SPEARS 0.1.4

SPEARS : SPARCL Pipeline for Emission-Absorption Line Retrieval and Spectroscopy

SPEARS - Sparcl Pipeline for Emission-Absorption Line Retrieval and Spectroscopy

This library aims to provide users with a quick, and easily scalable pipeline for spectroscopic analysis of spectra from the DESI-EDR accessed through the SPARCL API at NOIRLAB. Provides a list of spectral lines present in a given spectrum, along with other information outlined in spectro_analyze header. Specific usage of each function can be found under Features.

Features

Main Functionality

• spectro_analyze(limit, save_as_fits=False): Returns a list of QTables (or .fits file if specified) with the following headers:

  • ‘Ion’ (str): The ion type present

  • ‘Ion Line Wavelength’ (float64, angstrom): The wavelength of the present spectral line

  • ‘Spectral Flux at Line’ (float64, 1 / (erg17 cm2 s Angstrom)): The model-spectral flux at the given spectral line wavelength

  • ‘Observed Deviation’ (float64, angstrom): The distance from the observed spectral line and the actual line

  • ‘Normalized Deviation’ (float64, dimensionless): The observed deviation divided by the spectral resolution at that given wavelength

  • meta={‘id’}: id of spectrum, identical to dict key

Sub-modules

• fetch_sparcl_ids(limit): Fetches the first n SPARCL ids, based on the limit provided.

• sparcl_ids_to_spectra(sparcl_ids): Takes SPARCL ids and returns a list of Spectrum1D objects with each spectra’s flux, redshifted-accounted wavelength, and SPARCL id.

• normalize_spectra(model_spectra): Takes an array of Spectrum1D object(s) and returns the continuum normalized spectra for each (continuum derived by median-filter smoothing original spectrum).

• norm_spectra_to_lines(normalized_spectra, save_as_fits=False): Takes an array of normalized spectra, and returns the present spectral lines (and other info specified in spectro_analyze) in each in a list of QTables, or .fits file if specified.

Requirements

As listed in setup.py:

• astropy==6.0.0

• numpy==1.26.3

• scipy==1.12.0

• sparclclient==1.2.1

• specutils==1.12.0

• Unidecode==1.3.8

Installation

$ [sudo] pip install SPEARS

Usage

Retrieving spectral analysis info from the first 5 spectra in the database:

from SPEARS import SPEARS

sparcl_ids = SPEARS.fetch_sparcl_ids(limit=5)

info = SPEARS.spectro_analyze(sparcl_ids)

Documentation

Full documentation will be later uploaded to my GitHub.

License

MIT License

Copyright (c) 2024 Justin Domagala-Tang

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Acknowledgments

• Full accreditation can be found on my GitHub.

• Thanks to NOIRLAB for supplying their vast spectral data for free through SPARCL API.

Contact

Email: [e-mail]