https://github.com/zamorarr/tensorr

Sparse Tensors in R
https://github.com/zamorarr/tensorr

r rstats sparse sparse-tensors tensors

Last synced: about 1 month ago
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Sparse Tensors in R

• Host: GitHub
• URL: https://github.com/zamorarr/tensorr
• Owner: zamorarr
• Created: 2017-02-04T19:39:56.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2019-03-09T14:05:59.000Z (about 7 years ago)
• Last Synced: 2024-03-17T19:03:35.649Z (about 2 years ago)
• Topics: r, rstats, sparse, sparse-tensors, tensors
• Language: R
• Homepage: https://zamorarr.github.io/tensorr/
• Size: 226 KB
• Stars: 11
• Watchers: 4
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.Rmd

Awesome Lists containing this project

README

          
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "README-"

)

```

# tensorr: sparse tensors in R

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/tensorr)](https://cran.r-project.org/package=tensorr)

[![Build Status](https://travis-ci.org/zamorarr/tensorr.svg?branch=master)](https://travis-ci.org/zamorarr/tensorr) 

[![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/zamorarr/tensorr?branch=master&svg=true)](https://ci.appveyor.com/project/zamorarr/tensorr) 

[![Coverage Status](https://img.shields.io/codecov/c/github/zamorarr/tensorr/master.svg)](https://codecov.io/github/zamorarr/tensorr?branch=master)

`tensorr` provides methods to manipulate and store sparse tensors. Tensors are multi-dimensional generalizations of matrices (two dimensional) and vectors (one dimensional).

It has three main goals:

- Provide an efficient format to store sparse tensors in R.

- Provide standard tensor operations such as multiplication and unfolding.

- Provide standard tensor decomposition techniques such as CP and Tucker.

## Installation

The development version of **tensorr** is available on github.

```{r eval = FALSE}

devtools::install_github("zamorarr/tensorr")

```

## Usage

See the [introduction vignette](https://zamorarr.github.io/tensorr/articles/introduction.html)

for a comprehensive overview. To create a sparse tensor you have to provide the 

non-zero values, subscripts to the non-zero values, and the overall dimensions 

of the tensor.

```{r into-sparse, message = FALSE}

library(tensorr)

subs <- list(c(1,1,1), c(1,1,2))

vals <- c(10, 20)

dims <- c(2,2,2)

x <- sptensor(subs, vals, dims)

x

```

## Tensor References

Many of the dense and sparse implementation ideas were adpated from:

 - B. W. Bader and T. G. Kolda. Algorithm 862: MATLAB tensor classes for fast algorithm prototyping, ACM Transactions on Mathematical Software 32(4):635-653, December 2006.

- B. W. Bader and T. G. Kolda. Efficient MATLAB computations with sparse and factored tensors, SIAM Journal on Scientific Computing 30(1):205-231, December 2007.

- [scikit-tensor](https://github.com/mnick/scikit-tensor)

For a review on tensors, see:

- T. G. Kolda and B. W. Bader, Tensor Decompositions and Applications, SIAM Review 51(3):455-500, September 2009