SPEARS : SPARCL Pipeline for Emission-Absorption Line Retrieval and Spectroscopy
Project description
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:
specutils
numpy
astropy
json
warnings
scipy
sparcl.client
importlib
pytest
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
See LICENSE.txt file.
Acknowledgments
Full accreditation can be found on my GitHub.
Thanks to NOIRLAB for supplying their vast spectral data for free through SPARCL API.
Contact
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