In this Appendix a more exhaustive catalogue of the capabilities and parameters of the CCDPACK routines are given. Do not read it if the previous descriptions have met your present needs. Read it only if they don’t. Remember that help is available at any time in the XREDUCE Help menus, from the programs by returning a ‘?’ in response to a prompt, or by entering the on-line or hypertext help systems after starting CCDPACK.
Throughout the following descriptions various methodologies exist which are worthy of discussion as topics. They cover such aspects of data processing as the control of, saturation values, data types and data combination.
CCDPACK allows you to flag data values above a given limit as saturated. It performs this task using one of two methods, either setting the pixels BAD (often referred to as invalidating or setting to a magic value), in which case the future processing is transparent if applications which can accommodate BAD values are used, or alternatively by setting all such pixels to a defined value (this option may be necessary if the destination analysis programs cannot handle BAD values). In this latter case care is required because future operations to the data can easily modify the values, so that unintentional differentiation of the saturated data may occur. This will only happen in such situations as flatfielding where the pixels are modified singly, global operations such as subtraction, multiplication etc. by a constant will preserve the saturated value dataset, although modifying the actual saturation value.
If you process saturated data using a specified value within CCDPACK then a CCDPACK extension item is created and the saturation value is written to it. Future work within CCDPACK will then stop modification of these saturated values (the routines CALCOR and FLATCOR do this). In general if you can safely use BAD values this is by far the better option. If you are determined to mark saturated data using a specific value then it is recommended that calibration (dark, flash and flat) frames are processed using BAD values as the combination processes do not support saturated value preservation. If the resultant master calibration frames contain BAD values then replacement (by the value 1 or by the mean) of these can be performed in KAPPA (SUN/95: SETMAGIC).
The CCD data frames given to CCDPACK can be of any non-complex HDS (SUN/92) numeric type
(e.g. they could be of type
_UWORD - Fortran
_INTEGER or even
CCDPACK usually processes the data using this type. On occasion, however, frames, such as the
master flatfield, will not be returned in their original type. This is because normalising to a mean of
one precludes data storage of a precision less than
_REAL. However, the flatfield correction routine
FLATCOR will return the data in your input type regardless of the flatfield type so types are preserved
in the longer term.
If your input frames are of a mixed data type CCDPACK will preserve the data type of each individual frame. However, if you are combining mixed data types into a calibration master of some kind, CCDPACK will choose the least precise type which represents best all the input data types.
In the routines MAKEBIAS, MAKECAL and MAKEFLAT input images which have different physical sizes (because they have been previously sectioned, for some reason) will be padded to a common size before processing. This is so that no calibration data is lost.
The corrective routines (CALCOR, DEBIAS and FLATCOR) trim the data down to the size which contains the smallest dataset. The trimming processes occur separately for each input image. The most efficient method of processing is to keep the input data files of the same type and size, as this avoids costly trimming, padding, and mapping/unmapping of the data (CCDPACK always attempts to minimize the amount of re-mapping of calibration frames when processing lists of images).
The MAKEMOS application is specially designed to deal with datasets which may have very small regions in common and which produce large output mosaics.
CCDPACK supports many different methods of data combination:
The aim is to provide you with a fairly exhaustive list of ways in which you can combine your data. The methods include the most efficient (mean) and the most robust (median) estimators and a range of options in between these ideals. A description of the basis of the methods follows:
All of these methods, support variance propagation, provided that the input data errors have an approximately normal distribution.
In general if the input data comprise less than 5 datasets and spurious values are expected to be present, it is very difficult to perform better than the median, and this is the normal default.
ASTEXP Exports coordinate system information from images. 131
ASTIMP Imports coordinate system information into images. 135
CALCOR Performs dark or flash count corrections. 139
CCDALIGN Aligns images graphically by interactive object selection. 143
CCDCLEAR Clears global parameters. 147
CCDEDIT Edits the CCDPACK extensions of images. 148
CCDFORK Creates a script for executing CCDPACK commands in a background process. 156
CCDNDFAC Accesses a list of images, writing their names to a file. 157
CCDNOTE Adds a note to the log file. 159
CCDSETUP Sets up the CCDPACK global parameters. 160
CCDSHOW Displays the current values of any CCDPACK global parameters. 165
DEBIAS Debiasses lists of images either by bias image subtraction or by interpolation – applies bad data masks – extracts a subset of the data area – produces variances – applies saturation values. 166
DRAWNDF Draws aligned images or outlines on a graphics device. 175
DRIZZLE Resamples and mosaics using the drizzling algorithm. 180
FINDCENT Centroids image features. 185
FINDOBJ Locates and centroids image features. 189
FINDOFF Performs pattern-matching between position lists related by simple offsets. 194
FLATCOR Performs the flatfield correction on a list of images. 199
IDICURS Views and writes position lists interactively. 203
IMPORT Imports FITS information into CCDPACK extensions. 207
MAKEBIAS Produces a bias calibration image. 211
MAKECAL Produces calibration images for flash or dark counts. 216
MAKEFLAT Produces a flatfield image. 219
MAKEMOS Makes image mosaics by combining and normalising. 223
MAKESET Writes Set header information to images. 232
PAIRNDF Aligns images graphically by drag and drop 237
PLOTLIST Draws position markers on a graphics display. 243
PRESENT Presents a list of images to CCDPACK. 246
REDUCE Automatic CCD data reduction facility (command-line version) 252
REGISTER Determines transformations between lists of positions. 253
SCHEDULE Schedules an automated CCDPACK reduction. 260
SHOWSET Outputs image Set header information. 264
TRANLIST Transforms lists of positions. 267
TRANNDF Transforms (resamples) images. 274
WCSEDIT Modifies or examines image coordinate system information. 278
WCSREG Aligns images using multiple coordinate systems. 282
XREDUCE Starts the automated CCD data reduction GUI. 285
The CCDPACK routine descriptions are contained in the following pages.