Äîêóìåíò âçÿò èç êýøà ïîèñêîâîé ìàøèíû. Àäðåñ îðèãèíàëüíîãî äîêóìåíòà : http://www.stecf.org/conferences/adass/adassVII/reprints/hodgep.ps.gz Äàòà èçìåíåíèÿ: Mon Jun 12 18:51:46 2006 Äàòà èíäåêñèðîâàíèÿ: Tue Oct 2 03:06:44 2012 Êîäèðîâêà:

Astronomical Data Analysis Software and Systems VII
ASP Conference Series, Vol. 145, 1998
R. Albrecht, R. N. Hook and H. A. Bushouse, e
Ö Copyright 1998 Astronomical Society of the Pacific. All rights reserved.
ds.
Pipeline Calibration for STIS
P. E. Hodge, S. J. Hulbert, D. Lindler 1 , I. Busko, J. C. Hsu, S. Baum,
M. McGrath, P. Goudfrooij, R. Shaw, R. Katsanis, S. Keener 2 and R.
Bohlin
Space Telescope Science Institute, 3700 San Martin Dr, Baltimore, MD,
21218
Abstract. The CALSTIS program for calibration of Space Telescope
Imaging Spectrograph data in the OPUS pipeline di#ers in several signifi­
cant ways from calibration for earlier HST instruments, such as the use of
FITS format, computation of error estimates, and association of related
exposures. Several steps are now done in the pipeline that previously had
to be done o#­line by the user, such as cosmic ray rejection and extraction
of 1­D spectra. Although the program is linked with IRAF for image and
table I/O, it is written in ANSI C rather than SPP, which should make
the code more accessible. FITS extension I/O makes use of the new IRAF
FITS kernel for images and the HEASARC FITSIO package for tables.
1. Introduction
The Space Telescope Imaging Spectrograph (STIS) is a complex instrument
containing both CCD and MAMA detectors. STIS can observe in both spectro­
scopic and imaging modes, using either first order or echelle gratings, and taking
data in either accumulate or time­tag mode. STIS has many apertures, some
filtered, including large apertures for imaging as well as long and short slits for
spectroscopy. On­board processing options include binning and restricting the
image to a subset of the full detector.
CALSTIS is the program that performs the ``pipeline'' calibration of STIS
data, the processing that can be done non­interactively and with table­driven
parameters.
See the STIS Instrument Science Reports (ISRs) and HST Data Handbook
for further information. These can be reached via the URL
http://www.stsci.edu/documents/data­handbook.html
2. Discussion
The previous pipeline calibration tasks read and write so­called GEIS image
format, known in IRAF as Space Telescope Format (STF). The new programs,
1 Advanced Computer Concepts, Inc.
2 University of Illinois, Urbana­Champaign, Urbana, IL 61801
316

Pipeline Calibration for STIS 317
on the other hand, use FITS format. Global keywords are written to the primary
header, and the images are written as IMAGE extensions. The primary data unit
is null, i.e. is not present. Three IMAGE extensions are used for a STIS image,
the science data, corresponding error estimates, and data quality flags; this is
called an ``image set,'' or imset. Reference images (e.g. flat fields) use the same
format, while reference tables are in FITS BINTABLE extensions. Multiple
exposures at the same pointing (e.g. cosmic­ray splits or repeat observations)
are stored in the same file, one image set per exposure.
Previous pipeline routines were tasks under the IRAF CL and were written
in either SPP or fortran. The new routines are host level programs written
in ANSI C, although they are still linked with IRAF for I/O. The I/O interface
makes use of HSTIO and CVOS, written by Allen Farris. HSTIO is the higher
level interface for images; this can be used to read or write an entire image set
in one call. HSTIO is independent of IRAF at the interface level, although the
current implementation calls CVOS routines. CVOS is a C­callable interface to
the standard IRAF subroutines, in particular for image and table I/O. Image
I/O uses the IRAF FITS image kernel written by Nelson Zarate. Table I/O uses
the HEASARC FITSIO package written by Bill Pence. For both images and
tables, an input or output file with filename extension ``.fits'' will automatically
be treated as a FITS file.
There are several major components to CALSTIS: cosmic­ray rejection for
CCD data, basic 2­D reduction (bias, dark, flat, etc.), wavecal processing, 2­
D spectral rectification, and 1­D spectral extraction. These can be run either
combined into a single executable or as several individual executables (eight,
actually). The former is the pipeline version, but both options are available
o#­line. When running the single executable (cs0.e), the calibration switches
are read from the input primary header, as with previous calibration pipeline
routines. The individual executables, however, take the calibration switches
from the command line; the default is to perform all relevant steps.
Although the CALSTIS executables are host level programs, CL scripts
have been provided in the STIS package for running CALSTIS from IRAF, for
the convenience of IRAF users. calstis is the single executable, the pipeline
version; basic2d does basic 2­D reduction; ocrreject is the cosmic­ray rejec­
tion task; wavecal does wavecal processing; x2d does 2­D rectification; and
x1d does 1­D spectral extraction. These scripts have parameters for input and
output file names, for options, and--except for the calstis task itself--for the
calibration switches. They construct a command line string beginning with ``!''
(to escape from IRAF to Unix), and they invoke the program using the syntax:
print (cmdline) | cl.
3. Further Details
Processing starts with populating the data quality array from a reference table
and assigning initial values for the error estimates based on pixel values, gain,
and read noise.
For CCD data, the bias level from the overscan will be subtracted and the
overscan regions removed. If the file contains multiple exposures, the separate
exposures will then be combined to reject cosmic rays. The algorithm is very

318 Hodge et al.
similar to the one used in the crrej task in the wfpc package. Parameters
controlling the cosmic ray rejection are read from a reference table; the row in
that table is selected based on exposure time and number of exposures. The
individual exposures must have been taken at the same pointing.
The usual bias, dark, and flat field corrections are then applied. MAMA
data are corrected for nonlinearity. For CCD data, code is in place for shut­
ter shading and analog­to­digital correction, but these steps are not performed
because they do not appear to be required.
For medium or high resolution spectroscopic MAMA data, the reference
files need to be convolved to account for Doppler shift, because a correction for
spacecraft motion during the exposure is applied on­board. That is, whenever
a photon is detected, the on­board software reads the detector coordinates of
the event, adjusts the pixel number in the dispersion direction by the amount of
the Doppler shift at that moment, then the image bu#er is incremented at the
adjusted location. During calibration, therefore, the data quality initialization
table and the dark and flat field reference images need to be shifted by the same
amount before being applied. This amounts to a convolution by the various
Doppler shifts throughout the exposure.
For spectroscopic data, a wavecal (line lamp) observation is used for deter­
mining the location of the spectrum on the detector. The location is needed for
accurate assignment of wavelengths, and for position information in the case of
long­slit data. Flat fielding and 2­D rectification are first applied to the wavecal,
and cosmic rays (in CCD data) are rejected by looking for outliers in the cross
dispersion direction. The o#set in the dispersion direction between the expected
location of the spectrum and the actual location is found by cross correlating
the observed spectrum with a template. In the cross dispersion direction, the
o#set is found either by finding edges or by cross correlation, depending on the
length of the slit. The long slits have two occulting bars, and it is the edges of
these bars that are used for finding the location. Edges are found by convolving
with [­1, 0, +1]. The location is found to subpixel level by fitting a quadratic to
the three pixels nearest the maximum (or minimum, depending on the edge).
2­D rectification is performed for long­slit data; it can can also be done for
imaging mode but currently is not. For each pixel in the output rectified image,
the corresponding point is found in the input distorted image, and bilinear in­
terpolation is used on the four nearest pixels to determine the value to assign to
the output. No correction for flux conservation is applied, as this is accounted
for in the flat field. Mapping from an output pixel back into the input image
makes use of the dispersion relation and 1­D trace. The dispersion relation gives
the pixel number as a function of wavelength and spectral order number. The
1­D trace is the displacement in the cross dispersion direction at each pixel in
the dispersion direction. Both of these can vary along the slit, so the disper­
sion coe#cients and the 1­D trace are linearly interpolated for each image line.
Corrections are applied to account for image o#set, binning, and subarray. For
imaging mode, the mapping is a 2­D polynomial (Chebyshev) representing the
optical distortion, and the IRAF gsurfit package is used to evaluate the function.
Extraction of 1­D spectra is performed in the pipeline for echelle data, and
it can be performed for long­slit data. When running the o#­line x1d task,
the target location on the slit can be specified. When running the pipeline

Pipeline Calibration for STIS 319
version, however, the brightest object on the slit is assumed to be the target,
and the extraction will be centered on that object. The same corrections for
image o#set are applied for 1­D extraction that were done in 2­D rectification.
The location of the spectrum is then refined by cross correlating the data with
the 1­D trace. At each pixel in the dispersion direction, the data are summed
over some range of pixels for the on­source region and background regions. The
displacement of these extraction regions in the cross dispersion direction is taken
from the same 1­D trace used in 2­D rectification. No resampling is done in the
dispersion direction; the associated wavelengths are therefore nonlinear, and
they are computed using the dispersion relation. The output is written as a
FITS BINTABLE extension, with one row per spectral order. For long­slit
data, then, there will be just one row, while there can be 50 rows for echelle
data.