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R1448/Benchmarks/ChiBenchmark/chi.cpp
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chi.cpp
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#include <iostream>
#include <string.h>
//#include <cuda_runtime.h>
#include <math.h>
#include <sys/time.h>
#include <fstream>
#include <immintrin.h>
//#include "simd_math.h"
#include "chi.hpp"
#ifdef _OPENMP
#include <omp.h>
#endif
#define MIN(a,b) (((a)<(b))?(a):(b))
#define MAX(a,b) (((a)>(b))?(a):(b))
void chi_bruteforce_SOA_CPU_grid_srcplane(double *chi, int *error, runmode_param *runmode, const struct Potential_SOA *lens, const struct grid_param *frame, const int *nimages_strongLensing, galaxy *images){
double dx,dy,x_pos,y_pos; //pixelsize
dx = (frame->xmax - frame->xmin)/(runmode->nbgridcells-1);
dy = (frame->ymax - frame->ymin)/(runmode->nbgridcells-1);
int index=0; // index of the image within the total image array
int grid_dim;
double im_dist[MAXIMPERSOURCE]; // distance to a real image for an "theoretical" image found from a theoretical source
int im_index; // index of the closest real image for an image found from a theoretical source
int second_closest_id; // index of the second closest real image for an image found from a theoretical source
int thread_found_image = 0; // at each iteration in the lens plane, turn to 1 whether the thread find an image
struct point im_position, temp; // position of the image found from a theoretical source + temp variable for comparison
struct triplet Tsup, Tinf, Tsupsource, Tinfsource;// triangles for the computation of the images created by the theoretical sources
struct galaxy sources[runmode->nsets]; // theoretical sources (common for a set)
int nimagesfound[runmode->nimagestot][MAXIMPERSOURCE]; // number of images found from the theoretical sources
struct point tim[runmode->nimagestot][MAXIMPERSOURCE]; // theoretical images (computed from sources)
double *grid_srcplane_x, *grid_srcplane_y;
grid_srcplane_x = (double *)malloc((int) (runmode->nbgridcells) * (runmode->nbgridcells) * sizeof(double));
grid_srcplane_y = (double *)malloc((int) (runmode->nbgridcells) * (runmode->nbgridcells) * sizeof(double));
grid_dim = runmode->nbgridcells;
//Packaging the image to sourceplane conversion
grid_srcplane_conversion_CPU(grid_srcplane_x,grid_srcplane_y,frame,lens,images[0].dr,runmode->Nlens,grid_dim);
index = 0;
*chi = 0;
for( int source_id = 0; source_id < runmode->nsets; source_id ++){
//////////////////////////////////////Initialisation//////////////////////////////////////
for (int i=0; i < nimages_strongLensing[source_id]; ++i){
for (int j=0; j < nimages_strongLensing[source_id]; ++j){
nimagesfound[i][j] = 0;
}
}
for( int image_id = 0; image_id < nimages_strongLensing[source_id]; image_id++){
//////////////////////////////////////computation of theoretical sources//////////////////////////////////////
chi_transformImageToSourcePlane_SOA(runmode->Nlens, &images[index+image_id].center,images[index+image_id].dr,lens,&sources[source_id].center);
//if (DEBUG ==1 )
//printf("index %d image_id %d source_id %d %f \n",index, image_id, source_id,images[index+image_id].redshift);
sources[source_id].redshift = images[index+image_id].redshift;
sources[source_id].dr = images[index+image_id].dr;
sources[source_id].dls = images[index+image_id].dls;
sources[source_id].dos = images[index+image_id].dos;
for (int x_id = 0; x_id < runmode->nbgridcells-1; ++x_id ){
for (int y_id = 0; y_id < runmode->nbgridcells-1; ++y_id ){
x_pos = frame->xmin + x_id * dx;
y_pos = frame->ymin + y_id * dy;
// Define the upper + lower triangle, both together = square = pixel
Tsup.a.x=x_pos;
Tsup.b.x=x_pos;
Tsup.c.x=x_pos+dx;
Tinf.a.x=x_pos+dx;
Tinf.b.x=x_pos+dx;
Tinf.c.x=x_pos;
Tsup.a.y=y_pos;
Tsup.b.y=y_pos+dy;
Tsup.c.y=y_pos;
Tinf.a.y=y_pos+dy;
Tinf.b.y=y_pos;
Tinf.c.y=y_pos+dy;
// Lens to Sourceplane conversion of triangles
chi_transformtriangleImageToSourcePlane_SOA_Packed_upper(runmode->Nlens,&Tsup, &Tsupsource,grid_srcplane_x,grid_srcplane_y,x_id*grid_dim+y_id, grid_dim);
chi_transformtriangleImageToSourcePlane_SOA_Packed_lower(runmode->Nlens,&Tinf, &Tinfsource,grid_srcplane_x,grid_srcplane_y,x_id*grid_dim+y_id, grid_dim);
thread_found_image=0;
if(chi_insideborder(&sources[source_id].center,&Tsupsource)==1){
thread_found_image=1; // thread has just found an image
im_index=0;
im_position=chi_barycenter(&Tsup);
//printf("%d %d %d %f %f a %f %f b %f %f c %f %f \n",x_id*grid_dim+y_id,x_id,y_id,im_position.x,im_position.y,Tsupsource.a.x,Tsupsource.a.y,Tsupsource.b.x,Tsupsource.b.y,Tsupsource.c.x,Tsupsource.c.y);
im_dist[im_index]=chi_dist(im_position,images[index+im_index].center); // get the distance to the real image
for(int i=1; i<nimages_strongLensing[source_id]; i++){ // get the distance to each real image and keep the index of the closest real image
im_dist[i]=chi_dist(im_position,images[index+i].center);
if(im_dist[i]<im_dist[im_index]){
im_index=i;
}
//printf(" im_index %d im pos x %f y %f xS %f yS %f im_dist actual %f im_dist %f \n",im_index,im_position.x,im_position.y,chi_barycenter(&Tsupsource).x,chi_barycenter(&Tsupsource).y, im_dist[im_index], im_dist[i]);
}
}
if(chi_inside(&sources[source_id].center,&Tinfsource)==1){
thread_found_image=1; // thread has just found an image
im_index=0;
im_position=chi_barycenter(&Tinf); // get the barycenter of the triangle
//printf("%d %d %d %f %f a %f %f b %f %f c %f %f \n",x_id*grid_dim+y_id,x_id,y_id,im_position.x,im_position.y,Tsupsource.a.x,Tsupsource.a.y,Tsupsource.b.x,Tsupsource.b.y,Tsupsource.c.x,Tsupsource.c.y);
im_dist[im_index]=chi_dist(im_position,images[index+im_index].center); // get the distance to the real image
for(int i=1; i<nimages_strongLensing[source_id]; i++){ // get the distance to each real image and keep the index of the closest real image
im_dist[i]=chi_dist(im_position,images[index+i].center);
//printf("im_dist[i] %f, im_position %f %f , images[index+im_index].center %f %f\n",im_dist[i], im_position.x,im_position.y, images[index+i].center.x,images[index+i].center.y);
if(im_dist[i]<im_dist[im_index]){
im_index=i;
}
//printf(" im_index %d im pos x %f y %f xS %f yS %f im_dist actual %f im_dist %f \n",im_index,im_position.x,im_position.y,chi_barycenter(&Tinfsource).x,chi_barycenter(&Tinfsource).y, im_dist[im_index], im_dist[i]);
}
}
int skip_image = 0;
if(thread_found_image == 1 ){
skip_image = 0;
// Sometimes due to the numerical errors at the centerpoint, for SIE potentials an additional image will appear at the center of the Potential.
// This is due to the fact that it is not possible to simulate an infinity value at the center correctly, Check that sis correspond to Nlens[0]
for (int iterator=0; iterator < runmode->Nlens[0]; ++iterator){
//printf("lens[i].type %d %f %f %f \n",lens[i].type, fabs(im_position.x - lens[i].position.x) , fabs(im_position.y - lens[i].position.y), dx/2.);
if ( fabs(im_position.x - lens[0].position_x[iterator]) <= dx/2. and fabs(im_position.y - lens[0].position_y[iterator]) <= dx/2.){
skip_image = 1;
printf("WARNING: You are using SIE potentials. An image to close to one of the potential centers has been classified as numerical error and removed \n");
}
}
if(skip_image==0){
//checking whether a closest image has already been found
//printf("imagenumber %d im_index %d , im_position.x %f , im_position.y %f \n", image_id, im_index , im_position.x , im_position.y);
if(nimagesfound[image_id][im_index]==0){ // if no image found up to now
tim[image_id][im_index]=im_position; //image position is allocated to theoretical image
nimagesfound[image_id][im_index]++;
}
else if(nimagesfound[image_id][im_index]>0){ // if we have already found an image
// If the new image we found is closer than the previous image
if(im_dist[im_index]<chi_dist(images[index+im_index].center,tim[image_id][im_index]))
{
temp=tim[image_id][im_index]; // we store the position of the old image in temp
tim[image_id][im_index]=im_position; // we link the observed image with the image we just found
}
else
{
temp=im_position; // we store the position of the image we just found in temp
}
// initialising second_closest_id to the highest value
// Loop over all images in the set except the closest one
// and initialize to the furthest away image
second_closest_id=0;
for(int i=1; i<nimages_strongLensing[source_id] && i!=im_index; i++)
{
if(im_dist[i]>im_dist[second_closest_id]) second_closest_id=i;
}
///////////////////////////////////////////////////////////////
// Loop over all images in the set that are not yet allocated to a theoretical image
// and allocate the closest one
for(int i=0; i<nimages_strongLensing[source_id] && nimagesfound[image_id][i]==0; i++) // we search for an observed image not already linked (nimagesfound=0)
{
if(im_dist[i]<im_dist[second_closest_id])
{
second_closest_id=i;
im_index=i; // im_index value changes only if we found a not linked yet image
tim[image_id][im_index]=temp; // if we found an observed and not already linked image, we allocate the theoretical image temp
}
}
nimagesfound[image_id][im_index]++; // increasing the total number of images found (If we find more than 1 theoretical image linked to 1 real image, these theoretical
// images are included in this number)
}
}
thread_found_image=0; // for next iteration
}
}
}
}
//////////////////////////////////////computing the local chi square//////////////////////////////////////
double chiimage;
for( int iter = 0; iter < nimages_strongLensing[source_id]*nimages_strongLensing[source_id]; iter++){
int i=iter/nimages_strongLensing[source_id];
int j=iter % nimages_strongLensing[source_id];
if(i!=j){
// In the current method, we get the source in the source plane by ray tracing image in nimagesfound[i][i]. If we ray trace back,
// we arrive again at the same position and thus the chi2 from it is 0. Thus we do not calculate the chi2 (-> if i!=j)
if(nimagesfound[i][j]>0){
chiimage=pow(images[index+j].center.x-tim[i][j].x,2)+pow(images[index+j].center.y-tim[i][j].y,2); // compute the chi2
*chi += chiimage;
}
else if(nimagesfound[i][j]==0){
// If we do not find a correpsonding image, we add a big value to the chi2 to disfavor the model
*chi += 100.*nimages_strongLensing[source_id];
}
}
}
/*
for (int i=0; i < nimages_strongLensing[source_id]; ++i){
for (int j=0; j < nimages_strongLensing[source_id]; ++j){
printf(" %d",nimagesfound[i][j]);
}
printf("\n");
}*/
//Incrementing Index: Images already treated by previous source_id
index+=nimages_strongLensing[source_id];
}
free(grid_srcplane_x);
free(grid_srcplane_y);
}
void chi_bruteforce_SOA_CPU_grid_gradient(double *chi, int *error, runmode_param *runmode, const struct Potential_SOA *lens, const struct grid_param *frame, const int *nimages_strongLensing, galaxy *images){
double dx,dy,x_pos,y_pos; //pixelsize
dx = (frame->xmax - frame->xmin)/(runmode->nbgridcells-1);
dy = (frame->ymax - frame->ymin)/(runmode->nbgridcells-1);
int index=0; // index of the image within the total image array
int grid_dim;
double im_dist[MAXIMPERSOURCE]; // distance to a real image for an "theoretical" image found from a theoretical source
int im_index; // index of the closest real image for an image found from a theoretical source
int second_closest_id; // index of the second closest real image for an image found from a theoretical source
int thread_found_image = 0; // at each iteration in the lens plane, turn to 1 whether the thread find an image
struct point im_position, temp; // position of the image found from a theoretical source + temp variable for comparison
struct triplet Tsup, Tinf, Tsupsource, Tinfsource;// triangles for the computation of the images created by the theoretical sources
struct galaxy sources[runmode->nsets]; // theoretical sources (common for a set)
int nimagesfound[runmode->nimagestot][MAXIMPERSOURCE]; // number of images found from the theoretical sources
struct point tim[runmode->nimagestot][MAXIMPERSOURCE]; // theoretical images (computed from sources)
double *grid_gradient_x, *grid_gradient_y;
grid_gradient_x = (double *)malloc((int) (runmode->nbgridcells) * (runmode->nbgridcells) * sizeof(double));
grid_gradient_y = (double *)malloc((int) (runmode->nbgridcells) * (runmode->nbgridcells) * sizeof(double));
grid_dim = runmode->nbgridcells;
//Packaging the image to sourceplane conversion
gradient_grid_CPU(grid_gradient_x,grid_gradient_y,frame,lens,runmode->Nlens,grid_dim);
//printf ("%f %f \n", grid_srcplane_x[0],grid_srcplane_y[0]);
index = 0;
*chi = 0;
for( int source_id = 0; source_id < runmode->nsets; source_id ++){
//////////////////////////////////////Initialisation//////////////////////////////////////
for (int i=0; i < nimages_strongLensing[source_id]; ++i){
for (int j=0; j < nimages_strongLensing[source_id]; ++j){
nimagesfound[i][j] = 0;
}
}
for( int image_id = 0; image_id < nimages_strongLensing[source_id]; image_id++){
//////////////////////////////////////computation of theoretical sources//////////////////////////////////////
chi_transformImageToSourcePlane_SOA(runmode->Nlens, &images[index+image_id].center,images[index+image_id].dr,lens,&sources[source_id].center);
//if (DEBUG ==1 )
//printf("index %d image_id %d source_id %d %f \n",index, image_id, source_id,images[index+image_id].redshift);
sources[source_id].redshift = images[index+image_id].redshift;
sources[source_id].dr = images[index+image_id].dr;
sources[source_id].dls = images[index+image_id].dls;
sources[source_id].dos = images[index+image_id].dos;
for (int x_id = 0; x_id < runmode->nbgridcells-1; ++x_id ){
for (int y_id = 0; y_id < runmode->nbgridcells-1; ++y_id ){
x_pos = frame->xmin + x_id * dx;
y_pos = frame->ymin + y_id * dy;
// Define the upper + lower triangle, both together = square = pixel
Tsup.a.x=x_pos;
Tsup.b.x=x_pos;
Tsup.c.x=x_pos+dx;
Tinf.a.x=x_pos+dx;
Tinf.b.x=x_pos+dx;
Tinf.c.x=x_pos;
Tsup.a.y=y_pos;
Tsup.b.y=y_pos+dy;
Tsup.c.y=y_pos;
Tinf.a.y=y_pos+dy;
Tinf.b.y=y_pos;
Tinf.c.y=y_pos+dy;
// Lens to Sourceplane conversion of triangles
chi_transformtriangleImageToSourcePlane_SOA_grid_gradient_upper(runmode->Nlens,&Tsup, sources[source_id].dr,&Tsupsource,grid_gradient_x,grid_gradient_y,x_id*grid_dim+y_id, grid_dim);
chi_transformtriangleImageToSourcePlane_SOA_grid_gradient_lower(runmode->Nlens,&Tinf, sources[source_id].dr, &Tinfsource,grid_gradient_x,grid_gradient_y,x_id*grid_dim+y_id, grid_dim);
thread_found_image=0;
if(chi_insideborder(&sources[source_id].center,&Tsupsource)==1){
thread_found_image=1; // thread has just found an image
im_index=0;
im_position=chi_barycenter(&Tsup);
im_dist[im_index]=chi_dist(im_position,images[index+im_index].center); // get the distance to the real image
for(int i=1; i<nimages_strongLensing[source_id]; i++){ // get the distance to each real image and keep the index of the closest real image
im_dist[i]=chi_dist(im_position,images[index+i].center);
if(im_dist[i]<im_dist[im_index]){
im_index=i;
}
//printf(" im_index %d im_dist actual %f im_dist %f \n",im_index, im_dist[im_index], im_dist[i]);
}
}
if(chi_inside(&sources[source_id].center,&Tinfsource)==1){
thread_found_image=1; // thread has just found an image
im_index=0;
im_position=chi_barycenter(&Tinf); // get the barycenter of the triangle
im_dist[im_index]=chi_dist(im_position,images[index+im_index].center); // get the distance to the real image
for(int i=1; i<nimages_strongLensing[source_id]; i++){ // get the distance to each real image and keep the index of the closest real image
im_dist[i]=chi_dist(im_position,images[index+i].center);
//printf("im_dist[i] %f, im_position %f %f , images[index+im_index].center %f %f\n",im_dist[i], im_position.x,im_position.y, images[index+i].center.x,images[index+i].center.y);
if(im_dist[i]<im_dist[im_index]){
im_index=i;
}
//printf(" im_index %d im_dist actual %f im_dist %f \n",im_index, im_dist[im_index], im_dist[i]);
}
}
int skip_image = 0;
if(thread_found_image == 1 ){
skip_image = 0;
// Sometimes due to the numerical errors at the centerpoint, for SIE potentials an additional image will appear at the center of the Potential.
// This is due to the fact that it is not possible to simulate an infinity value at the center correctly, Check that sis correspond to Nlens[0]
for (int iterator=0; iterator < runmode->Nlens[0]; ++iterator){
//printf("lens[i].type %d %f %f %f \n",lens[i].type, fabs(im_position.x - lens[i].position.x) , fabs(im_position.y - lens[i].position.y), dx/2.);
if ( fabs(im_position.x - lens[0].position_x[iterator]) <= dx/2. and fabs(im_position.y - lens[0].position_y[iterator]) <= dx/2.){
skip_image = 1;
printf("WARNING: You are using SIE potentials. An image to close to one of the potential centers has been classified as numerical error and removed \n");
}
}
if(skip_image==0){
//checking whether a closest image has already been found
//printf("imagenumber %d im_index %d , im_position.x %f , im_position.y %f \n", image_id, im_index , im_position.x , im_position.y);
if(nimagesfound[image_id][im_index]==0){ // if no image found up to now
tim[image_id][im_index]=im_position; //image position is allocated to theoretical image
nimagesfound[image_id][im_index]++;
}
else if(nimagesfound[image_id][im_index]>0){ // if we have already found an image
// If the new image we found is closer than the previous image
if(im_dist[im_index]<chi_dist(images[index+im_index].center,tim[image_id][im_index]))
{
temp=tim[image_id][im_index]; // we store the position of the old image in temp
tim[image_id][im_index]=im_position; // we link the observed image with the image we just found
}
else
{
temp=im_position; // we store the position of the image we just found in temp
}
// initialising second_closest_id to the highest value
// Loop over all images in the set except the closest one
// and initialize to the furthest away image
second_closest_id=0;
for(int i=1; i<nimages_strongLensing[source_id] && i!=im_index; i++)
{
if(im_dist[i]>im_dist[second_closest_id]) second_closest_id=i;
}
///////////////////////////////////////////////////////////////
// Loop over all images in the set that are not yet allocated to a theoretical image
// and allocate the closest one
for(int i=0; i<nimages_strongLensing[source_id] && nimagesfound[image_id][i]==0; i++) // we search for an observed image not already linked (nimagesfound=0)
{
if(im_dist[i]<im_dist[second_closest_id])
{
second_closest_id=i;
im_index=i; // im_index value changes only if we found a not linked yet image
tim[image_id][im_index]=temp; // if we found an observed and not already linked image, we allocate the theoretical image temp
}
}
nimagesfound[image_id][im_index]++; // increasing the total number of images found (If we find more than 1 theoretical image linked to 1 real image, these theoretical
// images are included in this number)
}
}
thread_found_image=0; // for next iteration
}
}
}
}
//////////////////////////////////////computing the local chi square//////////////////////////////////////
double chiimage;
for( int iter = 0; iter < nimages_strongLensing[source_id]*nimages_strongLensing[source_id]; iter++){
int i=iter/nimages_strongLensing[source_id];
int j=iter % nimages_strongLensing[source_id];
if(i!=j){
// In the current method, we get the source in the source plane by ray tracing image in nimagesfound[i][i]. If we ray trace back,
// we arrive again at the same position and thus the chi2 from it is 0. Thus we do not calculate the chi2 (-> if i!=j)
if(nimagesfound[i][j]>0){
chiimage=pow(images[index+j].center.x-tim[i][j].x,2)+pow(images[index+j].center.y-tim[i][j].y,2); // compute the chi2
*chi += chiimage;
}
else if(nimagesfound[i][j]==0){
// If we do not find a correpsonding image, we add a big value to the chi2 to disfavor the model
*chi += 100.*nimages_strongLensing[source_id];
}
}
}
/*
for (int i=0; i < nimages_strongLensing[source_id]; ++i){
for (int j=0; j < nimages_strongLensing[source_id]; ++j){
printf(" %d",nimagesfound[i][j]);
}
printf("\n");
}*/
//Incrementing Index: Images already treated by previous source_id
index+=nimages_strongLensing[source_id];
}
free(grid_gradient_x);
free(grid_gradient_y);
}
/** @brief Tranform a point from image to source plane. Result stored in sourcepoint argument
*
* Tranform a point from image to source plane using lensequation
*
* @param image_point image position
* @param dlsds dls/ds
* @param nhalos number of halos
* @param potential_param gravitational potential information
* @param source_point address where source information will be stored
*
*
*/
void chi_transformImageToSourcePlane(const runmode_param *runmode, const struct point *image_point, double dlsds, const struct Potential *lens, struct point *source_point)
{ // dlsds is the distance between lens and source divided by the distance observer-source
struct point Grad; // gradient
Grad = module_potentialDerivatives_totalGradient(runmode->nhalos, image_point, lens);
//Grad = module_potentialDerivatives_totalGradient_SOA(image_point, lens, runmode->Nlens);
source_point->x = image_point->x - dlsds * Grad.x;
source_point->y = image_point->y - dlsds * Grad.y;
//printf("dlsds %f", dlsds);
}
void chi_transformImageToSourcePlane_SOA(const int *Nlens, const struct point *image_point, double dlsds, const struct Potential_SOA *lens, struct point *source_point)
{ // dlsds is the distance between lens and source divided by the distance observer-source
struct point Grad; // gradient
Grad = module_potentialDerivatives_totalGradient_SOA(image_point, &lens[1], Nlens[1]);
source_point->x = image_point->x - dlsds * Grad.x;
source_point->y = image_point->y - dlsds * Grad.y;
//printf("dlsds %f", dlsds);
}
void chi_transformImageToSourcePlane_SOA_Packed(const int *Nlens, const struct point *image_point, double dlsds, struct point *source_point, double *grad_x, double * grad_y, int grad_id)
{
source_point->x = image_point->x - dlsds * grad_x[grad_id];
source_point->y = image_point->y - dlsds * grad_y[grad_id];
//printf("dlsds %f", dlsds);
}
/** @brief Tranform a triangle from image to source plane. Result stored in S triangle argument
*
* Return a triplet of points in the source plane corresponding to the triplet
* of images. dlsds is the lens efficiency at the source redshift.
* I is the triangle in the image plane (input), S is the same triangle in the source plane (output)
*
* @param I triangle in image plane
* @param dlsds dls/ds
* @param nhalos number of halos
* @param potential_param gravitational potential information
* @param S address where triangle source information will be stored
*
*
*/
void chi_transformtriangleImageToSourcePlane_SOA_Packed_upper(const int *Nlens, struct triplet *I, struct triplet *S, double *grid_srcplane_x, double * grid_srcplane_y, int grad_id, int nbgridcell)
{
S->a.x = grid_srcplane_x[grad_id];
S->a.y = grid_srcplane_y[grad_id];
S->b.x = grid_srcplane_x[grad_id+1];
S->b.y = grid_srcplane_y[grad_id+1];
S->c.x = grid_srcplane_x[grad_id+nbgridcell];
S->c.y = grid_srcplane_y[grad_id+nbgridcell];
}
void chi_transformtriangleImageToSourcePlane_SOA_Packed_lower(const int *Nlens, struct triplet *I, struct triplet *S, double *grid_srcplane_x, double * grid_srcplane_y, int grad_id, int nbgridcell)
{
S->a.x = grid_srcplane_x[grad_id+nbgridcell+1];
S->a.y = grid_srcplane_y[grad_id+nbgridcell+1];
S->b.x = grid_srcplane_x[grad_id+nbgridcell];
S->b.y = grid_srcplane_y[grad_id+nbgridcell];
S->c.x = grid_srcplane_x[grad_id+1];
S->c.y = grid_srcplane_y[grad_id+1];
}
void chi_transformtriangleImageToSourcePlane_SOA_grid_gradient_upper(const int *Nlens, struct triplet *I, double dlsds, struct triplet *S, double *grad_x, double * grad_y, int grad_id, int nbgridcell)
{
chi_transformImageToSourcePlane_SOA_Packed(Nlens, &I->a, dlsds, &S->a, grad_x, grad_y, grad_id);
chi_transformImageToSourcePlane_SOA_Packed(Nlens, &I->b, dlsds, &S->b, grad_x, grad_y, grad_id+1);
chi_transformImageToSourcePlane_SOA_Packed(Nlens, &I->c, dlsds, &S->c, grad_x, grad_y, grad_id+nbgridcell);
}
void chi_transformtriangleImageToSourcePlane_SOA_grid_gradient_lower(const int *Nlens, struct triplet *I, double dlsds, struct triplet *S, double *grad_x, double * grad_y, int grad_id, int nbgridcell)
{
chi_transformImageToSourcePlane_SOA_Packed(Nlens, &I->a, dlsds, &S->a, grad_x, grad_y, grad_id+nbgridcell+1);
chi_transformImageToSourcePlane_SOA_Packed(Nlens, &I->b, dlsds, &S->b, grad_x, grad_y, grad_id+nbgridcell);
chi_transformImageToSourcePlane_SOA_Packed(Nlens, &I->c, dlsds, &S->c, grad_x, grad_y, grad_id+1);
}
/** @brief Return the scalar triple product (a*b).c of the 3 vectors A[x,y,1], B[x,y,1], C[x,y,1].
* If 2 of the 3 vectors are equal, colinear or form an orthogonal basis,
* the triple product is 0.
* This is also the determinant of the matrix
* | Ax Bx Cx |
* | Ay By Cy |
* | 1 1 1 |
*/
double chi_determinant(const struct point *A,
const struct point *B,
const struct point *C)
{
return( B->x * C->y - B->y * C->x +
A->x * B->y - A->y * B->x +
A->y * C->x - A->x * C->y );
}
/** @brief Return 1 if P is inside the triangle T, 0 otherwise.
*
* Return 1 if P is inside the triangle T, 0 otherwise.
* @param P a point
* @param T a triplet of points.
*
*
*/
int chi_inside(const struct point *P, struct triplet *T)
{
double s, s1, s2, d;
d = chi_determinant(&T->a, &T->b, &T->c);
s = chi_determinant(&T->a, &T->b, P) * d;
s1 = chi_determinant(&T->b, &T->c, P) * d;
s2 = chi_determinant(&T->c, &T->a, P) * d;
return((s > 0.) && (s1 > 0.) && (s2 > 0.)); // If all determinants are positive,
// the point must be inside the triangle
}
/** @brief Return 1 if P is inside the triangle T or on its border, 0 otherwise.
*
* Return 1 if P is inside the triangle T or on its border, 0 otherwise.
* @param P a point
* @param T a triplet of points.
*
*
*/
int chi_insideborder(const struct point *P, struct triplet *T)
{
double s, s1, s2, d;
d = chi_determinant(&T->a, &T->b, &T->c);
s = chi_determinant(&T->a, &T->b, P) * d;
s1 = chi_determinant(&T->b, &T->c, P) * d;
s2 = chi_determinant(&T->c, &T->a, P) * d;
return((s >= 0.) && (s1 >= 0.) && (s2 >= 0.)); // If all determinants are positive or 0,
// the point must be inside the triangle or on its border
}
/** @brief Barycentre of a triplet/triangle
*
* A is a structure triplet that contains 3 structures point a,b and c
* Return value B is a point
*
*
*/
struct point chi_barycenter(struct triplet *A)
{
struct point B;
B.x = (A->a.x + A->b.x + A->c.x) / 3.;
B.y = (A->a.y + A->b.y + A->c.y) / 3.;
return(B);
}
/** @brief Euclidean distance between 2 points
*
* Euclidean distance between 2 points
*
*/
double chi_dist(struct point A, struct point B)
{
double x, y;
x = A.x - B.x;
y = A.y - B.y;
return(sqrt(x*x + y*y));
}
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