EUCALYPTUS DATA REDUCTION MANUAL

November 14, 2003

(Advanced users: look for IFU specific instructions searching for ***IFU***)

SOAR_IFU PACKAGE INSTALLATION INSTRUCTIONS

The SOAR_IFU package runs on the IRAF software (PC-IRAF V2.12.1) installed on the Linux RedHat platform (RedHat 7.2). You will create a new login.cl file and a new uparm directory to run the SOAR_IFU package: in the home directory of the package, type mkiraf.

Set a few environment variables in your profile (.tcshrc):

setenv SOAR_IFU the_home_of_the_package

setenv ROOTSYS $SOAR_IFU

setenv LD_LIBRARY_PATH ${LD_LIBRARY_PATH}:$ {SOAR_IFU}/lib

DATA REDUCTION PROCEDURE

First combine all your bias frames with ZEROCOMBINE. To do this, create a list with all of your bias frames. For instance, if you call your bias frames bias????.fits, type:

cl > files bias*.fits > biaslist

The file biaslist will look like this:

cl > head biaslist

bias0001.fits bias0002.fits bias0003.fits bias0004.fits bias0005.fits bias0006.fits bias0007.fits bias0008.fits bias0009.fits bias0010.fits bias0011.fits bias0012.fits

Now, to combine all bias frames listed in biaslist, use ZEROCOMBINE with the following parameters:

cl > epar zerocomb

input = "@biaslist" List of zero level images to combine

(output = "Zero") Output zero level name

(combine = äverage") Type of combine operation

(reject = ävsigclip") Type of rejection

(ccdtype = "") CCD image type to combine

(process = no) Process images before combining?

(delete = no) Delete input images after combining?

(clobber = no) Clobber existing output image?

(scale = "none") Image scaling

(statsec = "") Image section for computing statistics

(nlow = 0) minmax: Number of low pixels to reject

(nhigh = 1) minmax: Number of high pixels to reject

(nkeep = 1) Minimum to keep (pos) or maximum to reject

(mclip = yes) Use median in sigma clipping algorithms?

(lsigma = 3.) Lower sigma clipping factor

(hsigma = 3.) Upper sigma clipping factor

(rdnoise = "0.") ccdclip: CCD readout noise (electrons)

(gain = "1.") ccdclip: CCD gain (electrons/DN)

(snoise = "0.") ccdclip: Sensitivity noise (fraction)

(pclip = -0.5) pclip: Percentile clipping parameter

(blank = 0.) Value if there are no pixels

(mode = "ql")

(for a detailed discussion on what are the best parameters, read Ä Guide to CCD data reductions" by Phil Massey - http://iraf.noao.edu)

You will need to make a list for each type of frames you took over the night. Flats, SkyFlats, NeAr arcs, whatever. Create a list for each type in the same way as you did for the biases:
biaslist - list of all bias frames
dirflatlist - list of all direct flats (see below)
objlist - list of all object frames
domeflatlist - list of all dome flats
masklist - list of all mask spectra
neonlist - list of all neon spectra

Now you need to subtract the bias frames from all your other frames. We do this by using CCDPROC (load NOAO, IMRED, CCDRED to get access to CCDPROC). Then, run CCDPROC with the following parameters:

cl > epar ccdproc

images = "@dirflatlist,@objlist,@domeflatlist,@masklist,@neonlist"

(output = "") List of output CCD images

(ccdtype = " ") CCD image type to correct

(max_cache = 0) Maximum image caching memory (in Mbytes)

(noproc = no) List processing steps only?

(fixpix = no) Fix bad CCD lines and columns?

(overscan = yes) Apply overscan strip correction?

(trim = yes) Trim the image?

(zerocor = yes) Apply zero level correction?

(darkcor = no) Apply dark count correction?

(flatcor = no) Apply flat field correction?

(illumcor = no) Apply illumination correction?

(fringecor = no) Apply fringe correction?

(readcor = no) Convert zero level image to readout correction?

(scancor = no) Convert flat field image to scan correction?

(readaxis = "line") Read out axis (column|line)

(fixfile = "") File describing the bad lines and columns

(biassec = "[1:50,50:2850]") Overscan strip image section

(trimsec = "[55:2095,50:2850]") Trim data section

(zero = "Zero") Zero level calibration image

(dark = "Dark") Dark count calibration image

(flat = "CorrDirFlat") Flat field images

(illum = "") Illumination correction images

(fringe = "") Fringe correction images

(minreplace = 1.) Minimum flat field value

(scantype = shortscan") Scan type (shortscan|longscan)

(nscan = 1) Number of short scan lines

(interactive = no) Fit overscan interactively?

(function = "legendre") Fitting function

(order = 1) Number of polynomial terms or spline pieces

(sample = "*") Sample points to fit

(naverage = 1) Number of sample points to combine

(niterate = 1) Number of rejection iterations

(low_reject = 3.) Low sigma rejection factor

(high_reject = 3.) High sigma rejection factor

(grow = 0.) Rejection growing radius

(mode = "ql")

(***IFU***) Now that you have subtracted the bias from all your other frames you can combine your direct flats. We call direct flats those flats taken illuminating the ccd directly, without passing the light through the fibers. Combine the direct flats using FLATCOMBINE with the following parameters:

cl > epar flatcombine

input = "@dirflatlist" List of flat field images to combine

(output = "DirFlat") Output flat field root name

(combine = "average") Type of combine operation

(reject = "avsigclip") Type of rejection

(ccdtype = "") CCD image type to combine

(process = no) Process images before combining?

(subsets = no) Combine images by subset parameter?

(delete = no) Delete input images after combining?

(clobber = no) Clobber existing output image?

(scale = "mode") Image scaling

(statsec = "") Image section for computing statistics

(nlow = 0) minmax: Number of low pixels to rejec

(nhigh = 1) 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 = 3.) Lower sigma clipping factor

(hsigma = 3.) Upper sigma clipping factor

(rdnoise = "0.") ccdclip: CCD readout noise (electrons)

(gain = "1.") ccdclip: CCD gain (electrons/DN)

(snoise = "0.") ccdclip: Sensitivity noise (fraction)

(pclip = -0.5) pclip: Percentile clipping parameter

(blank = 1.) Value if there are no pixels

(mode = "q")

The direct flat does not provide an uniform illumination of your chip, large scale variation will be visible and you do not want to divide your other frames by this flat field yet. Remove any large scale variation by using IMSURFIT or MKILLUMFLAT. This new image will have the information we need at this point: the pixel-to-pixel sensitivity variations. (If using IMSURFIT, do only step a). If using MKILLUMFLAT, use only step b). You don't need to do both.)

a) IMSURFIT will fit a 2D polynomial to your flat field images and write out a new image with the ratio of your flat field to the fit. The IMSURFIT parameters look like this:

cl > epar imsurfit

input = "DirFlat" Input images to be fit

output = "CorrDirFlat" Output images

xorder = 3 Order of function in x

yorder = 3 Order of function in y

(type_output = "response") Type of output

(function = ßpline3") Function to be fit

(cross_terms = yes) Include cross-terms for polynomials?

(xmedian = 1) X length of median box

(ymedian = 1) Y length of median box

(median_perce = 50.) Min. fraction of pixels in median box

(lower = 0.) Lower limit for residuals

(upper = 0.) Upper limit for residuals

(ngrow = 0) Radius of region growing circle

(niter = 0) Maximum number of rejection cycles

(regions = "all") Good regions

(rows = "*") Rows to be fit

(columns = "*") Columns to be fit

(border = "50") Width of border to be fit

(sections = ) File name for sections list

(circle = ) Circle specifications

(div_min = INDEF)ut Division minimum for response outp

(mode = "ql")

Then, do the following:

cl > hedit CorrDirFlat CCDMEAN 1 upd+

b) MKILLUMFLAT will smooth the flat field image and overwrite it with the ratio of the original flat field to the smoothed flat:

cl > imcopy DirFlat CorrDirFlat

cl > epar mkillumflat

input = "CorrDirFlat" Input CCD flat field images

output = " " Output images (same as input if none given)

(ccdtype = " ") CCD image type to select

(xboxmin = 5.) Minimum smoothing box size in x at edges

(xboxmax = 0.25) Maximum smoothing box size in x

(yboxmin = 5.) Minimum smoothing box size in y at edges

(yboxmax = 0.25) Maximum smoothing box size in y

(clip = yes) Clip input pixels?

(lowsigma = 2.5) Low clipping sigma

(highsigma = 2.5) High clipping sigma

(divbyzero = 1.) Result for division by zero

(ccdproc = "") CCD processing parameters

(mode = "ql")

Next you must divide all the remaining frames by the ``corrected`` direct flat. You can do this using CCDPROC again. The parameters will be:

cl > epar ccdproc

images = "@domeflatlist,@masklist,@neonlist,@objlist"

(output = "") List of output CCD images

(ccdtype = " ") CCD image type to correct

(max_cache = 0) Maximum image caching memory (in Mbytes)

(noproc = no) List processing steps only?

(fixpix = no) Fix bad CCD lines and columns?

(overscan = 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?

(illumcor = no) Apply illumination correction?

(fringecor = no) Apply fringe correction?

(readcor = no) Convert zero level image to readout correction?

(scancor = no) Convert flat field image to scan correction?

(readaxis = "line") Read out axis (column|line)

(fixfile = "") File describing the bad lines and columns

(biassec = "[1:50,50:2850]") Overscan strip image section

(trimsec = "[55:2095,50:2850]") Trim data section

(zero = "Zero") Zero level calibration image

(dark = "Dark") Dark count calibration image

(flat = "CorrDirFlat") Flat field images

(illum = "") Illumination correction images

(fringe = "") Fringe correction images

(minreplace = 1.) Minimum flat field value

(scantype = "shortscan") Scan type (shortscan|longscan)

(nscan = 1) Number of short scan lines

(interactive = no) Fit overscan interactively?

(function = "legendre") Fitting function

(order = 1) Number of polynomial terms or spline pieces

(sample = "*") Sample points to fit

(naverage = 1) Number of sample points to combine

(niterate = 1) Number of rejection iterations

(low_reject = 3.) Low sigma rejection factor

(high_reject = 3.) High sigma rejection factor

(grow = 0.) Rejection growing radius

(mode = "ql")

(***IFU***) By now we are ready to start working on the mask spectra. First we must combine all the spectra taken at each mask position. Use IMCOMBINE with the following for each mask position:

cl > epar imcombine

input = "mask-00-00-000?.fits" List of images to combine

output = "mask-00-00.fits" List of output images

(headers = "") List of header files (optional)

(bpmasks = "") List of bad pixel masks (optional)

(rejmasks = "") List of rejection masks (optional)

(nrejmasks = "") List of number rejected masks (optional)

(expmasks = "") List of exposure masks (optional)

(sigmas = "") List of sigma images (optional)

(logfile = "STDOUT") Log file

(combine = "average") Type of combine operation

(reject = "minmax") Type of rejection

(project = no) Project highest dimension of input images?

(outtype = "real") Output image pixel datatype

(outlimits = "") Output limits (x1 x2 y1 y2 ...)

(offsets = "none") Input image offsets

(masktype = "none") Mask type

(maskvalue = 0.) Mask value

(blank = 0.) Value if there are no pixels

(scale = "none") Image scaling

(zero = "none") Image zero point offset

(weight = "none") Image weights

(statsec = "") Image section for computing statistics

(expname = "") Image header exposure time keyword

(lthreshold = INDEF) Lower threshold

(hthreshold = INDEF) Upper threshold

(nlow = 0) minmax: Number of low pixels to reject

(nhigh = 1) 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 = 3.) Lower sigma clipping factor

(hsigma = 3.) Upper sigma clipping factor

(rdnoise = "0.") ccdclip: CCD readout noise (electrons)

(gain = "1.") ccdclip: CCD gain (electrons/DN)

(snoise = "0.") ccdclip: Sensitivity noise (fraction)

(sigscale = 0.1) Tolerance for sigma clipping scaling correction

(pclip = -0.5) pclip: Percentile clipping parameter

(grow = 0.) Radius (pixels) for neighbor rejection

(mode = "ql")

This is IMCOMBINE's output:

combine = average, scale = none, zero = none, weight = none, reject = minmax, nlow = 0, nhigh = 1, blank = 0.

Images mask-00-00-0001.fits mask-00-00-0002.fits mask-00-00-0003.fits

Output image = mask-00-00.fits, ncombine = 3

(***IFU***) Verify if APSCATTER, APDEF and APFIND are set as the following:

cl > epar apscat

input = " " List of input images to subtract scattered light

output = " " List of output corrected images

(apertures = "") Apertures

(scatter = "") List of scattered light images (optional)

(references = "") List of aperture reference images

(interactive = yes) Run task interactively?

(find = yes) Find apertures?

(recenter = no) Recenter apertures?

(resize = no) Resize apertures?

(edit = yes) Edit apertures?

(trace = yes) Trace apertures?

(fittrace = yes) Fit the traced points interactively?

(subtract = yes) Sbutract scattered light?

(smooth = no) Smooth scattered light along the dispersion?

(fitscatter = yes) Fit scattered light interactively?

(fitsmooth = no) Smooth the scattered light interactively?

(line = 1) Dispersion line

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

(buffer = 1.) Buffer distance from apertures

(apscat1 = "") Fitting parameters across the dispersion

(apscat2 = "") Fitting parameters along the dispersion

(mode = "ql")

cl > epar apdef

(lower = -1.5)r Lower aperture limit relative to cente

(upper = 1.5) Upper aperture limit relative to center

(apidtable = "") Aperture ID table

(b_function = "chebyshev") Background function

(b_order = 1) Background function order

(b_sample = "-10:-6,6:10") Background sample regions

(b_naverage = -3) Background average or median

(b_niterate = 0) Background rejection iterations

(b_low_reject = 3.) Background lower rejection sigma

(b_high_rejec = 3.) Background upper rejection sigma

(b_grow = 0.) Background rejection growing radius

(mode = "ql")

cl > epar apfind

input = " " List of input images

(apertures = "") Apertures

(references = "") Reference images

(interactive = yes) Run task interactively?

(find = yes) Find apertures?

(recenter = no) Recenter apertures?

(resize = no) Resize apertures?

(edit = yes) Edit apertures?

(line = INDEF) Dispersion line

(nsum = 1) Number of dispersion lines to sum or median

nfind = 102 Number of apertures to be found automatically

(minsep = 5.) Minimum separation between spectra

(maxsep = 1000.) Maximum separation between spectra

(order = ïncreasing") Order of apertures

(mode = "ql")

MASK will iterate over the masks, finding and tracing the apertures and subtracting scattered light:

cl > epar mask

nome = "mask" Base name for files

ver = 1 Number of vertical mask positions

hor = 5 Number of horizontal mask positions

ext = "fits" Filetype of images

colavg = 5 Number of columns to average during fits

colstep = 1 Number of columns to jump from one fit to the

apscatter = ""

lista = ""

(mode = "ql")

Type :go and press Enter:

mask-00-00 Find apertures for mask-00-00? (yes):

Press Enter:

Number of apertures to be found automatically (102):

Press Enter again:

Edit apertures for mask-00-00? (yes):

Press Enter. A graphic window should now appear. Enlarge it and position the mouse near the left edge (see figure mask1.png). Then type wxwx to zoom in the X direction (see figure mask2.png).

Verify the correspondence between the peaks and the numbered markings on top (the numbers are not important, only the positions). Type wr to see the next peaks. If there is an extra mark (see figure mask3.png), position the mouse over it and press d. If, on the other hand, a mark is missing (see figure mask4.png), position the mouse over it and press m.

When finished, press q.

Trace apertures for mask-00-00? (yes):

Press Enter:

Fit traced positions for mask-00-00 interactively? (yes):

Type NO (all uppercase) and press Enter:

Write apertures for mask-00-00 to database? (yes):

Press Enter:

Subtract scattered light in mask-00-00? (yes):

Press Enter again:

Fit scattered light interactively? (yes):

Type NO (all uppercase) and press Enter. This will take a while. Pay attention because the next question will appear on the text window, not on the graphic window:

mask-00-01 Find apertures for mask-00-01? (yes):

Repeat the procedure above for the remaining masks.

To verify the previous step, do:

cl > apedit mask
Edit apertures for mask? (yes):

Press Enter. In the graphic window, position the mouse near the left edge then type wxwxwxwx to zoom in the X direction and wr to see the next peaks (see figure mask5.png).

Press q.

Write apertures for mask to database? (yes):

Type NO (all uppercase) and press Enter. Another validation step is to extract and reconstruct the images of the masks with the IFU task:

cl > epar ifu

image = "mask-00-00" Input frame

(trref = "CorrDomeFlat.ql") Fiber transmission calibration

(imref = "Neon.ql") Calibration arc reference

(apref = "mask") Fiber apertures reference

(ccdcor = no) Run ccdproc on input images ? (yes/no)

(extract = yes) Extract fibers ? (yes/no)

(ql = yes) Quick look ? (yes/no)

(tcor = n Transmission correction? (yes/no)

(dcor = no)) Dispersion correction? (yes/no

(gencube = no) Generate datacube ? (yes/no)

(ldisplay = yes) Display reconstructed image ? (yes/no)

(ccdproc = "") ccdproc parameters (use :e to edit)

(dispcor = "") dispcor parameters (use :e to edit)

(mode = "ql")

Type :go and press Enter. After a while, the mask pattern will appear. This could be done also with the other masks. Press q to quit.

CALFIB will do a non-linear gaussian fit to find the center and width of the fibers at each dispersion. When using quick-look mode, this step is not necessary:

cl > epar calfib

nome = "mask" Base name for files

ver = 1 Number of vertical mask positions

hor = 5 Number of horizontal mask positions

ext = "fits" Filetype of images

colavg = 5 Number of columns to average during fits

colstep = 1 Number of columns to jump from one fit to the n

lista = ""

(mode = "ql")

Type :go and press Enter.

Combine the dome flats to create the transmission correction frames:

cl > epar flatcombine

input = "@domeflatlist" List of flat field images to combine

(output = "DomeFlat") Output flat field root name

(combine = "average") Type of combine operation

(reject = ävsigclip") Type of rejection

(ccdtype = "") CCD image type to combine

(process = no) Process images before combining?

(subsets = no) Combine images by subset parameter?

(delete = no) Delete input images after combining?

(clobber = no) Clobber existing output image?

(scale = "mode") Image scaling

(statsec = "") Image section for computing statistics

(nlow = 0) minmax: Number of low pixels to reject

(nhih = 1) 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 = 3.) Lower sigma clipping factor

(hsigma = 3.) Upper sigma clipping factor

(rdnoise = "0.") ccdclip: CCD readout noise (electrons)

(gain = "1.") ccdclip: CCD gain (electrons/DN)

(snoise = "0.") ccdclip: Sensitivity noise (fraction)

(pclip = -0.5) pclip: Percentile clipping parameter

(blank = 1.) Value if there are no pixels

(mode = "ql")

(***IFU***) Extract the spectra of all apertures from the DomeFlat frames. They will be used later to do the transmission corrections. Now we can use the IFU task in the SOAR-IFU package. Use it with the following parameters:

cl > epar ifu

image = "DomeFlat" Input CCD image

(trref = "") Fiber transmission calibration - unmasked flat

(imref = "") Calibration arc reference

(apref = "mask") Fiber apertures reference

(ccdcor = no) Run ccdproc on input images ? (yes/no)

(extract = yes) Extract fibers ? (yes/no)

(ql = yes) Quick look ? (yes/no)

(tcor = no) Transmission correction? (yes/no)

(dcor = no) Dispersion correction? (yes/no)

(gencube = no) Generate datacube ? (yes/no)

(ldisplay = yes) Display reconstructed image ? (yes/no)

(ccdproc = "") ccdproc parameters (use :e to edit)

(dispcor = "") dispcor parameters (use :e to edit)

(mode = "ql")

(***IFU***) We do not want to use the spectral information of the white lamp flat, because the lamp is not spectrally flat. To flatten the spectral response, first integrate the light on each fiber over the whole spectra using BLKAVG. Then, replicate the result over the dispersion axis with BLKREP:

cl > imhead DomeFlat.ql
DomeFlat.ql[2041,510][real]: Flat Cup
cl > blkavg DomeFlat.ql CorrDomeFlat.ql 2041 1
cl > blkrep CorrDomeFlat.ql CorrDomeFlat.ql 2041 1
cl > imhead CorrDomeFlat.ql
CorrDomeFlat.ql[2041,510][real]: Flat Cup
cl > imstat DomeFlat.ql,CorrDomeFlat.ql
# IMAGE NPIX MEAN STDDEV MIN MAX DomeFlat.ql 1040910 38886. 7808. 2509. 61462. CorrDomeFlat.ql 1040910 38886. 6178. 14315. 56706.

Combine your neon frames with IMCOMBINE.

(***IFU***) Extract the neon spectra for all fibers using the task IFU again:

cl > epar ifu

image = "Neon" Input CCD image

(trref = "CorrDomeFlat.ql") Fiber transmission calibration

(imref = "Neon.ql") Calibration arc reference

(apref = "mask") Fiber apertures reference

(ccdcor = no) Run ccdproc on input images ? (yes/no)

(extract = yes) Extract fibers ? (yes/no)

(ql = yes) Quick look ? (yes/no)

(tcor = no) Transmission correction? (yes/no)

(dcor = no) Dispersion correction? (yes/no)

(gencube = no) Generate datacube ? (yes/no)

(ldisplay = yes) Display reconstructed image ? (yes/no)

(ccdproc = "") ccdproc parameters (use :e to edit)

(dispcor = "") dispcor parameters (use :e to edit)

(mode = "ql")

Find the wavelength solution to one of the apertures in the neon frames using IDENTIFY:

cl > epar identify

images = "Neon.ql" Images containing features to be identified

(section = "line 1") Section to apply to two dimensional images

(database = "database") Database in which to record feature data

(coordlist = "linelists$idhenear.dat") User coordinate list

(units = "") Coordinate units

(nsum = "10") Number of lines/columns/bands to sum in 2D imag

(match = -3.) Coordinate list matching limit

(maxfeatures = 50) Maximum number of features for automatic identi

(zwidth = 100.) Zoom graph width in user units

(ftype = ëmission") Feature type

(fwidth = 7.) Feature width in pixels

(cradius = 5.) Centering radius in pixels

(threshold = 0.) Feature threshold for centering

(minsep = 2.) Minimum pixel separation

(function = "spline3") Coordinate function

(order = 3) Order of coordinate function

(sample = "*") Coordinate sample regions

(niterate = 0) Rejection iterations

(low_reject = 3.) Lower rejection sigma

(high_reject = 3.) Upper rejection sigma

(grow = 0.) Rejection growing radius

(autowrite = no) Automatically write to database

(graphics = ßtdgraph") Graphics output device

(cursor = "") Graphics cursor input

crval = "6450" Approximate coordinate (at reference pixel)

cdelt = ".3" Approximate dispersion

(aidpars = "") Automatic identification algorithm parameters

(mode = "ql")

Now use REIDENTIFY and let it find the solution to all other apertures:

cl > epar reident

reference = "Neon.ql" Reference image

images = "Neon.ql" Images to be reidentified

(interactive = ÿes") Interactive fitting?

(section = "line 1") Section to apply to two dimensional images

(newaps = no) Reidentify apertures in images not in reference

(override = no) Override previous solutions?

(refit = yes) Refit coordinate function?

(trace = yes) Trace reference image?

(step = "10") Step in lines/columns/bands for tracing an imag

(nsum = "1") Number of lines/columns/bands to sum

(shift = ÏNDEF") Shift to add to reference features (INDEF to se

(search = INDEF) Search radius

(nlost = 3) Maximum number of features which may be lost

(cradius = 7.) Centering radius

(threshold = 100.) Feature threshold for centering

(addfeatures = no) Add features from a line list?

(coordlist = "linelists$idhenear.dat") User coordinate list

(match = -3.) Coordinate list matching limit

(maxfeatures = 50) Maximum number of features for automatic identi

(minsep = 2.) Minimum pixel separation

(database = "database") Database

(logfiles = "Neon.log") List of log files

(plotfile = "") Plot file for residuals

(verbose = no) Verbose output?

(graphics = "stdgraph") Graphics output device

(cursor = "") Graphics cursor input

answer = "YES" Fit dispersion function interactively?

crval = Approximate coordinate (at reference pixel)

cdelt = Approximate dispersion

(aidpars = "") Automatic identification algorithm parameters

(mode = "ql")

(***IFU***) To validate the previous step, do the dispersion correction on the extracted Neon using IFU:

cl > epar ifu

image = "Neon.ql" nput CCD image

(trref = "CorrDomeFlat.ql") Fiber transmission calibration

(imref = "Neon.ql") Calibration arc reference

(apref = "mask") Fiber apertures reference

(ccdcor = no) Run ccdproc on input images ? (yes/no)

(extract = no) Extract fibers ? (yes/no)

(ql = yes) Quick look ? (yes/no)

(tcor = no) Transmission correction? (yes/no)

(dcor = yes) Dispersion correction? (yes/no)

(gencube = no) Generate datacube ? (yes/no)

(ldisplay = yes) Display reconstructed image ? (yes/no)

(ccdproc = "") ccdproc parameters (use :e to edit)

(dispcor = "") dispcor parameters (use :e to edit)

(mode = "ql")

Then use DISPLAY on the resulting image (Neon.ql.wl). The vertical lines must now be straight.

(***IFU***) Now, to extract and reconstruct the objects using IFU:

cl > epar ifu

image = "obj0001" Input frame

(trref = "CorrDomeFlat.ql") Fiber transmission calibration

(imref = "Neon.ql") Calibration arc reference

(apref = "mask") Fiber apertures reference

(ccdcor = no) Run ccdproc on input images ? (yes/no)

(extract = yes) Extract fibers ? (yes/no)

(ql = yes) Quick look ? (yes/no)

(tcor = no) Transmission correction? (yes/no)

(dcor = yes) Dispersion correction? (yes/no)

(gencube = no) Generate datacube ? (yes/no)

(ldisplay = yes) Display reconstructed image ? (yes/no)

(ccdproc = "") ccdproc parameters (use :e to edit)

(dispcor = "") dispcor parameters (use :e to edit)

(mode = "ql")

The images generated by IFU in quick-look mode are:

obj0001.ql: Extracted spectra
obj0001.ql.tc: Corrected for fiber transmission
obj0001.ql.tc.wl: Wavelength corrected
obj0001.ql.tc.wl.ldisp: Reconstructed 2D image
obj0001.ql.tc.wl.dc: 3D datacube

For complete reduction, the ql extension is replaced by lin. All reduction steps except extraction are optional, in which cases the correspondent extension (tc,wl,dc,ldisp) will be missing.

(***IFU***) To display an object that was previously extracted, use LDISPLAY:

cl > epar ldisplay

input = "obj0001.ql.tc.wl" Input fiber file

(output = "obj0001.ql.tc.wl.ldisp") Lens array image

(ldispdir = "soar_ifu$conf") Directory for config files

(lconf = "soar_ifu.cfg") File containing lens array geometry

(w1 = INDEF) Starting wavelength

(w2 = INDEF) Ending wavelength

(imagecur = "") Image cursor input

(mode = "ql")

Use the following commands with LDISPLAY:

e - examine the spectrum of the lens under the cursor with SPLOT. Use q to return to LDISPLAY;
w - implements a virtual wavelength filter on the reconstructed image, given the starting and ending wavelengths;
q - exit LDISPLAY.

There is not, at the moment, any task developed to deal with the Eucalyptus 3D datacube. But the user can perform all the usual procedures related to IFUs using simple IRAF tasks. Some hints are presented below.

(***IFU***) To create a white light 2D image, use LDISPLAY:

cl > epar ldisplay

input = "obj0001.ql.tc.wl" Input fiber file

(output = "white0001") Lens array image

(ldispdir = "soar_ifu$conf") Directory for config files

(lconf = "soar_ifu.cfg") File containing lens array geometry

(w1 = INDEF) Starting wavelength

(w2 = INDEF) Ending wavelength

(imagecur = "") Image cursor input

(mode = "ql")

The white light reconstructed image will be displayed. Once you exit LDISPLAY (q) the image will be saved with the name white0001.fits (in this example).

To construct a passband image, change the output parameter in LDISPLAY (otherwise your white light image will be overwritten) and set the wavelength limits (parameters w1 and w2). The images produced by LDISPLAY may be displayed (with the DISPLAY task) and combined (with IMCOMBINE or IMARITH) as usual.

(***IFU***) To examine the spectrum of each individual lens you may use LDISPLAY as cited above (item 21). A simple way to perform arithmetic operations with 2 or more lenses spectra (to sum lenses 204 and 235, for instance) is by using the task SARITH:

cl > epar sarith

input1 = "obj0001.ql.tc.wl[*,204]" List of input spectra

op = "+" Operation

input2 = "obj0001.ql.tc.wl[*,235]" List of input spectra or constants

output = "sum.fits" List of output spectra

(w1 = INDEF) Starting wavelength

(w2 = INDEF) Ending wavelength

(apertures = "")s List of input apertures or columns/line

(bands = "") List of input bands or lines/bands

(beams = "") List of input beams or echelle orders

(apmodulus = 0) Input aperture modulus (0=none)

(reverse = no) Reverse order of operands in binary operation?

(ignoreaps = yes) Ignore second operand aperture numbers?

(format = önedspec") Output spectral format

(renumber = no) Renumber output apertures?

(offset = 0) Output aperture number offset

(clobber = yes) Modify existing output images?

(merge = no) Merge with existing output images?

(rebin = yes) Rebin to exact wavelength region?

(errval = 0.) Arithmetic error replacement value

(verbose = yes) Print operations?

(mode = "ql")

Another way (perhaps more adequate to do operations with a large number of lenses) is by using SCOPY to create one individual archive to each spectrum:

cl > epar scopy

input = "obj0001.ql.tc.wl" List of input spectra

output = "sub" List of output spectra

(w1 = INDEF) Starting wavelength

(w2 = INDEF) Ending wavelength

(apertures = "240-249") List of input apertures or columns/lines

(bands = "") List of input bands or lines/bands

(beams = "") List of beams or echelle orders

(apmodulus = 0) Input aperture modulus (0=none)

(format = "onedspec") Output spectra format

(renumber = no) Renumber output apertures?

(offset = 0) Output aperture number offset

(clobber = no) Modify existing output images?

(merge = no) Merge with existing output images?

(rebin = yes) Rebin to exact wavelength region?

(verbose = yes) Print operations?

(mode = "ql")

This last example will create 10 spectra (named sub.0240.fits to sub.0249.fits). To create spectra for all lenses set the parameter apertures to null. Operations may now be applied to these spectra using SCOMBINE or SARITH.

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