umap

Uniform Manifold Approximation and Projection - R package

https://github.com/tkonopka/umap

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Keywords

dimensionality-reduction umap
Last synced: 6 months ago · JSON representation

Repository

Uniform Manifold Approximation and Projection - R package

Basic Info
  • Host: GitHub
  • Owner: tkonopka
  • License: other
  • Language: R
  • Default Branch: master
  • Homepage:
  • Size: 662 KB
Statistics
  • Stars: 133
  • Watchers: 8
  • Forks: 16
  • Open Issues: 4
  • Releases: 10
Topics
dimensionality-reduction umap
Created almost 8 years ago · Last pushed almost 2 years ago
Metadata Files
Readme License

README.md

umap

R implementation of Uniform Manifold Approximation and Projection

R-CMD-check CRAN

Uniform manifold approximation and projection (UMAP) is a technique for dimensional reduction. The original algorithm is described by McInnes, Heyes, and Melville and is implemented in a python package umap. This package provides an interface to the UMAP algorithm in R, including a translation of the original algorithm into R with minimal dependencies.

Examples

The figure below shows dimensional reduction on the MNIST digits dataset. This dataset consists of 70,000 observations in a 784-dimensional space and labeled by ten distinct classes. The output of this package's `umap' function provides the plot layout, i.e. the arrangement of dots on the plane. The coloring, added to visualize how the known labels are positioned within the layout, demonstrates separation of the underlying data groups.

A UMAP visualization of the MNIST digits dataset

The package also allows to project data onto an existing embedding. Below, the first figure shows a map created from a subset of 60,000 observations from the MNIST data. The second figure is a projection of the held-out 10,000 observations onto the layout defined by the training data.

A UMAP visualization of the MNIST digits dataset A UMAP visualization of the MNIST digits dataset

More information on usage can be found in the package vignettes.

Implementations

The package provides two implementations of the UMAP algorithm.

The default implementation is one written in R and Rcpp. This implementation follows the original python code. However, any bugs or errors should be regarded as arising solely from this implementation, not from the original. The implementation has minimal dependencies and should work on most platforms. (The MNIST graphic is generated based on this default implementation).

A second implementation is a wrapper for the python package. This offers similar functionality to another existing package umapr. To use this implementation, additional installation steps are required; see documentation for the python package for details.

Note: an independent R implementation of UMAP is also available in package uwot, also available on CRAN.

Acknowledgments

Many thanks to the R and github communities for comments, corrections, and bug reports.

References

The original UMAP algorithm is described in the following article

McInnes, Leland, and John Healy. "UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction." arXiv:1802.03426.

License

MIT License.

Owner

  • Name: Tomasz Konopka
  • Login: tkonopka
  • Kind: user

GitHub Events

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  • Watch event: 1
  • Issue comment event: 2
Last Year
  • Watch event: 1
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Last synced: over 2 years ago

All Time
  • Total Commits: 94
  • Total Committers: 3
  • Avg Commits per committer: 31.333
  • Development Distribution Score (DDS): 0.021
Past Year
  • Commits: 9
  • Committers: 1
  • Avg Commits per committer: 9.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
tkonopka t****a@g****m 92
JenniferSLyon 3****n@u****m 1
Tomasz Konopka t****a@u****m 1

Issues and Pull Requests

Last synced: 7 months ago

All Time
  • Total issues: 21
  • Total pull requests: 2
  • Average time to close issues: about 2 months
  • Average time to close pull requests: 2 days
  • Total issue authors: 19
  • Total pull request authors: 2
  • Average comments per issue: 2.76
  • Average comments per pull request: 2.5
  • Merged pull requests: 2
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  • Bot pull requests: 0
Past Year
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  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
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Top Authors
Issue Authors
  • JenniferSLyon (2)
  • gdkrmr (2)
  • ShanSabri (1)
  • BastienNguyen (1)
  • victor-moreno (1)
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  • HCMY (1)
  • bellenger-l (1)
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Packages

  • Total packages: 3
  • Total downloads:
    • cran 8,433 last-month
  • Total docker downloads: 56,797
  • Total dependent packages: 24
    (may contain duplicates)
  • Total dependent repositories: 127
    (may contain duplicates)
  • Total versions: 29
  • Total maintainers: 1
proxy.golang.org: github.com/tkonopka/umap
  • Versions: 4
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 7 months ago
cran.r-project.org: umap

Uniform Manifold Approximation and Projection

  • Versions: 14
  • Dependent Packages: 22
  • Dependent Repositories: 122
  • Downloads: 8,433 Last month
  • Docker Downloads: 56,797
Rankings
Dependent repos count: 1.9%
Stargazers count: 3.1%
Dependent packages count: 3.4%
Forks count: 4.1%
Downloads: 4.8%
Average: 6.4%
Docker downloads count: 21.1%
Maintainers (1)
Last synced: 7 months ago
conda-forge.org: r-umap
  • Versions: 11
  • Dependent Packages: 2
  • Dependent Repositories: 5
Rankings
Dependent repos count: 14.7%
Dependent packages count: 19.6%
Average: 26.0%
Stargazers count: 31.0%
Forks count: 38.7%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 3.6.0 depends
  • Matrix * imports
  • RSpectra * imports
  • Rcpp >= 0.12.6 imports
  • methods * imports
  • openssl * imports
  • reticulate * imports
  • stats * imports
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests
.github/workflows/R-CMD-check.yaml actions
  • actions/checkout v2 composite
  • actions/upload-artifact main composite
  • r-lib/actions/check-r-package v2 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite