public void Dispose()
{
//imgR.Dispose();
//imgG.Dispose();
//imgB.Dispose();
dmR = null;
dmG = null;
dmB = null;
dmRes = null;
ServiceTools.FlushMemory();
//throw new NotImplementedException();
}
private ImageOperationalValue ImageOperationalValueDDY(ImageOperationalValue a)
{
ImageOperationalValue res = new ImageOperationalValue();
if (a.operandType() == OperandTypes.DenseMatrix)
{
DenseMatrix dmOrig = (DenseMatrix)a.DmImageComponent.Clone();
DenseMatrix dmyPlus1 = (DenseMatrix)a.DmImageComponent.Clone();
dmyPlus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row < dmyPlus1.RowCount - 1)
{
return(dmOrig[row + 1, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmyMinus1 = (DenseMatrix)a.DmImageComponent.Clone();
dmyMinus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row > 0)
{
return(dmOrig[row - 1, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmGradY = dmyPlus1 - dmyMinus1;
//dmGradY.MapInplace(new Func<double, double>(x => x/2.0d));
dmGradY = (DenseMatrix)dmGradY.Multiply(0.5d);
dmyPlus1 = null;
ServiceTools.FlushMemory();
res.DmImageComponent = dmGradY;
dmGradY = null;
ServiceTools.FlushMemory();
}
else
{
res.dNumber = 0.0d;
}
return(res);
}
/// <summary>
/// Makes the thresholded image representing the data, using setting like
/// double thresholdingValue
/// bool thresholdingUsageTop
/// bool thresholdingUsageBtm
///
/// DEPRECATED - legacy only
/// </summary>
public void makeThresholdedDataImage()
{
if (currentColorScheme == null)
{
return;
}
MathNet.Numerics.LinearAlgebra.Double.DenseMatrix tmpDM = (MathNet.Numerics.LinearAlgebra.Double.DenseMatrix)(dmSourceData.Clone());
ImageProcessing.maskedImageChannelDenseMatrixThresholdedInplace(tmpDM, maskImageBinary, (double)thresholdingValue, 0.0d, thresholdingUsageTop, thresholdingUsageBtm);
thresholdedImage = ImageProcessing.grayscaleImageFromDenseMatrix(tmpDM);
ServiceTools.FlushMemory(null, null);
}
public static DenseMatrix sRGBluminanceFrom_sRGB(DenseMatrix dmR, DenseMatrix dmG, DenseMatrix dmB)
{
//Y_lin = 0.2126 R_lin + 0.7152 G_lin + 0.0722 B_lin
// MathNet.Numerics.Control.UseNativeMKL();
DenseMatrix dmLuminance;
DenseMatrix dmLin = (DenseMatrix)dmR.Clone();
//dmLin.MapInplace((val) => val/255.0d);
dmLin = (DenseMatrix)dmLin.Divide(255.0d);
// dmLin.MapInplace(sRGBtoLinear);
dmLin = sRGBtoLinear(dmLin);
//dmLin.MapInplace((val) => 0.2126d*val);
dmLin = (DenseMatrix)dmLin.Multiply(0.2126d);
dmLuminance = (DenseMatrix)dmLin.Clone();
ServiceTools.FlushMemory();
dmLin = (DenseMatrix)dmG.Clone();
// dmLin.MapInplace((val) => val / 255.0d);
dmLin = (DenseMatrix)dmLin.Divide(255.0d);
//dmLin.MapInplace(sRGBtoLinear);
dmLin = sRGBtoLinear(dmLin);
//dmLin.MapInplace((val) => 0.7152d * val);
dmLin = (DenseMatrix)dmLin.Multiply(0.7152d);
dmLuminance = dmLuminance + dmLin;
ServiceTools.FlushMemory();
dmLin = (DenseMatrix)dmB.Clone();
// dmLin.MapInplace((val) => val / 255.0d);
dmLin = (DenseMatrix)dmLin.Divide(255.0d);
//dmLin.MapInplace(sRGBtoLinear);
dmLin = sRGBtoLinear(dmLin);
//dmLin.MapInplace((val) => 0.0722d * val);
dmLin = (DenseMatrix)dmLin.Multiply(0.0722d);
dmLuminance = dmLuminance + dmLin;
ServiceTools.FlushMemory();
//dmLuminance.MapInplace(LinearTo_sRGB);
dmLuminance = LinearTo_sRGB(dmLuminance);
//dmLuminance.MapInplace((val) => val * 255.0d);
dmLuminance = (DenseMatrix)dmLuminance.Multiply(255.0d);
return(dmLuminance);
}
private ImageOperationalValue ImageOperationalValueAbs(ImageOperationalValue a)
{
ImageOperationalValue res = new ImageOperationalValue();
if (a.operandType() == OperandTypes.DenseMatrix)
{
DenseMatrix dmResLocal = (DenseMatrix)a.DmImageComponent.Clone();
dmResLocal.MapInplace((val) => Math.Abs(val));
res.DmImageComponent = dmResLocal;
ServiceTools.FlushMemory();
}
else
{
res.dNumber = Math.Abs(a.dNumber);
}
return(res);
}
private ImageOperationalValue ImageOperationalValueSigm(ImageOperationalValue a)
{
ImageOperationalValue res = new ImageOperationalValue();
if (a.operandType() == OperandTypes.DenseMatrix)
{
DenseMatrix dmResLocal = (DenseMatrix)a.DmImageComponent.Clone();
DescriptiveStatistics stat = new DescriptiveStatistics(dmResLocal.Values);
res.dNumber = stat.StandardDeviation;
ServiceTools.FlushMemory();
}
else
{
res.dNumber = 0.0d;
}
return(res);
}
private ImageOperationalValue ImageOperationalValueSqrt(ImageOperationalValue a)
{
ImageOperationalValue res = new ImageOperationalValue();
if (a.operandType() == OperandTypes.DenseMatrix)
{
DenseMatrix dmResLocal = (DenseMatrix)a.DmImageComponent.Clone();
//dmResLocal.MapInplace(new Func<double, double>((val) => Math.Pow(val, 0.5d)));
dmResLocal = (DenseMatrix)dmResLocal.PointwisePower(0.5d);
res.DmImageComponent = dmResLocal;
ServiceTools.FlushMemory();
}
else
{
res.dNumber = Math.Sqrt(a.dNumber);
}
return(res);
}
private ImageOperationalValue ImageOperationalValueGrad5p(ImageOperationalValue a)
{
ImageOperationalValue res = new ImageOperationalValue();
if (a.operandType() == OperandTypes.DenseMatrix)
{
DenseMatrix dmOrig = a.DmImageComponent.Copy();
DenseMatrix dmyPlus1 = a.DmImageComponent.Copy();
dmyPlus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row < dmyPlus1.RowCount - 1)
{
return(dmOrig[row + 1, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmyPlus2 = a.DmImageComponent.Copy();
dmyPlus2.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row < dmyPlus2.RowCount - 2)
{
return(dmOrig[row + 2, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmyMinus1 = a.DmImageComponent.Copy();
dmyMinus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row > 1)
{
return(dmOrig[row - 1, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmyMinus2 = a.DmImageComponent.Copy();
dmyMinus2.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row > 2)
{
return(dmOrig[row - 2, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmGradY = dmyMinus2 - 8.0d * dmyMinus1 + 8.0d * dmyPlus1 - dmyPlus2;
//dmGradY.MapInplace(x => x / 12.0d);
dmGradY = (DenseMatrix)dmGradY.Divide(12.0d);
dmyPlus1 = null;
dmyMinus1 = null;
dmyPlus2 = null;
dmyMinus2 = null;
ServiceTools.FlushMemory();
DenseMatrix dmxPlus1 = a.DmImageComponent.Copy();
dmxPlus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (column < dmxPlus1.ColumnCount - 1)
{
return(dmOrig[row, column + 1]);
}
else
{
return(val);
}
}));
DenseMatrix dmxPlus2 = a.DmImageComponent.Copy();
dmxPlus2.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (column < dmxPlus2.ColumnCount - 2)
{
return(dmOrig[row, column + 2]);
}
else
{
return(val);
}
}));
DenseMatrix dmxMinus1 = a.DmImageComponent.Copy();
dmxMinus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (column > 1)
{
return(dmOrig[row, column - 1]);
}
else
{
return(val);
}
}));
DenseMatrix dmxMinus2 = a.DmImageComponent.Copy();
dmxMinus2.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (column > 2)
{
return(dmOrig[row, column - 2]);
}
else
{
return(val);
}
}));
DenseMatrix dmGradX = dmxMinus2 - 8.0d * dmxMinus1 + 8.0d * dmxPlus1 - dmxPlus2;
//dmGradX.MapInplace(x => x / 12.0d);
dmGradX = (DenseMatrix)dmGradX.Divide(12.0d);
dmxPlus1 = null;
dmxMinus1 = null;
dmxMinus2 = null;
dmxPlus2 = null;
ServiceTools.FlushMemory();
res.lDMOtherComponents = new List <DenseMatrix>()
{
dmGradX, dmGradY
};
ServiceTools.FlushMemory();
}
else
{
res.dNumber = 0.0d;
}
return(res);
}
private ImageOperationalValue ImageOperationalValueGrad(ImageOperationalValue a)
{
ImageOperationalValue res = new ImageOperationalValue();
if (a.operandType() == OperandTypes.DenseMatrix)
{
DenseMatrix dmOrig = (DenseMatrix)a.DmImageComponent.Clone();
DenseMatrix dmyPlus1 = (DenseMatrix)a.DmImageComponent.Clone();
dmyPlus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row < dmyPlus1.RowCount - 1)
{
return(dmOrig[row + 1, column]);
}
else
{
return(val);
}
}));
DenseMatrix dmyMinus1 = (DenseMatrix)a.DmImageComponent.Clone();
dmyMinus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (row > 1)
{
return(dmOrig[row - 1, column]);
}
else
{
return(val);
}
}));
//DenseMatrix dmRes = DenseMatrix.Create(dmyPlus1.RowCount, dmyPlus1.ColumnCount, new Func<int,int,double>((x, y) => 0.0d));
DenseMatrix dmGradY = (dmyPlus1 - dmyMinus1);
// dmGradY.MapInplace(new Func<double, double>(x => x/2.0d));
dmGradY = (DenseMatrix)dmGradY.Multiply(0.5d);
//dmGradY.MapInplace(new Func<double,double>((val) => val/2.0d));
dmyPlus1 = null;
//dmyMinus1 = null;
ServiceTools.FlushMemory();
DenseMatrix dmxPlus1 = (DenseMatrix)a.DmImageComponent.Clone();
dmxPlus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (column < dmxPlus1.ColumnCount - 1)
{
return(dmOrig[row, column + 1]);
}
else
{
return(val);
}
}));
DenseMatrix dmxMinus1 = (DenseMatrix)a.DmImageComponent.Clone();
dmxMinus1.MapIndexedInplace(new Func <int, int, double, double>((row, column, val) =>
{
if (column > 1)
{
return(dmOrig[row, column - 1]);
}
else
{
return(val);
}
}));
DenseMatrix dmGradX = dmxPlus1 - dmxMinus1;
// dmGradX.MapInplace(new Func<double, double>(x => x/2.0d));
dmGradX = (DenseMatrix)dmGradX.Multiply(0.5d);
//dmGradX.MapInplace(new Func<double, double>((val) => val/2.0d));
dmxPlus1 = null;
//dmxMinus1 = null;
ServiceTools.FlushMemory();
//dmGradY.MapInplace(new Func<double, double>((val) => val * val));
dmGradY = (DenseMatrix)dmGradY.Power(2);
//dmGradX.MapInplace(new Func<double, double>((val) => val * val));
dmGradX = (DenseMatrix)dmGradX.Power(2);
DenseMatrix dmRes = dmGradX + dmGradY;
// dmRes.MapInplace(new Func<double, double>(val => Math.Sqrt(val)));
dmRes = (DenseMatrix)dmRes.PointwisePower(0.5d);
//dmRes.MapIndexedInplace(new Func<int,int,double,double>((x, y, val) => { return x+y; }));
res.DmImageComponent = dmRes;
dmGradY = null;
dmGradX = null;
ServiceTools.FlushMemory();
}
else
{
res.dNumber = 0.0d;
}
return(res);
}
public void RPNeval(bool forceUsingDistributedMatrixes = false)
{
dmRes = null;
resValue = 0.0d;
String input = exprString; //.Replace(" ", "");
if (!forceUsingDistributedMatrixes)
{
if (dmR == null)
{
dmR = ImageProcessing.DenseMatrixFromImage(imgR);
}
if (dmG == null)
{
dmG = ImageProcessing.DenseMatrixFromImage(imgG);
}
if (dmB == null)
{
dmB = ImageProcessing.DenseMatrixFromImage(imgB);
}
dmY = sRGBluminanceFrom_sRGB(dmR, dmG, dmB);
}
PostfixNotation rpn = new PostfixNotation();
string[] converted2RPN = rpn.ConvertToPostfixNotation(input);
Stack <ImageOperationalValue> stack = new Stack <ImageOperationalValue>();
Queue <string> queue = new Queue <string>(converted2RPN);
string str = queue.Dequeue();
while (queue.Count >= 0)
{
if (!rpn.operators.Contains(str))
{
pushImageToStackByColorChar(stack, str);
if (queue.Count > 0)
{
try
{
str = queue.Dequeue();
}
catch (Exception)
{
break;
}
}
else
{
break;
}
}
else
{
ImageOperationalValue summ = null;
try
{
switch (str)
{
case "+":
{
ImageOperationalValue a = stack.Pop();
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValueAdd(a, b); // b + a
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "-":
{
ImageOperationalValue a = stack.Pop();
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValueSubtract(a, b); // b - a
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "*":
{
ImageOperationalValue a = stack.Pop();
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValueMult(a, b); // b * a
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "/":
{
ImageOperationalValue a = stack.Pop();
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValueDivide(a, b); // b / a
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "^":
{
double a = stack.Pop().dNumber;
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValuePow(b, a); // b ^ a
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "grad":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueGrad(a); // grad(a)
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "grad5p":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueGrad5p(a); // grad 5-point(a)
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "ddx":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueDDX(a); // d(a)/dx
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "ddy":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueDDY(a); // d(a)/dy
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "sqrt":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueSqrt(a); // grad(a)
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "mean":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueMean(a); // mean(a)
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "stddev":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueSigm(a); // mean(a)
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "abs":
{
ImageOperationalValue a = stack.Pop();
summ = ImageOperationalValueAbs(a); // abs(a)
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "%":
{
double a = stack.Pop().dNumber;
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValueCut(b, a); // b cut a - cuts "b" matrix elements using "a"*sigma limit of distribution. remember 3-sigma rule?
ServiceTools.FlushMemory(tbLog, "");
break;
}
case "smoothcos":
{
double a = stack.Pop().dNumber;
ImageOperationalValue b = stack.Pop();
summ = ImageOperationalValueSmoothCos(b, a); // b cut a - cuts "b" matrix elements using "a"-nodes spreading cos-based kernel
ServiceTools.FlushMemory(tbLog, "");
break;
}
default:
break;
}
}
catch (Exception ex)
{
ThreadSafeOperations.SetTextTB(tbLog, ex.Message, true);
}
stack.Push(summ);
if (queue.Count > 0)
{
str = queue.Dequeue();
}
else
{
break;
}
}
}
//return Convert.ToDecimal(stack.Pop());
ImageOperationalValue theResult = stack.Pop();
dmRes = theResult.DmImageComponent;
resValue = theResult.dNumber;
lDMRes = theResult.lDMOtherComponents;
if (dmRes != null)
{
minValue = dmRes.Values.Min();
maxValue = dmRes.Values.Max();
}
else
{
minValue = resValue;
maxValue = resValue;
}
ThreadSafeOperations.SetTextTB(tbLog, Environment.NewLine + "min value: " + Math.Round(minValue, 2).ToString(), false);
ThreadSafeOperations.SetTextTB(tbLog, "max value: " + Math.Round(maxValue, 2).ToString(), true);
ServiceTools.FlushMemory(tbLog, "");
}
