Awesome-Mirrors/awesome-network-analysis
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standardize d3.js

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François Briatte 2019-06-14 11:52:56 +02:00
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@ -666,7 +666,7 @@ Inspired by [Awesome Deep Learning](https://github.com/ChristosChristofidis/awes
- [latentnet](https://CRAN.R-project.org/package=latentnet) - Latent position and cluster models for network objects.
- [levelnet](https://github.com/schochastics/levelnet) - Experimental package to analyze one-mode projections of bipartite (two-mode) networks. See also: `bipartite` R package.
- [lpNet](https://www.bioconductor.org/packages/release/bioc/html/lpNet.html) - Linear programming model aimed at infering biological (signalling, gene) networks.
- [networkD3](http://christophergandrud.github.io/networkD3/) - D3 JavaScript network graphs from R.
- [networkD3](http://christophergandrud.github.io/networkD3/) - Create d3.js network graphs from R.
- [ndtv](https://CRAN.R-project.org/package=ndtv) - Tools to construct animated visualizations of dynamic network data in various formats.
- [netdiffuseR](https://CRAN.R-project.org/package=netdiffuseR) - Tools to analyze the network diffusion of innovations.
- [netrankr](https://cran.r-project.org/package=netrankr) - Up-to-date collection of network centrality indices, with lots of documentation.