uves_utils_cpl.c

00001 /*                                                                              *
00002  *   This file is part of the ESO UVES Pipeline                                 *
00003  *   Copyright (C) 2004,2005 European Southern Observatory                      *
00004  *                                                                              *
00005  *   This library is free software; you can redistribute it and/or modify       *
00006  *   it under the terms of the GNU General Public License as published by       *
00007  *   the Free Software Foundation; either version 2 of the License, or          *
00008  *   (at your option) any later version.                                        *
00009  *                                                                              *
00010  *   This program is distributed in the hope that it will be useful,            *
00011  *   but WITHOUT ANY WARRANTY; without even the implied warranty of             *
00012  *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the              *
00013  *   GNU General Public License for more details.                               *
00014  *                                                                              *
00015  *   You should have received a copy of the GNU General Public License          *
00016  *   along with this program; if not, write to the Free Software                *
00017  *   Foundation, 51 Franklin St, Fifth Floor, Boston, MA  02111-1307  USA       *
00018  *                                                                              */
00019 
00020 /*
00021  * $Author: amodigli $
00022  * $Date: 2011/12/08 13:59:32 $
00023  * $Revision: 1.89 $
00024  * $Name: uves-4_9_15 $
00025  * $Log: uves_utils_cpl.c,v $
00026  * Revision 1.89  2011/12/08 13:59:32  amodigli
00027  * Fox warnings with CPL6
00028  *
00029  * Revision 1.88  2010/09/24 09:32:08  amodigli
00030  * put back QFITS dependency to fix problem spot by NRI on FIBER mode (with MIDAS calibs) data
00031  *
00032  * Revision 1.86  2010/02/13 12:22:31  amodigli
00033  * removed inlines (let's do work to compiler)
00034  *
00035  * Revision 1.85  2010/01/07 07:49:17  amodigli
00036  * added some 'check_nomsg' statementsuves_utils.c
00037  *
00038  * Revision 1.84  2008/09/29 07:00:55  amodigli
00039  * add #include <string.h>
00040  *
00041  * Revision 1.83  2007/08/21 13:08:26  jmlarsen
00042  * Removed irplib_access module, largely deprecated by CPL-4
00043  *
00044  * Revision 1.82  2007/06/06 08:17:33  amodigli
00045  * replace tab with 4 spaces
00046  *
00047  * Revision 1.81  2007/04/24 12:50:29  jmlarsen
00048  * Replaced cpl_propertylist -> uves_propertylist which is much faster
00049  *
00050  * Revision 1.80  2007/04/10 07:11:35  jmlarsen
00051  * Added check on input image type
00052  *
00053  * Revision 1.79  2007/03/05 10:20:22  jmlarsen
00054  * Support slope parameter in 1d fitting
00055  *
00056  * Revision 1.78  2007/02/27 14:08:46  jmlarsen
00057  * Extended interface of uves_find_property
00058  *
00059  * Revision 1.77  2007/01/29 12:14:49  jmlarsen
00060  * Added uves_find_property()
00061  *
00062  * Revision 1.76  2007/01/15 08:48:20  jmlarsen
00063  * Exported get_kth function
00064  *
00065  * Revision 1.75  2006/12/07 08:28:18  jmlarsen
00066  * compute median as average of two middle elements
00067  *
00068  * Revision 1.74  2006/11/15 15:02:15  jmlarsen
00069  * Implemented const safe workarounds for CPL functions
00070  *
00071  * Revision 1.72  2006/11/15 14:04:08  jmlarsen
00072  * Removed non-const version of parameterlist_get_first/last/next which is already
00073  * in CPL, added const-safe wrapper, unwrapper and deallocator functions
00074  *
00075  * Revision 1.71  2006/11/06 15:19:42  jmlarsen
00076  * Removed unused include directives
00077  *
00078  * Revision 1.70  2006/09/19 07:17:08  jmlarsen
00079  * Reformatted line
00080  *
00081  * Revision 1.69  2006/09/08 14:06:04  jmlarsen
00082  * Added uves_tools_get_median()
00083  *
00084  * Revision 1.68  2006/08/23 09:33:03  jmlarsen
00085  * Renamed local variables shadowing POSIX reserved names
00086  *
00087  * Revision 1.67  2006/08/18 14:21:03  jmlarsen
00088  * Added code to support CPL3 median filtering
00089  *
00090  * Revision 1.66  2006/08/17 14:11:25  jmlarsen
00091  * Use assure_mem macro to check for memory allocation failure
00092  *
00093  * Revision 1.65  2006/08/17 13:56:53  jmlarsen
00094  * Reduced max line length
00095  *
00096  * Revision 1.64  2006/08/14 12:19:59  jmlarsen
00097  * Removed unused functions
00098  *
00099  * Revision 1.63  2006/08/11 14:56:06  amodigli
00100  * removed Doxygen warnings
00101  *
00102  * Revision 1.62  2006/08/10 10:54:09  jmlarsen
00103  * Removed CX_PI definition
00104  *
00105  * Revision 1.61  2006/08/08 11:27:18  amodigli
00106  * upgrade to CPL3
00107  *
00108  * Revision 1.60  2006/07/03 13:21:41  jmlarsen
00109  * Changed 1d-fit parameter estimation method when only sky needs to be determined
00110  *
00111  * Revision 1.59  2006/06/13 12:02:22  jmlarsen
00112  * Renamed y0 -> y_0
00113  *
00114  * Revision 1.58  2006/06/01 14:43:17  jmlarsen
00115  * Added missing documentation
00116  *
00117  * Revision 1.57  2006/05/12 15:13:04  jmlarsen
00118  * Pass image bpm as extra parameter to fitting routine for efficiency reasons
00119  *
00120  * Revision 1.56  2006/04/24 09:27:48  jmlarsen
00121  * Allow fixing background in gauss. fit
00122  *
00123  * Revision 1.55  2006/03/09 13:54:44  jmlarsen
00124  * Optimization of median computation
00125  *
00126  * Revision 1.54  2006/03/09 10:51:19  jmlarsen
00127  * Changed order of for loops
00128  *
00129  * Revision 1.53  2006/03/03 13:54:11  jmlarsen
00130  * Changed syntax of check macro
00131  *
00132  * Revision 1.52  2006/02/21 14:24:45  jmlarsen
00133  * Parameterized behaviour of median filter near image border
00134  *
00135  * Revision 1.51  2006/01/31 08:25:49  jmlarsen
00136  * Renamed uves_fit_gaussian_2d -> uves_fit_gaussian_2d_image
00137  *
00138  * Revision 1.50  2006/01/25 16:13:20  jmlarsen
00139  * Changed interface of gauss.fitting routine
00140  *
00141  * Revision 1.49  2006/01/12 15:41:14  jmlarsen
00142  * Moved gauss. fitting to irplib
00143  *
00144  * Revision 1.48  2005/12/20 08:11:44  jmlarsen
00145  * Added CVS  entry
00146  *
00147  */
00148 
00149 #ifdef HAVE_CONFIG_H
00150 #  include <config.h>
00151 #endif
00152 #  include <assert.h>
00153 /*----------------------------------------------------------------------------*/
00160 /*----------------------------------------------------------------------------*/
00161 
00164 #include <uves_utils_cpl.h>
00165 
00166 #include <uves_utils.h>
00167 #include <uves_utils_wrappers.h>
00168 #include <uves_dump.h>
00169 #include <uves_error.h>
00170 
00171 #include <cpl.h>
00172 #include <stdbool.h>
00173 #include <string.h>
00174 
00175 static cpl_image *filter_median(const cpl_image *image, int radx, int rady,
00176                 bool extrapolate_border);
00177     
00178 
00179 /*----------------------------------------------------------------------------*/
00191 /*----------------------------------------------------------------------------*/
00192 const cpl_property *
00193 uves_find_property_const(const uves_propertylist *plist, const char *name,
00194                    int number)
00195 {
00196     int i = 0;
00197     int size = uves_propertylist_get_size(plist);
00198 
00199     assure( number >= 0, CPL_ERROR_ILLEGAL_INPUT, "Number (%d) must be non-negative",
00200             number);
00201 
00202     for (i = 0; i < size; i++)
00203     {
00204         const cpl_property *p = uves_propertylist_get_const(plist, i);
00205 
00206         if (strcmp(cpl_property_get_name(p), name) == 0)
00207         {
00208                     if (number == 0)
00209                         {
00210                             return p;
00211                         }
00212                     else
00213                         /* Continue search */
00214                         {
00215                             number--;
00216                         }
00217         }
00218     }
00219 
00220   cleanup:
00221     return NULL;
00222 }
00223 cpl_property *
00224 uves_find_property(uves_propertylist *plist, const char *name,
00225                    int number)
00226 {
00227     return (cpl_property *) uves_find_property_const(plist, name, number);
00228 }
00229 
00230 /*----------------------------------------------------------------------------*/
00242 /*----------------------------------------------------------------------------*/
00243 cpl_error_code
00244 uves_filter_image_average(cpl_image *image, int radius_x, int radius_y)
00245 {
00246     cpl_image *aux = NULL;
00247     double *image_data = NULL;
00248     double *aux_data = NULL;
00249     int nx, ny;
00250     int i;
00251 
00252     /* For bad pixel handling, create a similar auxillary image that counts the bad pixels */
00253     
00254     assure( image != NULL, CPL_ERROR_NULL_INPUT, "Null image");
00255     assure( radius_x >= 0, CPL_ERROR_ILLEGAL_INPUT, "Negative x-radius (%d)", radius_x);
00256     assure( radius_y >= 0, CPL_ERROR_ILLEGAL_INPUT, "Negative y-radius (%d)", radius_y);
00257     assure( cpl_image_get_type(image) == CPL_TYPE_DOUBLE, CPL_ERROR_TYPE_MISMATCH,
00258         "Type is %s. double expected", uves_tostring_cpl_type(cpl_image_get_type(image)));
00259     
00260     nx = cpl_image_get_size_x(image);
00261     ny = cpl_image_get_size_y(image);
00262     image_data = cpl_image_get_data_double(image);
00263     
00264     /* (Disabled:) To avoid problems with overflow (the total flux in the image might
00265        be larger than INT_MAX) subtract a constant (the average flux), apply the filter,
00266        then add the constant       */
00267     
00268     /* First build auxillary image:
00269      *
00270      * aux(x,y) = sum_{i=0,x-1} sum_{j=0,y-1}  image(i,j)
00271      *          = sum of rectangle (0,0)-(x-1,y-1)
00272      *
00273      */
00274 
00275     aux = cpl_image_new(nx+1, ny+1, CPL_TYPE_DOUBLE);          /* Initialized to zero */
00276     aux_data = cpl_image_get_data(aux);
00277 
00278     /* Column x=0 and row y=0 are already zero and need not be calculated,
00279      * start from 1.    */
00280 
00281 /* Slow:    for (x = 1; x < nx+1; x++)
00282             {
00283         for (y = 1; y < ny+1; y++)
00284         {
00285 */
00286     for (i = 0; i < (nx+1)*(ny+1); i++)
00287     {
00288         int x = i % (nx+1);
00289         int y = i / (nx+1);
00290         
00291         if ( x >= 1 && y >= 1)
00292         {
00293             aux_data[x + y*(nx+1)] = image_data[x-1 + (y-1) * nx]
00294             + aux_data  [x-1 +    y * (nx+1)]
00295             + aux_data  [x   + (y-1)* (nx+1)]
00296             - aux_data  [x-1 + (y-1)* (nx+1)];
00297         }
00298         
00299         /* Proof of induction step
00300          * (assume that formula holds up to (x-1,y) and (x,y-1) and prove formula for (x,y))
00301          *
00302          *  aux(x,y) = image(x-1, y-1) + aux(x-1, y) + aux(x, y-1) - aux(x-1, y-1)  (see code)
00303          *
00304          *  = image(x-1, y-1)
00305          *  + sum_{i=0,x-2}_{j=0,y-1} image(i,j)  _
00306          *  + sum_{i=0,x-1}_{j=0,y-2} image(i,j)   \_ sum_{j=0,y-2} image(x-1, j)  
00307          *  - sum_{i=0,x-2}_{j=0,y-2} image(i,j)  _/ 
00308          * 
00309          *  = sum_{i=0,x-2}_{j=0,y-1} image(i,j)
00310          *  + sum_          {j=0,y-1} image(x-1, j)  
00311          *  
00312          *  = sum_{j=0,y-1} [ ( sum_{i=0,x-2} image(i,j) ) + image(x-1,j) ]
00313          *  = sum_{j=0,y-1}     sum_{i=0,x-1} image(i,j)      q.e.d.
00314          *
00315          *  It's simpler when you draw it... 
00316          */
00317     }
00318 
00319     uves_msg_debug("Finished setting up auxillary image. Get average");
00320 
00321     /* Then calculate average = (flux in window) / (image size) */
00322     for (i = 0; i < nx*ny; i++)
00323     {
00324         int x = (i % nx);
00325         int y = (i / nx);
00326 
00327         int lower, upper;
00328         int left, right;
00329         
00330         lower = y - radius_y; if (lower <   0) lower = 0;
00331         upper = y + radius_y; if (upper >= ny) upper = ny - 1;
00332         
00333         left  = x - radius_x; if (left  <   0) left  = 0;
00334         right = x + radius_x; if (right >= nx) right = nx - 1;
00335         
00336         image_data[x + y*nx] =
00337         (
00338             aux_data[(right+1) + (upper+1)*(nx+1)] +
00339             aux_data[ left     +  lower   *(nx+1)] -
00340             aux_data[ left     + (upper+1)*(nx+1)] -
00341             aux_data[(right+1) +  lower   *(nx+1)]
00342             )
00343         /
00344         ( (double) (upper-lower+1) * (right-left+1) );
00345     }
00346     
00347   cleanup:
00348     uves_free_image(&aux);
00349     return cpl_error_get_code();
00350 }
00351 
00352 
00353 /*----------------------------------------------------------------------------*/
00367 /*----------------------------------------------------------------------------*/
00368 cpl_error_code
00369 uves_filter_image_median(cpl_image **image, int xwindow, int ywindow, bool extrapolate_border)
00370 {
00371     cpl_matrix *id = NULL;
00372     cpl_image *temp = NULL;
00373 
00374     assure( xwindow >= 0 && ywindow >= 0, CPL_ERROR_ILLEGAL_INPUT,
00375         "Illegal window radius: %d x %d", 
00376         (2*xwindow + 1),
00377         (2*ywindow + 1));
00378     
00379     UVES_TIME_START("median filter");
00380 
00381     if (xwindow <= 1 && ywindow <= 1)
00382 /* CPL 3 supports   if (xwindow <= 4 && ywindow <= 4) */
00383     {
00384         check(( id = cpl_matrix_new(2*xwindow+1, 2*ywindow+1),
00385             cpl_matrix_fill(id, 1)), "Could not create kernel matrix");
00386         
00387         /* Image to cpl_image_filter_median must be float or double */
00388         if (cpl_image_get_type(*image) == CPL_TYPE_INT)
00389         {
00390             temp = cpl_image_cast(*image, CPL_TYPE_DOUBLE);
00391             uves_free_image(image);
00392         }
00393         else
00394         {
00395             temp = *image;
00396         }
00397         check( *image = uves_image_filter_median(temp, id), "Error applying median filter");
00398 
00399         /* fixme: the CPL function marks border pixels as bad. Do something
00400            depending on the extrapolate_border flag */
00401     }
00402     else
00403     {
00404         temp = *image;
00405         check( *image = filter_median(temp, xwindow, ywindow, extrapolate_border),
00406            "Error applying median filter");
00407         uves_free_image(&temp);
00408     }
00409 
00410     UVES_TIME_END;    
00411     
00412   cleanup:
00413     uves_free_matrix(&id);
00414     uves_free_image(&temp);
00415     return cpl_error_get_code();
00416 }
00417 
00419 #define DOUBLE_SWAP(a,b) { register double t=(a);(a)=(b);(b)=t; }
00420 
00431 double uves_utils_get_kth_double(
00432         double  *   a, 
00433         int         n, 
00434         int         k)
00435 {
00436     register double x ;
00437     register int    i, j, l, m ;
00438 
00439     l=0 ; m=n-1 ;
00440     while (l<m) {
00441         x=a[k] ;
00442         i=l ;
00443         j=m ;
00444         do {
00445             while (a[i]<x) i++ ;
00446             while (x<a[j]) j-- ;
00447             if (i<=j) {
00448                 DOUBLE_SWAP(a[i],a[j]) ;
00449                 i++ ; j-- ;
00450             }
00451         } while (i<=j) ;
00452         if (j<k) l=i ;
00453         if (k<i) m=j ;
00454     }
00455     return a[k] ;
00456 }
00457 
00466 double
00467 uves_tools_get_median(double *a, int n)
00468 {
00469     if (n % 2 == 0)
00470     {
00471         return
00472         (uves_utils_get_kth_double(a, n, n/2) +
00473          uves_utils_get_kth_double(a, n, n/2-1))/2.0;
00474         
00475     }
00476     else
00477     {
00478         return uves_utils_get_kth_double(a, n, (n-1)/2);
00479     }
00480 }
00481 
00482 
00483 
00484 /*----------------------------------------------------------------------------*/
00506 /*----------------------------------------------------------------------------*/
00507 static cpl_image *
00508 filter_median(const cpl_image *image, int radx, int rady, bool extrapolate_border)
00509 {
00510     int x, y;
00511     int nx = cpl_image_get_size_x(image);
00512     int ny = cpl_image_get_size_y(image);
00513     cpl_image *result = cpl_image_new(nx, ny, CPL_TYPE_DOUBLE);
00514     double *result_data;
00515     const double *image_data;
00516     double *window = NULL;
00517 
00518     window = cpl_malloc(sizeof(double) * (2*radx+1)*(2*rady+1));
00519     assure_mem( result );
00520     assure( cpl_image_get_type(image) == CPL_TYPE_DOUBLE,
00521             CPL_ERROR_UNSUPPORTED_MODE, "Type is %s", 
00522             uves_tostring_cpl_type(cpl_image_get_type(image)));
00523 
00524     result_data = cpl_image_get_data_double(result);
00525     image_data = cpl_image_get_data_double_const(image);
00526 
00527     for (y = 1; y <= ny; y++)
00528     {
00529         for (x = 1; x <= nx; x++)
00530         {
00531             int x1, y_1, x2, y2;
00532             
00533             x1 = x - radx; y_1 = y - rady;
00534             x2 = x + radx; y2  = y + rady;
00535 
00536             if (extrapolate_border)
00537             {
00538                 /* At edge of image, move median box, so
00539                    that entire box is inside of image */
00540                 if (x1 < 1)
00541                 {
00542                     x2 += (1 - x1);
00543                     x1 += (1 - x1);
00544                 }
00545                 if (nx < x2)
00546                 {
00547                     x1 -= (x2 - nx);
00548                     x2 -= (x2 - nx);
00549                 }
00550                 
00551                 if (y_1 < 1)
00552                 {
00553                     y2  += (1 - y_1);
00554                     y_1 += (1 - y_1);
00555                 }
00556                 if (ny < y2)
00557                 {
00558                     y_1 -= (y2 - ny);
00559                     y2  -= (y2 - ny);
00560                 }
00561             }
00562             else { /* Rely on the use of min/max below */ }
00563             
00564 #if 0
00565             result_data[(x-1) + (y-1)*nx] = 
00566             cpl_image_get_median_window(image,  
00567                             uves_max_int(1,  x1),
00568                             uves_max_int(1,  y_1),
00569                             uves_min_int(nx, x2),
00570                             uves_min_int(ny, y2));
00571 
00572 #else
00573             /* This saves a few (~10-20) percent execution time */
00574             {
00575             int i, j, k;
00576             
00577             k = 0;
00578             for (j  = uves_max_int(1 , y_1)-1;
00579                  j <= uves_min_int(ny, y2 )-1;
00580                  j++)
00581                 for (i  = uves_max_int(1,  x1)-1; 
00582                  i <= uves_min_int(nx, x2)-1; 
00583                  i++)
00584                 {
00585                     window[k++] = image_data[i + j*nx];
00586                 }
00587             
00588             result_data[(x-1) + (y-1)*nx] = 
00589                 uves_utils_get_kth_double(window,k,(((k)&1)?((k)/2):(((k)/2)-1))) ;
00590             }
00591 #endif        
00592         }
00593     }
00594     
00595 
00596     assure( cpl_error_get_code() == CPL_ERROR_NONE, cpl_error_get_code(), 
00597         "Error calculating %dx%d median filter", radx, rady);
00598     
00599   cleanup:
00600     cpl_free(window);
00601     return result;
00602 }
00603 
00604 
00605 /*----------------------------------------------------------------------------*/
00633 /*----------------------------------------------------------------------------*/
00634 
00635 cpl_error_code
00636 uves_fit_gaussian_2d_image(const cpl_image *image, const cpl_image *noise,
00637                int x1, int y_1,
00638                int x2, int y2,
00639                double *x0, double *y_0, double *sigmax, double *sigmay,
00640                double *amplitude,
00641                double *dx0, double *dy0
00642     )
00643 {
00644     cpl_image  *marginal_x = NULL;
00645     cpl_image  *marginal_y = NULL;
00646     cpl_image  *marginal_x_noise = NULL;
00647     cpl_image  *marginal_y_noise = NULL;
00648     cpl_image  *variance = NULL;
00649     cpl_matrix *covariance = NULL;
00650 
00651     int nx, ny;
00652     double norm_x, norm_y;
00653     double background_x, background_y;
00654 
00655     /* Check input */
00656     assure( image != NULL, CPL_ERROR_NULL_INPUT, "Null image");
00657     nx = cpl_image_get_size_x(image);
00658     ny = cpl_image_get_size_y(image);
00659     assure( noise != NULL || (dx0 == NULL && dy0 == NULL), CPL_ERROR_INCOMPATIBLE_INPUT,
00660         "Cannot compute uncertainty of fit with no noise image specified");
00661     assure( noise == NULL || 
00662         (cpl_image_get_size_x(noise) == nx &&
00663          cpl_image_get_size_y(noise) == ny),
00664         CPL_ERROR_INCOMPATIBLE_INPUT,
00665         "Size of input image (%" CPL_SIZE_FORMAT "x%" CPL_SIZE_FORMAT ") and noise image (%" CPL_SIZE_FORMAT "x%" CPL_SIZE_FORMAT ") differ", 
00666         nx, ny,
00667         cpl_image_get_size_x(noise),
00668         cpl_image_get_size_y(noise));
00669     assure( 1 <= x1 && x1 <= x2 && x2 <= nx &&
00670         1 <= y_1 && y_1 <= y2 && y2 <= ny, CPL_ERROR_ILLEGAL_INPUT,
00671         "Illegal window: (%d, %d)-(%d, %d)", x1, y_1, x2, y2);
00672     assure( x0 != NULL, CPL_ERROR_NULL_INPUT, "Null x-center");
00673     assure( y_0 != NULL, CPL_ERROR_NULL_INPUT, "Null y-center");
00674     assure( sigmax != NULL, CPL_ERROR_NULL_INPUT, "Null sigma_x");
00675     assure( sigmay != NULL, CPL_ERROR_NULL_INPUT, "Null sigma_y");
00676     /* amplitude, dx0, dy0 may be NULL */
00677 
00678     if (noise != NULL)
00679     {
00680         /* Variance = noise^2 */
00681         check(( variance = cpl_image_extract(noise, x1, y_1, x2, y2),
00682             cpl_image_power(variance, 2.0)),
00683            "Error creating variance image");
00684     }
00685     
00686     /* Collapse along columns (result is horizontal) */
00687     check( marginal_x = cpl_image_collapse_window_create(image,
00688                              x1, y_1, x2, y2,
00689                              0),           /* Sum of columns */
00690        "Error collapsing window (%d, %d) - (%d, %d)", x1, y_1, x2, y2);  
00691 
00692     if (noise != NULL)
00693     {
00694         /* Sigma of sum = sqrt [ sum sigma_i^2 ] */
00695         
00696         check( marginal_x_noise = cpl_image_collapse_window_create(variance,
00697                                        1, 1, 
00698                                        x2-x1+1, y2-y_1+1,
00699                                        0), /* Sum of columns */
00700            "Error collapsing window (1, 1) - (%d, %d)", x2-x1+1, y2-y_1+1);
00701 
00702         /* Sqrt */
00703         cpl_image_power(marginal_x_noise, 0.5);
00704     }
00705     
00706     /* Collapse along rows (result is vertical) */
00707     check( marginal_y = cpl_image_collapse_window_create(image,
00708                              x1, y_1, x2, y2,
00709                              1),           /* Sum of rows */
00710        "Error collapsing window (%d, %d) - (%d, %d)", x1, y_1, x2, y2);  
00711     
00712     if (noise != NULL)
00713     {
00714         check( marginal_y_noise = cpl_image_collapse_window_create(variance,
00715                                        1, 1,
00716                                        x2-x1+1, y2-y_1+1,
00717                                        1), /* Sum of rows */
00718            "Error collapsing window (1, 1) - (%d, %d)", x2-x1+1, y2-y_1+1);
00719 
00720         /* Sqrt */
00721         cpl_image_power(marginal_y_noise, 0.5);
00722     }
00723 
00724     /* Fit x-distribution */
00725     uves_fit_1d_image(marginal_x, marginal_x_noise, NULL,
00726               true,                       /* Horizontal ?                  */
00727               false, false,               /* Fix/fit background ?          */
00728               1, x2 - x1 + 1, 1,          /* xlo, xhi, y                   */
00729               x0, sigmax, &norm_x, &background_x, NULL,
00730               NULL, NULL,                 /* mse, red. chi^2               */
00731               (dx0 != NULL) ? &covariance : NULL,
00732               uves_gauss, uves_gauss_derivative, 4);
00733 
00734     /* Set code 'CPL_ERROR_CONTINUE' if fitting failed, check for unexpected errors */
00735     assure( cpl_error_get_code() != CPL_ERROR_CONTINUE ||
00736         cpl_error_get_code() != CPL_ERROR_SINGULAR_MATRIX,
00737         CPL_ERROR_CONTINUE, "Fitting along x failed");
00738     assure( cpl_error_get_code() == CPL_ERROR_NONE, cpl_error_get_code(), 
00739         "Fitting along x failed");
00740      
00741     /* Map to world-coordinates */
00742     *x0 += (x1 - 1);
00743     
00744     if (dx0 != NULL)
00745     {
00746         *dx0 = cpl_matrix_get(covariance, 0, 0);
00747     }
00748 
00749 
00750     /* Fit y-distribution */
00751     uves_free_matrix(&covariance);
00752     uves_fit_1d_image(marginal_y, marginal_y_noise, NULL,
00753               false,                      /* Horizontal ?                  */
00754               false, false,               /* Fix/fit background ?          */
00755               1, y2 - y_1 + 1, 1,          /* ylo, yhi, x                   */
00756               y_0, sigmay, &norm_y, &background_y, NULL,
00757               NULL, NULL,                 /* mse, red. chi^2               */
00758               (dy0 != NULL) ? &covariance : NULL,
00759               uves_gauss, uves_gauss_derivative, 4);
00760     
00761     /* Set code 'CPL_ERROR_CONTINUE' if fitting failed, check for unexpected errors */
00762     assure( cpl_error_get_code() != CPL_ERROR_CONTINUE ||
00763         cpl_error_get_code() != CPL_ERROR_SINGULAR_MATRIX,
00764         CPL_ERROR_CONTINUE, "Fitting along y failed");
00765     assure( cpl_error_get_code() == CPL_ERROR_NONE, cpl_error_get_code(), 
00766         "Fitting along y failed");
00767     
00768     /* Map to world-coordinates */
00769     *y_0 += (y_1 - 1);
00770     
00771     if (dy0 != NULL)
00772     {
00773         *dy0 = cpl_matrix_get(covariance, 0, 0);
00774     }
00775     
00776     /* Set amplitude  = N / [ sqrt(2pi sigmax^2) sqrt(2pi sigmay^2) ].
00777      *
00778      * The fitted norm (area), N, is the same (up to numerical errors) in both directions,
00779      * so use geometric average as an estimate of N.
00780      */
00781     if (amplitude != NULL)
00782     {
00783         *amplitude = sqrt(norm_x * norm_y) / (2*M_PI * (*sigmax) * (*sigmay));
00784     }
00785     
00786   cleanup:
00787     uves_free_matrix(&covariance);
00788     uves_free_image(&variance);
00789     uves_free_image(&marginal_x);
00790     uves_free_image(&marginal_x_noise);
00791     uves_free_image(&marginal_y);
00792     uves_free_image(&marginal_y_noise);
00793     
00794     return cpl_error_get_code();
00795 }
00796 
00797 

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