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# DBSP_DRP
## Description
DBSP_DRP is a Data Reduction Pipeline for Palomar's workhorse spectrograph DBSP.
It is built on top of [PypeIt](https://github.com/pypeit/PypeIt).
DBSP_DRP automates the reduction, fluxing, telluric correction, and combining of the red and blue sides of one night's
data.
It adds several GUIs to allow for easier control of your reduction:
- select which data to reduce, and verify the correctness of your FITS headers in an editable table GUI
- manually place traces for a sort of manually "forced" spectroscopy with the `-m` option
- after manually placing traces, manually select sky regions and tweak the FWHM of your manual traces
The latest documentation can be found on [Read the Docs](https://dbsp-drp.readthedocs.io/en/latest/index.html).
## Citation
If you use DBSP_DRP in your research, please cite the following publications, or use the BibTeX provided below.
[![DOI](https://joss.theoj.org/papers/10.21105/joss.03612/status.svg)](https://doi.org/10.21105/joss.03612)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6241526.svg)](https://doi.org/10.5281/zenodo.6241526)
Additionally, please cite [PypeIt](https://github.com/pypeit/PypeIt#citation), with the BibTeX entries provided below (the Zenodo BibTex is for PypeIt 1.6.0, used in this version of DBSP_DRP).
### DBSP_DRP BibTeX
```
@article{dbsp_drp:joss,
doi = {10.21105/joss.03612},
url = {https://doi.org/10.21105/joss.03612},
year = {2022},
publisher = {The Open Journal},
volume = {7},
number = {70},
pages = {3612},
author = {Milan Sharma Mandigo-Stoba and Christoffer Fremling and Mansi M. Kasliwal},
title = {DBSP_DRP: A Python package for automated spectroscopic data reduction of DBSP data},
journal = {Journal of Open Source Software}
}
@misc{dbsp_drp:arxiv,
title={DBSP_DRP: A Python package for automated spectroscopic data reduction of DBSP data},
author={Milan Sharma Mandigo-Stoba and Christoffer Fremling and Mansi M. Kasliwal},
year={2021},
eprint={2107.12339},
archivePrefix={arXiv},
primaryClass={astro-ph.IM}
}
@software{dbsp_drp:zenodo,
author = {Mandigo-Stoba, Milan Sharma and
Fremling, Christoffer and
Kasliwal, Mansi M.},
title = {{DBSP\_DRP: A Python package for automated
spectroscopic data reduction of DBSP data}},
month = feb,
year = 2022,
publisher = {Zenodo},
version = {v1.0.0},
doi = {10.5281/zenodo.6241526},
url = {https://doi.org/10.5281/zenodo.6241526}
}
```
### PypeIt BibTeX
```
@article{pypeit:joss_pub,
doi = {10.21105/joss.02308},
url = {https://doi.org/10.21105/joss.02308},
year = {2020},
publisher = {The Open Journal},
volume = {5},
number = {56},
pages = {2308},
author = {J. Xavier Prochaska and Joseph F. Hennawi and Kyle B. Westfall and Ryan J. Cooke and Feige Wang and Tiffany Hsyu and Frederick B. Davies and Emanuele Paolo Farina and Debora Pelliccia},
title = {PypeIt: The Python Spectroscopic Data Reduction Pipeline},
journal = {Journal of Open Source Software}
}
@software{pypeit:zenodov_v1_6,
author = {J. Xavier Prochaska and
Joseph Hennawi and
Ryan Cooke and
Kyle Westfall and
Feige Wang and
Debora Pelliccia and
EmAstro and
Milan Roberson and
T. E. Pickering and
tiffanyhsyu and
badpandabear and
Asher Wasserman and
Timothy Ellsworth Bowers and
Nicolas Tejos and
Alexa Villaume and
Brad Holden and
marijana777 and
Sunil Simha and
JT Schindler and
David Young and
Andreas Flörs and
Matt Wilde and
S.Tang and
Erik Tollerud and
Jacob Isbell and
Kristen Thyng and
Dan Foreman-Mackey and
David Jones and
Edward Betts and
Zlatan Vasović},
title = {pypeit/PypeIt: Version 1.6.0},
month = oct,
year = 2021,
publisher = {Zenodo},
version = {1.6.0},
doi = {10.5281/zenodo.5548381},
url = {https://doi.org/10.5281/zenodo.5548381}
}
```
## Prerequisites
DBSP_DRP's dependencies are detailed in [environment.yml](environment.yml).
You can install all prerequisites for a `pip` or source install by downloading the environment.yml file, navigating to the directory containing it in your terminal window and running
```shell_session
$ conda env create -f environment.yml
```
Installing DBSP_DRP using `conda` does not require this step.
The telluric correction code provided by PypeIt relies on a large (5 GB) atmospheric model file,
TellFits_Lick_3100_11100_R10000.fits, which can be downloaded
[here](https://drive.google.com/drive/folders/1FFRWjUZ58HiDuDD33MYqBzMWDQanBRRy)
and must be installed into the ``pypeit/data/telluric/`` directory of your PypeIt installation.
An easier alternative is to use the [download_tellfile](bin/download_tellfile) script to download and install the atmospheric model file for you.
## Installation
You can install using `conda`
```shell_session
$ conda install -c conda-forge dbsp_drp
```
or `pip`
```shell_session
$ pip install dbsp-drp
```
Or you can install from source
```shell_session
$ git clone https://github.com/finagle29/DBSP_DRP.git
$ cd DBSP_DRP
$ pip install -e .
```
## Usage
```shell_session
$ dbsp_reduce -r /path/to/data/DBSP_YYYYMMDD -d /path/to/data/DBSP_YYYYMMDD_redux
[-a {red,blue}] [-i] [-m] [--debug] [-j N] [-p PARAMETER_FILE] [-t] [-c]
[--splicing-interpolate-gaps]
```
Raw data
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"description": "[![Documentation Status](https://readthedocs.org/projects/dbsp-drp/badge/?version=latest)](https://dbsp-drp.readthedocs.io/en/latest/?badge=latest)\n[![Test](https://github.com/finagle29/DBSP_DRP/actions/workflows/test.yml/badge.svg)](https://github.com/finagle29/DBSP_DRP/actions/workflows/test.yml)\n[![DOI](https://joss.theoj.org/papers/10.21105/joss.03612/status.svg)](https://doi.org/10.21105/joss.03612)\n\n![PyPI version](https://img.shields.io/pypi/v/DBSP_DRP?label=PyPI&logo=python&logoColor=white)\n![conda-forge version](https://img.shields.io/conda/vn/conda-forge/dbsp_drp?logo=conda-forge&logoColor=white)\n![pip downloads](https://img.shields.io/pypi/dm/DBSP_DRP)\n![conda downloads](https://img.shields.io/conda/dn/conda-forge/DBSP_DRP?label=conda%20downloads)\n\n# DBSP_DRP\n\n\n## Description\nDBSP_DRP is a Data Reduction Pipeline for Palomar's workhorse spectrograph DBSP.\nIt is built on top of [PypeIt](https://github.com/pypeit/PypeIt).\nDBSP_DRP automates the reduction, fluxing, telluric correction, and combining of the red and blue sides of one night's\ndata.\nIt adds several GUIs to allow for easier control of your reduction:\n- select which data to reduce, and verify the correctness of your FITS headers in an editable table GUI\n- manually place traces for a sort of manually \"forced\" spectroscopy with the `-m` option\n- after manually placing traces, manually select sky regions and tweak the FWHM of your manual traces\n\nThe latest documentation can be found on [Read the Docs](https://dbsp-drp.readthedocs.io/en/latest/index.html).\n\n## Citation\nIf you use DBSP_DRP in your research, please cite the following publications, or use the BibTeX provided below.\n[![DOI](https://joss.theoj.org/papers/10.21105/joss.03612/status.svg)](https://doi.org/10.21105/joss.03612)\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.6241526.svg)](https://doi.org/10.5281/zenodo.6241526)\n\nAdditionally, please cite [PypeIt](https://github.com/pypeit/PypeIt#citation), with the BibTeX entries provided below (the Zenodo BibTex is for PypeIt 1.6.0, used in this version of DBSP_DRP).\n\n### DBSP_DRP BibTeX\n```\n@article{dbsp_drp:joss,\n doi = {10.21105/joss.03612},\n url = {https://doi.org/10.21105/joss.03612},\n year = {2022},\n publisher = {The Open Journal},\n volume = {7},\n number = {70},\n pages = {3612},\n author = {Milan Sharma Mandigo-Stoba and Christoffer Fremling and Mansi M. Kasliwal},\n title = {DBSP_DRP: A Python package for automated spectroscopic data reduction of DBSP data},\n journal = {Journal of Open Source Software}\n}\n@misc{dbsp_drp:arxiv,\n title={DBSP_DRP: A Python package for automated spectroscopic data reduction of DBSP data}, \n author={Milan Sharma Mandigo-Stoba and Christoffer Fremling and Mansi M. Kasliwal},\n year={2021},\n eprint={2107.12339},\n archivePrefix={arXiv},\n primaryClass={astro-ph.IM}\n}\n@software{dbsp_drp:zenodo,\n author = {Mandigo-Stoba, Milan Sharma and\n Fremling, Christoffer and\n Kasliwal, Mansi M.},\n title = {{DBSP\\_DRP: A Python package for automated \n spectroscopic data reduction of DBSP data}},\n month = feb,\n year = 2022,\n publisher = {Zenodo},\n version = {v1.0.0},\n doi = {10.5281/zenodo.6241526},\n url = {https://doi.org/10.5281/zenodo.6241526}\n}\n```\n\n### PypeIt BibTeX\n```\n@article{pypeit:joss_pub,\n doi = {10.21105/joss.02308},\n url = {https://doi.org/10.21105/joss.02308},\n year = {2020},\n publisher = {The Open Journal},\n volume = {5},\n number = {56},\n pages = {2308},\n author = {J. Xavier Prochaska and Joseph F. Hennawi and Kyle B. Westfall and Ryan J. Cooke and Feige Wang and Tiffany Hsyu and Frederick B. 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Pickering and\n tiffanyhsyu and\n badpandabear and\n Asher Wasserman and\n Timothy Ellsworth Bowers and\n Nicolas Tejos and\n Alexa Villaume and\n Brad Holden and\n marijana777 and\n Sunil Simha and\n JT Schindler and\n David Young and\n Andreas Fl\u00f6rs and\n Matt Wilde and\n S.Tang and\n Erik Tollerud and\n Jacob Isbell and\n Kristen Thyng and\n Dan Foreman-Mackey and\n David Jones and\n Edward Betts and\n Zlatan Vasovi\u0107},\n title = {pypeit/PypeIt: Version 1.6.0},\n month = oct,\n year = 2021,\n publisher = {Zenodo},\n version = {1.6.0},\n doi = {10.5281/zenodo.5548381},\n url = {https://doi.org/10.5281/zenodo.5548381}\n}\n```\n\n## Prerequisites\nDBSP_DRP's dependencies are detailed in [environment.yml](environment.yml).\nYou can install all prerequisites for a `pip` or source install by downloading the environment.yml file, navigating to the directory containing it in your terminal window and running\n```shell_session\n$ conda env create -f environment.yml\n```\nInstalling DBSP_DRP using `conda` does not require this step.\n\nThe telluric correction code provided by PypeIt relies on a large (5 GB) atmospheric model file,\nTellFits_Lick_3100_11100_R10000.fits, which can be downloaded\n[here](https://drive.google.com/drive/folders/1FFRWjUZ58HiDuDD33MYqBzMWDQanBRRy)\nand must be installed into the ``pypeit/data/telluric/`` directory of your PypeIt installation.\n\nAn easier alternative is to use the [download_tellfile](bin/download_tellfile) script to download and install the atmospheric model file for you.\n\n## Installation\nYou can install using `conda`\n```shell_session\n$ conda install -c conda-forge dbsp_drp\n```\n\nor `pip`\n```shell_session\n$ pip install dbsp-drp\n```\n\nOr you can install from source\n```shell_session\n$ git clone https://github.com/finagle29/DBSP_DRP.git\n$ cd DBSP_DRP\n$ pip install -e .\n```\n\n## Usage\n```shell_session\n$ dbsp_reduce -r /path/to/data/DBSP_YYYYMMDD -d /path/to/data/DBSP_YYYYMMDD_redux\n [-a {red,blue}] [-i] [-m] [--debug] [-j N] [-p PARAMETER_FILE] [-t] [-c]\n [--splicing-interpolate-gaps]\n```\n",
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