).ToArray());
DataSubtracted = Helper.ArrayOfFunction(i => new float2(data[i].X, data[i].Y - Background[i]), Background.Length);
float GlobalMax = 0;
foreach (var peak in peaks)
{
int Pos = (int)((peak - MinX) * ScaleX * DataSubtracted.Length);
int First = Math.Max(0, Pos - 1);
int Last = Math.Min(DataSubtracted.Length, Pos + 1);
float MaxVal = GlobalMax * 0.05f;// DataSubtracted[First].Y;
for (int i = First; i < Last; i++)
{
MaxVal = Math.Max(MaxVal, DataSubtracted[i].Y);
}
Peaks.Add(new float2(peak, MaxVal));
GlobalMax = Math.Max(MaxVal, GlobalMax);
}
background = Zeros.Count > 1 ? new Cubic1D(Zeros.ToArray()) : new Cubic1D(new[] { new float2(0, 0), new float2(1, 0) });
scale = Peaks.Count > 1 ? new Cubic1D(Peaks.ToArray()) : new Cubic1D(new[] { new float2(0, 1), new float2(1, 1) });
return;
int EveryNth = 1;
float[] ZerosX = new float[Zeros.Count / EveryNth];
for (int i = 0; i < ZerosX.Length; i++)
{
ZerosX[i] = Zeros[i * EveryNth].X;
}
float[] PeaksX = new float[Peaks.Count / EveryNth];
for (int i = 0; i < PeaksX.Length; i++)
{
PeaksX[i] = Peaks[i * EveryNth].X;
}
float[] DataX = data.Select(v => v.X).ToArray();
float[] DataY = data.Select(v => v.Y).ToArray();
Func <double[], double> Eval = (input) =>
{
Cubic1D SplineBackground = new Cubic1D(Helper.ArrayOfFunction(i => new float2(ZerosX[i], (float)Math.Exp(input[i])), ZerosX.Length));
Cubic1D SplineScale = new Cubic1D(Helper.ArrayOfFunction(i => new float2(PeaksX[i], (float)Math.Exp(input[i + ZerosX.Length])), PeaksX.Length));
float[] ContinuumBackground = SplineBackground.Interp(DataX);
float[] ContinuumScale = SplineScale.Interp(DataX);
float[] Diff = Helper.ArrayOfFunction(i => ContinuumBackground[i] + ContinuumScale[i] * simulation[i] - DataY[i], ContinuumBackground.Length);
float DiffSq = 0;
for (int i = 0; i < Diff.Length; i++)
{
DiffSq += Diff[i] * Diff[i];
}
return(DiffSq);
};
Func <double[], double[]> Grad = (input) =>
{
double CurrentValue = Eval(input);
double[] Result = new double[input.Length];
Parallel.For(0, input.Length, i =>
{
double Delta = 1e-5;
double[] InputPlus = input.ToArray();
InputPlus[i] += Delta;
Result[i] = (Eval(InputPlus) - CurrentValue) / Delta;
});
return(Result);
};
double[] ResampledBackground = background.Interp(ZerosX).Select(v => Math.Log(Math.Max(v, 1e-5))).ToArray();
double[] ResampledScale = scale.Interp(PeaksX).Select(v => Math.Log(Math.Max(v, 1e-5))).ToArray();
double[] StartParams = Helper.Combine(ResampledBackground, ResampledScale);
BroydenFletcherGoldfarbShanno Optimizer = new BroydenFletcherGoldfarbShanno(StartParams.Length, Eval, Grad);
Optimizer.MaxIterations = 10;
Optimizer.Minimize(StartParams);
background = new Cubic1D(Helper.ArrayOfFunction(i => new float2(ZerosX[i], (float)Math.Exp(StartParams[i])), ZerosX.Length));
scale = new Cubic1D(Helper.ArrayOfFunction(i => new float2(PeaksX[i], (float)Math.Exp(StartParams[i + ZerosX.Length])), PeaksX.Length));
}
public static void FitCTF(float2[] data, Func <float[], float[]> approximation, float[] zeros, float[] peaks, out Cubic1D background, out Cubic1D scale)
{
float MinX = MathHelper.Min(data.Select(p => p.X)), MaxX = MathHelper.Max(data.Select(p => p.X)), ScaleX = 1f / (MaxX - MinX);
float MinY = MathHelper.Min(data.Select(p => p.Y)), MaxY = MathHelper.Max(data.Select(p => p.Y)), ScaleY = 1f / (MaxY - MinY);
if (float.IsNaN(ScaleY))
{
ScaleY = 1f;
}
peaks = peaks.Where(v => v >= MinX && v <= MaxX).Where((v, i) => i % 1 == 0).ToArray();
zeros = zeros.Where(v => v >= MinX && v <= MaxX).Where((v, i) => i % 1 == 0).ToArray();
float2[] ScaledData = data.Select(p => new float2((p.X - MinX) * ScaleX, (p.Y - MinY) * ScaleY)).ToArray();
float StdY = MathHelper.StdDev(data.Select(p => p.Y).ToArray());
double[] Start = new double[zeros.Length + peaks.Length];
double[] NodeX = new double[zeros.Length + peaks.Length];
Cubic1D DataSpline = new Cubic1D(data);
for (int i = 0; i < zeros.Length; i++)
{
NodeX[i] = (zeros[i] - MinX) * ScaleX;
Start[i] = DataSpline.Interp(zeros[i]) - MinY;
}
{
Cubic1D PreliminaryBackground = new Cubic1D(Helper.Zip(NodeX.Take(zeros.Length).Select(v => (float)v).ToArray(),
Start.Take(zeros.Length).Select(v => (float)v).ToArray()));
float[] PreliminaryInterpolated = PreliminaryBackground.Interp(data.Select(v => (v.X - MinX) * ScaleX).ToArray());
float2[] BackgroundSubtracted = data.Select((v, i) => new float2(v.X, v.Y - MinY - PreliminaryInterpolated[i])).ToArray();
Cubic1D BackgroundSpline = new Cubic1D(BackgroundSubtracted);
for (int i = 0; i < peaks.Length; i++)
{
NodeX[i + zeros.Length] = (peaks[i] - MinX) * ScaleX;
float PeakValue = BackgroundSpline.Interp(peaks[i]);
Start[i + zeros.Length] = Math.Max(0.0001f, PeakValue);
}
}
float[] DataX = ScaledData.Select(p => p.X).ToArray();
float[] OriginalDataX = data.Select(p => p.X).ToArray();
float[] SimulatedCTF = approximation(OriginalDataX);
float2[] NodesBackground = new float2[zeros.Length];
for (int i = 0; i < NodesBackground.Length; i++)
{
NodesBackground[i] = new float2((float)NodeX[i], 0f);
}
float2[] NodesScale = new float2[peaks.Length];
for (int i = 0; i < NodesScale.Length; i++)
{
NodesScale[i] = new float2((float)NodeX[i + zeros.Length], 0f);
}
Func <double[], double> Eval = input =>
{
float2[] NodesBackgroundCopy = new float2[NodesBackground.Length];
for (int i = 0; i < zeros.Length; i++)
{
NodesBackgroundCopy[i] = new float2(NodesBackground[i].X, (float)input[i]);
}
float2[] NodesScaleCopy = new float2[NodesScale.Length];
for (int i = 0; i < peaks.Length; i++)
{
NodesScaleCopy[i] = new float2(NodesScale[i].X, (float)input[i + zeros.Length]);
}
float[] InterpolatedBackground = new Cubic1D(NodesBackgroundCopy).Interp(DataX);
float[] InterpolatedScale = new Cubic1D(NodesScaleCopy).Interp(DataX);
double Sum = 0f;
for (int i = 0; i < ScaledData.Length; i++)
{
double Diff = ScaledData[i].Y - (InterpolatedBackground[i] + SimulatedCTF[i] * (double)InterpolatedScale[i]) * ScaleY;
Sum += Diff * Diff;
if (InterpolatedScale[i] < 0.0005f)
{
Sum += (0.0005 - InterpolatedScale[i]) * 10;
}
}
//return Math.Sqrt(Sum / data.Length) * 10;
return(0);
};
Func <double[], double[]> Gradient = input =>
{
double[] Result = new double[input.Length];
//Parallel.For(0, input.Length, i =>
for (int i = 0; i < input.Length; i++)
{
double[] UpperInput = new double[input.Length];
input.CopyTo(UpperInput, 0);
UpperInput[i] += 0.0001;
double UpperValue = Eval(UpperInput);
double[] LowerInput = new double[input.Length];
input.CopyTo(LowerInput, 0);
LowerInput[i] -= 0.0001;
double LowerValue = Eval(LowerInput);
Result[i] = (UpperValue - LowerValue) / 0.0002;
}//);
return(Result);
};
BroydenFletcherGoldfarbShanno Optimizer = new BroydenFletcherGoldfarbShanno(Start.Length, Eval, Gradient);
Optimizer.Minimize(Start);
{
for (int i = 0; i < zeros.Length; i++)
{
NodesBackground[i] = new float2((float)NodeX[i] / ScaleX + MinX, (float)Optimizer.Solution[i] + MinY);
}
for (int i = 0; i < peaks.Length; i++)
{
NodesScale[i] = new float2((float)NodeX[i + zeros.Length] / ScaleX + MinX, Math.Max(0.001f, (float)Optimizer.Solution[i + zeros.Length]));
}
background = new Cubic1D(NodesBackground);
scale = new Cubic1D(NodesScale);
}
}
public static void FitCTF(float2[] data, Func<float[], float[]> approximation, float[] zeros, float[] peaks, out Cubic1D background, out Cubic1D scale)
{
float MinX = MathHelper.Min(data.Select(p => p.X)), MaxX = MathHelper.Max(data.Select(p => p.X)), ScaleX = 1f / (MaxX - MinX);
float MinY = MathHelper.Min(data.Select(p => p.Y)), MaxY = MathHelper.Max(data.Select(p => p.Y)), ScaleY = 1f / (MaxY - MinY);
if (float.IsNaN(ScaleY))
ScaleY = 1f;
peaks = peaks.Where(v => v >= MinX && v <= MaxX).Where((v, i) => i % 1 == 0).ToArray();
zeros = zeros.Where(v => v >= MinX && v <= MaxX).Where((v, i) => i % 1 == 0).ToArray();
float2[] ScaledData = data.Select(p => new float2((p.X - MinX) * ScaleX, (p.Y - MinY) * ScaleY)).ToArray();
float StdY = MathHelper.StdDev(data.Select(p => p.Y).ToArray());
double[] Start = new double[zeros.Length + peaks.Length];
double[] NodeX = new double[zeros.Length + peaks.Length];
Cubic1D DataSpline = new Cubic1D(data);
for (int i = 0; i < zeros.Length; i++)
{
NodeX[i] = (zeros[i] - MinX) * ScaleX;
Start[i] = DataSpline.Interp(zeros[i]) - MinY;
}
{
Cubic1D PreliminaryBackground = new Cubic1D(Helper.Zip(NodeX.Take(zeros.Length).Select(v => (float)v).ToArray(),
Start.Take(zeros.Length).Select(v => (float)v).ToArray()));
float[] PreliminaryInterpolated = PreliminaryBackground.Interp(data.Select(v => (v.X - MinX) * ScaleX).ToArray());
float2[] BackgroundSubtracted = data.Select((v, i) => new float2(v.X, v.Y - MinY - PreliminaryInterpolated[i])).ToArray();
Cubic1D BackgroundSpline = new Cubic1D(BackgroundSubtracted);
for (int i = 0; i < peaks.Length; i++)
{
NodeX[i + zeros.Length] = (peaks[i] - MinX) * ScaleX;
float PeakValue = BackgroundSpline.Interp(peaks[i]);
Start[i + zeros.Length] = Math.Max(0.0001f, PeakValue);
}
}
float[] DataX = ScaledData.Select(p => p.X).ToArray();
float[] OriginalDataX = data.Select(p => p.X).ToArray();
float[] SimulatedCTF = approximation(OriginalDataX);
float2[] NodesBackground = new float2[zeros.Length];
for (int i = 0; i < NodesBackground.Length; i++)
NodesBackground[i] = new float2((float)NodeX[i], 0f);
float2[] NodesScale = new float2[peaks.Length];
for (int i = 0; i < NodesScale.Length; i++)
NodesScale[i] = new float2((float)NodeX[i + zeros.Length], 0f);
Func<double[], double> Eval = input =>
{
float2[] NodesBackgroundCopy = new float2[NodesBackground.Length];
for (int i = 0; i < zeros.Length; i++)
NodesBackgroundCopy[i] = new float2(NodesBackground[i].X, (float)input[i]);
float2[] NodesScaleCopy = new float2[NodesScale.Length];
for (int i = 0; i < peaks.Length; i++)
NodesScaleCopy[i] = new float2(NodesScale[i].X, (float)input[i + zeros.Length]);
float[] InterpolatedBackground = new Cubic1D(NodesBackgroundCopy).Interp(DataX);
float[] InterpolatedScale = new Cubic1D(NodesScaleCopy).Interp(DataX);
double Sum = 0f;
for (int i = 0; i < ScaledData.Length; i++)
{
double Diff = ScaledData[i].Y - (InterpolatedBackground[i] + SimulatedCTF[i] * (double)InterpolatedScale[i]) * ScaleY;
Sum += Diff * Diff;
if (InterpolatedScale[i] < 0.0005f)
Sum += (0.0005 - InterpolatedScale[i]) * 10;
}
//return Math.Sqrt(Sum / data.Length) * 10;
return 0;
};
Func<double[], double[]> Gradient = input =>
{
double[] Result = new double[input.Length];
//Parallel.For(0, input.Length, i =>
for (int i = 0; i < input.Length; i++)
{
double[] UpperInput = new double[input.Length];
input.CopyTo(UpperInput, 0);
UpperInput[i] += 0.0001;
double UpperValue = Eval(UpperInput);
double[] LowerInput = new double[input.Length];
input.CopyTo(LowerInput, 0);
LowerInput[i] -= 0.0001;
double LowerValue = Eval(LowerInput);
Result[i] = (UpperValue - LowerValue) / 0.0002;
}//);
return Result;
};
BroydenFletcherGoldfarbShanno Optimizer = new BroydenFletcherGoldfarbShanno(Start.Length, Eval, Gradient);
Optimizer.Minimize(Start);
{
for (int i = 0; i < zeros.Length; i++)
NodesBackground[i] = new float2((float) NodeX[i] / ScaleX + MinX, (float) Optimizer.Solution[i] + MinY);
for (int i = 0; i < peaks.Length; i++)
NodesScale[i] = new float2((float)NodeX[i + zeros.Length] / ScaleX + MinX, Math.Max(0.001f, (float)Optimizer.Solution[i + zeros.Length]));
background = new Cubic1D(NodesBackground);
scale = new Cubic1D(NodesScale);
}
}
public virtual void ProcessCTF(MapHeader originalHeader, Image originalStack, bool doastigmatism, decimal scaleFactor)
{
if (!Directory.Exists(PowerSpectrumDir))
Directory.CreateDirectory(PowerSpectrumDir);
//CTF = new CTF();
PS1D = null;
_SimulatedBackground = null;
_SimulatedScale = new Cubic1D(new[] { new float2(0, 1), new float2(1, 1) });
#region Dimensions and grids
int NFrames = originalHeader.Dimensions.Z;
int2 DimsImage = new int2(originalHeader.Dimensions);
int2 DimsRegion = new int2(MainWindow.Options.CTFWindow, MainWindow.Options.CTFWindow);
float OverlapFraction = 0.5f;
int2 DimsPositionGrid;
int3[] PositionGrid = Helper.GetEqualGridSpacing(DimsImage, new int2(DimsRegion.X / 1, DimsRegion.Y / 1), OverlapFraction, out DimsPositionGrid);
int NPositions = (int)DimsPositionGrid.Elements();
int CTFGridX = Math.Min(DimsPositionGrid.X, MainWindow.Options.GridCTFX);
int CTFGridY = Math.Min(DimsPositionGrid.Y, MainWindow.Options.GridCTFY);
int CTFGridZ = Math.Min(NFrames, MainWindow.Options.GridCTFZ);
GridCTF = new CubicGrid(new int3(CTFGridX, CTFGridY, CTFGridZ));
GridCTFPhase = new CubicGrid(new int3(1, 1, CTFGridZ));
bool CTFSpace = CTFGridX * CTFGridY > 1;
bool CTFTime = CTFGridZ > 1;
int3 CTFSpectraGrid = new int3(CTFSpace ? DimsPositionGrid.X : 1,
CTFSpace ? DimsPositionGrid.Y : 1,
CTFTime ? CTFGridZ : 1);
int MinFreqInclusive = (int)(MainWindow.Options.CTFRangeMin * DimsRegion.X / 2);
int MaxFreqExclusive = (int)(MainWindow.Options.CTFRangeMax * DimsRegion.X / 2);
int NFreq = MaxFreqExclusive - MinFreqInclusive;
float PixelSize = (float)(MainWindow.Options.CTFPixelMin + MainWindow.Options.CTFPixelMax) * 0.5f;
float PixelDelta = (float)(MainWindow.Options.CTFPixelMax - MainWindow.Options.CTFPixelMin) * 0.5f;
float PixelAngle = (float)MainWindow.Options.CTFPixelAngle / 180f * (float)Math.PI;
#endregion
#region Allocate GPU memory
Image CTFSpectra = new Image(IntPtr.Zero, new int3(DimsRegion.X, DimsRegion.X, (int)CTFSpectraGrid.Elements()), true);
Image CTFMean = new Image(IntPtr.Zero, new int3(DimsRegion), true);
Image CTFCoordsCart = new Image(new int3(DimsRegion), true, true);
Image CTFCoordsPolarTrimmed = new Image(new int3(NFreq, DimsRegion.X, 1), false, true);
#endregion
// Extract movie regions, create individual spectra in Cartesian coordinates and their mean.
#region Create spectra
GPU.CreateSpectra(originalStack.GetDevice(Intent.Read),
DimsImage,
NFrames,
PositionGrid,
NPositions,
DimsRegion,
CTFSpectraGrid,
CTFSpectra.GetDevice(Intent.Write),
CTFMean.GetDevice(Intent.Write));
originalStack.FreeDevice(); // Won't need it in this method anymore.
#endregion
// Populate address arrays for later.
#region Init addresses
{
float2[] CoordsData = new float2[CTFCoordsCart.ElementsSliceComplex];
Helper.ForEachElementFT(DimsRegion, (x, y, xx, yy, r, a) => CoordsData[y * (DimsRegion.X / 2 + 1) + x] = new float2(r, a));
CTFCoordsCart.UpdateHostWithComplex(new[] { CoordsData });
CoordsData = new float2[NFreq * DimsRegion.X];
Helper.ForEachElement(CTFCoordsPolarTrimmed.DimsSlice, (x, y) =>
{
float Angle = ((float)y / DimsRegion.X + 0.5f) * (float)Math.PI;
float Ny = 1f / DimsRegion.X;
CoordsData[y * NFreq + x] = new float2((x + MinFreqInclusive) * Ny, Angle);
});
CTFCoordsPolarTrimmed.UpdateHostWithComplex(new[] { CoordsData });
}
#endregion
// Retrieve average 1D spectrum from CTFMean (not corrected for astigmatism yet).
#region Initial 1D spectrum
{
Image CTFAverage1D = new Image(IntPtr.Zero, new int3(DimsRegion.X / 2, 1, 1));
GPU.CTFMakeAverage(CTFMean.GetDevice(Intent.Read),
CTFCoordsCart.GetDevice(Intent.Read),
(uint)CTFMean.ElementsSliceReal,
(uint)DimsRegion.X,
new[] { new CTF().ToStruct() },
new CTF().ToStruct(),
0,
(uint)DimsRegion.X / 2,
null,
1,
CTFAverage1D.GetDevice(Intent.Write));
//CTFAverage1D.WriteMRC("CTFAverage1D.mrc");
float[] CTFAverage1DData = CTFAverage1D.GetHost(Intent.Read)[0];
float2[] ForPS1D = new float2[DimsRegion.X / 2];
for (int i = 0; i < ForPS1D.Length; i++)
ForPS1D[i] = new float2((float)i / DimsRegion.X, (float)Math.Round(CTFAverage1DData[i], 4));
_PS1D = ForPS1D;
CTFAverage1D.Dispose();
}
#endregion
#region Background fitting methods
Action UpdateBackgroundFit = () =>
{
float2[] ForPS1D = PS1D.Skip(Math.Max(5, MinFreqInclusive / 2)).ToArray();
Cubic1D.FitCTF(ForPS1D,
v => v.Select(x => CTF.Get1D(x / (float)CTF.PixelSize, true)).ToArray(),
CTF.GetZeros(),
CTF.GetPeaks(),
out _SimulatedBackground,
out _SimulatedScale);
};
Action<bool> UpdateRotationalAverage = keepbackground =>
{
float[] MeanData = CTFMean.GetHost(Intent.Read)[0];
Image CTFMeanCorrected = new Image(new int3(DimsRegion), true);
float[] MeanCorrectedData = CTFMeanCorrected.GetHost(Intent.Write)[0];
// Subtract current background estimate from spectra, populate coords.
Helper.ForEachElementFT(DimsRegion,
(x, y, xx, yy, r, a) =>
{
int i = y * (DimsRegion.X / 2 + 1) + x;
MeanCorrectedData[i] = MeanData[i] - _SimulatedBackground.Interp(r / DimsRegion.X);
});
Image CTFAverage1D = new Image(IntPtr.Zero, new int3(DimsRegion.X / 2, 1, 1));
GPU.CTFMakeAverage(CTFMeanCorrected.GetDevice(Intent.Read),
CTFCoordsCart.GetDevice(Intent.Read),
(uint)CTFMeanCorrected.DimsEffective.ElementsSlice(),
(uint)DimsRegion.X,
new[] { CTF.ToStruct() },
CTF.ToStruct(),
0,
(uint)DimsRegion.X / 2,
null,
1,
CTFAverage1D.GetDevice(Intent.Write));
//CTFAverage1D.WriteMRC("CTFAverage1D.mrc");
float[] RotationalAverageData = CTFAverage1D.GetHost(Intent.Read)[0];
float2[] ForPS1D = new float2[PS1D.Length];
if (keepbackground)
for (int i = 0; i < ForPS1D.Length; i++)
ForPS1D[i] = new float2((float)i / DimsRegion.X, RotationalAverageData[i] + _SimulatedBackground.Interp((float)i / DimsRegion.X));
else
for (int i = 0; i < ForPS1D.Length; i++)
ForPS1D[i] = new float2((float)i / DimsRegion.X, RotationalAverageData[i]);
MathHelper.UnNaN(ForPS1D);
_PS1D = ForPS1D;
CTFMeanCorrected.Dispose();
CTFAverage1D.Dispose();
};
#endregion
// Fit background to currently best average (not corrected for astigmatism yet).
{
float2[] ForPS1D = PS1D.Skip(MinFreqInclusive).Take(Math.Max(2, NFreq / 2)).ToArray();
int NumNodes = Math.Max(3, (int)((MainWindow.Options.CTFRangeMax - MainWindow.Options.CTFRangeMin) * 5M));
_SimulatedBackground = Cubic1D.Fit(ForPS1D, NumNodes); // This won't fit falloff and scale, because approx function is 0
float[] CurrentBackground = _SimulatedBackground.Interp(PS1D.Select(p => p.X).ToArray()).Skip(MinFreqInclusive).Take(NFreq / 2).ToArray();
float[] Subtracted1D = new float[ForPS1D.Length];
for (int i = 0; i < ForPS1D.Length; i++)
Subtracted1D[i] = ForPS1D[i].Y - CurrentBackground[i];
MathHelper.NormalizeInPlace(Subtracted1D);
float ZMin = (float)MainWindow.Options.CTFZMin;
float ZMax = (float)MainWindow.Options.CTFZMax;
float ZStep = (ZMax - ZMin) / 100f;
float BestZ = 0, BestPhase = 0, BestScore = -999;
for (float z = ZMin; z <= ZMax + 1e-5f; z += ZStep)
{
for (float p = 0; p <= (MainWindow.Options.CTFDoPhase ? 1f : 0f); p += 0.01f)
{
CTF CurrentParams = new CTF
{
PixelSize = (MainWindow.Options.CTFPixelMin + MainWindow.Options.CTFPixelMax) * 0.5M,
Defocus = (decimal)z,
PhaseShift = (decimal)p,
Cs = MainWindow.Options.CTFCs,
Voltage = MainWindow.Options.CTFVoltage,
Amplitude = MainWindow.Options.CTFAmplitude
};
float[] SimulatedCTF = CurrentParams.Get1D(PS1D.Length, true).Skip(MinFreqInclusive).Take(Math.Max(2, NFreq / 2)).ToArray();
MathHelper.NormalizeInPlace(SimulatedCTF);
float Score = MathHelper.CrossCorrelate(Subtracted1D, SimulatedCTF);
if (Score > BestScore)
{
BestScore = Score;
BestZ = z;
BestPhase = p;
}
}
}
CTF = new CTF
{
PixelSize = (MainWindow.Options.CTFPixelMin + MainWindow.Options.CTFPixelMax) * 0.5M,
Defocus = (decimal)BestZ,
PhaseShift = (decimal)BestPhase,
Cs = MainWindow.Options.CTFCs,
Voltage = MainWindow.Options.CTFVoltage,
Amplitude = MainWindow.Options.CTFAmplitude
};
UpdateRotationalAverage(true); // This doesn't have a nice background yet.
UpdateBackgroundFit(); // Now get a reasonably nice background.
}
// Fit defocus, (phase shift), (astigmatism) to average background-subtracted spectrum,
// which is in polar coords at this point (for equal weighting of all frequencies).
#region Grid search
{
Image CTFMeanPolarTrimmed = CTFMean.AsPolar((uint)MinFreqInclusive, (uint)(MinFreqInclusive + NFreq / 1));
// Subtract current background.
Image CurrentBackground = new Image(_SimulatedBackground.Interp(PS1D.Select(p => p.X).ToArray()).Skip(MinFreqInclusive).Take(NFreq / 1).ToArray());
CTFMeanPolarTrimmed.SubtractFromLines(CurrentBackground);
CurrentBackground.Dispose();
/*Image WaterMask = new Image(new int3(NFreq, 1, 1));
float[] WaterData = WaterMask.GetHost(Intent.Write)[0];
for (int i = 0; i < NFreq; i++)
{
float f = (i + MinFreqInclusive) / (float)DimsRegion.X * 2f;
WaterData[i] = f > 0.2f && f < 0.6f ? 0f : 1f;
}
//CTFMeanPolarTrimmed.MultiplyLines(WaterMask);
WaterMask.Dispose();*/
// Normalize for CC (not strictly needed, but it's converted for fp16 later, so let's be on the safe side of the fp16 range.
GPU.Normalize(CTFMeanPolarTrimmed.GetDevice(Intent.Read), CTFMeanPolarTrimmed.GetDevice(Intent.Write), (uint)CTFMeanPolarTrimmed.ElementsReal, 1);
//CTFMeanPolarTrimmed.WriteMRC("ctfmeanpolartrimmed.mrc");
CTF StartParams = new CTF
{
PixelSize = (MainWindow.Options.CTFPixelMin + MainWindow.Options.CTFPixelMax) * 0.5M,
PixelSizeDelta = Math.Abs(MainWindow.Options.CTFPixelMax - MainWindow.Options.CTFPixelMin),
PixelSizeAngle = MainWindow.Options.CTFPixelAngle,
Defocus = CTF.Defocus,// (MainWindow.Options.CTFZMin + MainWindow.Options.CTFZMax) * 0.5M,
DefocusDelta = doastigmatism ? 0 : MainWindow.Options.CTFAstigmatism,
DefocusAngle = doastigmatism ? 0 : MainWindow.Options.CTFAstigmatismAngle,
Cs = MainWindow.Options.CTFCs,
Voltage = MainWindow.Options.CTFVoltage,
Amplitude = MainWindow.Options.CTFAmplitude
};
CTFFitStruct FitParams = new CTFFitStruct
{
//Pixelsize = new float3(-0.02e-10f, 0.02e-10f, 0.01e-10f),
//Pixeldelta = new float3(0.0f, 0.02e-10f, 0.01e-10f),
//Pixelangle = new float3(0, 2 * (float)Math.PI, 1 * (float)Math.PI / 18),
//Defocus = new float3((float)(MainWindow.Options.CTFZMin - StartParams.Defocus) * 1e-6f,
// (float)(MainWindow.Options.CTFZMax - StartParams.Defocus) * 1e-6f,
// 0.025e-6f),
Defocus = new float3(-0.4e-6f,
0.4e-6f,
0.025e-6f),
Defocusdelta = doastigmatism ? new float3(0, 0.8e-6f, 0.02e-6f) : new float3(0, 0, 0),
Astigmatismangle = doastigmatism ? new float3(0, 2 * (float)Math.PI, 1 * (float)Math.PI / 18) : new float3(0, 0, 0),
Phaseshift = MainWindow.Options.CTFDoPhase ? new float3(0, (float)Math.PI, 0.025f * (float)Math.PI) : new float3(0, 0, 0)
};
CTFStruct ResultStruct = GPU.CTFFitMean(CTFMeanPolarTrimmed.GetDevice(Intent.Read),
CTFCoordsPolarTrimmed.GetDevice(Intent.Read),
CTFMeanPolarTrimmed.DimsSlice,
StartParams.ToStruct(),
FitParams,
doastigmatism);
CTF.FromStruct(ResultStruct);
CTF.Defocus = Math.Max(CTF.Defocus, MainWindow.Options.CTFZMin);
CTFMeanPolarTrimmed.Dispose();
UpdateRotationalAverage(true); // This doesn't have a nice background yet.
UpdateBackgroundFit(); // Now get a reasonably nice background.
UpdateRotationalAverage(true); // This time, with the nice background.
UpdateBackgroundFit(); // Make the background even nicer!
}
#endregion
/*for (int i = 0; i < PS1D.Length; i++)
PS1D[i].Y -= SimulatedBackground.Interp(PS1D[i].X);
SimulatedBackground = new Cubic1D(SimulatedBackground.Data.Select(v => new float2(v.X, 0f)).ToArray());
OnPropertyChanged("PS1D");
CTFSpectra.Dispose();
CTFMean.Dispose();
CTFCoordsCart.Dispose();
CTFCoordsPolarTrimmed.Dispose();
Simulated1D = GetSimulated1D();
CTFQuality = GetCTFQuality();
return;*/
// Do BFGS optimization of defocus, astigmatism and phase shift,
// using 2D simulation for comparison
#region BFGS
bool[] CTFSpectraConsider = new bool[CTFSpectraGrid.Elements()];
for (int i = 0; i < CTFSpectraConsider.Length; i++)
CTFSpectraConsider[i] = true;
int NCTFSpectraConsider = CTFSpectraConsider.Length;
GridCTF = new CubicGrid(GridCTF.Dimensions, (float)CTF.Defocus, (float)CTF.Defocus, Dimension.X);
GridCTFPhase = new CubicGrid(GridCTFPhase.Dimensions, (float)CTF.PhaseShift, (float)CTF.PhaseShift, Dimension.X);
for (int preciseFit = 2; preciseFit < 3; preciseFit++)
{
NFreq = (MaxFreqExclusive - MinFreqInclusive) * (preciseFit + 1) / 3;
//if (preciseFit >= 2)
// NFreq = MaxFreqExclusive - MinFreqInclusive;
Image CTFSpectraPolarTrimmed = CTFSpectra.AsPolar((uint)MinFreqInclusive, (uint)(MinFreqInclusive + NFreq));
CTFSpectra.FreeDevice(); // This will only be needed again for the final PS1D.
#region Create background and scale
float[] CurrentScale = _SimulatedScale.Interp(PS1D.Select(p => p.X).ToArray());
Image CTFSpectraScale = new Image(new int3(NFreq, DimsRegion.X, 1));
float[] CTFSpectraScaleData = CTFSpectraScale.GetHost(Intent.Write)[0];
// Trim polar to relevant frequencies, and populate coordinates.
Parallel.For(0, DimsRegion.X, y =>
{
float Angle = ((float)y / DimsRegion.X + 0.5f) * (float)Math.PI;
for (int x = 0; x < NFreq; x++)
CTFSpectraScaleData[y * NFreq + x] = CurrentScale[x + MinFreqInclusive];
});
//CTFSpectraScale.WriteMRC("ctfspectrascale.mrc");
// Background is just 1 line since we're in polar.
Image CurrentBackground = new Image(_SimulatedBackground.Interp(PS1D.Select(p => p.X).ToArray()).Skip(MinFreqInclusive).Take(NFreq).ToArray());
#endregion
CTFSpectraPolarTrimmed.SubtractFromLines(CurrentBackground);
CurrentBackground.Dispose();
// Normalize background-subtracted spectra.
GPU.Normalize(CTFSpectraPolarTrimmed.GetDevice(Intent.Read),
CTFSpectraPolarTrimmed.GetDevice(Intent.Write),
(uint)CTFSpectraPolarTrimmed.ElementsSliceReal,
(uint)CTFSpectraGrid.Elements());
//CTFSpectraPolarTrimmed.WriteMRC("ctfspectrapolartrimmed.mrc");
#region Convert to fp16
Image CTFSpectraPolarTrimmedHalf = CTFSpectraPolarTrimmed.AsHalf();
CTFSpectraPolarTrimmed.Dispose();
Image CTFSpectraScaleHalf = CTFSpectraScale.AsHalf();
CTFSpectraScale.Dispose();
Image CTFCoordsPolarTrimmedHalf = CTFCoordsPolarTrimmed.AsHalf();
#endregion
// Wiggle weights show how the defocus on the spectra grid is altered
// by changes in individual anchor points of the spline grid.
// They are used later to compute the dScore/dDefocus values for each spectrum
// only once, and derive the values for each anchor point from them.
float[][] WiggleWeights = GridCTF.GetWiggleWeights(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, 1f / (CTFGridZ + 1)));
float[][] WiggleWeightsPhase = GridCTFPhase.GetWiggleWeights(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, 1f / (CTFGridZ + 1)));
// Helper method for getting CTFStructs for the entire spectra grid.
Func<double[], CTF, float[], float[], CTFStruct[]> EvalGetCTF = (input, ctf, defocusValues, phaseValues) =>
{
decimal AlteredDelta = (decimal)input[input.Length - 2];
decimal AlteredAngle = (decimal)(input[input.Length - 1] * 20 / (Math.PI / 180));
CTF Local = ctf.GetCopy();
Local.DefocusDelta = AlteredDelta;
Local.DefocusAngle = AlteredAngle;
CTFStruct LocalStruct = Local.ToStruct();
CTFStruct[] LocalParams = new CTFStruct[defocusValues.Length];
for (int i = 0; i < LocalParams.Length; i++)
{
LocalParams[i] = LocalStruct;
LocalParams[i].Defocus = defocusValues[i] * -1e-6f;
LocalParams[i].PhaseShift = phaseValues[i] * (float)Math.PI;
}
return LocalParams;
};
// Simulate with adjusted CTF, compare to originals
#region Eval and Gradient methods
float BorderZ = 0.5f / CTFGridZ;
Func<double[], double> Eval = input =>
{
CubicGrid Altered = new CubicGrid(GridCTF.Dimensions, input.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v).ToArray());
float[] DefocusValues = Altered.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CubicGrid AlteredPhase = new CubicGrid(GridCTFPhase.Dimensions, input.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v).ToArray());
float[] PhaseValues = AlteredPhase.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = EvalGetCTF(input, CTF, DefocusValues, PhaseValues);
float[] Result = new float[LocalParams.Length];
GPU.CTFCompareToSim(CTFSpectraPolarTrimmedHalf.GetDevice(Intent.Read),
CTFCoordsPolarTrimmedHalf.GetDevice(Intent.Read),
CTFSpectraScaleHalf.GetDevice(Intent.Read),
(uint)CTFSpectraPolarTrimmedHalf.ElementsSliceReal,
LocalParams,
Result,
(uint)LocalParams.Length);
float Score = 0;
for (int i = 0; i < Result.Length; i++)
if (CTFSpectraConsider[i])
Score += Result[i];
Score /= NCTFSpectraConsider;
if (float.IsNaN(Score) || float.IsInfinity(Score))
throw new Exception("Bad score.");
return (1.0 - Score) * 1000.0;
};
Func<double[], double[]> Gradient = input =>
{
const float Step = 0.005f;
double[] Result = new double[input.Length];
// In 0D grid case, just get gradient for all 4 parameters.
// In 1+D grid case, do simple gradient for astigmatism and phase...
int StartComponent = input.Length - 2;
//int StartComponent = 0;
for (int i = StartComponent; i < input.Length; i++)
{
double[] UpperInput = new double[input.Length];
input.CopyTo(UpperInput, 0);
UpperInput[i] += Step;
double UpperValue = Eval(UpperInput);
double[] LowerInput = new double[input.Length];
input.CopyTo(LowerInput, 0);
LowerInput[i] -= Step;
double LowerValue = Eval(LowerInput);
Result[i] = (UpperValue - LowerValue) / (2f * Step);
}
float[] ResultPlus = new float[CTFSpectraGrid.Elements()];
float[] ResultMinus = new float[CTFSpectraGrid.Elements()];
// ..., take shortcut for defoci...
{
CubicGrid AlteredPhase = new CubicGrid(GridCTFPhase.Dimensions, input.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v).ToArray());
float[] PhaseValues = AlteredPhase.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
{
CubicGrid AlteredPlus = new CubicGrid(GridCTF.Dimensions, input.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v + Step).ToArray());
float[] DefocusValues = AlteredPlus.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = EvalGetCTF(input, CTF, DefocusValues, PhaseValues);
GPU.CTFCompareToSim(CTFSpectraPolarTrimmedHalf.GetDevice(Intent.Read),
CTFCoordsPolarTrimmedHalf.GetDevice(Intent.Read),
CTFSpectraScaleHalf.GetDevice(Intent.Read),
(uint)CTFSpectraPolarTrimmedHalf.ElementsSliceReal,
LocalParams,
ResultPlus,
(uint)LocalParams.Length);
}
{
CubicGrid AlteredMinus = new CubicGrid(GridCTF.Dimensions, input.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v - Step).ToArray());
float[] DefocusValues = AlteredMinus.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = EvalGetCTF(input, CTF, DefocusValues, PhaseValues);
GPU.CTFCompareToSim(CTFSpectraPolarTrimmedHalf.GetDevice(Intent.Read),
CTFCoordsPolarTrimmedHalf.GetDevice(Intent.Read),
CTFSpectraScaleHalf.GetDevice(Intent.Read),
(uint)CTFSpectraPolarTrimmedHalf.ElementsSliceReal,
LocalParams,
ResultMinus,
(uint)LocalParams.Length);
}
float[] LocalGradients = new float[ResultPlus.Length];
for (int i = 0; i < LocalGradients.Length; i++)
LocalGradients[i] = ResultMinus[i] - ResultPlus[i];
// Now compute gradients per grid anchor point using the precomputed individual gradients and wiggle factors.
Parallel.For(0, GridCTF.Dimensions.Elements(), i => Result[i] = MathHelper.ReduceWeighted(LocalGradients, WiggleWeights[i]) / LocalGradients.Length / (2f * Step) * 1000f);
}
// ..., and take shortcut for phases.
if (MainWindow.Options.CTFDoPhase)
{
CubicGrid AlteredPlus = new CubicGrid(GridCTF.Dimensions, input.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v).ToArray());
float[] DefocusValues = AlteredPlus.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
{
CubicGrid AlteredPhasePlus = new CubicGrid(GridCTFPhase.Dimensions, input.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v + Step).ToArray());
float[] PhaseValues = AlteredPhasePlus.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = EvalGetCTF(input, CTF, DefocusValues, PhaseValues);
GPU.CTFCompareToSim(CTFSpectraPolarTrimmedHalf.GetDevice(Intent.Read),
CTFCoordsPolarTrimmedHalf.GetDevice(Intent.Read),
CTFSpectraScaleHalf.GetDevice(Intent.Read),
(uint)CTFSpectraPolarTrimmedHalf.ElementsSliceReal,
LocalParams,
ResultPlus,
(uint)LocalParams.Length);
}
{
CubicGrid AlteredPhaseMinus = new CubicGrid(GridCTFPhase.Dimensions, input.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v - Step).ToArray());
float[] PhaseValues = AlteredPhaseMinus.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = EvalGetCTF(input, CTF, DefocusValues, PhaseValues);
GPU.CTFCompareToSim(CTFSpectraPolarTrimmedHalf.GetDevice(Intent.Read),
CTFCoordsPolarTrimmedHalf.GetDevice(Intent.Read),
CTFSpectraScaleHalf.GetDevice(Intent.Read),
(uint)CTFSpectraPolarTrimmedHalf.ElementsSliceReal,
LocalParams,
ResultMinus,
(uint)LocalParams.Length);
}
float[] LocalGradients = new float[ResultPlus.Length];
for (int i = 0; i < LocalGradients.Length; i++)
LocalGradients[i] = ResultMinus[i] - ResultPlus[i];
// Now compute gradients per grid anchor point using the precomputed individual gradients and wiggle factors.
Parallel.For(0, GridCTFPhase.Dimensions.Elements(), i => Result[i + GridCTF.Dimensions.Elements()] = MathHelper.ReduceWeighted(LocalGradients, WiggleWeightsPhase[i]) / LocalGradients.Length / (2f * Step) * 1000f);
}
foreach (var i in Result)
if (double.IsNaN(i) || double.IsInfinity(i))
throw new Exception("Bad score.");
return Result;
};
#endregion
#region Minimize first time with potential outpiers
double[] StartParams = new double[GridCTF.Dimensions.Elements() + GridCTFPhase.Dimensions.Elements() + 2];
for (int i = 0; i < GridCTF.Dimensions.Elements(); i++)
StartParams[i] = GridCTF.FlatValues[i];
for (int i = 0; i < GridCTFPhase.Dimensions.Elements(); i++)
StartParams[i + GridCTF.Dimensions.Elements()] = GridCTFPhase.FlatValues[i];
StartParams[StartParams.Length - 2] = (double)CTF.DefocusDelta;
StartParams[StartParams.Length - 1] = (double)CTF.DefocusAngle / 20 * (Math.PI / 180);
// Compute correlation for individual spectra, and throw away those that are >.75 sigma worse than mean.
#region Discard outliers
if (CTFSpace || CTFTime)
{
CubicGrid Altered = new CubicGrid(GridCTF.Dimensions, StartParams.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v).ToArray());
float[] DefocusValues = Altered.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CubicGrid AlteredPhase = new CubicGrid(GridCTFPhase.Dimensions, StartParams.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v).ToArray());
float[] PhaseValues = AlteredPhase.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = EvalGetCTF(StartParams, CTF, DefocusValues, PhaseValues);
float[] Result = new float[LocalParams.Length];
GPU.CTFCompareToSim(CTFSpectraPolarTrimmedHalf.GetDevice(Intent.Read),
CTFCoordsPolarTrimmedHalf.GetDevice(Intent.Read),
CTFSpectraScaleHalf.GetDevice(Intent.Read),
(uint)CTFSpectraPolarTrimmedHalf.ElementsSliceReal,
LocalParams,
Result,
(uint)LocalParams.Length);
float MeanResult = MathHelper.Mean(Result);
float StdResult = MathHelper.StdDev(Result);
CTFSpectraConsider = new bool[CTFSpectraGrid.Elements()];
Parallel.For(0, CTFSpectraConsider.Length, i =>
{
//if (Result[i] > MeanResult - StdResult * 1.5f)
CTFSpectraConsider[i] = true;
/*else
{
CTFSpectraConsider[i] = false;
for (int j = 0; j < WiggleWeights.Length; j++)
// Make sure the spectrum's gradient doesn't affect the overall gradient.
WiggleWeights[j][i] = 0;
}*/
});
NCTFSpectraConsider = CTFSpectraConsider.Where(v => v).Count();
}
#endregion
BroydenFletcherGoldfarbShanno Optimizer = new BroydenFletcherGoldfarbShanno(StartParams.Length, Eval, Gradient)
{
Past = 1,
Delta = 1e-6,
MaxLineSearch = 15,
Corrections = 20
};
Optimizer.Minimize(StartParams);
#endregion
#region Retrieve parameters
CTF.Defocus = (decimal)MathHelper.Mean(Optimizer.Solution.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v));
CTF.DefocusDelta = (decimal)Optimizer.Solution[StartParams.Length - 2];
CTF.DefocusAngle = (decimal)(Optimizer.Solution[StartParams.Length - 1] * 20 / (Math.PI / 180));
CTF.PhaseShift = (decimal)MathHelper.Mean(Optimizer.Solution.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v));
if (CTF.DefocusDelta < 0)
{
CTF.DefocusAngle += 90;
CTF.DefocusDelta *= -1;
}
CTF.DefocusAngle = ((int)CTF.DefocusAngle + 180 * 99) % 180;
GridCTF = new CubicGrid(GridCTF.Dimensions, Optimizer.Solution.Take((int)GridCTF.Dimensions.Elements()).Select(v => (float)v).ToArray());
GridCTFPhase = new CubicGrid(GridCTFPhase.Dimensions, Optimizer.Solution.Skip((int)GridCTF.Dimensions.Elements()).Take((int)GridCTFPhase.Dimensions.Elements()).Select(v => (float)v).ToArray());
#endregion
// Dispose GPU resources manually because GC can't be bothered to do it in time.
CTFSpectraPolarTrimmedHalf.Dispose();
CTFCoordsPolarTrimmedHalf.Dispose();
CTFSpectraScaleHalf.Dispose();
#region Get nicer envelope fit
if (preciseFit >= 2)
{
if (!CTFSpace && !CTFTime)
{
UpdateRotationalAverage(true);
}
else
{
Image CTFSpectraBackground = new Image(new int3(DimsRegion), true);
float[] CTFSpectraBackgroundData = CTFSpectraBackground.GetHost(Intent.Write)[0];
// Construct background in Cartesian coordinates.
Helper.ForEachElementFT(DimsRegion, (x, y, xx, yy, r, a) =>
{
CTFSpectraBackgroundData[y * CTFSpectraBackground.DimsEffective.X + x] = _SimulatedBackground.Interp(r / DimsRegion.X);
});
CTFSpectra.SubtractFromSlices(CTFSpectraBackground);
float[] DefocusValues = GridCTF.GetInterpolatedNative(CTFSpectraGrid, new float3(DimsRegion.X / 2f / DimsImage.X, DimsRegion.Y / 2f / DimsImage.Y, BorderZ));
CTFStruct[] LocalParams = DefocusValues.Select(v =>
{
CTF Local = CTF.GetCopy();
Local.Defocus = (decimal)v + 0.0M;
return Local.ToStruct();
}).ToArray();
Image CTFAverage1D = new Image(IntPtr.Zero, new int3(DimsRegion.X / 2, 1, 1));
CTF CTFAug = CTF.GetCopy();
CTFAug.Defocus += 0.0M;
GPU.CTFMakeAverage(CTFSpectra.GetDevice(Intent.Read),
CTFCoordsCart.GetDevice(Intent.Read),
(uint)CTFSpectra.ElementsSliceReal,
(uint)DimsRegion.X,
LocalParams,
CTFAug.ToStruct(),
0,
(uint)DimsRegion.X / 2,
CTFSpectraConsider.Select(v => v ? 1 : 0).ToArray(),
(uint)CTFSpectraGrid.Elements(),
CTFAverage1D.GetDevice(Intent.Write));
CTFSpectra.AddToSlices(CTFSpectraBackground);
float[] RotationalAverageData = CTFAverage1D.GetHost(Intent.Read)[0];
float2[] ForPS1D = new float2[PS1D.Length];
for (int i = 0; i < ForPS1D.Length; i++)
ForPS1D[i] = new float2((float)i / DimsRegion.X, (float)Math.Round(RotationalAverageData[i], 4) + _SimulatedBackground.Interp((float)i / DimsRegion.X));
MathHelper.UnNaN(ForPS1D);
_PS1D = ForPS1D;
CTFSpectraBackground.Dispose();
CTFAverage1D.Dispose();
CTFSpectra.FreeDevice();
}
CTF.Defocus = Math.Max(CTF.Defocus, MainWindow.Options.CTFZMin);
UpdateBackgroundFit();
}
#endregion
}
#endregion
// Subtract background from 2D average and write it to disk.
// This image is used for quick visualization purposes only.
#region PS2D update
{
int3 DimsAverage = new int3(DimsRegion.X, DimsRegion.X / 2, 1);
float[] Average2DData = new float[DimsAverage.Elements()];
float[] OriginalAverageData = CTFMean.GetHost(Intent.Read)[0];
for (int y = 0; y < DimsAverage.Y; y++)
{
int yy = y * y;
for (int x = 0; x < DimsAverage.Y; x++)
{
int xx = DimsRegion.X / 2 - x - 1;
xx *= xx;
float r = (float)Math.Sqrt(xx + yy) / DimsRegion.X;
Average2DData[y * DimsAverage.X + x] = OriginalAverageData[(y + DimsRegion.X / 2) * (DimsRegion.X / 2 + 1) + x] - SimulatedBackground.Interp(r);
}
for (int x = 0; x < DimsRegion.X / 2; x++)
{
int xx = x * x;
float r = (float)Math.Sqrt(xx + yy) / DimsRegion.X;
Average2DData[y * DimsAverage.X + x + DimsRegion.X / 2] = OriginalAverageData[(DimsRegion.X / 2 - y) * (DimsRegion.X / 2 + 1) + (DimsRegion.X / 2 - 1 - x)] - SimulatedBackground.Interp(r);
}
}
IOHelper.WriteMapFloat(PowerSpectrumPath,
new HeaderMRC
{
Dimensions = DimsAverage,
MinValue = MathHelper.Min(Average2DData),
MaxValue = MathHelper.Max(Average2DData)
},
Average2DData);
PS2DTemp = null;
OnPropertyChanged("PS2D");
}
#endregion
for (int i = 0; i < PS1D.Length; i++)
PS1D[i].Y -= SimulatedBackground.Interp(PS1D[i].X);
SimulatedBackground = new Cubic1D(SimulatedBackground.Data.Select(v => new float2(v.X, 0f)).ToArray());
OnPropertyChanged("PS1D");
CTFSpectra.Dispose();
CTFMean.Dispose();
CTFCoordsCart.Dispose();
CTFCoordsPolarTrimmed.Dispose();
Simulated1D = GetSimulated1D();
CTFQuality = GetCTFQuality();
SaveMeta();
}