p-winds

Python implementation of Parker wind models for exoplanet atmospheres

https://github.com/ladsantos/p-winds

Science Score: 77.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 3 DOI reference(s) in README
  • Academic publication links
    Links to: arxiv.org, zenodo.org
  • Committers with academic emails
    3 of 4 committers (75.0%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (12.6%) to scientific vocabulary

Keywords

astronomy astrophysics atmosphere exoplanet exoplanet-atmospheres
Last synced: 6 months ago · JSON representation ·

Repository

Python implementation of Parker wind models for exoplanet atmospheres

Basic Info
Statistics
  • Stars: 12
  • Watchers: 1
  • Forks: 5
  • Open Issues: 4
  • Releases: 32
Topics
astronomy astrophysics atmosphere exoplanet exoplanet-atmospheres
Created about 5 years ago · Last pushed 10 months ago
Metadata Files
Readme License Citation

README.md

p-winds

Documentation Status Build Status arXiv Code DOI

Python implementation of Parker wind models for planetary atmospheres. p-winds produces simplified, 1-D models of the upper atmosphere of a planet, and perform radiative transfer to calculate observable spectral signatures.

The scalable implementation of 1D models allows for atmospheric retrievals to calculate atmospheric escape rates and temperatures. In addition, the modular implementation allows for a smooth plugging-in of more complex descriptions to forward model their corresponding spectral signatures (e.g., self-consistent or 3D models).

A paper describing p-winds (Dos Santos et al. 2022) and its usage for research-grade astronomical applications was published in the journal Astronomy & Astrophysics. If you use this code in your research, please consider citing it.

p-winds contains and distributes data products from the MUSCLES and Mega-MUSCLES treasury surveys. If you use the tools.generate_muscles_spectrum() function in your study, we highly encourage you to cite France et al. 2016, Youngblood et al. 2016, Loyd et al. 2016, Wilson et al. 2021 and Behr et al. 2023.

Warning: As of version 1.4.5, p-winds does not include the MUSCLES data anymore to make the package leaner. You will need to download this data separately and set an environment variable containing the path to the data. Follow the installation instructions below.

Background

p-winds is largely based on the theoretical framework of Oklopčić & Hirata (2018) and Lampón et al. (2020), which themselves based their work on the stellar wind model of Parker (1958). A description about the implementation of tidal effects is discussed in Vissapragada et al. (2022).

Requirements

p-winds requires the following packages:

  • python versions 3.8 or later; the code has also been tested and validated in versions 3.6 (not supported) and 3.9.
  • numpy
  • scipy version 1.5 or later
  • astropy
  • flatstar

Installation

You can install p-winds using pip or by compiling it from source.

Option 1: Using pip (stable version)

Simply run the following command: angular2html pip install p-winds

Option 2: Compile from source (development version)

First, clone the repository and then navigate to it: angular2html git clone https://github.com/ladsantos/p-winds.git cd p-winds

And then compile it from source: angular2html python setup.py install

You can test the installation from source with pytest (you may need to install pytest first): angular2html pytest tests

Download reference spectra and set environment variable

If you want to use the function tools.generate_muscles_spectrum() or tools.standard_spectrum(), you will need to download the reference data separately and set the environment variable $PWINDS_REFSPEC_DIR. For your convenience, you can download all spectra supported by p-winds in this compressed file.

After unzipping the compressed file, move the fits files to a path of your choosing; in this example, I will use the path /$HOME/Data/p-winds_reference_spectra. Next, set an environment variable $PWINDS_REFSPEC_DIR that points to this path; this is done by running the following code in the command line:

angular2html export PWINDS_REFSPEC_DIR="$HOME/Data/p-winds_reference_spectra"

If you do not want to set this environment variable every time you start a new session, you can add this line to your Record Columnar file (or rc) in your user folder. Usually, this file is ~/.bashrc if you use a bash shell, or ~/.zshrc if you use zshell.

Quickstart example

Check out a quickstart Google Colab Notebook here. A similar quickstart Jupyter notebook is also available inside the docs/source/ folder.

Contributing

You can contribute to the development of p-winds either by submitting issues, or by submitting pull requests (PR). If you choose to submit a PR, please pull it to the dev branch, which is where the experiments happen before being merged to the main branch.

Future features and known problems

Check out the open issues.

Owner

  • Name: Leonardo dos Santos
  • Login: ladsantos
  • Kind: user
  • Location: Baltimore, United States

STScI Fellow at the Space Telescope Science Institute.

Citation (CITATION.cff)

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Dos Santos"
  given-names: "Leonardo A."
  orcid: "https://orcid.org/0000-0002-2248-3838"
- family-names: "Vissapragada"
  given-names: "Shreyas"
  orcid: "https://orcid.org/0000-0003-2527-1475"
title: "p-winds"
version: 1.4.7
doi: 10.1051/0004-6361/202142038
date-released: 2021-12-21
url: "https://github.com/ladsantos/p-winds"

GitHub Events

Total
  • Watch event: 1
  • Push event: 4
Last Year
  • Watch event: 1
  • Push event: 4

Committers

Last synced: almost 3 years ago

All Time
  • Total Commits: 322
  • Total Committers: 4
  • Avg Commits per committer: 80.5
  • Development Distribution Score (DDS): 0.36
Past Year
  • Commits: 72
  • Committers: 2
  • Avg Commits per committer: 36.0
  • Development Distribution Score (DDS): 0.028
Top Committers
Name Email Commits
leonardo l****s@u****h 206
Leonardo dos Santos l****s@s****u 102
Shreyas Vissapragada s****r@c****u 12
gully i****y@g****m 2
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 36
  • Total pull requests: 12
  • Average time to close issues: 6 months
  • Average time to close pull requests: 11 days
  • Total issue authors: 6
  • Total pull request authors: 4
  • Average comments per issue: 0.97
  • Average comments per pull request: 1.0
  • Merged pull requests: 11
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 1
  • Average time to close issues: N/A
  • Average time to close pull requests: about 10 hours
  • Issue authors: 0
  • Pull request authors: 1
  • Average comments per issue: 0
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • ladsantos (28)
  • dlinssen (3)
  • gully (2)
  • admasson (1)
  • LarsKlijn (1)
  • mls1052 (1)
Pull Request Authors
  • astroshrey (6)
  • jseideleso (4)
  • ladsantos (3)
  • gully (1)
Top Labels
Issue Labels
enhancement (21) bug (7) documentation (2) question (1) wontfix (1) invalid (1)
Pull Request Labels

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 55 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 25
  • Total maintainers: 1
pypi.org: p-winds

Parker wind models for planetary atmospheres

  • Versions: 24
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 55 Last month
Rankings
Dependent packages count: 10.1%
Forks count: 14.2%
Average: 16.7%
Stargazers count: 18.5%
Downloads: 18.8%
Dependent repos count: 21.6%
Maintainers (1)
Last synced: 7 months ago
conda-forge.org: p-winds
  • Versions: 1
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent repos count: 34.0%
Average: 47.1%
Forks count: 49.6%
Dependent packages count: 51.2%
Stargazers count: 53.5%
Last synced: 7 months ago

Dependencies

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requirements.txt pypi
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setup.py pypi
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