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nextnetr

https://github.com/oist/nextnetr

Science Score: 44.0%

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Repository

Basic Info
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  • Stars: 0
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  • Open Issues: 0
  • Releases: 2
Created about 1 year ago · Last pushed 9 months ago
Metadata Files
Readme License Citation

README.md

Introduction

NEXTNetR (Next-reaction-based Epidemics eXtended to Temporal Networks) is an R package for the efficient simulation of epidemics on complex networks (including weighted and temporal networks) with arbitrary transmission and recovery time distributions. NEXTNetR is an R wrapper around the C++ library NEXTNet.

See the NEXTNetR website for a reference and usage examples.

Installation

If Git is available, the latest released version of NEXTNetR can be installed directly from Github by executing the following in R:

install.packages("remotes")
remotes::install_github("oist/NEXTNetR", ref="latest-release")

Alternatively, download the latest released version of NEXTNetR-v<version>-pkg.tar.gz. Then make sure all required dependencies are installed with install.packages(c("BH", "cpp11", "rappdirs")) and install NEXTNetR on the command line (not within R) with

R CMD INSTALL NEXTNetR-v<version>-pkg.tar.gz

Since NEXT-Net is implemented in C++, a C++ compiler is required to install NEXTNetR. On Linux a compiler should typically be already available, on Mac OS R a suitable compiler is provided by XCode or the XCode Command Line Tools, and on Windows by RTools.

Synopsis

The following minimal example simulated an epidemic on an Erdős–Rényi network with lognormally distributed transmission time

library(NEXTNetR)
sim <- simulation(
    erdos_renyi_network(1e5, 5),
    lognormal_time(6, 30, 0.1))
simulation_addinfections(sim, 1, 0.0)
r <- simulation_run(sim, stop=list(total_infected=300e3))
plot(r$time, r$infected, type='l')

See Getting Started for a step-by-step walkthrough of NEXTNetR's features.

NEXTNetR offers a range of common types of artifical networks such as Erdős–Rényi, Barabási–Albert and Watts–Strogatz, and can run simulations on arbitrary empirical weighted networks defined by an adjacency list. NEXTNetR also allows simulations on temporal networks, i.e. networks which change over time, possibly in response to epidemic events. Amongst the temporal networks currently supported by NEXTNetR are empirical networks defined by contact times between nodes, activity-driven networks, and networks defined by the proximity of diffusing particles.

Documentation

See https://oist.github.io/NEXTNetR/.

Owner

  • Name: Okinawa Institute of Science & Technology
  • Login: oist
  • Kind: organization
  • Email: webmaster@oist.jp
  • Location: Okinawa, Japan

Citation (CITATION.cff) 

cff-version: 1.2.0
message: If you use this software, please cite the article from preferred-citation.
authors:
  - family-names: Cure
    given-names: Samuel
  - family-names: Pflug
    given-names: Florian G.
    orcid: https://orcid.org/0000-0002-5344-5359
title: NEXT-NET
version: '0.9'
doi: 10.48550/arXiv.2412.07095
date-released: '2024-04-12'
preferred-citation:
  type: article
  status: preprint
  authors:
    - family-names: Cure
      given-names: Samuel
    - family-names: Pflug
      given-names: Florian G.
    - family-names: Pigolotti
      given-names: Simone
  title: Fast and exact simulations of stochastic epidemics on static and temporal networks
  year: 2024
  journal: arXiv
  number: '2412.07095'
  doi: 10.48550/arXiv.2412.07095

GitHub Events

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Last Year
  • Release event: 6
  • Delete event: 3
  • Push event: 167
  • Public event: 1
  • Create event: 11

Dependencies

DESCRIPTION cran
.github/workflows/pkgdown.yaml actions
  • JamesIves/github-pages-deploy-action v4.5.0 composite
  • actions/checkout v4 composite
  • r-lib/actions/setup-pandoc v2 composite
  • r-lib/actions/setup-r v2 composite
  • r-lib/actions/setup-r-dependencies v2 composite