The High Level Data Reduction Library

ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XXIV(2015)

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摘要
The European Southern Observatory (ESO) provides pipelines to reduce data for most of the instruments at its Very Large telescope (VLT). These pipelines are written as part of the development of VLT instruments, and are used both in the ESO's operational environment and by science users who receive VLT data. All the pipelines are highly specific geared toward instruments. However, experience showed that the independently developed pipelines include significant overlap, duplication and slight variations of similar algorithms. In order to reduce the cost of development, verification and maintenance of ESO pipelines, and at the same time improve the scientific quality of pipelines data products, ESO decided to develop a limited set of versatile high-level scientific functions that are to be used in all future pipelines. The routines are provided by the High-level Data Reduction Library (HDRL). To reach this goal, we first compare several candidate algorithms and verify them during a prototype phase using data sets from several instruments. Once the best algorithm and error model have been chosen, we start a design and implementation phase. The coding of HDRL is done in plain C and using the Common Pipeline Library (CPL) functionality. HDRL adopts consistent function naming conventions and a well defined API to minimise future maintenance costs, implements error propagation, uses pixel quality information, employs OpenMP to take advantage of multi-core processors, and is verified with extensive unit and regression tests. This poster describes the status of the project and the lesson learned during the development of reusable code implementing algorithms of high scientific quality.
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