fdaccc22db
Change the VTKM_CONT_EXPORT to VTKM_CONT. (Likewise for EXEC and EXEC_CONT.) Remove the inline from these macros so that they can be applied to everything, including implementations in a library. Because inline is not declared in these modifies, you have to add the keyword to functions and methods where the implementation is not inlined in the class.
199 lines
6.4 KiB
C++
199 lines
6.4 KiB
C++
//============================================================================
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// Copyright (c) Kitware, Inc.
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// All rights reserved.
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// See LICENSE.txt for details.
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// This software is distributed WITHOUT ANY WARRANTY; without even
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// the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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// PURPOSE. See the above copyright notice for more information.
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//
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// Copyright 2014 Sandia Corporation.
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// Copyright 2014 UT-Battelle, LLC.
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// Copyright 2014 Los Alamos National Security.
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//
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// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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// the U.S. Government retains certain rights in this software.
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//
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// Under the terms of Contract DE-AC52-06NA25396 with Los Alamos National
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// Laboratory (LANL), the U.S. Government retains certain rights in
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// this software.
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//============================================================================
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#ifndef VTKM_KERNEL_GAUSSIAN_H
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#define VTKM_KERNEL_GAUSSIAN_H
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#include "KernelBase.h"
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//
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// Gaussian kernel.
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// Compact support is achived by truncating the kernel beyond the cutoff radius
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// This implementation uses a factor of 5 between smoothing length and cutoff
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//
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namespace vtkm { namespace worklet {
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namespace splatkernels {
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template <int Dimensions>
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struct Gaussian : public KernelBase< Gaussian<Dimensions> >
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{
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//---------------------------------------------------------------------
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// Constructor
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// Calculate coefficients used repeatedly when evaluating the kernel
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// value or gradient
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VTKM_EXEC_CONT
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Gaussian(double smoothingLength)
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: KernelBase< Gaussian<Dimensions> >(smoothingLength)
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{
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Hinverse_ = 1.0/smoothingLength;
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Hinverse2_ = Hinverse_*Hinverse_;
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maxRadius_ = 5.0*smoothingLength;
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maxRadius2_ = maxRadius_*maxRadius_;
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//
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norm_ = 1.0 / pow(M_PI, static_cast<double>(Dimensions) / 2.0);
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scale_W_ = norm_ * PowerExpansion<Dimensions> (Hinverse_);
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scale_GradW_ = - 2.0 * PowerExpansion<Dimensions+1>(Hinverse_) / norm_;
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}
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//---------------------------------------------------------------------
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// return the multiplier between smoothing length and max cutoff distance
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VTKM_CONSTEXPR double getDilationFactor() const { return 5.0; }
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//---------------------------------------------------------------------
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// compute w(h) for the given distance
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VTKM_EXEC_CONT
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double w(double distance) const
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{
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if (distance<maxDistance()) {
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// compute r/h
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double normedDist = distance * Hinverse_;
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// compute w(h)
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return scale_W_ * exp(-normedDist * normedDist);
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}
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return 0.0;
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}
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//---------------------------------------------------------------------
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// compute w(h) for the given squared distance
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VTKM_EXEC_CONT
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double w2(double distance2) const
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{
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if (distance2<maxSquaredDistance()) {
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// compute (r/h)^2
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double normedDist = distance2 * Hinverse2_;
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// compute w(h)
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return scale_W_ * exp(-normedDist);
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}
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return 0.0;
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}
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//---------------------------------------------------------------------
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// compute w(h) for a variable h kernel
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VTKM_EXEC_CONT
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double w(double h, double distance) const
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{
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if (distance<maxDistance(h)) {
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double Hinverse = 1.0/h;
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double scale_W = norm_ * PowerExpansion<Dimensions>(Hinverse);
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double Q = distance * Hinverse;
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return scale_W * exp(-Q*Q);
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}
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return 0;
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}
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//---------------------------------------------------------------------
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// compute w(h) for a variable h kernel using distance squared
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VTKM_EXEC_CONT
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double w2(double h, double distance2) const
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{
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if (distance2<maxSquaredDistance(h)) {
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double Hinverse = 1.0/h;
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double scale_W = norm_ * PowerExpansion<Dimensions>(Hinverse);
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double Q = distance2 * Hinverse * Hinverse;
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return scale_W * exp(-Q);
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}
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return 0;
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}
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//---------------------------------------------------------------------
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// Calculates the kernel derivative for a distance {x,y,z} vector
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// from the centre
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VTKM_EXEC_CONT
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vector_type gradW(double distance, const vector_type& pos) const
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{
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double Q = distance * Hinverse_;
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if (Q != 0.0)
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{
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return scale_GradW_ * exp(-Q * Q) * pos;
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}
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else {
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return vector_type(0.0);
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}
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}
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//---------------------------------------------------------------------
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// Calculates the kernel derivative for a distance {x,y,z} vector
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// from the centre using a variable h
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VTKM_EXEC_CONT
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vector_type gradW(double h, double distance, const vector_type& pos) const
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{
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double Hinverse = 1.0/h;
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double scale_GradW = - 2.0 * PowerExpansion<Dimensions+1>(Hinverse)
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/ pow(M_PI, static_cast<double>(Dimensions) / 2.0);
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double Q = distance * Hinverse;
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//!!! check this due to the fitting offset
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if (distance != 0.0)
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{
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return scale_GradW * exp(-Q * Q) * pos;
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}
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else {
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return vector_type(0.0);
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}
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}
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//---------------------------------------------------------------------
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// return the maximum distance at which this kernel is non zero
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VTKM_EXEC_CONT
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double maxDistance() const
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{
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return maxRadius_;
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}
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//---------------------------------------------------------------------
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// return the maximum distance at which this variable h kernel is non zero
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VTKM_EXEC_CONT
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double maxDistance(double h) const
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{
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return getDilationFactor()*h;
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}
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//---------------------------------------------------------------------
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// return the maximum distance at which this kernel is non zero
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VTKM_EXEC_CONT
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double maxSquaredDistance() const
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{
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return maxRadius2_;
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}
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//---------------------------------------------------------------------
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// return the maximum distance at which this kernel is non zero
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VTKM_EXEC_CONT
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double maxSquaredDistance(double h) const
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{
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return PowerExpansion<2>(getDilationFactor())*h*h;
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}
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private:
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double norm_;
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double Hinverse_;
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double Hinverse2_;
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double maxRadius_;
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double maxRadius2_;
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double scale_W_;
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double scale_GradW_;
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};
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}}}
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#endif
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