TDAmapper: Analyze High-Dimensional Data Using Discrete Morse Theory

Topological Data Analysis using Mapper (discrete Morse theory). Generate a 1-dimensional simplicial complex from a filter function defined on the data: 1. Define a filter function (lens) on the data. 2. Perform clustering within within each level set and generate one node (vertex) for each cluster. 3. For each pair of clusters in adjacent level sets with a nonempty intersection, generate one edge between vertices. The function mapper1D uses a filter function with codomain R, while the the function mapper2D uses a filter function with codomain R^2.

Version: 1.0
Depends: R (≥ 3.1.2)
Suggests: fastcluster, igraph
Published: 2015-05-31
Author: Paul Pearson [aut, cre, trl], Daniel Muellner [aut, ctb], Gurjeet Singh [aut, ctb]
Maintainer: Paul Pearson <pearsonp at hope.edu>
BugReports: https://github.com/paultpearson/TDAmapper/issues
License: GPL-3
URL: https://github.com/paultpearson/TDAmapper/
NeedsCompilation: no
Materials: README
CRAN checks: TDAmapper results

Downloads:

Reference manual: TDAmapper.pdf
Package source: TDAmapper_1.0.tar.gz
Windows binaries: r-devel: TDAmapper_1.0.zip, r-release: TDAmapper_1.0.zip, r-oldrel: TDAmapper_1.0.zip
OS X El Capitan binaries: r-release: TDAmapper_1.0.tgz
OS X Mavericks binaries: r-oldrel: TDAmapper_1.0.tgz

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