public static DenseVector ConvKernel(StandardConvolutionKernels kernelType, int kernelHalfWidth = 10)
{
double maxL = ((double)kernelHalfWidth) * 2.0d;
DenseVector dvKernel = DenseVector.Create(2 * kernelHalfWidth + 1, 1.0d);
if (kernelType == StandardConvolutionKernels.cos)
{
dvKernel = DenseVector.Create(2 * kernelHalfWidth + 1, (idx) =>
{
double curDist =
(new PointD(idx - (double)kernelHalfWidth, 0.0d)).Distance(
new PointD(0.0d, 0.0d));
return(Math.Cos(curDist * Math.PI / (2.0d * maxL)));
});
}
else if (kernelType == StandardConvolutionKernels.gauss)
{
dvKernel = DenseVector.Create(2 * kernelHalfWidth + 1, (idx) =>
{
double curDist =
(new PointD(idx - (double)kernelHalfWidth, 0.0d)).Distance(
new PointD(0.0d, 0.0d));
return(Math.Exp(-curDist * curDist / (2.0d * (maxL * maxL / 9.0d))));
});
}
else if (kernelType == StandardConvolutionKernels.flat)
{
dvKernel = DenseVector.Create(2 * kernelHalfWidth + 1, 1.0d);
}
else if (kernelType == StandardConvolutionKernels.linear)
{
dvKernel = DenseVector.Create(2 * kernelHalfWidth + 1, (idx) =>
{
double curDist =
(new PointD(idx - (double)kernelHalfWidth, 0.0d)).Distance(
new PointD(0.0d, 0.0d));
return(Math.Max(1.0d - curDist * (1.0d / (double)kernelHalfWidth), 0.0d));
});
}
else if (kernelType == StandardConvolutionKernels.bilinear)
{
dvKernel = DenseVector.Create(2 * kernelHalfWidth + 1, (idx) =>
{
double curDist =
(new PointD(idx - (double)kernelHalfWidth, 0.0d)).Distance(
new PointD(0.0d, 0.0d));
return(Math.Max(1.0d - curDist * curDist * (1.0d / (double)(kernelHalfWidth * kernelHalfWidth)), 0.0d));
});
}
double kernelSum = dvKernel.Values.Sum();
dvKernel.MapInplace(dval => dval / kernelSum);
return(dvKernel);
}
public static DenseVector ConvKernelAsymmetric(StandardConvolutionKernels kernelType, int kernelWidth = 10, bool centerToTheRight = true)
{
DenseVector dvKernel = ConvKernel(kernelType, kernelWidth - 1);
if (centerToTheRight)
{
dvKernel = (DenseVector)dvKernel.SubVector(0, kernelWidth);
}
else
{
dvKernel = (DenseVector)dvKernel.SubVector(kernelWidth - 1, kernelWidth);
}
double kernelSum = dvKernel.Values.Sum();
dvKernel.MapInplace(dval => dval / kernelSum);
return(dvKernel);
}
public static DenseVector Conv(this DenseVector dvSource, StandardConvolutionKernels kernelType, int kernelHalfWidth = 10)
{
DenseVector dvKernel = ConvKernel(kernelType, kernelHalfWidth);
return(dvSource.Conv(dvKernel));
}