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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# vecsymr
<!-- badges: start -->
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![Codecov test coverage](https://codecov.io/gh/rgayler/vecsymr/branch/main/graph/badge.svg)](https://app.codecov.io/gh/rgayler/vecsymr?branch=main)
[![R-CMD-check](https://github.com/rgayler/vecsymr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/rgayler/vecsymr/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->
The goal of {vecsymr} is to implement Vector Symbolic Architecture (VSA)
primitives to support experimentation. It is intended to be a simple VSA
implementation (the VSA equivalent of the geneticist's fruit fly) to provide a
convenient base for experimentation. The design choices are
[my](https://www.rossgayler.com) personal preferences to support my research.
The initial emphasis is on functionality and flexibility with no specific
concern for performance.
I believe that phasor VSAs (where the vector elements are unit magnitude
complex numbers) are the best choice for basic VSAs. However, I have initially
imported functions for bipolar VSAs from
[VSA_altitude_hold](https://github.com/rgayler/VSA_altitude_hold) to provide
some code while I get the hang of writing an R package. Once the package
contains enough phasor VSA code I will probably remove the bipolar VSA code. The
phasor VSA code will probably include some extra features to support
non-negativity and experimentation with clean-up memory.
## Installation
You can install the development version of {vecsymr} from
[GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("rgayler/vecsymr")
```
There is currently no intention to put this package on CRAN. If it turns out to
be sufficiently useful and general I may try get it accepted as an
[rOpenSci](https://ropensci.org/packages/) package.
The current implementation is experimental. I expect the functional content to
evolve as I work out what I want this package to do. I also expect the API to
evolve as I work out how to make it easier to work with. If you want to do any
reproducible work with the package you will need to use something like
[{renv}](https://rstudio.github.io/renv/) to freeze the version in use.
## Ignore below here
Everything after this point is just boilerplate to be edited.
## Example
This is a basic example which shows you how to solve a common problem:
```{r example}
library(vecsymr)
## basic example code
```
## Remember
You'll still need to render `README.Rmd` regularly, to keep `README.md`
up-to-date. `devtools::build_readme()` is handy for this. You could also use
GitHub Actions to re-render `README.Rmd` every time you push. An example
workflow can be found here: <https://github.com/r-lib/actions/tree/v1/examples>.
If you create figures in the README don't forget to commit and push the
resulting figure files, so they display on GitHub.