| oscirinfo (September2002) | gemini.oscir | oscirinfo (September2002) |
The tasks are designed to provide a fast nearly "hands-off" reduction as well as the flexibility to optimize the hidden parameters to achieve the best possible results.
The tasks produce logfiles of the performed processing steps. The name of the logfile may be set in each individual task, or at the package level by setting the parameter oscir.logfile.
The tasks may add header keywords to the output images. These header keywords contain information about the performed processing steps and the values of the critical parameters for the tasks that were used.
All data from OSCIR are simple FITS images. The OSCIR package is designed to process the images as simple FITS. It is recommended to use imtype="fits". This is set automatically when loading the GEMINI package.
Dim Name Size 1 X dimension of array 128 2 Y dimension of array 128 3 Chop position Number of chop positions (1 or 2) 4 Savesets Number of savesets per nod position 5 Nod position Number of nod positions (1 or 2) 6 Nod sets Number of nod sets
The file format is much different from a visible or near-infrared FITS file, which usually contains a single 2-D image representing a single readout of the detector. Briefly, the OSCIR detector must be read out at several tens or hundreds of Hz in synchronization with the chopping secondary, so frames are co-added into two hardware buffers (one buffer for each chop position). The buffers are periodically (every 2 sec for most data) written to disk, forming a "Saveset". After several savesets are recorded, the data collection stops while the telescope nods, then resumes. A cycle during which the telescope nods to a new position and then back is called a "Nodset".
This pattern is summarized in the following example where the number of savesets per nod position is 3 and the number of nod sets is 4. With two frames per saveset this results in a total of 48 frames; the IRAF task IMHEAD will report the file dimensions as [128,128,2,3,2,4].
Frame ChopPos Source Saveset NodPos Nodset IRAFimage1 A * 1 1 1 [*,*,1,1,1,1] 2 B [*,*,2,1,1,1] 3 A * 2 [*,*,1,2,1,1] 4 B [*,*,2,2,1,1] 5 A * 3 [*,*,1,3,1,1] 6 B [*,*,2,3,1,1] ---Nod--- 7 A 1 2 [*,*,1,1,2,1] 8 B * [*,*,2,1,2,1] 9 A 2 [*,*,1,2,2,1] 10 B * [*,*,2,2,2,1] 11 A 3 [*,*,1,3,2,1] 12 B * [*,*,2,3,2,1] ---Nod--- 13 A * 1 1 2 [*,*,1,1,1,2] 14 B [*,*,2,1,1,2] 15 A * 2 [*,*,1,2,1,2] 16 B [*,*,2,2,1,2] 17 A * 3 [*,*,1,3,1,2] 18 B [*,*,2,3,1,2] ---Nod--- 19 A 1 2 [*,*,1,1,2,2] 20 B * [*,*,2,1,2,2] 21 A 2 [*,*,1,2,2,2] 22 B * [*,*,2,2,2,2] 23 A 3 [*,*,1,3,2,2] 24 B * [*,*,2,3,2,2] ---Nod--- etc 3 ---Nod--- 36 A * 1 1 4 [*,*,1,1,1,4] 37 B [*,*,2,1,1,4] 39 A * 2 [*,*,1,2,1,4] 40 B [*,*,2,2,1,4] 41 A * 3 [*,*,1,3,1,4] 42 B [*,*,2,3,1,4] ---Nod--- 43 A 1 2 [*,*,1,1,2,4] 44 B * [*,*,2,1,2,4] 45 A 2 [*,*,1,2,2,4] 46 B * [*,*,2,2,2,4] 47 A 3 [*,*,1,3,2,4] 48 B * [*,*,2,3,2,4]
The "IRAFimage" column gives the IRAF notation for accessing the specific frame, e.g. if the example given above is contained in a FITS file "image", the first frame would be accessed as "image[*,*,1,1,1,1]" and the last frame as "image[*,*,2,3,2,4]"
The "Source" column indicates whether the source is in Chop Beam A or B. This changes when the telescope nods. For the first nod position the object is in beam A and the sky is in beam B. For the second nod position the object is in beam B and the sky is in beam A. Thus, for the first nod position the difference beam_A - beam_B will be a sky subtracted image. For the second nod position the difference beam_B - beam_A will be a sky substracted image.
The usual method of reducing the images is to difference the chop pairs (compute [beam_A - beam_B] or [beam_B - beam_A] for each saveset, depending on the nod position), then average these differences to form a final image. The task OREDUCE does this.
Sky flat fields are usually taken without chopping and nodding. For an image containing 8 savesets IMHEAD would report the dimensions [128,128,1,8,1,1], since there is only one chop position, one nod position, and one nod set. The task OFLAT can be used to derive the flat fields. The task OREDUCE can be used to apply the flats after deriving the average of the chop and nod differences.
OVIEW is intended to allow one to quickly view the raw OSCIR frames within an OSCIR data file. By default it will view the 'sig' frames, which are the sum of all of the differenced savesets in a nodset, that is, there is one 'sig' frame per nodset. It is also possible to view the raw 'src' or 'ref' frames or the 'dif' frames from each saveset by setting the 'type' parameter. When viewing sig frames, you may set 'interactive=yes' and the task will start an imexam session with each frame displayed. (In this mode, you must type 'q' before the next frame will display.)
OBACKGROUND is used to analyze the background level in the reference frames and identify bad savesets or nodsets. This task will plot the mean background level in all reference frames and identify saveset and nodset values for any frames outside some sigma of the average mean level (default sigma=4).
OFLAT is used for deriving normalized flat fields for the OSCIR data. The input images are sky flat fields and exposures through polystyrene. OFLAT assumes that the images were taken without chopping and nodding. The output image is the normalized flat field.
OREDUCE is used for deriving the average of the chop and nod differences. The input image is a raw OSCIR data file, the output image is a 2-dimensional image which is the average of the chop and nod differences. The output image may also be flat field corrected. Bad nodsets and savesets can be omitted from the reduction.
For typical reductions the user will need appropriate flat fields (if desired) and on-target science images. The on-target science images will have two chop positions.
1. Use OFLAT to derive normalized flat fields.
2. Use OVIEW to view the sig frames as a quick check for bad frames. Also use OVIEW to view 'src', 'ref' or 'dif' frames as needed.
3. Use OBACKGROUND to analyze the background levels in the reference frames and identify any bad nodsets or savesets to be omitted.
4. Use OREDUCE to derive the chop and nod differences and average these to get a 2-dimensional image. Input bad nodsets or savesets which will be omitted from the co-added frame. OREDUCE can also apply the flat field.
The processed images may be co-added with the task GEMTOOLS.IMCOADD.
Photometry may be derived with any suitable photometry package.