https://github.com/t-kalinowski/listarrays

Functional tools for working with R arrays
https://github.com/t-kalinowski/listarrays

Last synced: 10 days ago
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Functional tools for working with R arrays

• Host: GitHub
• URL: https://github.com/t-kalinowski/listarrays
• Owner: t-kalinowski
• License: gpl-3.0
• Created: 2018-02-25T20:52:23.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2024-04-19T14:36:33.000Z (7 months ago)
• Last Synced: 2024-10-12T04:47:39.837Z (25 days ago)
• Language: R
• Homepage: https://t-kalinowski.github.io/listarrays/
• Size: 543 KB
• Stars: 14
• Watchers: 3
• Forks: 2
• Open Issues: 6
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE.md

Awesome Lists containing this project

README

        
---

output: github_document

---

```{r setup, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# listarrays

[![CRAN status](https://www.r-pkg.org/badges/version/listarrays)](https://cran.r-project.org/package=listarrays)

[![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/last-month/listarrays?color=blue)](https://r-pkg.org/pkg/listarrays)

A toolbox for working with R arrays in a functional programming style. Flexibly

split, bind, reshape, modify, subset, and name arrays.

The package provides:

+  `split_on_dim()` and `split_along_dim()` which take an array and return a list.

    

+  `bind_on_dim()` and `bind_as_dim()` take a list and return an array.

    

+  `modify_along_dim()` takes an array, calls the passed function `.f()` on each

    subset of the specified dimension, and returns an array of the same shape.

    (think of this as a safer and sometimes faster alternative to `base::apply()` 

    that is guaranteed to return an array of the same shape as it received)

    

+  `extract_dim()` a wrapper around `[` that allows you to specify the dimension 

   being subset as a function argument. For example, `extract_dim(X, 1, idx)`

   will extract `idx` on the first dimension, regardless how many dimensions are in 

   the array `X`.  Contrast this with the base alternative `X[idx,,]`, where you

   have to match the number of commas `,` to the number of dimensions in `X`.

    

+  Many of the functions have two variants `*_rows()` and `*_cols()` for the two 

   most common case of the first and last dimension. For example 

   `split_on_rows()` which is equivalent to `split_on_dim(X, 1)` and 

   `split_on_cols()` which is equivalent to `split_on_dim(X, -1)`

    

*  `set_dim()` and `set_dimnames()`, pipe-friendly and more flexible

    versions of `dim<-` and `dimnames<-`

    

*   `dim2()<-`,  `set_dim2()`, `array2()`, which reshape or fills arrays using

    row-major (C-style) semantics

    

*  A handful of lower-level helpers that abstract out patterns commonly

   encountered while working with arrays, for example `expand_dims()` 

   (the inverse of `base::drop()`, or `seq_along_rows()` (a

   combination of `seq_along()` and `nrow()`).

*  A set of functions that help encode atomic vectors as `onehot()` binary

   matrix's and `decode_onehot()` back into atomic vectors. (for example if

   training a neural network with keras)

*  Many of the functions work recursively if provided a list of arrays. 

## Installation

You can install listarrays from CRAN with:

```{r, eval=FALSE}

install.packages("listarrays")

```

Or install the development version from github with:

``` {r, eval=FALSE}

devtools::install_github("t-kalinowski/listarrays")

```