38 #include "irplib_mkmaster.h"
73 const double tolerance)
76 const cpl_image* img=NULL;
79 cpl_vector* levels=NULL;
85 cpl_error_ensure(iml != NULL, CPL_ERROR_NULL_INPUT,
return(levels),
86 "Null input image list");
87 cpl_error_ensure(kappa >= 0, CPL_ERROR_ILLEGAL_INPUT,
return(levels),
90 size=cpl_imagelist_get_size(iml);
91 levels=cpl_vector_new(size);
92 pval=cpl_vector_get_data(levels);
95 img=cpl_imagelist_get_const(iml,i);
96 irplib_ksigma_clip(img,1,1,
97 cpl_image_get_size_x(img),
98 cpl_image_get_size_y(img),
99 nclip,kappa,tolerance,&mean,&stdev);
100 cpl_msg_info(cpl_func,
"Ima %d mean level: %g",i+1,mean);
117 static cpl_error_code
126 size=cpl_imagelist_get_size(*iml);
127 pval=cpl_vector_get_data(values);
129 for(i=0;i<size;i++) {
130 img=cpl_imagelist_get(*iml,i);
131 cpl_image_subtract_scalar(img,pval[i]);
132 cpl_imagelist_set(*iml,img,i);
135 return cpl_error_get_code();
154 const double klow,
const double khigh,
int kiter)
156 cpl_vector *accepted;
159 double *data = cpl_vector_get_data(values);
160 int n = cpl_vector_get_size(values);
170 mean = cpl_vector_get_median(values);
172 for (i = 0; i < n; i++) {
173 sigma += (mean - data[i]) * (mean - data[i]);
175 sigma = sqrt(sigma / (n - 1));
179 for (i = 0; i < ngood; i++) {
180 if (data[i]-mean < khigh*sigma && mean-data[i] < klow*sigma) {
181 data[count] = data[i];
195 accepted = cpl_vector_wrap(count, data);
196 mean = cpl_vector_get_mean(accepted);
198 sigma = cpl_vector_get_stdev(accepted);
200 cpl_vector_unwrap(accepted);
202 if (count == ngood) {
233 double klow,
double khigh,
int kiter)
235 int ni, nx, ny, npix;
236 cpl_image *out_ima=NULL;
237 cpl_imagelist *loc_iml=NULL;
238 double *pout_ima=NULL;
239 cpl_image *image=NULL;
240 const double **data=NULL;
242 cpl_vector *time_line=NULL;
244 double *ptime_line=NULL;
246 double mean_of_medians=0;
248 cpl_error_ensure(imlist != NULL, CPL_ERROR_NULL_INPUT,
return(out_ima),
249 "Null input image list");
251 ni = cpl_imagelist_get_size(imlist);
252 loc_iml = cpl_imagelist_duplicate(imlist);
253 image = cpl_imagelist_get(loc_iml, 0);
254 nx = cpl_image_get_size_x(image);
255 ny = cpl_image_get_size_y(image);
258 out_ima = cpl_image_new(nx, ny, CPL_TYPE_DOUBLE);
259 pout_ima = cpl_image_get_data_double(out_ima);
261 time_line = cpl_vector_new(ni);
263 ptime_line = cpl_vector_get_data(time_line);
265 data = cpl_calloc(
sizeof(
double *), ni);
266 med = cpl_calloc(
sizeof(
double), ni);
268 for (i = 0; i < ni; i++) {
269 image = cpl_imagelist_get(loc_iml, i);
270 med[i]=cpl_image_get_median(image);
271 cpl_image_subtract_scalar(image,med[i]);
272 data[i] = cpl_image_get_data_double(image);
273 mean_of_medians+=med[i];
277 for (i = 0; i < npix; i++) {
278 for (j = 0; j < ni; j++) {
279 ptime_line[j] = data[j][i];
284 cpl_image_add_scalar(out_ima,mean_of_medians);
289 cpl_vector_delete(time_line);
290 cpl_imagelist_delete(loc_iml);
313 irplib_mkmaster_mean(cpl_imagelist* images,
const double kappa,
const int nclip,
const double tolerance,
const double klow,
const double khigh,
const int niter)
316 cpl_image* master=NULL;
317 cpl_vector* levels=NULL;
319 cpl_imagelist* iml=NULL;
321 cpl_msg_info(cpl_func,
"method mean");
322 iml=cpl_imagelist_duplicate(images);
324 mean=cpl_vector_get_mean(levels);
325 cpl_msg_info(cpl_func,
"Master mean level: %g",mean);
330 cpl_image_add_scalar(master,mean);
332 cpl_vector_delete(levels);
333 cpl_imagelist_delete(iml);
355 cpl_image* master=NULL;
356 cpl_vector* levels=NULL;
358 cpl_imagelist* iml=NULL;
360 cpl_msg_info(cpl_func,
"method median");
361 iml=cpl_imagelist_duplicate(images);
364 mean=cpl_vector_get_mean(levels);
365 cpl_msg_info(cpl_func,
"Master mean level: %g",mean);
368 master = cpl_imagelist_collapse_median_create(iml);
370 cpl_image_add_scalar(master,mean);
372 cpl_vector_delete(levels);
373 cpl_imagelist_delete(iml);
380 static cpl_error_code
381 irplib_mkmaster_dark_qc(
const cpl_imagelist* raw_images,
382 cpl_imagelist* preproc_images,
383 const cpl_parameterlist* parameters,
384 const int pr_num_x,
const int pr_num_y,
385 const int pr_box_sx,
const int pr_box_sy,
const char* recipe_id,
389 cpl_image* current_dark = 0;
391 cpl_ensure_code(qclog !=NULL, CPL_ERROR_NULL_INPUT);
392 cpl_ensure_code(recipe_id !=NULL, CPL_ERROR_NULL_INPUT);
393 cpl_ensure_code(parameters !=NULL, CPL_ERROR_NULL_INPUT);
395 if (pr_num_x != 0 && pr_num_y != 0 && pr_box_sx != 0 && pr_box_sy != 0) {
396 for (i = 0; i < cpl_imagelist_get_size(raw_images); i++) {
397 current_dark = cpl_image_duplicate(
398 cpl_imagelist_get_const(preproc_images, i));
399 cpl_msg_info(cpl_func,
"Calculating QC parameters on raw dark frame %d",
406 cpl_image_delete(current_dark);
409 return cpl_error_get_code();
427 result=cpl_propertylist_get_double(plist,
"EXPTIME");
428 cpl_ensure_code(result >= 0, CPL_ERROR_ILLEGAL_OUTPUT);
442 static cpl_error_code
445 cpl_propertylist_update_double(plist,
"EXPTIME", exptime);
446 cpl_propertylist_set_comment(plist,
"EXPTIME",
"Total integration time");
448 return cpl_error_get_code();
451 static cpl_imagelist*
452 irplib_mkmaster_dark_fill_imagelist(
const cpl_imagelist* raw_images,
453 cpl_propertylist** raw_headers,
const cpl_image* master_bias,
454 double* mean_exptime) {
458 cpl_imagelist* preproc_images = NULL;
460 cpl_image* current_dark = NULL;
461 double min_exptime = 0;
462 double max_exptime = 0;
464 preproc_images = cpl_imagelist_new();
465 for (i = 0; i < cpl_imagelist_get_size(raw_images); i++) {
466 double exposure_time = 0.0;
467 const cpl_propertylist *current_header;
469 current_dark = cpl_image_duplicate(cpl_imagelist_get_const(raw_images, i));
470 current_header = raw_headers[i];
473 if (master_bias != NULL) {
474 cpl_msg_info(cpl_func,
"Subtracting master bias");
475 cpl_image_subtract(current_dark, master_bias);
477 cpl_msg_info(cpl_func,
"Skipping bias subtraction");
483 if (i == 0 || exposure_time < min_exptime) {
484 min_exptime = exposure_time;
486 if (i == 0 || exposure_time > max_exptime) {
487 max_exptime = exposure_time;
498 cpl_imagelist_set(preproc_images, current_dark, i);
507 cpl_msg_info(cpl_func,
508 "Exposure times range from %e s to %e s (%e %% variation)", min_exptime,
509 max_exptime, 100 * (max_exptime - min_exptime) / min_exptime);
511 if ((max_exptime - min_exptime) / min_exptime > .001) {
512 cpl_msg_warning(cpl_func,
"Exposure times differ by %e %%",
513 100 * (max_exptime - min_exptime) / min_exptime);
517 *mean_exptime=0.5 * (max_exptime + min_exptime);
518 return preproc_images;
523 irplib_mdark_process_chip(
const cpl_imagelist *raw_images,
524 cpl_propertylist **raw_headers,
const cpl_image *master_bias,
525 cpl_propertylist *mdark_header,
const cpl_parameterlist *parameters,
526 const char* recipe_id, cpl_table* qclog,
const int do_qc,
527 const char* STACK_METHOD,
const double STACK_KLOW,
const double STACK_KHIGH,
528 const int STACK_NITER,
529 const int pr_num_x,
const int pr_num_y,
530 const int pr_box_sx,
const int pr_box_sy) {
531 cpl_image *master_dark = NULL;
532 cpl_image *current_dark = NULL;
533 cpl_imagelist *preproc_images = NULL;
534 double mean_exptime = 0;
538 preproc_images = irplib_mkmaster_dark_fill_imagelist(raw_images, raw_headers,
539 master_bias, &mean_exptime);
542 irplib_mkmaster_dark_qc(raw_images, preproc_images, parameters, pr_num_x,
543 pr_num_y, pr_box_sx, pr_box_sy, recipe_id, qclog);
547 if (strcmp(STACK_METHOD,
"MEDIAN") == 0) {
548 cpl_msg_info(cpl_func,
"Calculating stack median");
549 master_dark = cpl_imagelist_collapse_median_create(preproc_images);
551 cpl_msg_info(cpl_func,
"Calculating stack mean");
553 STACK_KHIGH, STACK_NITER);
558 cpl_image_delete(current_dark);
559 cpl_imagelist_delete(preproc_images);
560 if (cpl_error_get_code() != CPL_ERROR_NONE) {
561 cpl_image_delete(master_dark);
static double irplib_vector_ksigma(cpl_vector *values, const double klow, const double khigh, int kiter)
Perform kappa-sigma clip.
static double irplib_head_get_exptime(const cpl_propertylist *plist)
Find out the exposure time in seconds.
static cpl_vector * irplib_imagelist_get_clean_mean_levels(const cpl_imagelist *iml, const double kappa, const int nclip, const double tolerance)
find out the character string associated to the DIT keyword in a propertylist
static cpl_error_code irplib_head_set_exptime(cpl_propertylist *plist, double exptime)
Write the exposure time.
static cpl_image * irplib_imagelist_ksigma_stack(const cpl_imagelist *imlist, double klow, double khigh, int kiter)
Stack images using k-sigma clipping.
static cpl_error_code irplib_imagelist_subtract_values(cpl_imagelist **iml, cpl_vector *values)
Subtract from input imagelist values specified in input vector.
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.