Convolutional Kernels¶

Provides the kernel classes for the convolution done when computing the weighted density of the points.

Authors

Simone Balducci, Felice Pantaleo, Marco Rovere, Wahid Redjeb, Aurora Perego, Francesco Giacomini

namespace clue¶

class ExponentialKernel¶

#include <ConvolutionalKernel.hpp>

The ExponentialKernel class implements an exponential kernel for convolution. It computes the kernel value based on the exponential function, which is defined by its average and amplitude.

Public Functions¶

ExponentialKernel(float exp_avg, float exp_amplitude)¶

Construct an ExponentialKernel object.

Parameters:¶

float exp_avg¶

The average value for the exponential kernel

float exp_amplitude¶

The amplitude for the exponential kernel

template<typename TAcc>
ALPAKA_FN_ACC float operator()(const TAcc &acc, float dist_ij, int point_id, int j) const¶

Computes the kernel value between two points.

Parameters:¶

const TAcc &acc¶

The accelerator to use for the computation

float dist_ij¶

The distance between the two points

int point_id¶

The index of the first point

int j¶

The index of the second point

Returns:¶

The computed kernel value

Private Members¶

float m_exp_avg¶

float m_exp_amplitude¶

class FlatKernel¶

#include <ConvolutionalKernel.hpp>

The FlatKernel class implements a flat kernel for convolution. It returns a constant value for the kernel, regardless of the distance between points.

Public Functions¶

FlatKernel(float flat)¶

Construct a FlatKernel object.

Parameters:¶

float flat¶

The flat value for the kernel

template<typename TAcc>
ALPAKA_FN_ACC float operator()(const TAcc &acc, float dist_ij, int point_id, int j) const¶

Computes the kernel value between two points.

Parameters:¶

const TAcc &acc¶

The accelerator to use for the computation

float dist_ij¶

The distance between the two points

int point_id¶

The index of the first point

int j¶

The index of the second point

Returns:¶

The computed kernel value

Private Members¶

float m_flat¶

class GaussianKernel¶

#include <ConvolutionalKernel.hpp>

The GaussianKernel class implements a Gaussian kernel for convolution. It computes the kernel value based on the Gaussian function, which is defined by its average, standard deviation, and amplitude.

Public Functions¶

GaussianKernel(float gaus_avg, float gaus_std, float gaus_amplitude)¶

Construct a GaussianKernel object.

Parameters:¶

float gaus_avg¶

The average value for the Gaussian kernel

float gaus_std¶

The standard deviation for the Gaussian kernel

float gaus_amplitude¶

The amplitude for the Gaussian kernel

template<typename TAcc>
ALPAKA_FN_ACC float operator()(const TAcc &acc, float dist_ij, int point_id, int j) const¶

Computes the kernel value between two points.

Parameters:¶

const TAcc &acc¶

The accelerator to use for the computation

float dist_ij¶

The distance between the two points

int point_id¶

The index of the first point

int j¶

The index of the second point

Returns:¶

The computed kernel value

Private Members¶

float m_gaus_avg¶

float m_gaus_std¶

float m_gaus_amplitude¶