tidysdm

R package to fit species distribution models (SDMs) using the 'tidymodels' framework

https://github.com/evolecolgroup/tidysdm

Science Score: 57.0%

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
  • Committers with academic emails
    3 of 11 committers (27.3%) from academic institutions
  • Institutional organization owner
    Organization evolecolgroup has institutional domain (www.eeg.zoo.cam.ac.uk)
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (18.5%) to scientific vocabulary

Keywords

r species-distribution-modelling tidymodels

Keywords from Contributors

tidy-data tidyverse shiny ggplot-extension setup
Last synced: 6 months ago · JSON representation

Repository

R package to fit species distribution models (SDMs) using the 'tidymodels' framework

Basic Info
Statistics
  • Stars: 34
  • Watchers: 3
  • Forks: 10
  • Open Issues: 7
  • Releases: 4
Topics
r species-distribution-modelling tidymodels
Created over 2 years ago · Last pushed 6 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct

README.md

tidysdm

R-CMD-check codecov CRAN status CRAN downloads <!-- badges: end -->

The goal of tidysdm is to implement Species Distribution Models using the tidymodels framework. The advantage of tidymodels is that the model syntax and the results returned to the user are standardised, thus providing a coherent interface to modelling. Given the variety of models required for SDM, tidymodels is an ideal framework. tidysdm provides a number of wrappers and specialised functions to facilitate the fitting of SDM with tidymodels.

Besides modelling contemporary species, tidysdm has a number of functions specifically designed to work with palaeontological data.

Whilst users are free to use their own environmental data, the articles showcase the potential integration with pastclim, which helps downloading and manipulating present day data, future predictions, and palaeoclimate reconstructions.

An overview of the capabilities of tidysdm is given in Leonardi et al. (2023).

Installation

tidysdm is on CRAN, and the easiest way to install it is with:

install.packages("tidysdm")

The version on CRAN is recommended for every day use. New features and bug fixes appear first on the dev branch on GitHub, before they make their way to CRAN. If you need to have early access to these new features, you can install the latest dev version of tidysdm from r-universe with:

r install.packages("tidysdm", repos = c("https://evolecolgroup.r-universe.dev", "https://cloud.r-project.org"))

Alternatively, you can also use devtools and install the package from source directly from GitHub, but you might need to set up your development environment first:

``` r

install.packages("devtools") # if you haven't installed devtools yet

devtools::install_github("EvolEcolGroup/tidysdm", ref = "dev") ```

Overview of functionality

On its dedicated website, you can find Articles giving you a step-by-step overview of the fitting SDMs to contemporary species, as well as an equivalent tutorial for using palaeontological data. Furthermore, there is an Article with examples of how to leverage various features of tidymodels that are not commonly adopted in SDM pipelines

There is also a dev version of the site updated for the dev branch of tidysdm (on the top left of the dev website, the version number is in red and in the format x.x.x.9xxx, indicating it is a development version). If you want to contribute, make sure to read our contributing guide.


Getting help

If some of your models are failing, first look at our Article on how to diagnose failing models. It is not a fully comprehensive list of everything that could go wrong, but it will hopefully give you ideas on how to dig deeper in what is wrong.

If after reading the article you are still unsure what is going wrong, there are two places to get help with tidysdm:

1) If you are unsure how to do something, go to StackOverflow and, after checking that a similar question has not been asked yet, tag your question with tidymodels and r (there is no tidysdm tag yet, as there aren't enough questions), and make sure tidysdm is in the title. This will ensure that the developers see your question and can help you. If you have not received an answer after a couple of days, feel free to drop us an email in case we missed your post.

2) If you think you have found a bug, or have a feature request, open an issue on our GitHub repository. Before doing so, please make sure that you have installed the latest development version of tidysdm (as the bug might have already been fixed), as well as updating all other packages on your system. If the problem persists, and there is no issue already opened that deals with your bug, file a new issue providing a reproducible example for the developers to investigate the problem. A small reproducible example is crucial in allowing us to understand the problem and fix it, so please do your best to come up with the shortest bit of code needed to show the bug.

Owner

  • Name: Evolutionary Ecology Group at University of Cambridge
  • Login: EvolEcolGroup
  • Kind: organization

GitHub Events

Total
  • Create event: 17
  • Release event: 1
  • Issues event: 33
  • Watch event: 9
  • Delete event: 12
  • Issue comment event: 90
  • Push event: 157
  • Pull request review comment event: 21
  • Pull request review event: 10
  • Pull request event: 24
  • Fork event: 3
Last Year
  • Create event: 17
  • Release event: 1
  • Issues event: 33
  • Watch event: 9
  • Delete event: 12
  • Issue comment event: 90
  • Push event: 157
  • Pull request review comment event: 21
  • Pull request review event: 10
  • Pull request event: 24
  • Fork event: 3

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 407
  • Total Committers: 11
  • Avg Commits per committer: 37.0
  • Development Distribution Score (DDS): 0.187
Past Year
  • Commits: 114
  • Committers: 5
  • Avg Commits per committer: 22.8
  • Development Distribution Score (DDS): 0.096
Top Committers
Name Email Commits
Andrea Manica a****5@c****k 331
m-colucci m****l@g****m 34
avpozzi a****6@c****k 12
July Pilowsky j****o 11
Johanna Paijmans p****a@g****m 7
Ben Tupper b****r@b****g 5
topepo m****n@g****m 2
Michela Leonardi m****7@c****k 2
simonpcouch s****h@g****m 1
Michael Chirico m****4@g****m 1
Emil Hvitfeldt e****t@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 32
  • Total pull requests: 88
  • Average time to close issues: 16 days
  • Average time to close pull requests: 1 day
  • Total issue authors: 21
  • Total pull request authors: 12
  • Average comments per issue: 1.94
  • Average comments per pull request: 0.94
  • Merged pull requests: 66
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 20
  • Pull requests: 29
  • Average time to close issues: 7 days
  • Average time to close pull requests: 2 days
  • Issue authors: 13
  • Pull request authors: 5
  • Average comments per issue: 2.25
  • Average comments per pull request: 1.69
  • Merged pull requests: 21
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • dramanica (4)
  • ramiromagno (3)
  • kolive4 (3)
  • jmburgos (2)
  • ManuelSpinola (2)
  • jlapaijmans (2)
  • btupper (2)
  • hpilat (1)
  • OndraPelanek (1)
  • EmilHvitfeldt (1)
  • djensing (1)
  • evhersh (1)
  • piabenaud (1)
  • zpmdal (1)
  • topepo (1)
Pull Request Authors
  • dramanica (60)
  • m-colucci (7)
  • avpozzi (4)
  • japilo (4)
  • EmilHvitfeldt (2)
  • btupper (2)
  • barnabasharris (2)
  • MichaelChirico (2)
  • topepo (2)
  • jlapaijmans (1)
  • simonpcouch (1)
  • mikleonardi (1)
Top Labels
Issue Labels
enhancement (1) bug (1) documentation (1) good first issue (1) help wanted (1)
Pull Request Labels

Packages

  • Total packages: 3
  • Total downloads:
    • cran 412 last-month
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 1
    (may contain duplicates)
  • Total versions: 15
  • Total maintainers: 1
proxy.golang.org: github.com/EvolEcolGroup/tidysdm
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
proxy.golang.org: github.com/evolecolgroup/tidysdm
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
cran.r-project.org: tidysdm

Species Distribution Models with Tidymodels

  • Versions: 7
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 412 Last month
Rankings
Stargazers count: 20.6%
Forks count: 21.0%
Dependent repos count: 23.8%
Average: 25.3%
Dependent packages count: 28.6%
Downloads: 32.4%
Maintainers (1)
Last synced: 6 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.4.1 composite
  • actions/checkout v3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
.github/workflows/test-coverage.yaml actions
  • actions/checkout v3 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite
DESCRIPTION cran
  • R >= 2.10 depends
  • spatialsample * depends
  • tidymodels * depends
  • dials * imports
  • dplyr * imports
  • ggplot2 * imports
  • lubridate * imports
  • magrittr * imports
  • maxnet * imports
  • overlapping * imports
  • parsnip * imports
  • patchwork * imports
  • recipes * imports
  • rlang >= 1.0.0 imports
  • rsample * imports
  • sf * imports
  • stats * imports
  • terra * imports
  • tibble * imports
  • tune * imports
  • workflows * imports
  • workflowsets * imports
  • yardstick * imports
  • doParallel * suggests
  • earth * suggests
  • knitr * suggests
  • pastclim * suggests
  • ranger * suggests
  • readr * suggests
  • rmarkdown * suggests
  • stacks * suggests
  • testthat >= 3.0.0 suggests
  • tidyterra * suggests
  • xgboost * suggests