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https://github.com/nowosad/acspatial
Algorithmic Complexity of Spatial Data
https://github.com/nowosad/acspatial
r r-package rspatial rstats spatial
Last synced: 3 months ago
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Algorithmic Complexity of Spatial Data
- Host: GitHub
- URL: https://github.com/nowosad/acspatial
- Owner: Nowosad
- License: other
- Created: 2024-05-08T08:58:54.000Z (8 months ago)
- Default Branch: main
- Last Pushed: 2024-05-25T13:18:04.000Z (8 months ago)
- Last Synced: 2024-06-11T16:07:09.825Z (7 months ago)
- Topics: r, r-package, rspatial, rstats, spatial
- Language: R
- Homepage:
- Size: 175 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.Rmd
- License: LICENSE
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%"
)
```# acspatial
[![R-CMD-check](https://github.com/Nowosad/spatcomplexity/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Nowosad/spatcomplexity/actions/workflows/R-CMD-check.yaml)
The goal of **acspatial** is to provide a function to calculate the layered block decomposition method (layered BDM) for spatial data.
The layered BDM is a method to estimate the algorithmic complexity of spatial data, a measure of the amount of information in a data set.
The algorithmic complexity is calculated using the Kolmogorov complexity, which is the length of the shortest computer program that can generate the provided data set.## Installation
You can install the development version of **acspatial** from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("Nowosad/acspatial")
```## Examples
```{r}
library(acspatial)
# 1
data(mini_array)
mini_array
layered_bdm(mini_array)# 2
mini_array2 = matrix(1, nrow = 8, ncol = 8)
mini_array2
layered_bdm(mini_array2)
```## References
- Rueda-Toicen, Antonio, Image Analysis with Estimations of Kolmogorov Complexity, (2018), GitHub repository, https://github.com/andandandand/ImageAnalysisWithAlgorithmicInformation, DOI: /10.5281/zenodo.1291510
- Hector Zenil, Santiago Hernández-Orozco, Narsis A.Kiani, Fernando Soler-Toscano, Antonio Rueda-Toicen, and Jesper Tegner "A Decomposition Method for Global Evaluation of Shannon Entropy and Local Estimations of Algorithmic Complexity", https://arxiv.org/abs/1609.00110
- https://www.complexity-calculator.com/