rMVPA/README.rmd at master · bbuchsbaum/rMVPA · GitHub

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---
output: github_document
---

```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "README-"
)
```

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## Multivoxel Pattern Analysis in R


```{r, echo = FALSE}
version <- as.vector(read.dcf('DESCRIPTION')[, 'Version'])
version <- gsub('-', '.', version)
```

### This package is under development.

### Introduction

`rMVPA` is an R library for multivariate pattern analysis of neuroimaging data. The goal of this library is to make MVPA analyses easy. It can be used both programmatically from within R or using a command line interface. 'rMVPA' provides a lightweight model registry and efficient resampling methods for machine learning. What `rMVPA` provides is the infrastructure for conducting machine learning analyses on neuroimaging data.

Documentation and vignettes: https://bbuchsbaum.github.io/rMVPA/

### Installation

### Using devtools

To install `rMVPA` from within R, use the `devtools` function `install_github`. You will need the development version of `neuroim2` as well.

From within R:

```
#library(devtools)
install_github("bbuchsbaum/neuroim2")
install_github("bbuchsbaum/rMVPA")
```

### Using `git` from the command line

```
git clone git@github.com:bbuchsbaum/rMVPA.git
R CMD install rMVPA
```

### Command line scripts

`rMVPA` now ships packaged CLI wrappers with native command names:

- `rmvpa-searchlight`
- `rmvpa-regional`

Install the package:

```r
pak::pak("bbuchsbaum/rMVPA")
```

Then copy the wrappers into a directory on your `PATH`:

```r
rMVPA::install_cli("~/.local/bin", overwrite = TRUE)
```

If needed, add that directory to `PATH`:

```bash
export PATH="$HOME/.local/bin:$PATH"
```

On macOS/Linux, you can then run:

```bash
rmvpa-searchlight --help
rmvpa-regional --help
rmvpa-searchlight --version
```

The unified CLI vignette is `vignette("CommandLine")`. The legacy source-tree
entrypoints remain available as compatibility shims, but the packaged commands
above are the supported interface.