/* this is similar to a difference of gaussian (DoG) filter */
void update_centre_surround(unsigned char * img,
int img_width, int img_height,
int bitsperpixel,
long * integral_image,
int patch_width,
unsigned char * output_img,
int output_img_width,
int output_img_height)
{
int x, y, x0, y0, n=0, tx, ty, bx, by, c;
int outer = patch_width/2;
int inner = patch_width/4;
int patch_pixels = patch_width*patch_width/2;
long response_outer, response_inner, v;
int bytesperpixel = bitsperpixel/8;
/* update the integral image */
update_integral_image(img, img_width, img_height, bitsperpixel,
integral_image);
for (y = 0; y < output_img_height; y++) {
y0 = y * img_height / output_img_height;
ty = y0 - outer;
by = ty + patch_width;
if (ty < 0) ty = 0;
if (by >= img_height) by = img_height-1;
for (x = 0; x < output_img_width; x++) {
n = y*output_img_width + x;
x0 = x * img_width / output_img_width;
tx = x0 - outer;
bx = tx + patch_width;
if (tx < 0) tx = 0;
if (bx >= img_width) bx = img_width-1;
response_outer =
get_integral(integral_image,
tx, ty, bx, by, img_width);
response_inner =
get_integral(integral_image,
tx + inner, ty + inner,
tx + inner + outer, ty + inner + outer,
img_width)*4;
v = 127 + ((response_inner - response_outer)/
patch_pixels);
if (v < 0) v = 0;
if (v > 255) v = 255;
for (c = 0; c < bytesperpixel; c++) {
output_img[n*bytesperpixel + c] = (unsigned char)v;
}
}
}
}
int main(void)
{
double res, term1, term2, t1, t2, t3, t4, term;
int l, m, l1, m1, l_max;
printf("Insert l_max\n");
scanf( "%d" , &l_max);
printf("l_max = %i \n", l_max);
res = 0.;
for (l = 0; l <= l_max; l++){
for (m = -l; m <= l; m++){
l1 = l;
for (m1 = -l1; m1 <= l1; m1++){
printf(" l=%d , m=%d \n", l, m);
printf(" l1=%d , m1=%d \n", l1, m1);
// phi part
t1 = get_integral(0.,2.*PI, (double)l, (double)m, 1);
t2 = get_integral(0.,2.*PI, (double)l, (double)m, 2);
t3 = get_integral(0.,2.*PI, (double)l1, (double)m1, 1);
t4 = get_integral(0.,2.*PI, (double)l1, (double)m1, 2);
term1 = t1*t3 + t2*t4;
//term1 = get_integral(0.,2.*PI, (double)l, (double)m, 4);
//printf("term1 = %lf \n", term1);
// integrals over theta
term2 = get_integral(-1., 1., l, m, 3)*get_integral(-1., 1., l1, m1, 3);
//printf("term2 = %lf \n", term2);
term = term1*term2;
if (term != 0.0){
printf(" \n term = %lf \n", term);
}
res = res + term;
}
}
}
printf("\n res = %lf \n", res);
return 0;
}
int main(int argc,char* argv[]) {
AIDA::IAnalysisFactory* af = AIDA_createAnalysisFactory();
if(!af) return EXIT_FAILURE;
AIDA::ITreeFactory* trf = af->createTreeFactory();
if(!trf) return EXIT_FAILURE;
AIDA::ITree* tree = trf->create();
delete trf;
if(!tree) return EXIT_FAILURE;
AIDA::IHistogramFactory* hf = af->createHistogramFactory(*tree);
if(!hf) return EXIT_FAILURE;
AIDA::IHistogram1D* h1d = hf->createHistogram1D("master 1d","master 1d",50,-3,3);
AIDA::IHistogram1D* hr = hf->createHistogram1D("random","random",50,-3,3);
delete hf;
if(!h1d) return EXIT_FAILURE;
if(!hr) return EXIT_FAILURE;
{ // fill the "master" histogram with a gaussian centered at zero, and a rms of one
for (int i=0; i<1000000; i++) {
h1d->fill(rgauss_shoot());
}
}
{ // fill the "random" histogram with values sampled from the "master"
std::vector<double> integral;
if(!get_integral(*h1d,integral)) return EXIT_FAILURE;
for (int i=0; i<1000000; i++) {
hr->fill(get_random(*h1d,integral));
}
}
AIDA::IPlotterFactory* pf = af->createPlotterFactory(argc,argv);
if(pf) {
AIDA::IPlotter* plotter = pf->create();
delete pf;
if(plotter) {
plotter->createRegions(1,2,0);
plotter->region(0)->plot(*h1d);
plotter->region(1)->plot(*hr);
plotter->show();
plotter->interact();
delete plotter;
}
} else {
// Printing some statistical values of the "master" histogram
std::cout << "Master :" << std::endl;
std::cout << "Title : " << h1d->title() << std::endl;
std::cout << "Entries: " << h1d->entries() << std::endl;
std::cout << "Mean : " << h1d->mean() << std::endl;
std::cout << "RMS : " << h1d->rms() << std::endl;
std::cout << "========" << std::endl;
// ... and the same for the "randomly sampled" histogram
std::cout << "Sampled:" << std::endl;
std::cout << "Title : " << hr->title() << std::endl;
std::cout << "Entries: " << hr->entries() << std::endl;
std::cout << "Mean : " << hr->mean() << std::endl;
std::cout << "RMS : " << hr->rms() << std::endl;
}
delete af;
std::cout << "That's it !" << std::endl;
return EXIT_SUCCESS;
}