DBSP_DRP

Description

DBSPDRP is a Data Reduction Pipeline for Palomar's workhorse spectrograph DBSP. It is built on top of PypeIt. DBSPDRP 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.

Citation

If you use DBSP_DRP in your research, please cite the following publications, or use the BibTeX provided below.

Additionally, please cite PypeIt, 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:zenodovv16, 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

DBSPDRP's dependencies are detailed in 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 ```shellsession $ conda env create -f environment.yml `` Installing DBSP_DRP usingconda` does not require this step.

The telluric correction code provided by PypeIt relies on a large (5 GB) atmospheric model file, TellFitsLick310011100R10000.fits, which can be downloaded here and must be installed into the pypeit/data/telluric/ directory of your PypeIt installation.

An easier alternative is to use the 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]