The processing of OM data with SAS is run by the pipeline at the SOC. Users can also process their data at their home institute using SAS. Three processing chains, omichain, omfchain and omgchain are used for image, fast mode data and grisms spectra processing, respectively. The chains are Perl scripts that concatenate the individual SAS tasks so as to go from the input raw data up to the final output results without further interaction. The tasks can also be run one by one having more control on all needed parameters.
In the following pages we describe this processing paying attention to the concepts and functions implemented in the different tasks to accomplish all corrections and calibrations necessary to exploit OM data. A detailed description of the tasks and the parameters controlling their functionality is provided in the SAS on-line documentation and processing threads.
It should be noted that the pipeline does not run the processing chains we describe, but an equivalent concatenation of the same SAS tasks.
The whole processing of image and fast mode data is depicted in figure 44 and figure 45. Figure 46 gives an overview of the spectra data reduction.
In order to process the OM image data successfully, an input dataset is required. Input datasets are not changed during the OM processing with omichain. They are copied to intermediate datasets and keywords. Extensions are added to the FITS data files as needed. Intermediate task products, which are passed from one task to another, are generally not described.
The processing of OM image data can be divided in three parts (see figure 44)
This core of the image processing can be divided as well
As it can be seen in the flow chart of the OM processing chain (figure 44), the OM tracking information for each exposure is treated before and independently from the image data processing. In the following, for each task description, a reference is given to the analysis step in the processing example.