diff --git a/src/HFS_API.cpp b/src/HFS_API.cpp
index ca6a31cd86bb8fe1b1e584870a41e10ba16aca0e..39b918650fac5a18a2f20cdb9dcae76c7fa2d785 100644
--- a/src/HFS_API.cpp
+++ b/src/HFS_API.cpp
@@ -1,8 +1,8 @@
/**
* @file HFS_API.cpp
* @author Gerald Mösenlechner (gerald.moesenlechner@univie.ac.at)
-* @date November, 2023
-* @version 1.0
+* @date January, 2024
+* @version 1.1
*
* @copyright
* This program is free software; you can redistribute it and/or modify it
@@ -32,11 +32,9 @@
const char* MODE_ACQU = "Acquisition";
const char* MODE_TRAC = "Tracking";
const char* MODE_STBY = "Standby";
-static double ROTMATRIX[9] = {-1, 0, 0, 0, 0.999998, -0.0017, 0, -0.0017, -0.999998};
-static double ROTMATRIX_SC[9] = {0, -1, 0, 0, 0, 1, -1, 0, 0};
-double smear_kernel_os[125*125];
-double smear_kernel[25*25];
+double smear_kernel_os[XDIM_KERNEL*5*YDIM_KERNEL*5];
+double smear_kernel[XDIM_KERNEL*YDIM_KERNEL];
double bias_sample[128];
double bias[XDIM*YDIM];
double dark[XDIM*YDIM];
@@ -79,7 +77,7 @@ int FGS :: reset_fgs(const char* config_file, int hard_reset)
const char* smear_buffer;
const char* psf1_buffer;
const char* psf2_buffer;
- const char* catalouge_buffer;
+ const char* catalogue_buffer;
const char* modeInput;
targets -> number = 0;
@@ -186,6 +184,7 @@ int FGS :: reset_fgs(const char* config_file, int hard_reset)
cTracking -> FirstChildElement("thresholding") -> QueryUnsignedText(&threshold_track);
cTracking -> FirstChildElement("delay") -> QueryDoubleText(&delay_track);
cTracking -> FirstChildElement("exposure_time") -> QueryDoubleText(&exp_track);
+ cTracking -> FirstChildElement("tolerance") -> QueryUnsignedText(&tolerance_track);
cTracking -> FirstChildElement("dim") -> QueryUnsignedText(&track_dim);
tinyxml2::XMLElement *cAcquisition = cRootElement -> FirstChildElement("Acquisition");
@@ -199,11 +198,11 @@ int FGS :: reset_fgs(const char* config_file, int hard_reset)
cAcquisition -> FirstChildElement("FGS2_dim") -> QueryUnsignedText(&acq_dim_fgs2);
cAcquisition -> FirstChildElement("target_limit") -> QueryUnsignedText(&max_targets);
cAcquisition -> FirstChildElement("extension_sigma") -> QueryUnsignedText(&extension_sigma);
- /*Parse and read stars from catalouge*/
- catalouge_buffer = cRootElement -> FirstChildElement("Star_catalouge") -> GetText();
- catalouge.assign(catalouge_buffer);
+ /*Parse and read stars from catalogue*/
+ catalogue_buffer = cRootElement -> FirstChildElement("Star_catalogue") -> GetText();
+ catalogue.assign(catalogue_buffer);
- search_star_id(targets, catalouge_buffer);
+ search_star_id(targets, catalogue_buffer);
cRootElement -> FirstChildElement("use_saved_files") -> QueryUnsignedText(&use_save);
hp_buffer = cRootElement -> FirstChildElement("hp_map") -> GetText();
@@ -317,7 +316,7 @@ int FGS :: reset_fgs(const char* config_file, int hard_reset)
smear_if.open(smear_buffer, std::ifstream::in);
if (smear_if.is_open()){
- for (i = 0; i < 125*125; i++){
+ for (i = 0; i < XDIM_KERNEL*5*YDIM_KERNEL*5; i++){
smear_if >> smear_kernel_os[i];
}
}
@@ -336,8 +335,7 @@ int FGS :: reset_fgs(const char* config_file, int hard_reset)
return 0;
}
-double angular_rate_sc[3];
-double angular_rate_opt[3];
+
double angular_rate_drf[3];
/**
@@ -357,50 +355,29 @@ double angular_rate_drf[3];
int FGS :: generate_smear(double (&angular_rate)[3], double dt)
{
- struct dmatrix rot_matrix_sc, rot_matrix_opt, ar, transf_opt, transf;
double unit_vec[3] = {0., 0., 1.};
+ double ar[3];
double x_smear, y_smear;
unsigned int i;
+ int status;
- rot_matrix_sc.data = ROTMATRIX_SC;
- rot_matrix_sc.xdim = 3;
- rot_matrix_sc.ydim = 3;
-
- rot_matrix_opt.data = ROTMATRIX;
- rot_matrix_opt.xdim = 3;
- rot_matrix_opt.ydim = 3;
-
- ar.data = angular_rate;
- ar.xdim = 1;
- ar.ydim = 3;
for (i = 0; i < 3; i++){
- ar.data[i] = ar.data[i]/3600; /*convert to degrees/s*/
+ ar[i] = angular_rate[i]/3600; /*convert to degrees/s*/
}
- transf_opt.data = angular_rate_sc;
- transf.data = angular_rate_opt;
+ cross3(ar, unit_vec, angular_rate_drf);
- dmatmult(rot_matrix_sc, ar, &transf_opt);
- dmatmult(rot_matrix_opt, transf_opt, &transf);
+ x_smear = - angular_rate_drf[0]*dt*3600000/plate_scale;
+ y_smear = - angular_rate_drf[1]*dt*3600000/plate_scale;
- cross3(transf.data, unit_vec, angular_rate_drf);
+ status = generate_linear_smearing_kernel(smear_kernel_os, x_smear_0 * 5, y_smear_0 * 5, x_smear * 5, y_smear * 5, XDIM_KERNEL*5);
- x_smear = -angular_rate_drf[0]*dt*3600000/plate_scale;
- y_smear = -angular_rate_drf[1]*dt*3600000/plate_scale;
-
- generate_linear_smearing_kernel(smear_kernel_os, x_smear_0 * 5, y_smear_0 * 5, x_smear * 5, y_smear * 5, 125);
x_smear_0 += x_smear;
y_smear_0 += y_smear;
-#if 0
- std::ofstream test_file;
- test_file.open("image.txt", std::ios_base::app);
- for (i = 0; i < 125*125; i++) {
- test_file << smear_kernel_os[i] << " ";
- if (i && !((i + 1) % (int)125))
- test_file << "\n";
- }
- test_file.close();
-#endif
+
+ if(status == 1){
+ std::cerr << "WARNING: angular rate exeeds smearing kernel borders at t = " << sim_time << "s!\n";
+ }
return 0;
}
@@ -416,11 +393,11 @@ int FGS :: generate_smear(double (&angular_rate)[3], double dt)
int FGS :: generate_image()
{
unsigned int i;
-
- downsample_image(smear_kernel_os, smear_kernel, 125, 125, 5);
-
- shift_smear(smear_kernel, x_smear_0, y_smear_0, 25);
-
+
+ shift_smear(smear_kernel_os, x_smear_0*5, y_smear_0*5, XDIM_KERNEL*5);
+
+ downsample_image(smear_kernel_os, smear_kernel, XDIM_KERNEL*5, YDIM_KERNEL*5, 5);
+
generate_bias(bias, bias_sample, bias_value, 128, dim_x, dim_y);
generate_dark(dark, dark_mean, exposure_time, hot_pixels, dim_x, dim_y);
@@ -442,10 +419,10 @@ int FGS :: generate_image()
}
for(i = 0; i < dim_x*dim_y; i++)
- {
+ {
starimage[i] = starimage[i] + bkgr[i];
}
-
+
generate_shot(starimage, shot, dim_x, dim_y);
for(i = 0; i < dim_x*dim_y; i++){
@@ -453,17 +430,6 @@ int FGS :: generate_image()
if (image[i] > full_well_cap)
image[i] = full_well_cap;
}
- /*Debug output for image*/
-#if 0
- std::ofstream test_file;
- test_file.open("image.txt");
- for (i = 0; i < dim_y*dim_y; i++) {
- test_file << image[i] << " ";
- if (i && !((i + 1) % (int)dim_x))
- test_file << "\n";
- }
- test_file.close();
-#endif
return 0;
}
@@ -484,7 +450,7 @@ int FGS :: perform_algorithm()
unsigned int i;
output.x = 0.;
output.y = 0.;
-
+
if(strcmp(mode, MODE_ACQU) == 0){
if (threshold_acq == 1){
min = GetMin(image, dim_x*dim_y);
@@ -497,10 +463,10 @@ int FGS :: perform_algorithm()
}
if (med_acq == 1){
MedFilter3x3(image, dim_x, dim_y, med_threshold, filtered_image);
- output = SourceDetection(filtered_image, dim_x, dim_y, 0, channel, max_targets, target_signal*exposure_time, tolerance_acq, extension_sigma, iter_acq, fwhm_x, fwhm_y, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma, pearson_limit);
+ output = SourceDetection(filtered_image, dim_x, dim_y, channel, max_targets, target_signal*exposure_time, tolerance_acq, extension_sigma, iter_acq, fwhm_x, fwhm_y, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma*(lower_sig_lim/100)*exposure_time, pearson_limit);
}
else{
- output = SourceDetection(image, dim_x, dim_y, 0, channel, max_targets, target_signal*exposure_time, tolerance_acq, extension_sigma, iter_acq, fwhm_x, fwhm_y, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma, pearson_limit);
+ output = SourceDetection(image, dim_x, dim_y, channel, max_targets, target_signal*exposure_time, tolerance_acq, extension_sigma, iter_acq, fwhm_x, fwhm_y, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma*(lower_sig_lim/100)*exposure_time, pearson_limit);
}
}
else if (strcmp(mode, MODE_TRAC) == 0){
@@ -512,13 +478,13 @@ int FGS :: perform_algorithm()
}
else if(threshold_track == 2){
std_threshold(image, dim_x, dim_y);
- }
+ }
if(med_track == 1){
MedFilter3x3(image, dim_x, dim_y, med_threshold, filtered_image);
- output = ArielCoG(filtered_image, dim_x, dim_y, iter_track, 0, fwhm_x, fwhm_y, channel, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma, pearson_limit);
+ output = ArielCoG(filtered_image, dim_x, dim_y, iter_track, fwhm_x, fwhm_y, channel, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma*(lower_sig_lim/100)*exposure_time, pearson_limit, tolerance_track, target_signal*exposure_time);
}
else{
- output = ArielCoG(image, dim_x, dim_y, iter_track, 0, fwhm_x, fwhm_y, channel, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma, pearson_limit);
+ output = ArielCoG(image, dim_x, dim_y, iter_track, fwhm_x, fwhm_y, channel, target_signal*(lower_sig_lim/100)*exposure_time, val_sigma*(lower_sig_lim/100)*exposure_time, pearson_limit, tolerance_track, target_signal*exposure_time);
}
}
@@ -616,24 +582,24 @@ int FGS :: reset_arrays(int reset_all)
unsigned int i;
random_normal_trm(bias_sample, 0, read_noise, 128);
//#pragma omp parallel for
- for(i = 0; i < XDIM*YDIM; i++){
- bias[i] = 0.;
- dark[i] = 0.;
- shot[i] = 0.;
- bkgr[i] = 0.;
- starmask[i] = 0.;
- starimage[i] = 0.;
- smeared_mask[i] = 0.;
- image[i] = 0;
- filtered_image[i] = 0;
- if(reset_all != 0){
- flat[i] = 0.;
- hot_pixels[i] = 0.;
- }
- if(i < 125*125){
- smear_kernel_os[i] = 0.;
+ for(i = 0; i < XDIM_KERNEL*5*YDIM_KERNEL*5; i++){
+ smear_kernel_os[i] = 0.;
+ if(i < XDIM*YDIM){
+ bias[i] = 0.;
+ dark[i] = 0.;
+ shot[i] = 0.;
+ bkgr[i] = 0.;
+ starmask[i] = 0.;
+ starimage[i] = 0.;
+ smeared_mask[i] = 0.;
+ image[i] = 0;
+ filtered_image[i] = 0;
+ if(reset_all != 0){
+ flat[i] = 0.;
+ hot_pixels[i] = 0.;
+ }
}
- if(i < 25*25){
+ if(i < XDIM_KERNEL*YDIM_KERNEL){
smear_kernel[i] = 0.;
}
}
@@ -854,6 +820,10 @@ int FGS :: generate_config(const char* output_file)
cTrackExp->SetText(exp_track);
cTracking->InsertEndChild(cTrackExp);
+ tinyxml2::XMLElement* cTrackTol = config.NewElement("tolerance");
+ cTrackTol->SetText(tolerance_track);
+ cTracking->InsertEndChild(cTrackTol);
+
tinyxml2::XMLElement* cTrackDim = config.NewElement("dim");
cTrackDim->SetText(track_dim);
cTracking->InsertEndChild(cTrackDim);
@@ -901,9 +871,9 @@ int FGS :: generate_config(const char* output_file)
cAcqExtSig->SetText(extension_sigma);
cAcquisition->InsertEndChild(cAcqExtSig);
- tinyxml2::XMLElement* cCatalouge = config.NewElement("Star_catalouge");
- cCatalouge->SetText(catalouge.c_str());
- cRoot->InsertEndChild(cCatalouge);
+ tinyxml2::XMLElement* ccatalogue = config.NewElement("Star_catalogue");
+ ccatalogue->SetText(catalogue.c_str());
+ cRoot->InsertEndChild(ccatalogue);
tinyxml2::XMLElement* cSave = config.NewElement("use_saved_files");
cSave->SetText(1);
@@ -952,7 +922,7 @@ int FGS :: generate_config(const char* output_file)
flat_of.close();
smear_of.open(smear_save, std::ofstream::out | std::ofstream::app);
- for (i = 0; i < 125*125; i++){
+ for (i = 0; i < XDIM_KERNEL*5*YDIM_KERNEL*5; i++){
smear_of << std::setprecision(std::numeric_limits<double>::max_digits10) << smear_kernel_os[i] << "\n";
}
smear_of.close();
@@ -1016,6 +986,7 @@ struct hfs_state FGS :: get_hfs_state()
output.med_acq = med_acq;
output.threshold_track = threshold_track;
output.threshold_acq = threshold_acq;
+ output.tolerance_track = tolerance_track;
output.tolerance_acq = tolerance_acq;
output.mode = mode;
output.targets = targets;
@@ -1043,17 +1014,12 @@ struct hfs_state FGS :: get_hfs_state()
output.psf_fgs1 = psf_fgs1;
output.psf_fgs2 = psf_fgs2;
output.input_file = input_file;
- output.catalouge = catalouge;
+ output.catalogue = catalogue;
output.targets = targets;
output.centroid = centroid;
return output;
}
-double transform_sc[3];
-double transform_opt[3];
-double transform_sc_vel[3];
-double transform_opt_vel[3];
-
/**
* @brief transforms vector from spacecraft reference frame to detector
* reference frame
@@ -1071,37 +1037,9 @@ double transform_opt_vel[3];
int FGS :: transform_to_detector(double (&vec)[3], double (&velVec)[3], int trf_x, int trf_y, double* output)
{
- struct dmatrix rot_matrix_sc, rot_matrix_opt, vector, transf_opt, transf, transf_opt_vel, transf_vel, velocity;
- double x_pos, y_pos, x_vel, y_vel;
-
- rot_matrix_sc.data = ROTMATRIX_SC;
- rot_matrix_sc.xdim = 3;
- rot_matrix_sc.ydim = 3;
-
- rot_matrix_opt.data = ROTMATRIX;
- rot_matrix_opt.xdim = 3;
- rot_matrix_opt.ydim = 3;
-
- vector.data = vec;
- vector.xdim = 1;
- vector.ydim = 3;
- velocity.data = velVec;
- velocity.xdim = 1;
- velocity.ydim = 3;
- transf_opt.data = transform_sc;
- transf.data = transform_opt;
- transf_opt_vel.data = transform_sc_vel;
- transf_vel.data = transform_opt_vel;
-
- dmatmult(rot_matrix_sc, vector, &transf_opt);
- dmatmult(rot_matrix_opt, transf_opt, &transf);
-
- dmatmult(rot_matrix_sc, velocity, &transf_opt_vel);
- dmatmult(rot_matrix_opt, transf_opt_vel, &transf_vel);
-
- x_vel = transf_vel.data[0];
- y_vel = transf_vel.data[1];
+ double x_pos, y_pos;
+ apply_aberration(vec, velVec);
if(strcmp(mode, MODE_TRAC) == 0){
/*Check if tracking window is inside of Acq window*/
@@ -1121,23 +1059,13 @@ int FGS :: transform_to_detector(double (&vec)[3], double (&velVec)[3], int trf_
trf_y = acq_dim_fgs2/2 - dim_y/2;
}
}
-
-
- transf.data[0] = transf.data[0] - x_vel/CVEL;
- transf.data[1] = transf.data[1] - y_vel/CVEL;
-
- x_pos = (transf.data[0]*(360/TWO_PI)*3600000 + offset[0])/plate_scale - trf_x;
- y_pos = (transf.data[1]*(360/TWO_PI)*3600000 + offset[1])/plate_scale - trf_y;
+ x_pos = (vec[0]*(360/TWO_PI)*3600000 + offset[0])/plate_scale - trf_x;
+ y_pos = (vec[1]*(360/TWO_PI)*3600000 + offset[1])/plate_scale - trf_y;
}
else{
- transf.data[0] = transf.data[0] - x_vel/CVEL;
- transf.data[1] = transf.data[1] - y_vel/CVEL;
-
-
- x_pos = (transf.data[0]*(360/TWO_PI)*3600000 + offset[0])/plate_scale;
- y_pos = (transf.data[1]*(360/TWO_PI)*3600000 + offset[1])/plate_scale;
- }
-
+ x_pos = (vec[0]*(360/TWO_PI)*3600000 + offset[0])/plate_scale;
+ y_pos = (vec[1]*(360/TWO_PI)*3600000 + offset[1])/plate_scale;
+ }
if(abs(x_pos) < (dim_x/2)){
if(abs(y_pos) < (dim_y/2)){
output[0] = x_pos;
@@ -1205,11 +1133,6 @@ int FGS :: transform_star_coordinates(double (&quaternion)[4], double (&velocity
}
}
-#if 0
- for(i = 0; i < targets -> number; i++)
- std::cout << targets -> id[i] << ": " << targets -> visible[i] << "\n";
-#endif
-
return 0;
}
@@ -1238,8 +1161,8 @@ int FGS :: generate_centroid(hfs_parameters update)
centroid.x = (centroid.x - dim_x/2) * plate_scale;
centroid.y = (centroid.y - dim_y/2) * plate_scale;
- centroid.x = (centroid.x + random_normal_number(0, jitter_error) + ((double) update.add_shift_x/10)) * update.mult_shift_x;
- centroid.y = (centroid.y + random_normal_number(0, jitter_error) + ((double) update.add_shift_y/10)) * update.mult_shift_y;
+ centroid.x = (centroid.x + random_normal_number(0, jitter_error) + ((double) update.add_shift_x)) * update.mult_shift_x;
+ centroid.y = (centroid.y + random_normal_number(0, jitter_error) + ((double) update.add_shift_y)) * update.mult_shift_y;
@@ -1378,7 +1301,7 @@ int FGS :: set_params(hfs_parameters update, outputHfs *outPacket)
if((strcmp(mode, update_mode_char) != 0) || channel != update.channel){
transition_end = sim_time + transition_delay;
- }
+ }
}
else{
generate_smear(update.ang_rate, timestep);
@@ -1427,29 +1350,29 @@ int FGS :: set_params(hfs_parameters update, outputHfs *outPacket)
char line[1024];
/**
- * @brief searches star catalouge for given id and adds it to a stars struct
+ * @brief searches star catalogue for given id and adds it to a stars struct
*
- * Parser searching the star catalouge for the given target name and adding the
+ * Parser searching the star catalogue for the given target name and adding the
* cordinates and fluxes to the passed struct. Automatically handels the
* incrementation of the the target counter.
*
* @param sim_stars: pointer to the destination struct
- * @param catalouge: star catalouge used
+ * @param catalogue: star catalogue used
*
* @return 0 on success, 1 if target cannot be found
*/
-int search_star_id(struct stars* sim_stars, const char* catalouge)
+int search_star_id(struct stars* sim_stars, const char* catalogue)
{
- FILE* stream = fopen(catalouge, "r");
+ FILE* stream = fopen(catalogue, "r");
char* end;
const char* tok;
unsigned int i;
if(stream == NULL){
- std::cerr << "Star catalouge could not be found!\n";
+ std::cerr << "Star catalogue could not be found!\n";
return -1;
}
@@ -1462,20 +1385,17 @@ int search_star_id(struct stars* sim_stars, const char* catalouge)
i = 0;
for(tok = strtok(NULL, ",\n"); tok && *tok; i++, tok = strtok(NULL, ",\n")){
- switch(i){
+ switch(i){
case 0:
- strtod(tok, &end);
- break;
- case 1:
sim_stars -> signalFGS1[sim_stars -> number] = strtod(tok, &end);
break;
- case 2:
+ case 1:
sim_stars -> signalFGS2[sim_stars -> number] = strtod(tok, &end);
break;
- case 3:
+ case 2:
sim_stars -> ra[sim_stars -> number] = strtod(tok, &end);
break;
- case 4:
+ case 3:
sim_stars -> dec[sim_stars -> number] = strtod(tok, &end);
sim_stars -> number++;
break;
@@ -1519,4 +1439,72 @@ int multiply_quaternion(double (&quaternion1)[4], double (&quaternion2)[4], doub
return 0;
}
+/**
+ * @brief Normalizes a 3D Vector
+ *
+ * The function normalizes a 3 dimensional vector
+ *
+ * @param vec: input vector
+ */
+void normalize(double* vec)
+{
+ double norm;
+ unsigned int i;
+ norm = sqrt(dot(vec, vec, 3));
+ for (i = 0; i < 3; ++i) {
+ vec[i] /= norm;
+ }
+}
+
+/**
+ * @brief Determine relativistic aberration based on velocity vector
+ *
+ * The function shifts the input vector starVec based on the realtivistic aberration
+ * introduced by the velocity vector vel´.
+ *
+ * @param starVec: stellar input vector
+ * @param vel: velocity vector in km/s
+ */
+void apply_aberration(double* starVec, double *vel)
+{
+ double n_AX[3], n_AY[3], n_AZ[3], paraCheck[3];
+ double cosTheta0, sinTheta0, cosTheta, sinTheta, velOnCNorm;
+ unsigned int i;
+
+ cross3(starVec, vel, paraCheck);
+
+ normalize(starVec);
+
+ if (dot(vel, vel, 3) < 1e-20) {
+ return; /* neglect tiny correction */
+ }
+
+ if(fabs(paraCheck[0]) < 1e-5 && fabs(paraCheck[1]) < 1e-5 && fabs(paraCheck[2]) < 1e-5){
+ return; /*check if parallel*/
+ }
+ n_AX[0] = vel[0];
+ n_AX[1] = vel[1];
+ n_AX[2] = vel[2];
+
+ normalize(n_AX);
+
+ cross3(n_AX, starVec, n_AZ);
+
+ normalize(n_AZ);
+
+ cross3(n_AZ, n_AX, n_AY);
+
+ cosTheta0 = -1.0 * dot(starVec, n_AX, 3);
+ sinTheta0 = -1.0 * dot(starVec, n_AY, 3);
+
+ velOnCNorm = sqrt(dot(vel, vel, 3)) / CVEL;
+
+ cosTheta = (cosTheta0 - velOnCNorm) / (1 - velOnCNorm*cosTheta0);
+ sinTheta = (sinTheta0 > 0 ? +1.0 : -1.0) * sqrt(1 - cosTheta*cosTheta);
+
+ for (i = 0; i < 3; ++i){
+ starVec[i] = -1.0 * (cosTheta * n_AX[i] + sinTheta * n_AY[i]);
+ }
+ return;
+}
\ No newline at end of file
diff --git a/src/HFS_API.hpp b/src/HFS_API.hpp
index 27afae073b6a81814cfff4023626f8f5ed18a96b..5fbcdc2f3fc16df5d766c5327d5a2f85f2a1b91d 100644
--- a/src/HFS_API.hpp
+++ b/src/HFS_API.hpp
@@ -1,8 +1,8 @@
/**
* @file HFS_API.hpp
* @author Gerald Mösenlechner (gerald.moesenlechner@univie.ac.at)
-* @date November, 2023
-* @version 1.0
+* @date January, 2024
+* @version 1.1
*
* @copyright
* This program is free software; you can redistribute it and/or modify it
@@ -46,8 +46,8 @@
#define YDIM 200
#define XDIM_PSF 40
#define YDIM_PSF 40
-#define XDIM_KERNEL 25
-#define YDIM_KERNEL 25
+#define XDIM_KERNEL 50
+#define YDIM_KERNEL 50
#define TWO_PI 6.28318531f
#define CVEL 299792.458f //km/s
@@ -106,6 +106,7 @@ struct hfs_state
unsigned int iter_track;
unsigned int iter_acq;
unsigned int med_track;
+ unsigned int tolerance_track;
unsigned int med_acq;
unsigned int threshold_track;
unsigned int threshold_acq;
@@ -135,7 +136,7 @@ struct hfs_state
std::string psf_fgs1;
std::string psf_fgs2;
const char* input_file;
- std::string catalouge;
+ std::string catalogue;
struct stars* targets = new stars();
struct coord centroid;
};
@@ -224,6 +225,8 @@ int search_star_id(struct stars*, const char*);
int multiply_quaternion(double (&)[4], double (&)[4], double (&)[4]);
int generate_shotnoise(double*, double*, double*, unsigned int);
+
+void apply_aberration(double* ,double*);
/**
* /class FGS
* @brief The FGS class provides the main interface for the HFS.
@@ -292,6 +295,7 @@ class FGS{
unsigned int iter_track;
unsigned int iter_acq;
unsigned int med_track;
+ unsigned int tolerance_track;
unsigned int med_acq;
unsigned int threshold_track;
unsigned int threshold_acq;
@@ -322,7 +326,7 @@ class FGS{
std::string psf_fgs1;
std::string psf_fgs2;
const char* input_file;
- std::string catalouge;
+ std::string catalogue;
struct stars* targets = new stars();
struct coord centroid;
centroidError error;
diff --git a/src/HFS_Wrapper.cpp b/src/HFS_Wrapper.cpp
index 7af6b6a3d1c8dfec05aef13a2fa5e5ffbdea15f6..96ae9b2dc019f794ba8064537ddb48d6ae3a1e8b 100644
--- a/src/HFS_Wrapper.cpp
+++ b/src/HFS_Wrapper.cpp
@@ -1,8 +1,8 @@
/**
* @file HFS_Wrapper.cpp
* @author Gerald Mösenlechner (gerald.moesenlechner@univie.ac.at)
-* @date November, 2023
-* @version 1.0
+* @date January, 2024
+* @version 1.1
*
* @copyright
* This program is free software; you can redistribute it and/or modify it
diff --git a/src/Star_catalogue.csv b/src/Star_catalogue.csv
new file mode 100644
index 0000000000000000000000000000000000000000..27da4fa502d3f0e5088ffb7e20763ebd34dd3ffb
--- /dev/null
+++ b/src/Star_catalogue.csv
@@ -0,0 +1,2214 @@
+Name,FGS1,FGS2,ra,dec
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+BKGR1456,7075.324796138,56890.4339663181,94.79328,73.827682
+BKGR1457,819.87261612076,6592.33466620078,94.767155,73.819916
diff --git a/src/detector_features.c b/src/detector_features.c
index cf17a88cd6f1ee33097d95b79e9cf9930a0fa89d..20ef70f9d4959262b6e3abaa1d56f676a6448d0e 100644
--- a/src/detector_features.c
+++ b/src/detector_features.c
@@ -1,8 +1,8 @@
/**
* @file detector_features.c
* @author Gerald Mösenlechner (gerald.moesenlechner@univie.ac.at)
-* @date November, 2023
-* @version 1.0
+* @date January, 2024
+* @version 1.1
*
* @copyright
* This program is free software; you can redistribute it and/or modify it
@@ -201,7 +201,6 @@ void set_star_in_image(double *image, unsigned int width, unsigned int height, d
*/
void generate_starmask(double *mask, struct stars star_field, double exposure_time, unsigned int detector_width, unsigned int detector_height, unsigned int channel)
{
-
unsigned int i;
double signal;
@@ -326,49 +325,57 @@ double complement(double x)
* @param oversampling: Oversampling of the image
*
*/
-void generate_linear_smearing_kernel(double *smear_kernel, double x_origin, double y_origin, double x, double y, unsigned int dim)
+int generate_linear_smearing_kernel(double *smear_kernel, double x_origin, double y_origin, double x, double y, unsigned int dim)
{
double dx, dy, grad, xEnd, yEnd, xGap, x0, x1, y0, y1, inter;
unsigned int xPoint1, xPoint2, yPoint1, yPoint2, i;
bool steep;
+ int warning = 0;
x0 = dim/2 + x_origin;
y0 = dim/2 + y_origin;
x1 = x0 + x;
y1 = y0 + y;
- if(x0 == x1 && y0 == y1){
+
+ if(fabs(x0-x1) < 1e-7 && fabs(y0 - y1) < 1e-7){
SET_PIXEL_SMEAR(smear_kernel, dim, (int) x0, (int )y0, 1);
- return;
+ return warning;
}
-
if(x0 > (dim-1)){
x0 = dim-1;
- }
+ warning = 1;
+ }
if(x0 < 0){
x0 = 0;
+ warning = 1;
}
if(x1 > (dim-1)){
x1 = dim-1;
+ warning = 1;
}
if(x1 < 0){
x1 = 0;
}
if(y0 > (dim-1)){
y0 = dim-1;
+ warning = 1;
}
if(y0 < 0){
y0 = 0;
+ warning = 1;
}
if(y1 > (dim-1)){
y1 = dim-1;
+ warning = 1;
}
if(y1 < 0){
y1 = 0;
+ warning = 1;
}
- steep = abs(y1 - y0) > abs(x1 - x0);
+ steep = fabs(y1 - y0) > fabs(x1 - x0);
if(steep){
SWAP(double, x0, y0);
SWAP(double, x1, y1);
@@ -382,7 +389,8 @@ void generate_linear_smearing_kernel(double *smear_kernel, double x_origin, doub
dx = x1 - x0;
dy = y1 - y0;
- if(dx == 0.0){
+
+ if(fabs(dx) < 1e-7){
grad = 1.0;
}
else{
@@ -441,7 +449,7 @@ void generate_linear_smearing_kernel(double *smear_kernel, double x_origin, doub
}
if((xPoint2 - xPoint1) <=1 && (yPoint2 - yPoint1) <=1){
- return;
+ return warning;
}
if(steep){
@@ -458,6 +466,7 @@ void generate_linear_smearing_kernel(double *smear_kernel, double x_origin, doub
inter = inter + grad;
}
}
+ return warning;
}
/**
@@ -500,11 +509,11 @@ void generate_shot(double *signal, double *shot_noise, unsigned int width, unsig
}
}
-double smear_buffer[50*50];
+double smear_buffer[500*500];
/**
* @brief Function for inverting and normalizing the smearing kernel so that the end
- * point is centered note that this function is designed for the downsampled kernel with size 25*25
+ * point is centered note that this function is designed for the downsampled kernel with size 50*50
*
* @param[out] smear: smearing kernel
* @param x_smear: endpoint of the smear in x dim
@@ -521,13 +530,13 @@ void shift_smear(double *smear, double x_smear, double y_smear, unsigned int dim
x_diff = (int) - x_smear;
y_diff = (int) - y_smear;
- bzero(smear_buffer, 50*50);
+ bzero(smear_buffer, 500*500);
for(i = 0; i < dim; i++){
for(j = 0; j < dim; j++){
if((i+x_diff) >= 0 && (i+x_diff) < dim){
if((j+y_diff) >= 0 && (j+y_diff) < dim){
- SET_PIXEL(smear_buffer, 50, i+x_diff, j+y_diff, smear[i + dim*j]);
+ SET_PIXEL(smear_buffer, 500, i+x_diff, j+y_diff, smear[i + dim*j]);
}
}
}
@@ -535,7 +544,7 @@ void shift_smear(double *smear, double x_smear, double y_smear, unsigned int dim
for(i = 0; i < dim; i++){
for(j = 0; j < dim; j++){
- smear[i + dim*j] = smear_buffer[i + 50*j];
+ smear[i + dim*j] = smear_buffer[i + 500*j];
sum = sum + smear[i + dim*j];
}
}
diff --git a/src/detector_features.h b/src/detector_features.h
index e09b5d27b9689c77885130f363576abe1194583c..73c8dd8e1d8eb780a0d2a0f9ba460334c99c53f6 100644
--- a/src/detector_features.h
+++ b/src/detector_features.h
@@ -45,7 +45,7 @@ void generate_background(double *, double, double, double, int, int);
void smear_star_image(double *, double *, double*, unsigned int, unsigned int, unsigned int, unsigned int);
-void generate_linear_smearing_kernel(double *, double, double, double, double, unsigned int);
+int generate_linear_smearing_kernel(double *, double, double, double, double, unsigned int);
void generate_shot(double *, double *, unsigned int, unsigned int);
diff --git a/src/fcu_algorithms.c b/src/fcu_algorithms.c
index 596568e3f41e9d542d41159bd41884e0419003fe..7209ab8a2c60668512a8568aff18795c06704482 100644
--- a/src/fcu_algorithms.c
+++ b/src/fcu_algorithms.c
@@ -1,8 +1,8 @@
/**
* @file fcu_algorithms.c
* @author Gerald Mösenlechner (gerald.moesenlechner@univie.ac.at)
-* @date November, 2023
-* @version 1.0
+* @date January, 2024
+* @version 1.1
*
* @copyright
* This program is free software; you can redistribute it and/or modify it
@@ -36,7 +36,6 @@
#define SIGDIVFWHM 0.42466452f
#define AMPL_PSF 270.0f
#define TWO_PI 6.28318531f
-#define MODE_GAUSS 0
#define XDIM 200
#define YDIM 200
#define BIN 3
@@ -155,139 +154,6 @@ void get_2D_gaussian (float *img, unsigned int cols, unsigned int rows, float ce
return;
}
-/**
- * @brief Function for generating a linear approximation of a gaussian
- * weighting function.
- *
- * This functions takes a 1D gaussian function approximated by multiple linear
- * functions and rotates it in order to generate a weighting function with
- * a FWHM of 10 px in x and 15 px in y. (This methods is no longer in use as
- * the current size makes this function slower than the analytical gaussian.)
- *
- * @param[out] img: target buffer for gaussian function
- * @param cols/rows: dimensions of the input buffer
- * @param center_x/center_y: coordinates of center of gaussian
- * @param Fgs: channel of the fgs
- */
-void GetArielPSF(float *img, unsigned int cols, unsigned int rows, float center_x, float center_y, unsigned int Fgs)
-{
- unsigned int x, y;
- float value;
- float xdist, ydist, dist, a4, b4, a3, b3, a2, b2, a1, b1, a0, b0;
-
- /* coefficients for intensity(dist) = a*dist + b */
- if (Fgs == 1) {
- a4 = -2.0340121888836554e-05;
- b4 = 0.00040693710306002716;
- a3 = -0.0003334301023466291;
- b3 = 0.0041640168685535385;
- a2 = -0.0010417032033561069;
- b2 = 0.009830201676629366;
- a1 = -0.0011177934419147849;
- b1 = 0.0101345626308640 ;
- a0 = -0.000463224129535777;
- b0 = 0.00882542400610606;
- }
- else { /* only FGS == 2 applies */
- a4 = -2.0340121888836554e-05;
- b4 = 0.00040693710306002716;
- a3 = -0.0003334301023466291;
- b3 = 0.0041640168685535385;
- a2 = -0.0010417032033561069;
- b2 = 0.009830201676629366;
- a1 = -0.0011177934419147849;
- b1 = 0.0101345626308640 ;
- a0 = -0.000463224129535777;
- b0 = 0.00882542400610606;
- }
-
- for (y = 0; y < rows; y++)
- for (x = 0; x < cols; x++){
- /* calculate distance square to center */
- xdist = x - center_x;
- ydist = (y - center_y)/1.5;
-
- /* speed up */
- if ((xdist <= 20) || (ydist <= 20)){
- dist = sqrtf(xdist*xdist + ydist*ydist); /* fsqrts takes 22 cycles */
-
- /* calculate PSF from piecewise linear approximation */
- if (dist > 20) /* outer border */
- value = 0;
- else if (dist > 12)
- value = (a4*dist + b4);
-
- else if (dist > 8) /* 6..20 */
- value = (a3*dist + b3);
-
- else if (dist > 4) /* 6..20 */
- value = (a2*dist + b2);
-
- else if (dist > 2) /* 2..6 */
- value = (a1*dist + b1);
-
- else /* 0..2 */
- value = (a0*dist + b0);
- }
- else
- value = 0;
-
- SET_PIXEL(img, cols, x, y, value);
- }
-
-#if 0
- for (y=0; y<rows; y++)
- {
- for (x=0; x<cols; x++)
- printf("%d ", GET_PIXEL(img,cols,x,y));
- printf("\n");
- }
-#endif
-
- return;
-}
-
-/**
- * @brief Median determination based on the Torben method (non destructive)
- *
- * @param data: input array
- * @param lenght: lenght of the input buffer
- *
- * @return median of the dataset
- */
-unsigned int torben(unsigned int *data, unsigned int lenght)
-{
- int less, greater, equal;
- unsigned int min, max, guess, maxltguess, mingtguess, i;
-
- min = max = data[0] ;
- for (i=1 ; i<lenght ; i++) {
- if (data[i]<min) min=data[i];
- if (data[i]>max) max=data[i];
- }
-
- while (1) {
- guess = (min+max)/2;
- less = 0; greater = 0; equal = 0;
- maxltguess = min ;
- mingtguess = max ;
- for (i=0; i<lenght; i++) {
- if (data[i]<guess) {
- less++;
- if (data[i]>maxltguess) maxltguess = data[i] ;
- } else if (data[i]>guess) {
- greater++;
- if (data[i]<mingtguess) mingtguess = data[i] ;
- } else equal++;
- }
- if (less <= (lenght+1)/2 && greater <= (lenght+1)/2) break ;
- else if (less>greater) max = maxltguess ;
- else min = mingtguess;
- }
- if (less >= (lenght+1)/2) return maxltguess;
- else if (less+equal >= (lenght+1)/2) return guess;
- else return mingtguess;
-}
/**
* @brief Function for checking the extent of the bright source.
@@ -306,16 +172,22 @@ unsigned int torben(unsigned int *data, unsigned int lenght)
* @param threshold: threshold criteria for neighbour identification
*
*/
-void check8 (unsigned int *image, unsigned int *sum, int *is_target, unsigned int x, unsigned int y, unsigned int width, unsigned int height, unsigned int threshold) {
+void check_neighbours (unsigned int *image, unsigned int *sum, int *is_target, unsigned int x, unsigned int y, unsigned int width, unsigned int height, unsigned int threshold) {
unsigned int val, ctr=0;
- int i, j;
-
- for(i = -1;i<=1;i++){
- for(j = -1;j<=1;j++){
- val = GET_PIXEL(image, width, x+i, y+j);
- if (val > threshold){
- *sum = *sum + val;
- ctr = ctr + 1;
+ int i, j, x_tmp, y_tmp;
+
+ for(i = -2;i<=2;i++){
+ for(j = -2;j<=2;j++){
+ x_tmp = x + i;
+ y_tmp = y + j;
+ if(x_tmp > 0 && y_tmp > 0){
+ if(x_tmp <= (width-1) && (y_tmp <= (height-1))){
+ val = GET_PIXEL(image, width, (x_tmp), (y_tmp));
+ if (val > threshold){
+ *sum = *sum + val;
+ ctr = ctr + 1;
+ }
+ }
}
}
}
@@ -344,26 +216,29 @@ void check8 (unsigned int *image, unsigned int *sum, int *is_target, unsigned in
void std_threshold(unsigned int *image, unsigned int dimX, unsigned int dimY){
unsigned int mean, std, i;
unsigned long sum, sumSquare;
-
+ if(dimX == 0 || dimY == 0)
+ return;
+
sum = 0;
sumSquare = 0;
for(i = 0; i < dimX*dimY; i++){
sum = sum + image[i];
sumSquare = sumSquare + (image[i] * image[i]);
}
-
- if(dimX == 0 || dimY == 0){
+
+ if(sum == 0)
return;
- }else{
- mean = (unsigned int) (sum / (dimX * dimY));
- std = (unsigned int) sqrt((sumSquare / (dimX * dimY)) - (mean*mean));
- }
+
+ mean = (unsigned int) (sum / (dimX * dimY));
+ std = (unsigned int) sqrt((sumSquare / (dimX * dimY)) - (mean*mean));
+
for(i = 0; i < dimX*dimY; i++){
if(image[i] < (mean + std))
image[i] = 0;
else
image[i] = image[i] - (mean + std);
}
+ return;
}
/**
@@ -396,8 +271,6 @@ int identify_star (unsigned int *image, unsigned int *brightness, int *is_target
if (y_dim == 0)
return -1;
-
-
for(i = 0; i < length; i++){
brightness[i] = 0;
is_target[i] = 1;
@@ -418,26 +291,15 @@ int identify_star (unsigned int *image, unsigned int *brightness, int *is_target
}
}
-#if 0
- for(i=0; i<length; i++){
- printf("Position Targets: %i, %i, %i, %i\n", positions[i], positions[i] % x_dim, positions[i] / x_dim, is_target[i]);
- }
-#endif
for(i = 0; i < length; i++){
if(is_target[i] != 0){
pos_x = (positions[i] % x_dim);
pos_y = (positions[i] / x_dim);
- check8(image, &brightness[i], &is_target[i], pos_x, pos_y, x_dim, y_dim, sigma);
+ check_neighbours(image, &brightness[i], &is_target[i], pos_x, pos_y, x_dim, y_dim, sigma);
}
}
-#if 0
- for(i=0; i<length; i++){
- printf("Position Targets after check8: %i, %i, %i, %i, %i\n", positions[i], positions[i] % x_dim, positions[i] / x_dim, is_target[i], brightness[i]);
- }
-#endif
-
minimum = 0;
loc = 0;
for(i = 0; i < length; i++){
@@ -872,6 +734,7 @@ unsigned int ref_y[25];
* 5. The sigma must be larger than a certain span
* 6. The pearson correlation between the image and a reference function at
* the center must be larger than the defined value
+ * 7. The measured signal of the target must not exeed the specified range
*
* The background that is subtracted from the image for the photometry is given
* by the minimum pixel value inside of the ROI with the exception of known dead
@@ -887,11 +750,13 @@ unsigned int ref_y[25];
* @param fgs: channel for reference function
* @param x_center: estimated center in x
* @param y_center: estimated center in y
+ * @param signalTolerance: Tolerance range for 7
+ * @param targetSignal: Signal for 7
*
* @returns struct containing the validity data of the centroid
*/
-struct valpack CheckRoiForStar (unsigned int *data, unsigned int x_dim, unsigned int y_dim, unsigned int CenSignalLimit, unsigned int CenSigmaLimit, float PearsonLimit, unsigned int fgs, double x_center, double y_center)
+struct valpack CheckRoiForStar (unsigned int *data, unsigned int x_dim, unsigned int y_dim, unsigned int CenSignalLimit, unsigned int CenSigmaLimit, float PearsonLimit, unsigned int fgs, double x_center, double y_center, unsigned int signalTolerance, unsigned int targetSignal)
{
unsigned int i;
unsigned int median, minimum, maximum;
@@ -1001,7 +866,6 @@ struct valpack CheckRoiForStar (unsigned int *data, unsigned int x_dim, unsigned
return package;
}
/*rule 6: the signal inside of a 5px radius circle around the estimated center must contain a certain percentage of the total signal*/
-//#pragma omp parallel for private(xdist), private(ydist)
for (y = 0; y < y_dim; y++){
for (x = 0; x < x_dim; x++){
/* calculate distance square to center */
@@ -1019,6 +883,11 @@ struct valpack CheckRoiForStar (unsigned int *data, unsigned int x_dim, unsigned
mag = sum;
+ if(abs(targetSignal - mag) > targetSignal*((float)signalTolerance/100)){
+ package.index = 107;
+ package.magnitude = mag;
+ return package;
+ }
/*Multiply with signal to scale reference to extracted sample*/
if(fgs == 1){
@@ -1161,9 +1030,6 @@ void WeightedCenterOfGravity2D (unsigned int *img, float *weights, unsigned int
for (i = 0; i < rows * cols; i++){
/* multiply image with weights */
tmpImg[i] = (unsigned int) (weights[i]*img[i]);
-
- /* and find max value */
- //max = img[i] > max ? img[i] : max;
}
/* determine size of datatype and shift so that it is back within CogBits (e.g. 16) bits */
@@ -1202,44 +1068,6 @@ void IntensityWeightedCenterOfGravity2D (unsigned int *img, unsigned int rows, u
return;
}
-/**
- * @brief Calculates centroid using Iteratively Weighted Center of Gravity for
- * a 2d image
- *
- * In the IWCoG algorithm, the image is multiplied with a weighting function
- * centred on the given estimate and the @ref WeightedCenterOfGravity2D is
- * performed. Based on the result, the weighting function is relocated and the
- * process is repeated n times
- *
- * @param img: a buffer holding the image
- * @param weights: buffer holding the weighting function
- * @param rows: the number of rows in the image
- * @param cols: the number of columns in the image
- * @param iter: number of iterations
- * @param[out] x: x position
- * @param[out] y: y position
- * @param mode: mode defining the used weighting function
- * @param fwhm_x: FWHM of gaussian weighting function in x
- * @param fwhm_y: FWHM of gaussian weighting function in y
- * @param fgs: FGS channel for approximated weighting function
- *
- */
-void IterativelyWeightedCenterOfGravity2D (unsigned int *img, float *weights, unsigned int rows, unsigned int cols, unsigned int iter, float *x, float *y, int mode, float fwhm_x, float fwhm_y, int fgs)
-{
- unsigned int i;
-
- for (i = 0; i < iter; i++){
- if (mode == MODE_GAUSS){
- get_2D_gaussian (weights, cols, rows, *x, *y, fwhm_x, fwhm_y);
- }
- else{
- GetArielPSF (weights, cols, rows, *x, *y, fgs);
- }
-
- WeightedCenterOfGravity2D (img, weights, rows, cols, x, y);
- }
- return;
-}
float weights_cog[REFINEDROISIZE*REFINEDROISIZE];
unsigned int roi_cog[REFINEDROISIZE*REFINEDROISIZE];
@@ -1257,7 +1085,6 @@ unsigned int roi_cog[REFINEDROISIZE*REFINEDROISIZE];
* @param rows: the number of rows in the image
* @param cols: the number of columns in the image
* @param iterations: number of iterations
- * @param mode: mode defining the used weighting function
* @param fwhm_x: FWHM of gaussian weighting function in x
* @param fwhm_y: FWHM of gaussian weighting function in y
* @param fgs: FGS channel for approximated weighting function
@@ -1268,7 +1095,7 @@ unsigned int roi_cog[REFINEDROISIZE*REFINEDROISIZE];
* @returns Centroid packet in form of coord struct
*/
-struct coord ArielCoG (unsigned int *img, unsigned int rows, unsigned int cols, unsigned int iterations, int mode, float fwhm_x, float fwhm_y, int fgs, unsigned int CenSignalLimit, unsigned int CenSigmaLimit, float PearsonLimit)
+struct coord ArielCoG (unsigned int *img, unsigned int rows, unsigned int cols, unsigned int iterations, float fwhm_x, float fwhm_y, int fgs, unsigned int CenSignalLimit, unsigned int CenSigmaLimit, float PearsonLimit, unsigned int signalTolerance, unsigned int targetSignal)
{
float x_res, y_res;
@@ -1306,25 +1133,25 @@ struct coord ArielCoG (unsigned int *img, unsigned int rows, unsigned int cols,
}
if (x_start < 0){
+ x_roi = x_roi + x_start;
x_start = 0;
}
if (y_start < 0){
+ y_roi = y_roi + y_start;
y_start = 0;
}
if (x_start > (rows - REFINEDROISIZE)){
+ x_roi = x_roi + x_start - (rows - REFINEDROISIZE);
x_start = rows - REFINEDROISIZE;
}
if (y_start > (cols - REFINEDROISIZE)){
+ y_roi = y_roi + y_start - (cols - REFINEDROISIZE);
y_start = cols - REFINEDROISIZE;
}
refine_RoI (img, roi_cog, rows, cols, x_start, y_start, REFINEDROISIZE);
- if (mode == MODE_GAUSS){
- get_2D_gaussian (weights_cog, REFINEDROISIZE, REFINEDROISIZE, x_roi, y_roi, fwhm_x, fwhm_y);
- }
- else{
- GetArielPSF (weights_cog, REFINEDROISIZE, REFINEDROISIZE, x_roi, y_roi, fgs);
- }
-
+ get_2D_gaussian (weights_cog, REFINEDROISIZE, REFINEDROISIZE, x_roi, y_roi, fwhm_x, fwhm_y);
+
+
WeightedCenterOfGravity2D (roi_cog, weights_cog, REFINEDROISIZE, REFINEDROISIZE, &x_roi, &y_roi);
}
@@ -1333,7 +1160,7 @@ struct coord ArielCoG (unsigned int *img, unsigned int rows, unsigned int cols,
res.y = y_start + y_roi;
- res.validity = CheckRoiForStar (img, rows, cols, CenSignalLimit, CenSigmaLimit, PearsonLimit,fgs , res.x, res.y);
+ res.validity = CheckRoiForStar (img, rows, cols, CenSignalLimit, CenSigmaLimit, PearsonLimit,fgs , res.x, res.y, signalTolerance, targetSignal);
if(res.validity.index > 99){
res.validity.flag = 0;
@@ -1357,7 +1184,6 @@ unsigned int roi[BIN*BIN*ROISIZE*ROISIZE];
*
* @param data: array of input samples
* @param xdim/ydim: size of the image
- * @param mode: mode used in the centroiding step
* @param fgs: FGS channel. needed for weighting function
* @param target_number: number of expected stars inside of the image
* @param target_brightness: signal of the target star in ADU
@@ -1372,7 +1198,7 @@ unsigned int roi[BIN*BIN*ROISIZE*ROISIZE];
* @returns coordiates of the target star
*/
-struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int ydim, int mode, int fgs, unsigned int target_number, unsigned int target_brightness, unsigned int brightness_tolerance, unsigned int sigma, unsigned int iter, float fwhm_x, float fwhm_y, unsigned int CenSignalLimit, unsigned int CenSigmaLimit, float PearsonLimit)
+struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int ydim, int fgs, unsigned int target_number, unsigned int target_brightness, unsigned int brightness_tolerance, unsigned int sigma, unsigned int iter, float fwhm_x, float fwhm_y, unsigned int CenSignalLimit, unsigned int CenSigmaLimit, float PearsonLimit)
{
unsigned int binnedwidth, binnedheight, binx, biny, x, y, xstart, ystart;
unsigned int source_val[target_number];
@@ -1393,11 +1219,16 @@ struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int
else{
result.x = 0;
result.y = 0;
+ result.validity.index = 111;
+ result.validity.flag = 0;
return result;
}
if ((binnedwidth == 0) || (binnedheight == 0)){
- result.validity.index = 108;
+ result.x = 0;
+ result.y = 0;
+ result.validity.index = 111;
+ result.validity.flag = 0;
return result;
}
@@ -1426,33 +1257,10 @@ struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int
}
mean = (unsigned int) sum / (binnedwidth * binnedheight);
-#if 0
- for(i=0; i<(binnedwidth * binnedheight); i++){
- printf("%i ", binned[i]);
- if (i && !((i + 1) % binnedwidth))
- printf("\n");
-
- }
-#endif
-
find_brightest_uint(binned, (binnedwidth * binnedheight), target_number, source_val, source_pos);
-/*Debug flag for source extraction*/
-#if 0
- for(i=0; i<target_number; i++){
- printf("x = %i, y = %i, width = %i\n", source_pos[i]% binnedwidth, source_pos[i] / binnedwidth, binnedwidth);
- }
-#endif
-
identify_star(binned, source_br, target, binnedwidth, binnedheight, source_pos, target_number, mean + sigma, target_brightness);
-/*Debug flag for target identification*/
-#if 0
- for(i=0; i<target_number; i++){
- printf("%i, %i\n", target[i], source_br[i]);
- }
-#endif
-
for(i=0; i<target_number;i++){
if (target[i] == 1){
if (source_br[i] > tmp_br && (abs(source_br[i]-target_brightness) < (int)(target_brightness*brightness_tolerance/100))){
@@ -1464,8 +1272,6 @@ struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int
}
}
-
-
pos_x = pos_x - ROISIZE/2;
pos_y = pos_y - ROISIZE/2;
@@ -1487,14 +1293,6 @@ struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int
}
extract_RoI(data, xdim, ydim, pos_x, pos_y, roi);
-/*Debug flag Print RoI*/
-#if 0
- for (i=0; i<ROISIZE*ROISIZE*BIN*BIN; i++){
- printf("%i ", roi[i]);
- if (i && !((i + 1) % (ROISIZE*BIN)))
- printf("\n");
- }
-#endif
th = GetMin(roi, ROISIZE*BIN*ROISIZE*BIN);
@@ -1502,11 +1300,12 @@ struct coord SourceDetection(unsigned int *data, unsigned int xdim, unsigned int
roi[i] = roi[i] - th;
}
- result = ArielCoG(roi, ROISIZE*BIN, ROISIZE*BIN, iter, mode, fwhm_x, fwhm_y, fgs, CenSignalLimit, CenSigmaLimit, PearsonLimit);
+ result = ArielCoG(roi, ROISIZE*BIN, ROISIZE*BIN, iter, fwhm_x, fwhm_y, fgs, CenSignalLimit, CenSigmaLimit, PearsonLimit, brightness_tolerance, target_brightness);
result.x = result.x + (float) (pos_x*BIN);
result.y = result.y + (float) (pos_y*BIN);
if(flag == 0){
result.validity.index = 107;
+ result.validity.magnitude = source_br[0];
}
if(result.validity.index > 99){
result.validity.flag = 0;
diff --git a/src/fcu_algorithms.h b/src/fcu_algorithms.h
index 4998641a73d74093e846bd1f40fb5ab1a93a0d89..4a6cd3b287fccb7fd867f09b11615ff6b5cf41fb 100644
--- a/src/fcu_algorithms.h
+++ b/src/fcu_algorithms.h
@@ -30,11 +30,11 @@ void std_threshold(unsigned int *, unsigned int, unsigned int);
int MedFilter3x3 (unsigned int *, unsigned int, unsigned int, unsigned int, unsigned int *);
-struct valpack CheckRoiForStar(unsigned int *, unsigned int, unsigned int, unsigned int, unsigned int, float, unsigned int, double, double);
+struct valpack CheckRoiForStar(unsigned int *, unsigned int, unsigned int, unsigned int, unsigned int, float, unsigned int, double, double, unsigned int, unsigned int);
-struct coord SourceDetection(unsigned int *, unsigned int , unsigned int, int, int, unsigned int, unsigned int, unsigned int, unsigned int, unsigned int, float, float, unsigned int, unsigned int, float);
+struct coord SourceDetection(unsigned int *, unsigned int , unsigned int, int, unsigned int, unsigned int, unsigned int, unsigned int, unsigned int, float, float, unsigned int, unsigned int, float);
-struct coord ArielCoG (unsigned int *, unsigned int, unsigned int, unsigned int, int, float, float, int, unsigned int, unsigned int, float);
+struct coord ArielCoG (unsigned int *, unsigned int, unsigned int, unsigned int, float, float, int, unsigned int, unsigned int, float, unsigned int, unsigned int);
void CenterOfGravity2D(unsigned int *, unsigned int, unsigned int, float *, float *);
@@ -42,7 +42,7 @@ void WeightedCenterOfGravity2D(unsigned int *, float *, unsigned int, unsigned i
void IntensityWeightedCenterOfGravity2D(unsigned int *, unsigned int, unsigned int, float *, float *);
-void IterativelyWeightedCenterOfGravity2D(unsigned int *, float *, unsigned int, unsigned int, unsigned int, float *, float *, int, float, float, int);
+int MeanSigma (int *, int, float *, float *);
unsigned int GetMin(unsigned int*, unsigned int);
diff --git a/src/utilities.c b/src/utilities.c
index b6292e13dbf4d2040ae5247ddfa5be86ce9bb056..e62c1e89fb32f80f39af19e18481c6e99b16581f 100644
--- a/src/utilities.c
+++ b/src/utilities.c
@@ -1,8 +1,8 @@
/**
* @file utilities.c
* @author Gerald Mösenlechner (gerald.moesenlechner@univie.ac.at)
-* @date November, 2023
-* @version 1.0
+* @date January, 2024
+* @version 1.1
*
* @copyright
* This program is free software; you can redistribute it and/or modify it
@@ -44,34 +44,6 @@
#pragma GCC target("avx")
#endif
-size_t get_next_pow_2_bound(size_t n)
-{
- size_t c = 0;
-
- n = n - 1;
- while (n >>= 1)
- c++;
-
- return (1 << (c + 1));
-}
-
-double random_poisson(double mean)
-{
- double L;
- double p = 1.;
- int result = 0;
-
- L = exp(-mean);
- do {
- result++;
- if (result == INT_MAX)
- break;
- p *= ((double) random()) / INT_MAX;
- } while (p > L);
- result--;
- return (double) result;
-};
-
/**
* @brief Random poisson number generator based on the Transformed Rejection Method from Wolfgang Hoermann
*
@@ -265,7 +237,7 @@ int upsample_image(double *image, double *upsampled_image, unsigned int width, u
}
/**
- * @brief simple downsampling of an image
+ * @brief simple downsampling of an image with normalization
*
* @param image: Original image
* @param[out] downsampled_image: buffer of downsampled image