Optimizing one’s observing strategy while at the telescope relies on knowing the current observing conditions and the obtained data quality. In particular the latter is not straight forward with current wide-field imagers, such as the WIYN One Degree Imager (ODI), currently consisting of 13 detectors, each of them read out in 64 independent cells.
Here we present a fast data reduction software for ODI, optimized for a first data inspection during acquisition at the the telescope, but capable enough for science-quality data reductions. The pipeline is coded in pure python with minimal additional requirements. It is installed on the ODI observer’s interface and publicly available from the author’s webpage. It performs all basic reduction steps as well as more advanced corrections for pupil-ghost removal, fringe correction and masking of persistent pixels. Additional capabilities include adding an accurate astrometric WCS solution based on the 2MASS reference system as well as photometric zeropoint calibration for frames covered by the SDSS foot-print.
The pipeline makes use of multiple CPU-cores wherever possible, resulting in an execution time of only a few seconds per frame. As such this QuickReduce pipeline offers the ODI observer a convenient way to closely monitor data quality, a necessity to optimize the observing strategy during the night.
Date added: Mon, 21 Oct 13