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!