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: 2007/06/06 08:17:33 $
00023  * $Revision: 1.82 $
00024  * $Name: uves-3_3_1 $
00025  * $Log: uves_utils_cpl.c,v $
00026  * Revision 1.82  2007/06/06 08:17:33  amodigli
00027  * replace tab with 4 spaces
00028  *
00029  * Revision 1.81  2007/04/24 12:50:29  jmlarsen
00030  * Replaced cpl_propertylist -> uves_propertylist which is much faster
00031  *
00032  * Revision 1.80  2007/04/10 07:11:35  jmlarsen
00033  * Added check on input image type
00034  *
00035  * Revision 1.79  2007/03/05 10:20:22  jmlarsen
00036  * Support slope parameter in 1d fitting
00037  *
00038  * Revision 1.78  2007/02/27 14:08:46  jmlarsen
00039  * Extended interface of uves_find_property
00040  *
00041  * Revision 1.77  2007/01/29 12:14:49  jmlarsen
00042  * Added uves_find_property()
00043  *
00044  * Revision 1.76  2007/01/15 08:48:20  jmlarsen
00045  * Exported get_kth function
00046  *
00047  * Revision 1.75  2006/12/07 08:28:18  jmlarsen
00048  * compute median as average of two middle elements
00049  *
00050  * Revision 1.74  2006/11/15 15:02:15  jmlarsen
00051  * Implemented const safe workarounds for CPL functions
00052  *
00053  * Revision 1.72  2006/11/15 14:04:08  jmlarsen
00054  * Removed non-const version of parameterlist_get_first/last/next which is already
00055  * in CPL, added const-safe wrapper, unwrapper and deallocator functions
00056  *
00057  * Revision 1.71  2006/11/06 15:19:42  jmlarsen
00058  * Removed unused include directives
00059  *
00060  * Revision 1.70  2006/09/19 07:17:08  jmlarsen
00061  * Reformatted line
00062  *
00063  * Revision 1.69  2006/09/08 14:06:04  jmlarsen
00064  * Added uves_tools_get_median()
00065  *
00066  * Revision 1.68  2006/08/23 09:33:03  jmlarsen
00067  * Renamed local variables shadowing POSIX reserved names
00068  *
00069  * Revision 1.67  2006/08/18 14:21:03  jmlarsen
00070  * Added code to support CPL3 median filtering
00071  *
00072  * Revision 1.66  2006/08/17 14:11:25  jmlarsen
00073  * Use assure_mem macro to check for memory allocation failure
00074  *
00075  * Revision 1.65  2006/08/17 13:56:53  jmlarsen
00076  * Reduced max line length
00077  *
00078  * Revision 1.64  2006/08/14 12:19:59  jmlarsen
00079  * Removed unused functions
00080  *
00081  * Revision 1.63  2006/08/11 14:56:06  amodigli
00082  * removed Doxygen warnings
00083  *
00084  * Revision 1.62  2006/08/10 10:54:09  jmlarsen
00085  * Removed CX_PI definition
00086  *
00087  * Revision 1.61  2006/08/08 11:27:18  amodigli
00088  * upgrade to CPL3
00089  *
00090  * Revision 1.60  2006/07/03 13:21:41  jmlarsen
00091  * Changed 1d-fit parameter estimation method when only sky needs to be determined
00092  *
00093  * Revision 1.59  2006/06/13 12:02:22  jmlarsen
00094  * Renamed y0 -> y_0
00095  *
00096  * Revision 1.58  2006/06/01 14:43:17  jmlarsen
00097  * Added missing documentation
00098  *
00099  * Revision 1.57  2006/05/12 15:13:04  jmlarsen
00100  * Pass image bpm as extra parameter to fitting routine for efficiency reasons
00101  *
00102  * Revision 1.56  2006/04/24 09:27:48  jmlarsen
00103  * Allow fixing background in gauss. fit
00104  *
00105  * Revision 1.55  2006/03/09 13:54:44  jmlarsen
00106  * Optimization of median computation
00107  *
00108  * Revision 1.54  2006/03/09 10:51:19  jmlarsen
00109  * Changed order of for loops
00110  *
00111  * Revision 1.53  2006/03/03 13:54:11  jmlarsen
00112  * Changed syntax of check macro
00113  *
00114  * Revision 1.52  2006/02/21 14:24:45  jmlarsen
00115  * Parameterized behaviour of median filter near image border
00116  *
00117  * Revision 1.51  2006/01/31 08:25:49  jmlarsen
00118  * Renamed uves_fit_gaussian_2d -> uves_fit_gaussian_2d_image
00119  *
00120  * Revision 1.50  2006/01/25 16:13:20  jmlarsen
00121  * Changed interface of gauss.fitting routine
00122  *
00123  * Revision 1.49  2006/01/12 15:41:14  jmlarsen
00124  * Moved gauss. fitting to irplib
00125  *
00126  * Revision 1.48  2005/12/20 08:11:44  jmlarsen
00127  * Added CVS  entry
00128  *
00129  */
00130 
00131 #ifdef HAVE_CONFIG_H
00132 #  include <config.h>
00133 #endif
00134 #  include <assert.h>
00135 /*----------------------------------------------------------------------------*/
00142 /*----------------------------------------------------------------------------*/
00143 
00146 #include <uves_utils_cpl.h>
00147 
00148 #include <uves_utils.h>
00149 #include <uves_utils_wrappers.h>
00150 #include <uves_dump.h>
00151 #include <uves_error.h>
00152 
00153 #include <irplib_access.h>
00154 #include <cpl.h>
00155 #include <stdbool.h>
00156 
00157 static cpl_image *filter_median(const cpl_image *image, int radx, int rady,
00158                 bool extrapolate_border);
00159     
00160 
00161 /*----------------------------------------------------------------------------*/
00173 /*----------------------------------------------------------------------------*/
00174 const cpl_property *
00175 uves_find_property_const(const uves_propertylist *plist, const char *name,
00176                    int number)
00177 {
00178     int i = 0;
00179     int size = uves_propertylist_get_size(plist);
00180 
00181     assure( number >= 0, CPL_ERROR_ILLEGAL_INPUT, "Number (%d) must be non-negative",
00182             number);
00183 
00184     for (i = 0; i < size; i++)
00185     {
00186         const cpl_property *p = uves_propertylist_get_const(plist, i);
00187 
00188         if (strcmp(cpl_property_get_name(p), name) == 0)
00189         {
00190                     if (number == 0)
00191                         {
00192                             return p;
00193                         }
00194                     else
00195                         /* Continue search */
00196                         {
00197                             number--;
00198                         }
00199         }
00200     }
00201 
00202   cleanup:
00203     return NULL;
00204 }
00205 cpl_property *
00206 uves_find_property(uves_propertylist *plist, const char *name,
00207                    int number)
00208 {
00209     return (cpl_property *) uves_find_property_const(plist, name, number);
00210 }
00211 
00212 /*----------------------------------------------------------------------------*/
00224 /*----------------------------------------------------------------------------*/
00225 cpl_error_code
00226 uves_filter_image_average(cpl_image *image, int radius_x, int radius_y)
00227 {
00228     cpl_image *aux = NULL;
00229     double *image_data = NULL;
00230     double *aux_data = NULL;
00231     int nx, ny;
00232     int i;
00233 
00234     /* For bad pixel handling, create a similar auxillary image that counts the bad pixels */
00235     
00236     assure( image != NULL, CPL_ERROR_NULL_INPUT, "Null image");
00237     assure( radius_x >= 0, CPL_ERROR_ILLEGAL_INPUT, "Negative x-radius (%d)", radius_x);
00238     assure( radius_y >= 0, CPL_ERROR_ILLEGAL_INPUT, "Negative y-radius (%d)", radius_y);
00239     assure( cpl_image_get_type(image) == CPL_TYPE_DOUBLE, CPL_ERROR_TYPE_MISMATCH,
00240         "Type is %s. double expected", uves_tostring_cpl_type(cpl_image_get_type(image)));
00241     
00242     nx = cpl_image_get_size_x(image);
00243     ny = cpl_image_get_size_y(image);
00244     image_data = irplib_image_get_data_double(image);
00245     
00246     /* (Disabled:) To avoid problems with overflow (the total flux in the image might
00247        be larger than INT_MAX) subtract a constant (the average flux), apply the filter,
00248        then add the constant       */
00249     
00250     /* First build auxillary image:
00251      *
00252      * aux(x,y) = sum_{i=0,x-1} sum_{j=0,y-1}  image(i,j)
00253      *          = sum of rectangle (0,0)-(x-1,y-1)
00254      *
00255      */
00256 
00257     aux = cpl_image_new(nx+1, ny+1, CPL_TYPE_DOUBLE);          /* Initialized to zero */
00258     aux_data = irplib_image_get_data(aux);
00259 
00260     /* Column x=0 and row y=0 are already zero and need not be calculated,
00261      * start from 1.    */
00262 
00263 /* Slow:    for (x = 1; x < nx+1; x++)
00264             {
00265         for (y = 1; y < ny+1; y++)
00266         {
00267 */
00268     for (i = 0; i < (nx+1)*(ny+1); i++)
00269     {
00270         int x = i % (nx+1);
00271         int y = i / (nx+1);
00272         
00273         if ( x >= 1 && y >= 1)
00274         {
00275             aux_data[x + y*(nx+1)] = image_data[x-1 + (y-1) * nx]
00276             + aux_data  [x-1 +    y * (nx+1)]
00277             + aux_data  [x   + (y-1)* (nx+1)]
00278             - aux_data  [x-1 + (y-1)* (nx+1)];
00279         }
00280         
00281         /* Proof of induction step
00282          * (assume that formula holds up to (x-1,y) and (x,y-1) and prove formula for (x,y))
00283          *
00284          *  aux(x,y) = image(x-1, y-1) + aux(x-1, y) + aux(x, y-1) - aux(x-1, y-1)  (see code)
00285          *
00286          *  = image(x-1, y-1)
00287          *  + sum_{i=0,x-2}_{j=0,y-1} image(i,j)  _
00288          *  + sum_{i=0,x-1}_{j=0,y-2} image(i,j)   \_ sum_{j=0,y-2} image(x-1, j)  
00289          *  - sum_{i=0,x-2}_{j=0,y-2} image(i,j)  _/ 
00290          * 
00291          *  = sum_{i=0,x-2}_{j=0,y-1} image(i,j)
00292          *  + sum_          {j=0,y-1} image(x-1, j)  
00293          *  
00294          *  = sum_{j=0,y-1} [ ( sum_{i=0,x-2} image(i,j) ) + image(x-1,j) ]
00295          *  = sum_{j=0,y-1}     sum_{i=0,x-1} image(i,j)      q.e.d.
00296          *
00297          *  It's simpler when you draw it... 
00298          */
00299     }
00300 
00301     uves_msg_debug("Finished setting up auxillary image. Get average");
00302 
00303     /* Then calculate average = (flux in window) / (image size) */
00304     for (i = 0; i < nx*ny; i++)
00305     {
00306         int x = (i % nx);
00307         int y = (i / nx);
00308 
00309         int lower, upper;
00310         int left, right;
00311         
00312         lower = y - radius_y; if (lower <   0) lower = 0;
00313         upper = y + radius_y; if (upper >= ny) upper = ny - 1;
00314         
00315         left  = x - radius_x; if (left  <   0) left  = 0;
00316         right = x + radius_x; if (right >= nx) right = nx - 1;
00317         
00318         image_data[x + y*nx] =
00319         (
00320             aux_data[(right+1) + (upper+1)*(nx+1)] +
00321             aux_data[ left     +  lower   *(nx+1)] -
00322             aux_data[ left     + (upper+1)*(nx+1)] -
00323             aux_data[(right+1) +  lower   *(nx+1)]
00324             )
00325         /
00326         ( (double) (upper-lower+1) * (right-left+1) );
00327     }
00328     
00329   cleanup:
00330     uves_free_image(&aux);
00331     return cpl_error_get_code();
00332 }
00333 
00334 
00335 /*----------------------------------------------------------------------------*/
00349 /*----------------------------------------------------------------------------*/
00350 cpl_error_code
00351 uves_filter_image_median(cpl_image **image, int xwindow, int ywindow, bool extrapolate_border)
00352 {
00353     cpl_matrix *id = NULL;
00354     cpl_image *temp = NULL;
00355 
00356     assure( xwindow >= 0 && ywindow >= 0, CPL_ERROR_ILLEGAL_INPUT,
00357         "Illegal window radius: %d x %d", 
00358         (2*xwindow + 1),
00359         (2*ywindow + 1));
00360     
00361     UVES_TIME_START("median filter");
00362 
00363     if (xwindow <= 1 && ywindow <= 1)
00364 /* CPL 3 supports   if (xwindow <= 4 && ywindow <= 4) */
00365     {
00366         check(( id = cpl_matrix_new(2*xwindow+1, 2*ywindow+1),
00367             cpl_matrix_fill(id, 1)), "Could not create kernel matrix");
00368         
00369         /* Image to cpl_image_filter_median must be float or double */
00370         if (cpl_image_get_type(*image) == CPL_TYPE_INT)
00371         {
00372             temp = cpl_image_cast(*image, CPL_TYPE_DOUBLE);
00373             uves_free_image(image);
00374         }
00375         else
00376         {
00377             temp = *image;
00378         }
00379         check( *image = cpl_image_filter_median(temp, id), "Error applying median filter");
00380 
00381         /* fixme: the CPL function marks border pixels as bad. Do something
00382            depending on the extrapolate_border flag */
00383     }
00384     else
00385     {
00386         temp = *image;
00387         check( *image = filter_median(temp, xwindow, ywindow, extrapolate_border),
00388            "Error applying median filter");
00389         uves_free_image(&temp);
00390     }
00391 
00392     UVES_TIME_END;    
00393     
00394   cleanup:
00395     uves_free_matrix(&id);
00396     uves_free_image(&temp);
00397     return cpl_error_get_code();
00398 }
00399 
00401 #define DOUBLE_SWAP(a,b) { register double t=(a);(a)=(b);(b)=t; }
00402 
00413 inline
00414 double uves_utils_get_kth_double(
00415         double  *   a, 
00416         int         n, 
00417         int         k)
00418 {
00419     register double x ;
00420     register int    i, j, l, m ;
00421 
00422     l=0 ; m=n-1 ;
00423     while (l<m) {
00424         x=a[k] ;
00425         i=l ;
00426         j=m ;
00427         do {
00428             while (a[i]<x) i++ ;
00429             while (x<a[j]) j-- ;
00430             if (i<=j) {
00431                 DOUBLE_SWAP(a[i],a[j]) ;
00432                 i++ ; j-- ;
00433             }
00434         } while (i<=j) ;
00435         if (j<k) l=i ;
00436         if (k<i) m=j ;
00437     }
00438     return a[k] ;
00439 }
00440 
00449 inline double
00450 uves_tools_get_median(double *a, int n)
00451 {
00452     if (n % 2 == 0)
00453     {
00454         return
00455         (uves_utils_get_kth_double(a, n, n/2) +
00456          uves_utils_get_kth_double(a, n, n/2-1))/2.0;
00457         
00458     }
00459     else
00460     {
00461         return uves_utils_get_kth_double(a, n, (n-1)/2);
00462     }
00463 }
00464 
00465 
00466 
00467 /*----------------------------------------------------------------------------*/
00489 /*----------------------------------------------------------------------------*/
00490 static cpl_image *
00491 filter_median(const cpl_image *image, int radx, int rady, bool extrapolate_border)
00492 {
00493     int x, y;
00494     int nx = cpl_image_get_size_x(image);
00495     int ny = cpl_image_get_size_y(image);
00496     cpl_image *result = cpl_image_new(nx, ny, CPL_TYPE_DOUBLE);
00497     double *result_data;
00498     const double *image_data;
00499     double *window = NULL;
00500 
00501     window = cpl_malloc(sizeof(double) * (2*radx+1)*(2*rady+1));
00502     assure_mem( result );
00503     assure( cpl_image_get_type(image) == CPL_TYPE_DOUBLE,
00504             CPL_ERROR_UNSUPPORTED_MODE, "Type is %s", 
00505             uves_tostring_cpl_type(cpl_image_get_type(image)));
00506 
00507     result_data = irplib_image_get_data_double(result);
00508     image_data = irplib_image_get_data_double_const(image);
00509 
00510     for (y = 1; y <= ny; y++)
00511     {
00512         for (x = 1; x <= nx; x++)
00513         {
00514             int x1, y_1, x2, y2;
00515             
00516             x1 = x - radx; y_1 = y - rady;
00517             x2 = x + radx; y2  = y + rady;
00518 
00519             if (extrapolate_border)
00520             {
00521                 /* At edge of image, move median box, so
00522                    that entire box is inside of image */
00523                 if (x1 < 1)
00524                 {
00525                     x2 += (1 - x1);
00526                     x1 += (1 - x1);
00527                 }
00528                 if (nx < x2)
00529                 {
00530                     x1 -= (x2 - nx);
00531                     x2 -= (x2 - nx);
00532                 }
00533                 
00534                 if (y_1 < 1)
00535                 {
00536                     y2  += (1 - y_1);
00537                     y_1 += (1 - y_1);
00538                 }
00539                 if (ny < y2)
00540                 {
00541                     y_1 -= (y2 - ny);
00542                     y2  -= (y2 - ny);
00543                 }
00544             }
00545             else { /* Rely on the use of min/max below */ }
00546             
00547 #if 0
00548             result_data[(x-1) + (y-1)*nx] = 
00549             cpl_image_get_median_window(image,  
00550                             uves_max_int(1,  x1),
00551                             uves_max_int(1,  y_1),
00552                             uves_min_int(nx, x2),
00553                             uves_min_int(ny, y2));
00554 
00555 #else
00556             /* This saves a few (~10-20) percent execution time */
00557             {
00558             int i, j, k;
00559             
00560             k = 0;
00561             for (j  = uves_max_int(1 , y_1)-1;
00562                  j <= uves_min_int(ny, y2 )-1;
00563                  j++)
00564                 for (i  = uves_max_int(1,  x1)-1; 
00565                  i <= uves_min_int(nx, x2)-1; 
00566                  i++)
00567                 {
00568                     window[k++] = image_data[i + j*nx];
00569                 }
00570             
00571             result_data[(x-1) + (y-1)*nx] = 
00572                 uves_utils_get_kth_double(window,k,(((k)&1)?((k)/2):(((k)/2)-1))) ;
00573             }
00574 #endif        
00575         }
00576     }
00577     
00578 
00579     assure( cpl_error_get_code() == CPL_ERROR_NONE, cpl_error_get_code(), 
00580         "Error calculating %dx%d median filter", radx, rady);
00581     
00582   cleanup:
00583     cpl_free(window);
00584     return result;
00585 }
00586 
00587 
00588 /*----------------------------------------------------------------------------*/
00616 /*----------------------------------------------------------------------------*/
00617 
00618 cpl_error_code
00619 uves_fit_gaussian_2d_image(const cpl_image *image, const cpl_image *noise,
00620                int x1, int y_1,
00621                int x2, int y2,
00622                double *x0, double *y_0, double *sigmax, double *sigmay,
00623                double *amplitude,
00624                double *dx0, double *dy0
00625     )
00626 {
00627     cpl_image  *marginal_x = NULL;
00628     cpl_image  *marginal_y = NULL;
00629     cpl_image  *marginal_x_noise = NULL;
00630     cpl_image  *marginal_y_noise = NULL;
00631     cpl_image  *variance = NULL;
00632     cpl_matrix *covariance = NULL;
00633 
00634     int nx, ny;
00635     double norm_x, norm_y;
00636     double background_x, background_y;
00637 
00638     /* Check input */
00639     assure( image != NULL, CPL_ERROR_NULL_INPUT, "Null image");
00640     nx = cpl_image_get_size_x(image);
00641     ny = cpl_image_get_size_y(image);
00642     assure( noise != NULL || (dx0 == NULL && dy0 == NULL), CPL_ERROR_INCOMPATIBLE_INPUT,
00643         "Cannot compute uncertainty of fit with no noise image specified");
00644     assure( noise == NULL || 
00645         (cpl_image_get_size_x(noise) == nx &&
00646          cpl_image_get_size_y(noise) == ny),
00647         CPL_ERROR_INCOMPATIBLE_INPUT,
00648         "Size of input image (%dx%d) and noise image (%dx%d) differ", 
00649         nx, ny,
00650         cpl_image_get_size_x(noise),
00651         cpl_image_get_size_y(noise));
00652     assure( 1 <= x1 && x1 <= x2 && x2 <= nx &&
00653         1 <= y_1 && y_1 <= y2 && y2 <= ny, CPL_ERROR_ILLEGAL_INPUT,
00654         "Illegal window: (%d, %d)-(%d, %d)", x1, y_1, x2, y2);
00655     assure( x0 != NULL, CPL_ERROR_NULL_INPUT, "Null x-center");
00656     assure( y_0 != NULL, CPL_ERROR_NULL_INPUT, "Null y-center");
00657     assure( sigmax != NULL, CPL_ERROR_NULL_INPUT, "Null sigma_x");
00658     assure( sigmay != NULL, CPL_ERROR_NULL_INPUT, "Null sigma_y");
00659     /* amplitude, dx0, dy0 may be NULL */
00660 
00661     if (noise != NULL)
00662     {
00663         /* Variance = noise^2 */
00664         check(( variance = cpl_image_extract(noise, x1, y_1, x2, y2),
00665             cpl_image_power(variance, 2.0)),
00666            "Error creating variance image");
00667     }
00668     
00669     /* Collapse along columns (result is horizontal) */
00670     check( marginal_x = cpl_image_collapse_window_create(image,
00671                              x1, y_1, x2, y2,
00672                              0),           /* Sum of columns */
00673        "Error collapsing window (%d, %d) - (%d, %d)", x1, y_1, x2, y2);  
00674 
00675     if (noise != NULL)
00676     {
00677         /* Sigma of sum = sqrt [ sum sigma_i^2 ] */
00678         
00679         check( marginal_x_noise = cpl_image_collapse_window_create(variance,
00680                                        1, 1, 
00681                                        x2-x1+1, y2-y_1+1,
00682                                        0), /* Sum of columns */
00683            "Error collapsing window (1, 1) - (%d, %d)", x2-x1+1, y2-y_1+1);
00684 
00685         /* Sqrt */
00686         cpl_image_power(marginal_x_noise, 0.5);
00687     }
00688     
00689     /* Collapse along rows (result is vertical) */
00690     check( marginal_y = cpl_image_collapse_window_create(image,
00691                              x1, y_1, x2, y2,
00692                              1),           /* Sum of rows */
00693        "Error collapsing window (%d, %d) - (%d, %d)", x1, y_1, x2, y2);  
00694     
00695     if (noise != NULL)
00696     {
00697         check( marginal_y_noise = cpl_image_collapse_window_create(variance,
00698                                        1, 1,
00699                                        x2-x1+1, y2-y_1+1,
00700                                        1), /* Sum of rows */
00701            "Error collapsing window (1, 1) - (%d, %d)", x2-x1+1, y2-y_1+1);
00702 
00703         /* Sqrt */
00704         cpl_image_power(marginal_y_noise, 0.5);
00705     }
00706 
00707     /* Fit x-distribution */
00708     uves_fit_1d_image(marginal_x, marginal_x_noise, NULL,
00709               true,                       /* Horizontal ?                  */
00710               false, false,               /* Fix/fit background ?          */
00711               1, x2 - x1 + 1, 1,          /* xlo, xhi, y                   */
00712               x0, sigmax, &norm_x, &background_x, NULL,
00713               NULL, NULL,                 /* mse, red. chi^2               */
00714               (dx0 != NULL) ? &covariance : NULL,
00715               uves_gauss, uves_gauss_derivative, 4);
00716 
00717     /* Set code 'CPL_ERROR_CONTINUE' if fitting failed, check for unexpected errors */
00718     assure( cpl_error_get_code() != CPL_ERROR_CONTINUE ||
00719         cpl_error_get_code() != CPL_ERROR_SINGULAR_MATRIX,
00720         CPL_ERROR_CONTINUE, "Fitting along x failed");
00721     assure( cpl_error_get_code() == CPL_ERROR_NONE, cpl_error_get_code(), 
00722         "Fitting along x failed");
00723      
00724     /* Map to world-coordinates */
00725     *x0 += (x1 - 1);
00726     
00727     if (dx0 != NULL)
00728     {
00729         *dx0 = cpl_matrix_get(covariance, 0, 0);
00730     }
00731 
00732 
00733     /* Fit y-distribution */
00734     uves_free_matrix(&covariance);
00735     uves_fit_1d_image(marginal_y, marginal_y_noise, NULL,
00736               false,                      /* Horizontal ?                  */
00737               false, false,               /* Fix/fit background ?          */
00738               1, y2 - y_1 + 1, 1,          /* ylo, yhi, x                   */
00739               y_0, sigmay, &norm_y, &background_y, NULL,
00740               NULL, NULL,                 /* mse, red. chi^2               */
00741               (dy0 != NULL) ? &covariance : NULL,
00742               uves_gauss, uves_gauss_derivative, 4);
00743     
00744     /* Set code 'CPL_ERROR_CONTINUE' if fitting failed, check for unexpected errors */
00745     assure( cpl_error_get_code() != CPL_ERROR_CONTINUE ||
00746         cpl_error_get_code() != CPL_ERROR_SINGULAR_MATRIX,
00747         CPL_ERROR_CONTINUE, "Fitting along y failed");
00748     assure( cpl_error_get_code() == CPL_ERROR_NONE, cpl_error_get_code(), 
00749         "Fitting along y failed");
00750     
00751     /* Map to world-coordinates */
00752     *y_0 += (y_1 - 1);
00753     
00754     if (dy0 != NULL)
00755     {
00756         *dy0 = cpl_matrix_get(covariance, 0, 0);
00757     }
00758     
00759     /* Set amplitude  = N / [ sqrt(2pi sigmax^2) sqrt(2pi sigmay^2) ].
00760      *
00761      * The fitted norm (area), N, is the same (up to numerical errors) in both directions,
00762      * so use geometric average as an estimate of N.
00763      */
00764     if (amplitude != NULL)
00765     {
00766         *amplitude = sqrt(norm_x * norm_y) / (2*M_PI * (*sigmax) * (*sigmay));
00767     }
00768     
00769   cleanup:
00770     uves_free_matrix(&covariance);
00771     uves_free_image(&variance);
00772     uves_free_image(&marginal_x);
00773     uves_free_image(&marginal_x_noise);
00774     uves_free_image(&marginal_y);
00775     uves_free_image(&marginal_y_noise);
00776     
00777     return cpl_error_get_code();
00778 }
00779 
00780 

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