This directory contains code and documentation for the Green Bank Telescope(GBT) data analysis pipelines.
The GBT Pipeline Project has two main goals.
The first is to generate a quick-look data reduction pipeline for GBT spectroscopy data that is capable of processing at least 80% of all sessions observed with the GBT in "Standard Observing Modes". The quick-look pipeline will operate with minimal user intervention. The pipeline determines the observing mode used for spectroscopic data, calibrates and averages data for each target in the session, fits a spectral baseline, and writes the reduced data into both an sdfits file and a png image. Where appropriate, the pipeline attempts to identify and flag RFI. In cases where complex baselines or extensive RFI are major issues, the observer will always do better to process the data by hand.
The pipeline will eventually generate a set of statistics and in some cases it will provide nominal scientific parameters (for example, fitting extragalactic HI profiles). The purpose of the quick-look pipeline is to provide the community with easy access to GBT data, including data from projects that they were not involved with. The product of this pipeline (i.e. reduced spectra) will be provided to the astronomical community through an NRAO Image Archive web interface.
The second main goal of the GBT Pipeline Project is to provide a set of data processing tools to help observers produce publication-quality data products. These tools will allow observers to tweak parameters in their data reduction steps with a straightforward interface. Users should expect to engage in an iterative process, working with the data and examining the results of their processing several times before achieving the best result. These tools will assist users in making maps from their spectral line mapping observations. They will also be applicable for point-source spectroscopy, allowing users to specify calibration parameters and other relevant parameters to achieve their best product. That product might be either a data cube representing a map, or a spectrum for a single position on the sky. The KFPA pipeline, the initial product of the GBT Pipeline Project, is an example of a tool in this category.
https://safe.nrao.edu/wiki/bin/view/GB/Gbtpipeline/WebHome
Mapping pipeline code is written in Python. Dependencies include getForecastValues, idlToSdfits, Obit, parseltongue and AIPS.
SDFITS files are the required input.
Due to the interaction with weather prediction scripts only available in Green Bank, the code can only be effectively run on a Green Bank network computer.
The spectral pipeline code is written in GBTIDL.
Last modified: 07 August 2013