Implementation of network diffusion algorithms such as heat diffusion or Markov random walks. Network diffusion algorithms generally spread information in the form of node weights along the edges of a graph to other nodes. These weights can for example be interpreted as temperature, an initial amount of water, the activation of neurons in the brain, or the location of a random surfer in the internet. The information (node weights) is iteratively propagated to other nodes until a equilibrium state or stop criterion occurs.
Version: | 0.1.4 |
Depends: | R (≥ 3.4) |
Imports: | Rcpp, igraph, methods |
LinkingTo: | Rcpp, RcppEigen |
Suggests: | knitr, rmarkdown, testthat, lintr, Matrix |
Published: | 2018-05-17 |
Author: | Simon Dirmeier [aut, cre] |
Maintainer: | Simon Dirmeier <simon.dirmeier at gmx.de> |
BugReports: | https://github.com/dirmeier/diffusr/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/dirmeier/diffusr |
NeedsCompilation: | yes |
SystemRequirements: | C++11 |
Materials: | NEWS |
CRAN checks: | diffusr results |
Reference manual: | diffusr.pdf |
Vignettes: |
The diffusr tutorial |
Package source: | diffusr_0.1.4.tar.gz |
Windows binaries: | r-devel: diffusr_0.1.4.zip, r-release: diffusr_0.1.4.zip, r-oldrel: diffusr_0.1.4.zip |
macOS binaries: | r-release (arm64): diffusr_0.1.4.tgz, r-oldrel (arm64): diffusr_0.1.4.tgz, r-release (x86_64): diffusr_0.1.4.tgz, r-oldrel (x86_64): diffusr_0.1.4.tgz |
Old sources: | diffusr archive |
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