SimpleSDMLayers.jl and GBIF.jl

SimpleSDMLayers.jl and GBIF.jl: A Framework for Species Distribution Modeling in Julia - Published in JOSS (2021)

https://github.com/PoisotLab/SimpleSDMLayers.jl

Science Score: 59.0%

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

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 2 DOI reference(s) in README
  • Academic publication links
    Links to: joss.theoj.org, zenodo.org
  • Committers with academic emails
    2 of 6 committers (33.3%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.7%) to scientific vocabulary

Keywords

bioclim climate-change geotiff landcover raster species-distribution-models

Keywords from Contributors

pde standardization fluxes plasma interpretability ecology cfd finite-volume fluid-dynamics kinetic-theory
Last synced: 6 months ago · JSON representation

Repository

Simple layers for species distribution modeling and bioclimatic data

Basic Info
Statistics
  • Stars: 18
  • Watchers: 5
  • Forks: 2
  • Open Issues: 9
  • Releases: 28
Archived
Topics
bioclim climate-change geotiff landcover raster species-distribution-models
Created almost 7 years ago · Last pushed about 3 years ago
Metadata Files
Readme Contributing Funding License Code of conduct Zenodo

README.md

Simple Layers for Species Distributions Modelling

MAINTENANCE MODE - this repo is being moved to a monorepo with better integration between features

What is this package? SimpleSDMLayers offers a series of types, methods, and additional helper functions to build species distribution models. It does not implement any species distribution models, although there are a few examples of how this can be done in the documentation.

Who is developping this package? This package is primarily maintained by the Quantitative & Computational Ecology group at Université de Montréal, and is part of the broader EcoJulia organisation.

Can I sponsor this project? Sure! There is a link in the sidebar on the right. Any money raised this way will go towards the snacks and coffee fund for students, or any charitable cause we like to support.

How can I cite this package? This repository itself can be cited through its Zenodo archive (4902317; this will generate a DOI for every release), and there is a manuscript in Journal of Open Science Software describing the package as well (10.21105/joss.02872).

Is there a manual to help with the package? Yes. You can read the documentation for the current stable release, which includes help on the functions, as well as a series of tutorials and vignettes ranging from simple analyses to full-fledged mini-studies.

Don't you have some swanky badges to display? We do. They are listed at the very end of this README.

Can I contribute to this project? Absolutely. The most immediate way to contribute is to use the package, see what breaks, or where the documentation is incomplete, and open an issue. If you have a more general question, you can also start a discussion. Please read the Code of Conduct and the contributing guidelines.

How do I install the package? The latest tagged released can be installed just like any Julia package: ]add SimpleSDMLayers. To get the most of it, we strongly suggest to also add StatsPlots and GBIF.

Why are there no code examples in this README? In short, because keeping the code in the README up to date with what the package actually does is tedious; the documentation is built around many case studies, with richer text, and with a more narrative style. This is where you will find the code examples and the figures you are looking for!


GitHub

Project Status: Active – The project has reached a stable, usable state and is being actively developed. GitHub contributors GitHub commit activity

GitHub last commit GitHub issues GitHub pull requests

GitHub release (latest SemVer) GitHub Release Date

GitHub Workflow Status Codecov GitHub Workflow Status

Owner

  • Name: the Poisot lab
  • Login: PoisotLab
  • Kind: organization
  • Location: Montréal, Canada

Quantitative and Computational Ecology

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 777
  • Total Committers: 6
  • Avg Commits per committer: 129.5
  • Development Distribution Score (DDS): 0.243
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Timothée Poisot t****t@u****a 588
Gabriel Dansereau g****u@u****a 171
github-actions[bot] 4****] 10
CompatHelper Julia c****y@j****g 5
Michael Krabbe Borregaard m****d@s****k 2
Daniel S. Katz d****z@i****g 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 48
  • Total pull requests: 52
  • Average time to close issues: 2 months
  • Average time to close pull requests: 20 days
  • Total issue authors: 5
  • Total pull request authors: 5
  • Average comments per issue: 2.23
  • Average comments per pull request: 2.02
  • Merged pull requests: 41
  • Bot issues: 0
  • Bot pull requests: 10
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • tpoisot (28)
  • gabrieldansereau (12)
  • gottacatchenall (6)
  • claireh93 (1)
  • JuliaTagBot (1)
Pull Request Authors
  • tpoisot (28)
  • github-actions[bot] (10)
  • gabrieldansereau (9)
  • gottacatchenall (3)
  • danielskatz (1)
Top Labels
Issue Labels
enhancement (9) difficulty-low (7) priority-high (5) bug (5) documentation (4) priority-medium (3) feature-request (3) difficulty-medium (2) compatibility (1) installation (1) priority-low (1) need-details (1) domain-data (1) need-triage (1) internals (1) on-pause (1) domain-plotting (1)
Pull Request Labels

Dependencies

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