https://github.com/landscitech/pfocal

Fast parallel convolution in R.
https://github.com/landscitech/pfocal

convolution image-processing landscape-ecology r raster-data

Last synced: 8 months ago
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Fast parallel convolution in R.

• Host: GitHub
• URL: https://github.com/landscitech/pfocal
• Owner: LandSciTech
• License: other
• Created: 2020-12-11T14:43:43.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-08-24T17:35:43.000Z (almost 4 years ago)
• Last Synced: 2024-06-20T18:21:51.263Z (about 2 years ago)
• Topics: convolution, image-processing, landscape-ecology, r, raster-data
• Language: R
• Homepage: https://landscitech.github.io/pfocal/
• Size: 23.1 MB
• Stars: 2
• Watchers: 4
• Forks: 1
• Open Issues: 5
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE.md

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%"

)

set.seed(77)

```

# pfocal 

[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](http://www.gnu.org/licenses/gpl-3.0)

[![Project Status: Active](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)

[![R-CMD-check](https://github.com/LandSciTech/pfocal/workflows/R-CMD-check/badge.svg)](https://github.com/LandSciTech/pfocal/actions)

[![Codecov test coverage](https://codecov.io/gh/LandSciTech/pfocal/branch/master/graph/badge.svg)](https://app.codecov.io/gh/LandSciTech/pfocal?branch=master)

The goal of `pfocal` is to implement fast parallel convolution. R version >= 4.0.0 is required.

## Installation

You can install the package as such:

```{r, eval=FALSE}

# From CRAN

install.packages("devtools")

# Dev version from GitHub

devtools::install_github("LandSciTech/pfocal")

```

## Example

```{r}

library(pfocal)

data <- matrix(nrow = 100, ncol = 100, 

               data = runif(n = 100*100, min = 0, max = 10))

image(data, asp = 1)

```

```{r}

kernel <- exponential_kernel()

convoluted <- pfocal(data = data, kernel = kernel, edge_value = 0)

image(convoluted, asp = 1)

```