https://github.com/nvinuesa/sparsal

Sparse approximation library
https://github.com/nvinuesa/sparsal

scala signal-processing sparse sparse-coding

Last synced: 23 days ago
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Sparse approximation library

• Host: GitHub
• URL: https://github.com/nvinuesa/sparsal
• Owner: nvinuesa
• License: mit
• Created: 2017-01-06T21:07:34.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2017-05-14T18:32:59.000Z (over 7 years ago)
• Last Synced: 2023-07-01T01:06:14.682Z (over 1 year ago)
• Topics: scala, signal-processing, sparse, sparse-coding
• Language: Scala
• Homepage:
• Size: 22.5 KB
• Stars: 5
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

        
## sparsal - Sparse Approximation Library

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

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## Overview

The Sparse Approximation Library aims to provide easy-to-read, modern and maintainable sparse approximation algorithms written in a functional style.




At the moment only [the matching pursuit algorithm][mp] is implemented. Future versions will increment the number of algorithms.




Check [this article][blog] for some basic theoretical background.

[blog]: https://underscorenico.github.io/blog/2017/01/14/about-sparsal

[mp]: https://en.wikipedia.org/wiki/Matching_pursuit

## Using sparsal

Builds are available for scala 2.10.x, 2.11.x and 2.12.2.

### SBT

Simply add sparsal's dependency to your build.sbt if you don't know which version of scala you are using and sbt will automatically detect and search for the appropriate package:

```scala

libraryDependencies += "com.github.underscorenico" %% "sparsal" % "0.2.0"

```

Or either specify the desired target version:

```scala

libraryDependencies += "com.github.underscorenico" % "sparsal_2.12" % "0.2.0"

```

### Maven

If you are using Maven, simply add sparsal to your dependencies to your pom.xml:

```xml

    com.github.underscorenico

    sparsal_2.12

    0.2.0

```

### Try it

First initialize your MatchingPursuit (or Orthogonal Matching Pursuit) object with an input and a defined dictionary:

```scala

val input = Array.fill(10)(5)

val dictionary = Gabor(input.length)

val mp =  MatchingPursuit1D(input, dictionary)

```

Then recover the approximation (after the algorithm converges to a certain provided accuracy measure):

```scala

    val result: (List[(Double, Int)], Seq[Double]) = mp.run(SNR(20.0))

```

The result will contain a list of selected atoms from the dictionary. The first element of the touple (type Double) will contain the inner product between the input at Iteration n-1 and the selected atom. 




The second element contains the index of the atom from the dictionary.

## Contributing

Everyone is welcome to contribute, either by adding features, solving bugs or helping with documentation.




Sparsal embraces [the open code of conduct][codeofconduct] from the [TODO group][todogroup], therefore all of its channels should respect its guidelines.




That being said, we are a community and we should not need guidelines for our conduct but leave it to our common sense instead.

[codeofconduct]: http://todogroup.org/opencodeofconduct

[todogroup]: http://todogroup.org