1.1 HOW-TO Calibrations: overview

The calibration part of the Astro-WISE Environment is divided into three major pipelines: a bias pipeline, a flat field pipeline, and a photometric pipeline. All of these are composed of several fine-grained, atomic processing steps known as tasks. In the following sections, these pipelines are discussed. A summary is given of the atomic tasks that make up the various pipelines, and their place therein is described. Also given are a few examples of how the different tasks can be steered through the DPU interface. For the interface and use of every individual task, please read the corresponding HOW-TO.

1.1.1 The atomic tasks and their context

The atomic tasks that make up the calibration pipelines are summarized in Table , together with their role in the system and the identifier under which these are known to the DPU interface.

The sequence of tasks that make up the bias and flat field pipelines is shown in Figure . The sequence of tasks that should be run for the photometric calibration is shown in Figure . In these figures, each one of the individual tasks is represented by one box. The arrows indicate the flow of the pipeline, and the shaded parts show particular (optional) branches therein.

1.1.2 The bias and flatfield pipelines

The bias and flat field pipelines are pretty straightforward: no difficulties or surprises here. Note, however, that after having derived the masterflat, the processing continues in the photometric pipeline (hence the arrow at the end of the line in Fig. ).

1.1.3 The photometric pipeline

The photometric pipeline is more tricky than the bias or flatfield pipeline for two reasons: (1) a piece of the image pipeline must be run to process the photometric standard fields (hence the http://www.astro-wise.org/portal/howtos/man_howto_reduce/man_howto_reduce.shtmlReduce and http://www.astro-wise.org/portal/howtos/man_howto_astrom/man_howto_astrom.shtmlAstrometry boxes in Fig. ), (2) the optional branch of the illumination correction is an iterative loop that in Fig.  actually runs backwards (characterising the illumination variation is more of an interactive process)

1.1.4 Examples of running the atomic tasks with the DPU

Make master biases for all CCDs of OmegaCAM for a certain bias template:

    awe> dpu.run('Bias', instrument='OMEGACAM', template='2014-07-04T10:39:28')

Make a twilightflat for the specified night and filter:

    awe> dpu.run('TwilightFlat', i='OMEGACAM', d='2014-06-29', f='OCAM_r_SDSS')

Make photometric catalogs from a particular standard field exposure:

    awe> dpu.run('Photcat', i='OMEGACAM', raw=['OMEGACAM.2014-04-26T23:55:32.384_32.fits'])

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