DISCLAIMER: This manual for standard star reductions is just a guideline. It is something I have had to learn myself through toil, blood and sweat. If you want to use this manual to reduce standard star spectra, or maybe even other data, please do so, but be advised that this is *NOT THE* way of reducing them and it is absolutely *NOT* garantueed to be free of errors.

If you enjoyed this manual, have any suggestions/comments/questions/etc, you can send me an email on .

Last update:
07/03/06 Updated CCD information.
07/02/06 and before: Written by Eduard Westra.


First the biassubtraction and flatfielding has to be done. In this case the bias is only subtracted using a fit to the overscan region. For CCD 1 this is [*,1:4], for CCD 2 this is [*,1030:1033]. The data sections are for CCD 1 [*,5:967], for CCD 2 this is [*,311:1029].
region CCD 1 CCD 2
overscan [*,1:4] [*,1030:1033]
data [*,5:967][*,311:1029]
gain 1.43 1.43
readnoise2.90 3.15
readaxis column column
It seems that in older periods FORS2 had only 1 CCD. It has both a pre- and an overscan. Info for that CCD is below:
region CCD
prescan [1:16,*]
overscan [2065:2080,*]
data [17:2064,*]
gain 0.52
readnoise5.41
readaxis line

Biassubtraction

This is done in noao.imred.ccdred using ccdproc. The file list contains the following files:
stdstar01_1
flatmos01_1
flatmos02_1
flatmos03_1
flatmos04_1
flatmos05_1
wavemos01_1
PACKAGE = ccdred
   TASK = ccdproc

images  =                @list  List of CCD images to correct
(output =                     ) List of output CCD images
(ccdtype=                     ) CCD image type to correct
(max_cac=                    0) Maximum image caching memory (in Mbytes)
(noproc =                   no) List processing steps only?

(fixpix =                   no) Fix bad CCD lines and columns?
(oversca=                  yes) Apply overscan strip correction?
(trim   =                  yes) Trim the image?
(zerocor=                   no) Apply zero level correction?
(darkcor=                   no) Apply dark count correction?
(flatcor=                   no) Apply flat field correction?
(illumco=                   no) Apply illumination correction?
(fringec=                   no) Apply fringe correction?
(readcor=                   no) Convert zero level image to readout correction?
(scancor=                   no) Convert flat field image to scan correction?

(readaxi=               column) Read out axis (column|line)
(fixfile=                     ) File describing the bad lines and columns
(biassec=              [*,1:4]) Overscan strip image section
(trimsec=            [*,5:967]) Trim data section
(zero   =                     ) Zero level calibration image
(dark   =                     ) Dark count calibration image
(flat   =                     ) Flat field images
(illum  =                     ) Illumination correction images
(fringe =                     ) Fringe correction images
(minrepl=                   1.) Minimum flat field value
(scantyp=            shortscan) Scan type (shortscan|longscan)
(nscan  =                    1) Number of short scan lines

(interac=                  yes) Fit overscan interactively?
(functio=             legendre) Fitting function
(order  =                    3) Number of polynomial terms or spline pieces
(sample =                    *) Sample points to fit
(naverag=                    1) Number of sample points to combine
(niterat=                    1) Number of rejection iterations
(low_rej=                   3.) Low sigma rejection factor
(high_re=                   3.) High sigma rejection factor
(grow   =                   0.) Rejection growing radius
(mode   =                   ql)
If you trust the fitting perfectly you can leave interac on no. Otherwise you get the following displays:

Flatfielding

The bias has been subtracted, so now normalize the frames. Combine the flatfield images into one image. As we know the gain and readnoise we can use crreject for the rejection. The gain is 1.43 e-/ADU and read noise is 2.90 e- for CCD 1. For CCD 2 the gain is 1.43e-/ADU and the read noise is 3.15 e-.
The flatfield images are combined using median and some sigma clipping. The input file list_flats contains the following:
flatmos01_1
flatmos02_1
flatmos03_1
flatmos04_1
flatmos05_1
PACKAGE = immatch
   TASK = imcombine

input   =          @list_flats  List of images to combine
output  =               flat_1  List of output images
(rejmask=                     ) List of rejection masks (optional)
(plfile =                     ) List of pixel list files (optional)
(sigma  =                     ) List of sigma images (optional)
(logfile=               STDOUT) Log file

(combine=              average) Type of combine operation
(reject =             crreject) Type of rejection
(project=                   no) Project highest dimension of input images?
(outtype=                 real) Output image pixel datatype
(offsets=                     ) Input image offsets
(masktyp=                 none) Mask type
(maskval=                   0.) Mask value
(blank  =                   0.) Value if there are no pixels

(scale  =               median) Image scaling
(zero   =                 none) Image zero point offset
(weight =                 none) Image weights
(statsec=                     ) Image section for computing statistics
(expname=                     ) Image header exposure time keyword

(lthresh=                INDEF) Lower threshold
(hthresh=                INDEF) Upper threshold
(nlow   =                    3) minmax: Number of low pixels to reject
(nhigh  =                    3) minmax: Number of high pixels to reject
(nkeep  =                    1) Minimum to keep (pos) or maximum to reject (neg)
(mclip  =                  yes) Use median in sigma clipping algorithms?
(lsigma =                   5.) Lower sigma clipping factor
(hsigma =                   5.) Upper sigma clipping factor
(rdnoise=                  2.9) ccdclip: CCD readout noise (electrons)
(gain   =                 1.43) ccdclip: CCD gain (electrons/DN)
(snoise =                   0.) ccdclip: Sensitivity noise (fraction)
(sigscal=                  0.1) Tolerance for sigma clipping scaling corrections
(pclip  =                 -0.5) pclip: Percentile clipping parameter
(grow   =                   0.) Radius (pixels) for neighbor rejection
(mode   =                   ql)

Removing lamp shape

As the lamp is not uniform across the wavelength space, you need to correct for this. This is done in noao.twodspec.apextract using apnormalize.
DELETE THE LAST 5 POINTS!!! As these are not fitting the polynomial very well.
Some useful keystrokes to make an aperture that spans the whole width:
PACKAGE = apextract 
TASK = apnormalize

input   =               flat_1  List of images to normalize
output  =          flat_norm_1  List of output normalized images
(apertur=                     ) Apertures
(referen=                     ) List of reference images

(interac=                  yes) Run task interactively?
(find   =                   no) Find apertures?
(recente=                   no) Recenter apertures?
(resize =                   no) Resize apertures?
(edit   =                  yes) Edit apertures?
(trace  =                   no) Trace apertures?
(fittrac=                   no) Fit traced points interactively?
(normali=                  yes) Normalize spectra?
(fitspec=                  yes) Fit normalization spectra interactively?

(line   =                INDEF) Dispersion line
(nsum   =                   10) Number of dispersion lines to sum or median
(cennorm=                   no) Normalize to the aperture center?
(thresho=                  10.) Threshold for normalization spectra

(backgro=                 none) Background to subtract
(weights=                 none) Extraction weights (none|variance)
(pfit   =                fit1d) Profile fitting type (fit1d|fit2d)
(clean  =                   no) Detect and replace bad pixels?
(skybox =                    1) Box car smoothing length for sky
(saturat=                INDEF) Saturation level
(readnoi=                 2.90) Read out noise sigma (photons)
(gain   =                 1.43) Photon gain (photons/data number)
(lsigma =                   4.) Lower rejection threshold
(usigma =                   4.) Upper rejection threshold

(functio=            chebyshev) Fitting function for normalization spectra
(order  =                  200) Fitting function order
(sample =                    *) Sample regions
(naverag=                    1) Average or median
(niterat=                   10) Number of rejection iterations
(low_rej=                   3.) Lower rejection sigma
(high_re=                   3.) High upper rejection sigma
(grow   =                   0.) Rejection growing radius
(mode   =                   ql)

Normalization

Now the flatfielding and the lampshape removal can be applied. This is done in noao.imred.ccdred using ccdproc
PACKAGE = ccdred
   TASK = ccdproc

images  =          stdstar01_1  List of CCD images to correct
(output =     stdstar_norm01_1) List of output CCD images
(ccdtype=                     ) CCD image type to correct
(max_cac=                    0) Maximum image caching memory (in Mbytes)
(noproc =                   no) List processing steps only?

(fixpix =                   no) Fix bad CCD lines and columns?
(oversca=                   no) Apply overscan strip correction?
(trim   =                   no) Trim the image?
(zerocor=                   no) Apply zero level correction?
(darkcor=                   no) Apply dark count correction?
(flatcor=                  yes) Apply flat field correction?
(illumco=                   no) Apply illumination correction?
(fringec=                   no) Apply fringe correction?
(readcor=                   no) Convert zero level image to readout correction?
(scancor=                   no) Convert flat field image to scan correction?

(readaxi=               column) Read out axis (column|line)
(fixfile=                     ) File describing the bad lines and columns
(biassec=              [*,1:4]) Overscan strip image section
(trimsec=            [*,5:967]) Trim data section
(zero   =                     ) Zero level calibration image
(dark   =                     ) Dark count calibration image
(flat   =          flat_norm_1) Flat field images
(illum  =                     ) Illumination correction images
(fringe =                     ) Fringe correction images
(minrepl=                   1.) Minimum flat field value
(scantyp=            shortscan) Scan type (shortscan|longscan)
(nscan  =                    1) Number of short scan lines

(interac=                  yes) Fit overscan interactively?
(functio=             legendre) Fitting function
(order  =                    3) Number of polynomial terms or spline pieces
(sample =                    *) Sample points to fit
(naverag=                    1) Number of sample points to combine
(niterat=                    1) Number of rejection iterations
(low_rej=                   3.) Low sigma rejection factor
(high_re=                   3.) High sigma rejection factor
(grow   =                   0.) Rejection growing radius
(mode   =                   ql)

2D wavelength calibration

The reason for 2D wavelength calibration is to correct for the spectrum in the dispersion direction. It might be a bit of overkill, but now a very accurate background subtraction can be done.
Use figure D.3 from the FORS1+2 manual to identify the lines.
With implot the spectrum center, aperture (roughly) and background are determined from the standard star frame (stdstar01_1). To get to the columns use :c value.
Before continueing with the normal procedure of aperture extraction, wavelength calibration and flux calibration a solution for the distortion in the field needs to be found. This is done as follows. First have the arc-spectrum. For this one knows that the spectral features should along in the dispersion axis.
Now use identify of the onedspec package to identify the arc-lines of the spectrum.
PACKAGE = onedspec
   TASK = identify

images  =          wavemos01_1  Images containing features to be identified
(section=          middle line) Section to apply to two dimensional images
(databas=             database) Database in which to record feature data
(coordli= linelists$ctiohenear.dat) User coordinate list
(units  =            angstroms) Coordinate units
(nsum   =                   10) Number of lines/columns/bands to sum in 2D image
(match  =                  -2.) Coordinate list matching limit
(maxfeat=                   50) Maximum number of features for automatic identif
(zwidth =                 100.) Zoom graph width in user units
(ftype  =             emission) Feature type
(fwidth =                   4.) Feature width in pixels
(cradius=                   8.) Centering radius in pixels
(thresho=                   0.) Feature threshold for centering
(minsep =                   2.) Minimum pixel separation
(functio=            chebyshev) Coordinate function
(order  =                    4) Order of coordinate function
(sample =                    *) Coordinate sample regions
(niterat=                    0) Rejection iterations
(low_rej=                   3.) Lower rejection sigma
(high_re=                   3.) Upper rejection sigma
(grow   =                   0.) Rejection growing radius
(autowri=                   no) Automatically write to database
(graphic=             stdgraph) Graphics output device
(cursor =                     ) Graphics cursor input
crval   =                       Approximate coordinate (at reference pixel)
cdelt   =                       Approximate dispersion
(aidpars=                     ) Automatic identification algorithm parameters
(mode   =                   ql)
To get the solution for the complete arc-frame use reidentify.
PACKAGE = onedspec
   TASK = reidentify

referenc=          wavemos01_1  Reference image
images  =          wavemos01_1  Images to be reidentified
(interac=                  yes) Interactive fitting?
(section=          middle line) Section to apply to two dimensional images
(newaps =                  yes) Reidentify apertures in images not in reference?
(overrid=                  yes) Override previous solutions?
(refit  =                  yes) Refit coordinate function?

(trace  =                   no) Trace reference image?
(step   =                   10) Step in lines/columns/bands for tracing an image
(nsum   =                    3) Number of lines/columns/bands to sum
(shift  =                   0.) Shift to add to reference features (INDEF to sea
(search =                   0.) Search radius
(nlost  =                    0) Maximum number of features which may be lost

(cradius=                   5.) Centering radius
(thresho=                   1.) Feature threshold for centering
(addfeat=                   no) Add features from a line list?
(coordli= linelists$ctiohenear.dat) User coordinate list
(match  =                  -2.) Coordinate list matching limit
(maxfeat=                   50) Maximum number of features for automatic identif
(minsep =                   2.) Minimum pixel separation

(databas=             database) Database
(logfile=              logfile) List of log files
(plotfil=                     ) Plot file for residuals
(verbose=                  yes) Verbose output?
(graphic=             stdgraph) Graphics output device
(cursor =                     ) Graphics cursor input

answer  =                   NO  Fit dispersion function interactively?
crval   =                       Approximate coordinate (at reference pixel)
cdelt   =                       Approximate dispersion
(aidpars=                     ) Automatic identification algorithm parameters
(mode   =                   ql)
Answer to the first question: NO (note the capitals this time!).
Ignore the errors, they will just be ignored in the solutions further on.
Unfortunately the playing comes just now... From the package noao.twodspec.longslit use fitcoords.
PACKAGE = longslit
   TASK = fitcoords

images  =          wavemos01_1  Images whose coordinates are to be fit
(fitname=                     ) Name for coordinate fit in the database
(interac=                  yes) Fit coordinates interactively?
(combine=                   no) Combine input coordinates for a single fit?
(databas=             database) Database
(deletio=         deletions.db) Deletion list file (not used if null)
(functio=            chebyshev) Type of fitting function
(xorder =                    6) X order of fitting function
(yorder =                    6) Y order of fitting function
(logfile=       STDOUT,logfile) Log files
(plotfil=             plotfile) Plot log file
(graphic=             stdgraph) Graphics output device
(cursor =                     ) Graphics cursor input
(mode   =                   ql)
Fit, of course, it interactively. With the keys 'x' and 'y' one can set the data on the x- and y-axis, respectively. It's useful to start with the x pixels on x and y pixels on y. Always do a redraw 'r' after a change in axes.
Then plot on x the x-axis and on y the 'r'esiduals. Set the fitting function to Chebyshev with :function cheb. Then play around with :xorder 6 to get the best fit. Do exactly the same for y on the x-axis and the residuals on y. You might 'd'elete certain 'p'oints, but then you are fine. Exit with 'q'. Write it to the database and you are ready to transform the image. This will be the last step of this complicated procedure. It is very easily executed. To transform the image do the following:
lo> transform wavemos01_1 wavemos01_1t wavemos01_1

NOAO/IRAF V2.11.3EXPORT westra@matrix Tue 16:16:15 22-Jun-2004
  Transform wavemos01_1 to wavemos01_1t.
  Conserve flux per pixel.
  User coordinate transformations:
    wavemos01_1
  Interpolation is spline3.
  Output coordinate parameters are:
    x1 =      7752., x2 =      9508., dx =     0.8579, nx = 2048, xlog = no
    y1 =         1., y2 =       963., dy =         1., ny =  963, ylog = no
Dispersion axis (1=along lines, 2=along columns, 3=along z) (1:3) (1): 
lo> transform stdstar_norm01_1 stdstar_norm01_1t wavemos01_1

NOAO/IRAF V2.11.3EXPORT westra@matrix Tue 16:18:46 22-Jun-2004
  Transform stdstar_norm01_1 to stdstar_norm01_1t.
  Conserve flux per pixel.
  User coordinate transformations:
    wavemos01_1
  Interpolation is spline3.
  Output coordinate parameters are:
    x1 =      7752., x2 =      9508., dx =     0.8579, nx = 2048, xlog = no
    y1 =         1., y2 =       963., dy =         1., ny =  963, ylog = no
Dispersion axis (1=along lines, 2=along columns, 3=along z) (1:3) (1): 
lo> 
The dispersion axis is in my case along lines (no 1!!!). Answer that nicely and you have a perfectly straight image!
When this is all finished, remember the old values written down before. This translates into the following apall input parameters:
PACKAGE = apextract
   TASK = apall
    
input   =    stdstar_norm01_1t  List of input images
(output =               std.ms) List of output spectra
(apertur=                     ) Apertures
(format =            multispec) Extracted spectra format
(referen=                     ) List of aperture reference images
(profile=                     ) List of aperture profile images

(interac=                  yes) Run task interactively?
(find   =                  yes) Find apertures?
(recente=                  yes) Recenter apertures?
(resize =                   no) Resize apertures?
(edit   =                  yes) Edit apertures?
(trace  =                  yes) Trace apertures?
(fittrac=                  yes) Fit the traced points interactively?
(extract=                  yes) Extract spectra?
(extras =                  yes) Extract sky, sigma, etc.?
(review =                  yes) Review extractions?

(line   =                  120) Dispersion line
(nsum   =                   10) Number of dispersion lines to sum or median

                                # DEFAULT APERTURE PARAMETERS

(lower  =                  -8.) Lower aperture limit relative to center
(upper  =                   8.) Upper aperture limit relative to center
(apidtab=                     ) Aperture ID table (optional)

                                # DEFAULT BACKGROUND PARAMETERS

(b_funct=            chebyshev) Background function
(b_order=                    1) Background function order
(b_sampl=        -119:-6,6:819) Background sample regions
(b_naver=                  -10) Background average or median
(b_niter=                    0) Background rejection iterations
(b_low_r=                   3.) Background lower rejection sigma
(b_high_=                   3.) Background upper rejection sigma
(b_grow =                   0.) Background rejection growing radius

                                # APERTURE CENTERING PARAMETERS

(width  =                   5.) Profile centering width
(radius =                  10.) Profile centering radius
(thresho=                   0.) Detection threshold for profile centering

                                # AUTOMATIC FINDING AND ORDERING PARAMETERS

nfind   =                    1  Number of apertures to be found automatically
(minsep =                   5.) Minimum separation between spectra
(maxsep =                1000.) Maximum separation between spectra
(order  =           increasing) Order of apertures

                                # RECENTERING PARAMETERS

(aprecen=                     ) Apertures for recentering calculation
(npeaks =                INDEF) Select brightest peaks
(shift  =                  yes) Use average shift instead of recentering?

                                # RESIZING PARAMETERS

(llimit =                INDEF) Lower aperture limit relative to center
(ulimit =                INDEF) Upper aperture limit relative to center
(ylevel =                  0.1) Fraction of peak or intensity for automatic widt
(peak   =                  yes) Is ylevel a fraction of the peak?
(bkg    =                  yes) Subtract background in automatic width?
(r_grow =                   0.) Grow limits by this factor
(avglimi=                   no) Average limits over all apertures?

                                # TRACING PARAMETERS

(t_nsum =                   10) Number of dispersion lines to sum
(t_step =                   10) Tracing step
(t_nlost=                    3) Number of consecutive times profile is lost befo
(t_funct=             legendre) Trace fitting function
(t_order=                    2) Trace fitting function order
(t_sampl=                    *) Trace sample regions
(t_naver=                    1) Trace average or median
(t_niter=                    1) Trace rejection iterations
(t_low_r=                   3.) Trace lower rejection sigma
(t_high_=                   3.) Trace upper rejection sigma
(t_grow =                   0.) Trace rejection growing radius

                                # EXTRACTION PARAMETERS

(backgro=                  fit) Background to subtract
(skybox =                    1) Box car smoothing length for sky
(weights=                 none) Extraction weights (none|variance)
(pfit   =                fit1d) Profile fitting type (fit1d|fit2d)
(clean  =                   no) Detect and replace bad pixels?
(saturat=                INDEF) Saturation level
(readnoi=                   0.) Read out noise sigma (photons)
(gain   =                   1.) Photon gain (photons/data number)
(lsigma =                   4.) Lower rejection threshold
(usigma =                   4.) Upper rejection threshold
(nsubaps=                    1) Number of subapertures per aperture
(mode   =                   ql)
Reasons for certain values:
(resize = no) Resize apertures?
We don't want to use an aperture which is set by the drop in the spatial profile to sink to some fractional value of the peak value.
(line = 120) Dispersion line
(nsum = 10) Number of dispersion lines to sum or median
Dispersion line is the central line where the spectrum roughly runs through. The number of lines to sum or median is around the value where you still have a lot of flux in the spectrum. Is around 10 here.
(lower = -8.) Lower aperture limit relative to center
(upper = 8.) Upper aperture limit relative to center
This are the lower and upper limit on the aperture relative to the center. I.e. all the flux are roughly contained in here.
(b_sampl= -119:-6,6:819) Background sample regions (b_naver= -10) Background average or median
The lines relative to the central dispersion line where the backround resides. Make sure that there is no dependence on the spatial direction of the background, otherwise this goes horrible wrong in the end!!! b_naver is set to a number so there are several points to make the background from.
(t_nsum = 10) Number of dispersion lines to sum
(t_step = 10) Tracing step
t_nsum is roughly the number of lines in the aperture sum (nsum). t_step is a nice number around 10 (depending on the length of your spectrum in pixels.
That's it. Now run the stuff!

Anwer positively on the question Find apertures for stdstar01_1? (yes):.
Number of apertures to be found automatically (1): is indeed just 1.
Edit apertures for stdstar01_1? (yes): again anwer positively.
A screen pops-up (see on the right). It might happen that the computer chose the wrong aperture (as is the case now). Delete it by pressing 'd' on the aperture. Create a new aperture on the spectrum by pressing 'n'. Finish with 'q'.
Then indeed trace apertures for the image and fit it interactively.
Usually you need a 3rd order Chebyshev to fit the trace. Apply this by typing in the pop-up: :funct cheb<enter> :order 3<enter>. Check the fit with 'f' and the residuals with 'j'. They are in this case very very small (~0.01). Again, exit with 'q'.
Then the result need to be written into a database. If you have previous solutions, please delete the directory database before accepting. Then extract the spectra for the image and review it.
Before proceeding, first give the settings for the onedspec package of IRAF (if you haven't done this before). Set in this case the observatory to ESO and the standard star directory to the Bessell spectra:
PACKAGE = noao
   TASK = onedspec

(observa=              paranal) Observatory for data
(caldir =    onedstds$bessell/) Standard star calibration directory
(interp =                poly5) Interpolation type
(dispaxi=                    1) Image axis for 2D/3D images
(nsum   =                    1) Number of lines/columns to sum for 2D/3D images
(records=                     ) Record number extensions

(version= ONEDSPEC: January 1996)
(mode   =                   ql)
($nargs =                    0)
The next step is to extinction correct the spectrum. Do this using calibrate.
PACKAGE = onedspec
   TASK = calibrate

input   =               std.ms  Input spectra to calibrate
output  =            std.ms.ec  Output calibrated spectra
(extinct=                  yes) Apply extinction correction?
(flux   =                   no) Apply flux calibration?
(extinct= onedstds$ctioextinct.dat) Extinction file
(observa=                  eso) Observatory of observation
(ignorea=                   no) Ignore aperture numbers in flux calibration?
(sensiti=                     ) Image root name for sensitivity spectra
(fnu    =                   no) Create spectra having units of FNU?
airmass =                  1.1  Airmass
exptime =                  50.  Exposure time (seconds)
(mode   =                   ql)
Apply the standard star to the spectrum. If the standard star is not available on the system, you can install it locally by creating a file called standards.men, which contains the following:
Standard stars in .:

l7379
If a Bessell spectrum from his site is used, then you can use this Perl-script to convert it to an IRAF readable file. The output file should be the starname mentioned in the above standards.men file and have the extension .dat. To get it to work, put in the standard script below for the option (caldir = ./).
PACKAGE = onedspec
   TASK = standard

input   =            std.ms.ec  Input image file root name
output  =        standard_star  Output flux file (used by SENSFUNC)
(samesta=                  yes) Same star in all apertures?
(beam_sw=                   no) Beam switch spectra?
(apertur=                     ) Aperture selection list
(bandwid=                INDEF) Bandpass widths
(bandsep=                INDEF) Bandpass separation
(fnuzero=  3.6800000000000E-20) Absolute flux zero point
(extinct= onedstds$ctioextinct.dat) Extinction file
(caldir =    onedstds$bessell/) Directory containing calibration data
(observa=       )._observatory) Observatory for data
(interac=                  yes) Graphic interaction to define new bandpasses
(graphic=             stdgraph) Graphics output device
(cursor =                     ) Graphics cursor input
star_nam=                l2415  Star name in calibration list
airmass =                  1.1  Airmass
exptime =              50.0056  Exposure time (seconds)
mag     =                       Magnitude of star
magband =                       Magnitude type
teff    =                       Effective temperature or spectral type
answer  =                  yes  (no|yes|NO|YES|NO!|YES!)
(mode   =                   ql)
and derive the sensitivity function using sensfunc.
There are telluric bands, which cause the fit to go wrong. These bands are at 6800A, 7600A and 9300A. Only the latter is in our spectrum. You can delete them with 'd'.
PACKAGE = onedspec
   TASK = sensfunc

standard=        standard_star  Input standard star data file (from STANDARD)
sensitiv=             sens_fie  Output root sensitivity function imagename
(apertur=                     ) Aperture selection list
(ignorea=                  yes) Ignore apertures and make one sensitivity functi
(logfile=              logfile) Output log for statistics information
(extinct=                     ) Extinction file
(newexti= onedstds$ctioextinct.dat) Output revised extinction file
(observa=       )_.observatory) Observatory of data
(functio=             legendre) Fitting function
(order  =                    5) Order of fit
(interac=                  yes) Determine sensitivity function interactively?
(graphs =                   sr) Graphs per frame
(marks  =       plus cross box) Data mark types (marks deleted added)
(colors =              2 1 3 4) Colors (lines marks deleted added)
(cursor =                     ) Graphics cursor input
(device =             stdgraph) Graphics output device
answer  =                  yes  (no|yes|NO|YES)
Now you have the sensitivity function. KEEP IT WELL STORED!!!