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https://github.com/r-hyperspec/unmixR

N-FINDR, Vertex Component Analysis (VCA) and Iterative Constrained Endmember (ICE) algorithms for hyperspectral unmixing in R.
https://github.com/r-hyperspec/unmixR

Last synced: 2 months ago
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N-FINDR, Vertex Component Analysis (VCA) and Iterative Constrained Endmember (ICE) algorithms for hyperspectral unmixing in R.

Host: GitHub
URL: https://github.com/r-hyperspec/unmixR
Owner: r-hyperspec
License: mit
Created: 2022-01-26T14:36:22.000Z (over 2 years ago)
Default Branch: develop
Last Pushed: 2023-07-14T16:26:05.000Z (about 1 year ago)
Last Synced: 2024-06-11T05:34:02.213Z (4 months ago)
Language: R
Homepage: https://r-hyperspec.github.io/unmixR/
Size: 63.4 MB
Stars: 2
Watchers: 1
Forks: 0
Open Issues: 15
Metadata Files:
- Readme: README.md
- License: LICENSE

Awesome Lists containing this project

README

        # `unmixR`: An R Package for Unmixing of Hyperspectral Images

[![R-CMD-check](https://github.com/r-hyperspec/unmixR/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/r-hyperspec/unmixR/actions/workflows/R-CMD-check.yaml)

[![Test coverage](https://github.com/r-hyperspec/unmixR/actions/workflows/test-coverage.yaml/badge.svg)](https://github.com/r-hyperspec/unmixR/actions/workflows/test-coverage.yaml)

[![Codecov test coverage](https://codecov.io/gh/r-hyperspec/unmixR/branch/develop/graph/badge.svg)](https://app.codecov.io/gh/r-hyperspec/unmixR?branch=develop)

[![Website (pkgdown)](https://github.com/r-hyperspec/unmixR/actions/workflows/pkgdown.yaml/badge.svg)](https://github.com/r-hyperspec/unmixR/actions/workflows/pkgdown.yaml)

[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)

[![Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.](https://www.repostatus.org/badges/latest/wip.svg)](https://www.repostatus.org/#wip)

This `README` is for GitHub only. `pkgdown` website currently has a separate `README`.




`unmixR` is **WORK IN PROGRESS**.




The fundamental structures & behavior may change.

For the time being, use at your own risk.

Hyperspectral data are also called 'imaging spectroscopy' and 'imaging spectrometer data' depending upon the discipline.

Such data consists of spectra collected over an x, y grid.

Data sets like this are found in airborne land imaging studies, biomedical studies and art history investigations.

The spectra are often visible, infrared, near-infrared, raman spectra or mass spectrometer data sets.

## Installation

**Installation:** works easiest using `remotes::install_git()`:

```r

library("remotes")

remotes::install_github("r-hyperspec/unmixR", subdir = "pkg/unmixR")

```

## Acknoledgements

Development of `unmixR` has been supported by Google Summer of Code 2013 (Conor McManus) and 2016 (Anton Belov). 

Thank you Google!

![GSOC 2016 logo](https://gitlab.com/chemometrics/unmixR/raw/master/GSoC2016Logo.png)