vtk-m/vtkm/worklet/splatkernels/Gaussian.h

192 lines
5.6 KiB
C
Raw Normal View History

2015-09-15 09:13:05 +00:00
//============================================================================
// Copyright (c) Kitware, Inc.
// All rights reserved.
// See LICENSE.txt for details.
2019-04-15 23:24:21 +00:00
//
2015-09-15 09:13:05 +00:00
// This software is distributed WITHOUT ANY WARRANTY; without even
// the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
// PURPOSE. See the above copyright notice for more information.
//============================================================================
#ifndef VTKM_KERNEL_GAUSSIAN_H
#define VTKM_KERNEL_GAUSSIAN_H
#include <vtkm/worklet/splatkernels/KernelBase.h>
//
// Gaussian kernel.
// Compact support is achieved by truncating the kernel beyond the cutoff radius
// This implementation uses a factor of 5 between smoothing length and cutoff
//
2017-05-18 14:29:41 +00:00
namespace vtkm
{
namespace worklet
{
namespace splatkernels
{
template <int Dimensions>
2017-05-18 14:29:41 +00:00
struct Gaussian : public KernelBase<Gaussian<Dimensions>>
{
2017-05-18 14:29:41 +00:00
//---------------------------------------------------------------------
// Constructor
// Calculate coefficients used repeatedly when evaluating the kernel
// value or gradient
VTKM_EXEC_CONT
Gaussian(double smoothingLength)
: KernelBase<Gaussian<Dimensions>>(smoothingLength)
{
Hinverse_ = 1.0 / smoothingLength;
Hinverse2_ = Hinverse_ * Hinverse_;
maxRadius_ = 5.0 * smoothingLength;
maxRadius2_ = maxRadius_ * maxRadius_;
//
norm_ = 1.0 / vtkm::Pow(M_PI, static_cast<double>(Dimensions) / 2.0);
2017-05-18 14:29:41 +00:00
scale_W_ = norm_ * PowerExpansion<Dimensions>(Hinverse_);
scale_GradW_ = -2.0 * PowerExpansion<Dimensions + 1>(Hinverse_) / norm_;
}
//---------------------------------------------------------------------
// return the multiplier between smoothing length and max cutoff distance
VTKM_EXEC_CONT
2018-02-22 16:34:08 +00:00
constexpr double getDilationFactor() const { return 5.0; }
2017-05-18 14:29:41 +00:00
//---------------------------------------------------------------------
// compute w(h) for the given distance
VTKM_EXEC_CONT
double w(double distance) const
{
if (distance < maxDistance())
{
2017-05-18 14:29:41 +00:00
// compute r/h
double normedDist = distance * Hinverse_;
// compute w(h)
return scale_W_ * vtkm::Exp(-normedDist * normedDist);
}
2017-05-18 14:29:41 +00:00
return 0.0;
}
//---------------------------------------------------------------------
// compute w(h) for the given squared distance
VTKM_EXEC_CONT
double w2(double distance2) const
{
if (distance2 < maxSquaredDistance())
{
2017-05-18 14:29:41 +00:00
// compute (r/h)^2
double normedDist = distance2 * Hinverse2_;
// compute w(h)
return scale_W_ * vtkm::Exp(-normedDist);
}
2017-05-18 14:29:41 +00:00
return 0.0;
}
//---------------------------------------------------------------------
// compute w(h) for a variable h kernel
VTKM_EXEC_CONT
double w(double h, double distance) const
{
if (distance < maxDistance(h))
{
2017-05-18 14:29:41 +00:00
double Hinverse = 1.0 / h;
double scale_W = norm_ * PowerExpansion<Dimensions>(Hinverse);
double Q = distance * Hinverse;
return scale_W * vtkm::Exp(-Q * Q);
}
2017-05-18 14:29:41 +00:00
return 0;
}
//---------------------------------------------------------------------
// compute w(h) for a variable h kernel using distance squared
VTKM_EXEC_CONT
double w2(double h, double distance2) const
{
if (distance2 < maxSquaredDistance(h))
{
2017-05-18 14:29:41 +00:00
double Hinverse = 1.0 / h;
double scale_W = norm_ * PowerExpansion<Dimensions>(Hinverse);
double Q = distance2 * Hinverse * Hinverse;
return scale_W * vtkm::Exp(-Q);
}
2017-05-18 14:29:41 +00:00
return 0;
}
//---------------------------------------------------------------------
// Calculates the kernel derivative for a distance {x,y,z} vector
// from the centre
VTKM_EXEC_CONT
vector_type gradW(double distance, const vector_type& pos) const
{
double Q = distance * Hinverse_;
if (Q != 0.0)
{
return scale_GradW_ * vtkm::Exp(-Q * Q) * pos;
}
2017-05-18 14:29:41 +00:00
else
{
2017-05-18 14:29:41 +00:00
return vector_type(0.0);
}
2017-05-18 14:29:41 +00:00
}
//---------------------------------------------------------------------
// Calculates the kernel derivative for a distance {x,y,z} vector
// from the centre using a variable h
VTKM_EXEC_CONT
vector_type gradW(double h, double distance, const vector_type& pos) const
{
double Hinverse = 1.0 / h;
double scale_GradW = -2.0 * PowerExpansion<Dimensions + 1>(Hinverse) /
vtkm::Pow(M_PI, static_cast<double>(Dimensions) / 2.0);
2017-05-18 14:29:41 +00:00
double Q = distance * Hinverse;
//!!! check this due to the fitting offset
if (distance != 0.0)
{
return scale_GradW * vtkm::Exp(-Q * Q) * pos;
}
2017-05-18 14:29:41 +00:00
else
{
2017-05-18 14:29:41 +00:00
return vector_type(0.0);
}
2017-05-18 14:29:41 +00:00
}
//---------------------------------------------------------------------
// return the maximum distance at which this kernel is non zero
VTKM_EXEC_CONT
double maxDistance() const { return maxRadius_; }
//---------------------------------------------------------------------
// return the maximum distance at which this variable h kernel is non zero
VTKM_EXEC_CONT
double maxDistance(double h) const { return getDilationFactor() * h; }
//---------------------------------------------------------------------
// return the maximum distance at which this kernel is non zero
VTKM_EXEC_CONT
double maxSquaredDistance() const { return maxRadius2_; }
//---------------------------------------------------------------------
// return the maximum distance at which this kernel is non zero
VTKM_EXEC_CONT
double maxSquaredDistance(double h) const
{
return PowerExpansion<2>(getDilationFactor()) * h * h;
}
private:
2017-05-18 14:29:41 +00:00
double norm_;
double Hinverse_;
double Hinverse2_;
double maxRadius_;
double maxRadius2_;
double scale_W_;
double scale_GradW_;
};
2017-05-18 14:29:41 +00:00
}
}
}
#endif