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https://github.com/tidymodels/spatialsample
Create and summarize spatial resampling objects 🗺
https://github.com/tidymodels/spatialsample
Last synced: about 1 month ago
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Create and summarize spatial resampling objects 🗺
- Host: GitHub
- URL: https://github.com/tidymodels/spatialsample
- Owner: tidymodels
- License: other
- Created: 2021-01-19T21:06:51.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2023-11-14T15:37:36.000Z (about 1 year ago)
- Last Synced: 2024-05-02T02:27:34.078Z (8 months ago)
- Language: R
- Homepage: https://spatialsample.tidymodels.org
- Size: 87.6 MB
- Stars: 69
- Watchers: 6
- Forks: 5
- Open Issues: 2
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- Contributing: .github/CONTRIBUTING.md
- License: LICENSE
- Code of conduct: .github/CODE_OF_CONDUCT.md
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
library(ggplot2)
theme_set(theme_minimal())
```
# spatialsample 
[](https://github.com/tidymodels/spatialsample/actions/workflows/R-CMD-check.yaml)
[](https://CRAN.R-project.org/package=spatialsample)
[](https://app.codecov.io/gh/tidymodels/spatialsample?branch=main)
[](https://lifecycle.r-lib.org/articles/stages.html)
## Introduction
The goal of spatialsample is to provide functions and classes for spatial resampling to use with [rsample](https://rsample.tidymodels.org/), including:
- [spatial clustering cross-validation](https://doi.org/10.1109/IGARSS.2012.6352393)
- [spatial block cross-validation](https://doi.org/10.1111/ecog.02881)
- [spatially buffered cross-validation](https://doi.org/10.1111/geb.12161)
- [leave-location-out cross-validation](https://doi.org/10.1016/j.envsoft.2017.12.001)
Like [rsample](https://rsample.tidymodels.org/), spatialsample provides building blocks for creating and analyzing resamples of a spatial data set but does not include code for modeling or computing statistics. The resampled data sets created by spatialsample are efficient and do not have much memory overhead.
## Installation
You can install the released version of spatialsample from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("spatialsample")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("pak")
pak::pak("tidymodels/spatialsample")
```
## Example
The most straightforward spatial resampling strategy is `spatial_clustering_cv()`, which uses k-means clustering to identify cross-validation folds:
```{r}
library(spatialsample)
set.seed(1234)
folds <- spatial_clustering_cv(boston_canopy, v = 5)
folds
```
In this example, the `boston_canopy` data on tree cover in Boston, MA is resampled with `v = 5`; notice that the resulting partitions do not contain an equal number of observations.
In addition to resampling algorithms, spatialsample provides methods to visualize resamples using [ggplot2](https://ggplot2.tidyverse.org/) through the `autoplot()` function:
```{r 2022-06-12_boston_static, fig.width=7, fig.height=5}
autoplot(folds)
```
We can use the same function to visualize each fold separately:
```{r 2022-06-12_boston-anim, animation.hook="gifski", fig.width=7, fig.height=5}
library(purrr)
walk(folds$splits, function(x) print(autoplot(x)))
```
So far, we've only scratched the surface of the functionality spatialsample provides. For more information, check out the [Getting Started](https://spatialsample.tidymodels.org/articles/spatialsample.html) documentation!
## Contributing
This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/1/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).
- If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/rules/issues).
- Either way, learn how to create and share a [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html) (a minimal, reproducible example), to clearly communicate about your code.
- Check out further details on [contributing guidelines for tidymodels packages](https://www.tidymodels.org/contribute/) and [how to get help](https://www.tidymodels.org/help/).