centerpars -- edit the centering algorithm parameters
- calgorithm = "centroid"
- The centering algorithm. The "gauss" and "ofilter" options depend critically
on the value of the fwhmpsf parameter in the DATAPARS task. The centering
- The initial positions are assumed to be the true centers. Users may select this option if the initial centers are know to be accurate, e.g. they were computed by DAOFIND task.
- The object centers are determined by computing the intensity weighted means of the marginal profiles in x and y. This is the recommended default algorithm for APPHOT users.
- The object centers are computed by fitting a Gaussian of fixed fwhmpsf, specified by the DATAPARS fwhmpsf parameter, to the marginal profiles in x and y using non-linear least squares techniques.
- The object centers are computed using optimal filtering techniques, a triangular weighting function of half width equal to fwhmpsf as specified by the DATAPARS fwhmpsf parameter, and the marginal distributions in x and y.
- cbox = 5.(scale units)
- The width of the subraster used for object centering in units of the DATAPARS scale parameter. Cbox must be big enough to include a reasonable number of pixels for center determination but not so large so as to include a lot of noise. Recommended initial values are 2.5-4.0 * the FWHM of the PSF value.
- cthreshold = 0.(sigma units)
- Pixels cthreshold * sigma above (emission features) or below (absorption features) the data minimum or maximum respectively are used by the centering algorithms where sigma is equal to the value of the DATAPARS sigma parameter. Most APPHOT users should leave this value at 0.0 which invokes the appropriate default thresholding technique for each centering algorithm. Setting cthreshold to INDEF turns off thresholding altogether for all the centering algorithms.
- minsnratio = 1.0
- The minimum signal to noise ratio for object centering. If the estimated signal to noise ratio is less than minsnratio the computed center will be returned with an error flag.
- cmaxiter = 10
- The maximum number of iterations performed by the centering algorithm. All the centering algorithms use this parameter.
- maxshift = 1.(scale units)
- The maximum permissible shift of the center with respect to the initial coordinates in units of the scale parameter. If the shift produced by the centering algorithms is larger than maxshift, the computed center is returned with an error flag.
- clean = no
- Symmetry-clean the centering subrater before centering? APPHOT users should leave clean set to "no".
- rclean = 1.(scale units)
- The cleaning radius for the symmetry-clean algorithm in units of the scale parameter.
- rclip = 2.(scale units)
- The clipping radius for the symmetry-clean algorithm in units of the scale parameter.
- kclean = 3.(sigma)
- The number of sky background standard deviations for the symmetry-clean algorithm where sigma is the value of the DATAPARS parameter sigma.
- mkcenter = no
- Mark the fitted object centers on the displayed image ?
The centering algorithm parameters control the action of the centering algorithms. The default parameters values have been proven to produce reasonable results in the majority of cases. Several of the centering parameters are defined in terms of the DATAPARS parameter scale , the scale of the image, and sigma the standard deviation of the sky pixels.
For each object to be measured a subraster of data cbox / scale pixels wide around the initial position supplied by the user is extracted from the IRAF image. If scale is defined in units of the number the half-width half-maximum of the psf per pixel, then a single value of cbox can be used for centering objects in images with different psfs.
If clean is "yes" the symmetry-clean algorithm is applied to the centering subraster prior to centering. The cleaning algorithm attempts to correct defects in the centering subraster by assuming that the image is radially symmetric and comparing pixels on opposite sides of the center of symmetry. The center of symmetry is assumed to be the maximum pixel in the subraster, unless the maximum pixel is more than maxshift / scale from the initial center, in which case the initial center is used as the center of symmetry. Pixels inside the cleaning radius are not edited. Pairs of pixels in the cleaning region, r > rclean / scale and r <= rclip / scale and diametrically opposed about the center of symmetry are tested for equality. If the difference between the pixels is greater than kclean * sigma , the larger value is replaced by the smaller. In the cleaning region the sigma is determined by the noise model assumed for the data. Pairs of pixels in the clipping region, r > rclip / scale are tested in the same manner as those in the cleaning region. However the sigma employed is the sigma of the sky background. Most APPHOT users should leave clean set to "no".
New centers are computed using the centering algorithm specified by calgorithm , the data specified by cbox / scale , and pixels that are some threshold above (below) an estimate of the local minimum (maximum). Cthreshold values of 0.0, a positive number, and INDEF invoke the default thresholding algorithm, a threshold equal to the local minimum (maximum) plus (minus) datapars.sigma * cthreshold , and a threshold exactly equal to the local minimum (maximum) respectively.
After thresholding the signal to noise ratio of the subraster is estimated. If the SNR < minsnratio the new center is still computed but an error flag is set.
The default centering algorithm is centroid . Centroid computes the intensity weighted mean and mean error of the centering box x and y marginal distributions using points in the marginal arrays above (below) the minimum (maximum) data pixel plus (minus) a threshold value.
The threshold value is either the mean, datapars.sigma * cthreshold above (below) the local minimum (maximum) if cthreshold is greater than zero, or zero above (below) the local minimum (maximum) if cthreshold is INDEF. The centroid algorithm is similar to that by the old KPNO Mountain Photometry Code. Note that centroid is the only centering algorithm which does not depend on the value of datapars.fwhmpsf .
The centering algorithm gauss computes the new centers by fitting a 1D Gaussian function to the marginal distributions in x and y using a fixed fwhmpsf set by datapars.fwhmpsf . Initial guesses for the fit parameters are derived from the data. The gauss algorithm iterates until a best fit solution is achieved.
The final centering algorithm choice ofilter employs a variation of the optimal filtering technique in which the profile is simulated by a triangle function of width datapars.fwhmpsf .
The default thresholding algorithm for all centering algorithms other than "centroid" is no thresholding.
If the computed shift in either coordinate > maxshift / scale , the new center is returned but an error flag is set.
1. List the centering parameters.
ap> lpar centerpars
2. Edit the centering parameters
3. Edit the CENTERPARS parameters from with the PHOT task.
da> epar phot ... edit a few phot parameters ... move to the centerpars parameter and type :e ... edit the centerpars parameters and type :wq ... finish editing the phot parameters and type :wq
4. Save the current CENTERPARS parameter set in a text file ctrnite1.par. This can also be done from inside a higher level task as in the previous example.
da> centerpars ... edit the parameters ... type ":w ctrnite1.par" from within epar