| Name | goodman-pipeline JSON |
| Version |
1.3.13
JSON |
| download |
| home_page | None |
| Summary | Pipeline for reducing Goodman HTS data. |
| upload_time | 2025-08-14 22:20:33 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | BSD 3-Clause License
Copyright (c) 2018, SOAR Telescope
All rights reserved.
Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
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list of conditions and the following disclaimer.
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this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.
* Neither the name of the copyright holder nor the names of its
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this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
|
| keywords |
soar
pipelines
astronomy
images
spectroscopy
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
astropy
astroplan
astroscrappy
ccdproc
coveralls
cython
recommonmark
matplotlib
mock
numpy
pandas
scipy
sphinx
sphinxcontrib.napoleon
sphinx_rtd_theme
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
|
# Goodman High Throughput Spectrograph Data Reduction Pipeline
[](https://codecov.io/gh/soar-telescope/goodman_pipeline)
[](http://goodman.readthedocs.io/en/latest/?badge=latest)
[](https://pypi.org/project/goodman-pipeline/)
[](http://www.astropy.org/)
## Overview
The Goodman High Throughput Spectrograph (Goodman HTS) Data-Reduction Pipeline
is the SOAR Telescope's official data reduction pipeline for *Goodman HTS*.
It has been fully developed in Python and uses mostly astropy affiliated packages
with the exception of [dcr](http://users.camk.edu.pl/pych/DCR/) which is an external tool
that does cosmic ray identification and correction. The reason for using it
instead of LACosmic is that it works very well for spectroscopic data and the
results are evidently superior. Some of the negative aspects of using this
external (meaning outside of Python domains) software were: The integration into
the pipeline's workflow and the use of an external `dcr.par` parameter file.
Such parameters have to be changed by hand and can't be integrated into the
pipeline's workflow itself. In particular for binning 2x2 and custom ROI those
parameters contained in _dcr.par_ has to be specifically tuned.
## Documentation
You will find a user manual on [goodman.readthedocs.org](http://goodman.readthedocs.io/en/latest/)
If you wish to know more about the instrument please check the
[SOAR website](http://www.ctio.noao.edu/soar/content/goodman-high-throughput-spectrograph)
## Having trouble?
If you are having trouble operating the Goodman Pipeline we suggest the following
procedure.
* Check [existing issues](https://github.com/soar-telescope/goodman_pipeline/issues) or
open a [new Issue](https://github.com/soar-telescope/goodman_pipeline/issues/new) on GitHub.
## Development Team
- [Simón Torres](https://github.com/simontorres) (NOIRLab Software Engineer - main code developer)
- [César Briceño](https://github.com/cbaorion) (SOAR Telescope Scientist - team lead)
- [Bruno Quint](https://github.com/b1quint) (Brazil Support Astronomer - code development adviser)
## Acknowledgements
We acknowledge the important contribution of [David Sanmartim](https://github.com/dsanmartim), who developed
the initial incarnation of the redccd module. We thank [Tina Armond](https://github.com/tarmond) for her
invaluable help in adding calibrated comparison lamps to the [library](https://goodman.readthedocs.io/projects/lamps/en/latest/) of
reference comparison lamps for wavelength solution.
Our work would not be possible without the friendly work atmosphere at CTIO
headquarters in La Serena, were we can interact with our SOAR and CTIO
colleagues in lively and useful discussions that have been important in making
the Goodman pipeline possible. We also acknowledge fruitful discussions and
suggestions from our colleagues Bart Dunlop, Chris Clemens, and Erik Dennihy,
at University of North Carolina at Chapel Hill.
## Citations:
This pipeline makes extensive use of Astropy therefore you should cite as suggested
on [Astropy Citation Page](https://github.com/astropy/astropy/blob/master/CITATION) as follows:
This research made use of Astropy, a community-developed core Python package
for Astronomy (Astropy Collaboration, 2013, 2018).
It also uses [DCR](http://users.camk.edu.pl/pych/DCR/) for cosmic rays identification
and removal. You should cite [this paper](http://adsabs.harvard.edu/abs/2004PASP..116..148P)
Pych, W., 2004, PASP, 116, 148
Raw data
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"description": "# Goodman High Throughput Spectrograph Data Reduction Pipeline\n\n\n[](https://codecov.io/gh/soar-telescope/goodman_pipeline)\n[](http://goodman.readthedocs.io/en/latest/?badge=latest)\n[](https://pypi.org/project/goodman-pipeline/)\n[](http://www.astropy.org/)\n\n\n\n\n\n## Overview\nThe Goodman High Throughput Spectrograph (Goodman HTS) Data-Reduction Pipeline\nis the SOAR Telescope's official data reduction pipeline for *Goodman HTS*.\n\nIt has been fully developed in Python and uses mostly astropy affiliated packages\nwith the exception of [dcr](http://users.camk.edu.pl/pych/DCR/) which is an external tool\nthat does cosmic ray identification and correction. The reason for using it\ninstead of LACosmic is that it works very well for spectroscopic data and the\nresults are evidently superior. Some of the negative aspects of using this\nexternal (meaning outside of Python domains) software were: The integration into\nthe pipeline's workflow and the use of an external `dcr.par` parameter file.\n Such parameters have to be changed by hand and can't be integrated into the\n pipeline's workflow itself. In particular for binning 2x2 and custom ROI those\n parameters contained in _dcr.par_ has to be specifically tuned.\n\n## Documentation\n\nYou will find a user manual on [goodman.readthedocs.org](http://goodman.readthedocs.io/en/latest/)\n\nIf you wish to know more about the instrument please check the \n[SOAR website](http://www.ctio.noao.edu/soar/content/goodman-high-throughput-spectrograph)\n\n## Having trouble?\n\nIf you are having trouble operating the Goodman Pipeline we suggest the following\nprocedure.\n\n* Check [existing issues](https://github.com/soar-telescope/goodman_pipeline/issues) or \nopen a [new Issue](https://github.com/soar-telescope/goodman_pipeline/issues/new) on GitHub.\n\n## Development Team\n\n- [Sim\u00f3n Torres](https://github.com/simontorres) (NOIRLab Software Engineer - main code developer)\n- [C\u00e9sar Brice\u00f1o](https://github.com/cbaorion) (SOAR Telescope Scientist - team lead)\n- [Bruno Quint](https://github.com/b1quint) (Brazil Support Astronomer - code development adviser)\n\n\n## Acknowledgements\n\nWe acknowledge the important contribution of [David Sanmartim](https://github.com/dsanmartim), who developed\nthe initial incarnation of the redccd module. We thank [Tina Armond](https://github.com/tarmond) for her\ninvaluable help in adding calibrated comparison lamps to the [library](https://goodman.readthedocs.io/projects/lamps/en/latest/) of\nreference comparison lamps for wavelength solution.\n\nOur work would not be possible without the friendly work atmosphere at CTIO\nheadquarters in La Serena, were we can interact with our SOAR and CTIO\ncolleagues in lively and useful discussions that have been important in making\nthe Goodman pipeline possible. We also acknowledge fruitful discussions and\nsuggestions from our colleagues Bart Dunlop, Chris Clemens, and Erik Dennihy,\nat University of North Carolina at Chapel Hill.\n \n## Citations:\n This pipeline makes extensive use of Astropy therefore you should cite as suggested\n on [Astropy Citation Page](https://github.com/astropy/astropy/blob/master/CITATION) as follows:\n \n This research made use of Astropy, a community-developed core Python package\n for Astronomy (Astropy Collaboration, 2013, 2018).\n \n It also uses [DCR](http://users.camk.edu.pl/pych/DCR/) for cosmic rays identification\n and removal. You should cite [this paper](http://adsabs.harvard.edu/abs/2004PASP..116..148P)\n \n Pych, W., 2004, PASP, 116, 148\n\n",
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