38 #include "irplib_mkmaster.h"
70 irplib_imagelist_get_clean_mean_levels(
const cpl_imagelist* iml,
73 const double tolerance)
78 cpl_vector* levels=NULL;
84 cpl_error_ensure(iml != NULL, CPL_ERROR_NULL_INPUT,
return(levels),
85 "Null input image list");
86 cpl_error_ensure(kappa >= 0, CPL_ERROR_ILLEGAL_INPUT,
return(levels),
89 size=cpl_imagelist_get_size(iml);
90 levels=cpl_vector_new(size);
91 pval=cpl_vector_get_data(levels);
94 const cpl_image* img=cpl_imagelist_get_const(iml,i);
95 irplib_ksigma_clip(img,1,1,
96 cpl_image_get_size_x(img),
97 cpl_image_get_size_y(img),
98 nclip,kappa,tolerance,&mean,&stdev);
99 cpl_msg_info(cpl_func,
"Ima %d mean level: %g",i+1,mean);
116 static cpl_error_code
117 irplib_imagelist_subtract_values(cpl_imagelist** iml, cpl_vector* values)
124 size=cpl_imagelist_get_size(*iml);
125 pval=cpl_vector_get_data(values);
127 for(i=0;i<size;i++) {
128 cpl_image* img=cpl_imagelist_get(*iml,i);
129 cpl_image_subtract_scalar(img,pval[i]);
130 cpl_imagelist_set(*iml,img,i);
133 return cpl_error_get_code();
151 irplib_vector_ksigma(cpl_vector *values,
152 const double klow,
const double khigh,
int kiter)
156 double *data = cpl_vector_get_data(values);
157 int n = cpl_vector_get_size(values);
166 mean = cpl_vector_get_median(values);
168 for (i = 0; i < n; i++) {
169 sigma += (mean - data[i]) * (mean - data[i]);
171 sigma = sqrt(sigma / (n - 1));
174 cpl_vector *accepted;
176 for (i = 0; i < ngood; i++) {
177 if (data[i]-mean < khigh*sigma && mean-data[i] < klow*sigma) {
178 data[count] = data[i];
192 accepted = cpl_vector_wrap(count, data);
193 mean = cpl_vector_get_mean(accepted);
195 sigma = cpl_vector_get_stdev(accepted);
197 cpl_vector_unwrap(accepted);
199 if (count == ngood) {
229 irplib_imagelist_ksigma_stack(
const cpl_imagelist *imlist,
230 double klow,
double khigh,
int kiter)
232 int ni, nx, ny, npix;
233 cpl_image *out_ima=NULL;
234 cpl_imagelist *loc_iml=NULL;
235 double *pout_ima=NULL;
236 cpl_image *image=NULL;
237 const double **data=NULL;
239 cpl_vector *time_line=NULL;
241 double *ptime_line=NULL;
243 double mean_of_medians=0;
245 cpl_error_ensure(imlist != NULL, CPL_ERROR_NULL_INPUT,
return(out_ima),
246 "Null input image list");
248 ni = cpl_imagelist_get_size(imlist);
249 loc_iml = cpl_imagelist_duplicate(imlist);
250 image = cpl_imagelist_get(loc_iml, 0);
251 nx = cpl_image_get_size_x(image);
252 ny = cpl_image_get_size_y(image);
255 out_ima = cpl_image_new(nx, ny, CPL_TYPE_DOUBLE);
256 pout_ima = cpl_image_get_data_double(out_ima);
258 time_line = cpl_vector_new(ni);
260 ptime_line = cpl_vector_get_data(time_line);
262 data = cpl_calloc(
sizeof(
double *), ni);
263 med = cpl_calloc(
sizeof(
double), ni);
265 for (i = 0; i < ni; i++) {
266 image = cpl_imagelist_get(loc_iml, i);
267 med[i]=cpl_image_get_median(image);
268 cpl_image_subtract_scalar(image,med[i]);
269 data[i] = cpl_image_get_data_double(image);
270 mean_of_medians+=med[i];
274 for (i = 0; i < npix; i++) {
275 for (j = 0; j < ni; j++) {
276 ptime_line[j] = data[j][i];
278 pout_ima[i] = irplib_vector_ksigma(time_line, klow, khigh, kiter);
281 cpl_image_add_scalar(out_ima,mean_of_medians);
286 cpl_vector_delete(time_line);
287 cpl_imagelist_delete(loc_iml);
310 irplib_mkmaster_mean(cpl_imagelist* images,
const double kappa,
const int nclip,
const double tolerance,
const double klow,
const double khigh,
const int niter)
313 cpl_image* master=NULL;
314 cpl_vector* levels=NULL;
316 cpl_imagelist* iml=NULL;
318 cpl_msg_info(cpl_func,
"method mean");
319 iml=cpl_imagelist_duplicate(images);
320 levels=irplib_imagelist_get_clean_mean_levels(iml,kappa,nclip,tolerance);
321 mean=cpl_vector_get_mean(levels);
322 cpl_msg_info(cpl_func,
"Master mean level: %g",mean);
324 irplib_imagelist_subtract_values(&iml,levels);
326 master = irplib_imagelist_ksigma_stack(iml,klow,khigh,niter);
327 cpl_image_add_scalar(master,mean);
329 cpl_vector_delete(levels);
330 cpl_imagelist_delete(iml);
352 cpl_image* master=NULL;
353 cpl_vector* levels=NULL;
355 cpl_imagelist* iml=NULL;
357 cpl_msg_info(cpl_func,
"method median");
358 iml=cpl_imagelist_duplicate(images);
359 levels=irplib_imagelist_get_clean_mean_levels(iml,kappa,nclip,tolerance);
361 mean=cpl_vector_get_mean(levels);
362 cpl_msg_info(cpl_func,
"Master mean level: %g",mean);
363 irplib_imagelist_subtract_values(&iml,levels);
365 master = cpl_imagelist_collapse_median_create(iml);
367 cpl_image_add_scalar(master,mean);
369 cpl_vector_delete(levels);
370 cpl_imagelist_delete(iml);
377 static cpl_error_code
378 irplib_mkmaster_dark_qc(
const cpl_imagelist* raw_images,
379 cpl_imagelist* preproc_images,
380 const cpl_parameterlist* parameters,
381 const int pr_num_x,
const int pr_num_y,
382 const int pr_box_sx,
const int pr_box_sy,
const char* recipe_id,
385 cpl_ensure_code(qclog !=NULL, CPL_ERROR_NULL_INPUT);
386 cpl_ensure_code(recipe_id !=NULL, CPL_ERROR_NULL_INPUT);
387 cpl_ensure_code(parameters !=NULL, CPL_ERROR_NULL_INPUT);
389 if (pr_num_x != 0 && pr_num_y != 0 && pr_box_sx != 0 && pr_box_sy != 0) {
391 for (i = 0; i < cpl_imagelist_get_size(raw_images); i++) {
392 cpl_image* current_dark = cpl_image_duplicate(
393 cpl_imagelist_get_const(preproc_images, i));
394 cpl_msg_info(cpl_func,
"Calculating QC parameters on raw dark frame %d",
401 cpl_image_delete(current_dark);
404 return cpl_error_get_code();
419 irplib_head_get_exptime(
const cpl_propertylist * plist) {
422 result=cpl_propertylist_get_double(plist,
"EXPTIME");
423 cpl_ensure_code(result >= 0, CPL_ERROR_ILLEGAL_OUTPUT);
437 static cpl_error_code
438 irplib_head_set_exptime(cpl_propertylist *plist,
double exptime)
440 cpl_propertylist_update_double(plist,
"EXPTIME", exptime);
441 cpl_propertylist_set_comment(plist,
"EXPTIME",
"Total integration time");
443 return cpl_error_get_code();
446 static cpl_imagelist*
447 irplib_mkmaster_dark_fill_imagelist(
const cpl_imagelist* raw_images,
448 cpl_propertylist** raw_headers,
const cpl_image* master_bias,
449 double* mean_exptime) {
453 cpl_imagelist* preproc_images = NULL;
455 double min_exptime = 0;
456 double max_exptime = 0;
458 preproc_images = cpl_imagelist_new();
459 for (i = 0; i < cpl_imagelist_get_size(raw_images); i++) {
460 double exposure_time = 0.0;
461 cpl_image* current_dark = NULL;
462 const cpl_propertylist *current_header;
464 current_dark = cpl_image_duplicate(cpl_imagelist_get_const(raw_images, i));
465 current_header = raw_headers[i];
468 if (master_bias != NULL) {
469 cpl_msg_info(cpl_func,
"Subtracting master bias");
470 cpl_image_subtract(current_dark, master_bias);
472 cpl_msg_info(cpl_func,
"Skipping bias subtraction");
475 exposure_time = irplib_head_get_exptime(current_header);
478 if (i == 0 || exposure_time < min_exptime) {
479 min_exptime = exposure_time;
481 if (i == 0 || exposure_time > max_exptime) {
482 max_exptime = exposure_time;
493 cpl_imagelist_set(preproc_images, current_dark, i);
502 cpl_msg_info(cpl_func,
503 "Exposure times range from %e s to %e s (%e %% variation)", min_exptime,
504 max_exptime, 100 * (max_exptime - min_exptime) / min_exptime);
506 if ((max_exptime - min_exptime) / min_exptime > .001) {
507 cpl_msg_warning(cpl_func,
"Exposure times differ by %e %%",
508 100 * (max_exptime - min_exptime) / min_exptime);
512 *mean_exptime=0.5 * (max_exptime + min_exptime);
513 return preproc_images;
518 irplib_mdark_process_chip(
const cpl_imagelist *raw_images,
519 cpl_propertylist **raw_headers,
const cpl_image *master_bias,
520 cpl_propertylist *mdark_header,
const cpl_parameterlist *parameters,
521 const char* recipe_id, cpl_table* qclog,
const int do_qc,
522 const char* STACK_METHOD,
const double STACK_KLOW,
const double STACK_KHIGH,
523 const int STACK_NITER,
524 const int pr_num_x,
const int pr_num_y,
525 const int pr_box_sx,
const int pr_box_sy) {
526 cpl_image *master_dark = NULL;
527 cpl_image *current_dark = NULL;
528 cpl_imagelist *preproc_images = NULL;
529 double mean_exptime = 0;
533 preproc_images = irplib_mkmaster_dark_fill_imagelist(raw_images, raw_headers,
534 master_bias, &mean_exptime);
537 irplib_mkmaster_dark_qc(raw_images, preproc_images, parameters, pr_num_x,
538 pr_num_y, pr_box_sx, pr_box_sy, recipe_id, qclog);
542 if (strcmp(STACK_METHOD,
"MEDIAN") == 0) {
543 cpl_msg_info(cpl_func,
"Calculating stack median");
544 master_dark = cpl_imagelist_collapse_median_create(preproc_images);
546 cpl_msg_info(cpl_func,
"Calculating stack mean");
547 master_dark = irplib_imagelist_ksigma_stack(preproc_images, STACK_KLOW,
548 STACK_KHIGH, STACK_NITER);
551 irplib_head_set_exptime(mdark_header, mean_exptime );
553 cpl_image_delete(current_dark);
554 cpl_imagelist_delete(preproc_images);
555 if (cpl_error_get_code() != CPL_ERROR_NONE) {
556 cpl_image_delete(master_dark);
cpl_image * irplib_mkmaster_median(cpl_imagelist *images, const double kappa, const int nclip, const double tolerance)
Computes master frame by clean stack median of the input imagelist.
cpl_image * irplib_mkmaster_mean(cpl_imagelist *images, const double kappa, const int nclip, const double tolerance, const double klow, const double khigh, const int niter)
Computes master frame by clean stack mean of the input imagelist.