https://github.com/pyspeckit/pyspeckit

Python Spectroscopic Toolkit
https://github.com/pyspeckit/pyspeckit

Last synced: 26 days ago
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Python Spectroscopic Toolkit

• Host: GitHub
• URL: https://github.com/pyspeckit/pyspeckit
• Owner: pyspeckit
• License: mit
• Created: 2012-10-07T22:12:19.000Z (about 12 years ago)
• Default Branch: master
• Last Pushed: 2024-08-22T00:08:36.000Z (4 months ago)
• Last Synced: 2024-08-22T01:37:55.242Z (4 months ago)
• Language: Python
• Size: 35.1 MB
• Stars: 103
• Watchers: 14
• Forks: 84
• Open Issues: 77
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGES.rst
  • License: LICENSE
  • Citation: CITATION.cff

Awesome Lists containing this project

• awesome-spectra - pyspeckit

README

        
PySpecKit Spectroscopic Toolkit

-------------------------------

* Documentation: ``_

* Source pages: ``_

* ADS reference: https://ui.adsabs.harvard.edu/abs/2022AJ....163..291G/abstract

This is a code framework designed to allow for analysis of spectroscopic data

from a wide variety of astronomical instruments.  It is motivated by the lack

of general spectroscopic analysis tools applicable at multiple wavelengths

(compare to IRAF, SPLAT, etc. - these are wavelength-specific and/or do not

make user scripting easy).

Initial implementation focuses on optical and radio applications, e.g.

gaussian and voigt profile fitting, baseline/continuum fitting, and equivalent

width measurements.  However, the design is meant to be extensible.  We want

additional features to be trivial to implement.

In that vein, there is a growing set of spectral models implemented.  The

model and hyperfinemodel classes makes

model implementation quite straightforward, if not trivial (you still have to

plug in the right frequency offsets and relative line strengths).

Plotting is straightforward, as is usually the case with matplotlib-based

codes.  We have a few different methods of error bar plotting implemented, a

decent (and expanding) units class for pretty printing of spectroscopic units,

and different methods of fit plotting.

We're also looking for more users to give us more use cases!  Contact us

at [email protected] or post `issues

`_

Requirements:

`astropy `_

`matplotlib `_

`numpy `_

Optional:

`scipy `_

`lmfit `_

`lineid_plot `_

`spectral-cube `_

Authors:

`Adam Ginsburg `_ and several others.

Contributors: (see https://github.com/pyspeckit/pyspeckit/graphs/contributors)

 * Erik Rosolowsky (Ammonia models, RADEX-based models)

 * Jordan Mirocha (optical line labeling)

 * Vlas Sokolov (cube fitting, ammonia and N2H+ modeling)

 * Miguel de Val-Borro (CLASS file reading, python3 compatibility, bugfixes)

 * Brigitta Sipocz (internals & logistics)

 * Jaime Pineda (N2D+, N2H+ models, bugfixes)

 * Allison Youngblood (H2 model fit)

 * Taylor Hogge (Ammonia models)

 * Dinos Kousidis (ESO summer student - Astropy integration)

 * Mike Lum (EQW fitter)

 * Matt Craig, Erik Tollerud, Thomas Robitaille (minor - Astropy integration)

The PySpecKit logo uses the Voyager 1 image of Earth known as the "Pale Blue Dot"

[ `original source `_ |  `reprocessed image `_ ]

.. image:: https://zenodo.org/badge/6116896.svg

   :target: https://zenodo.org/badge/latestdoi/6116896

pyspeckit development has been supported by the NSF under grants AST 2008101 and CAREER 2142300

.. image:: https://www.nsf.gov/news/mmg/media/images/nsf%20logo_ba604992-ed6d-46a7-8f5b-151b1c3e17e3.jpg

    :target:  https://www.nsf.gov/policies/images/NSF_Official_logo_High_Res_1200ppi.png

    :width: 200