Overview#

The Goodman Data Reduction Pipeline - The Goodman Pipeline - is a Python-based package for producing science-ready data from both spectroscopic and imaging observations. The goal of The Goodman Pipeline is to provide SOAR users with an easy to use, very well documented software for reducing data obtained with the Goodman High Throughput Spectrograph. For spectroscopic data, the pipeline produces wavelength-calibrated, 1-D spectra, while for imaging data it provides calibrated images with astrometric solutions and photometric measurements.

The pipeline is available for local installation. The Goodman Spectroscopic Pipeline project is hosted at GitHub at it’s GitHub Repository. Instructions for running the software are provided in the General Guidelines section of this guide and installation instructions are in Install.

Currently the pipeline is separated into several main components. The initial processing is done by redccd, which does the following processes:

  • Identifies calibrations and science frames.

  • Create master bias.

  • Creates master flats and normalizes it.

  • Apply overscan correction.

  • Trims the image.

  • For spectroscopic data find slit edges and trims again.

  • Applies bias correction.

  • Applies flat correction.

  • Applies cosmic ray removal.

The spectroscopic processing is done by redspec and carries out the following steps:

  • Identifies point-source targets.

  • Traces the spectra.

  • Extracts the spectra.

  • Estimates and subtract background.

  • Saves extracted (1D) spectra, without wavelength calibration.

  • Finds the wavelength solution.

  • Linearizes data (resample)

  • Writes the wavelength solution to FITS header

  • Creates a new file for the wavelength-calibrated 1D spectrum

The astrometric processing is done by redastrometry and carries out the following steps:

  • Detects sources in the image using configurable parameters.

  • Creates masks based on flat fields or default circular masks.

  • Uses offline Astrometry.net software for plate solving with local index files.

  • Determines pixel scale and world coordinate system (WCS) using SIP projections.

  • Writes astrometric solution to FITS header.

  • Creates a new file with WCS information (_wcs.fits).

The photometric processing is done by redphotometry and carries out the following steps:

  • Uses astrometrically calibrated images as input.

  • Performs aperture photometry on detected sources.

  • Cross-matches sources with Gaia catalog.

  • Applies photometric calibration using Gaia reference stars.

  • Provides magnitude measurements and uncertainties.

  • Supports configurable aperture sizes and detection parameters.

  • Generates diagnostic plots and photometric analysis.