Package: wdnet 1.2.4

Yelie Yuan

wdnet: Weighted and Directed Networks

Assortativity coefficients, centrality measures, and clustering coefficients for weighted and directed networks. Rewiring unweighted networks with given assortativity coefficients. Generating general preferential attachment networks.

Authors:Yelie Yuan [aut, cre], Tiandong Wang [aut], Jun Yan [aut], Panpan Zhang [aut]

wdnet_1.2.4.tar.gz
wdnet_1.2.4.tar.gz(r-4.7-arm64)wdnet_1.2.4.tar.gz(r-4.7-x86_64)wdnet_1.2.4.tar.gz(r-4.6-arm64)wdnet_1.2.4.tar.gz(r-4.6-x86_64)
wdnet_1.2.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
wdnet/json (API)
NEWS

# Install 'wdnet' in R:
install.packages('wdnet', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://gitlab.com/wdnetwork/wdnet

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

openblascpp

1.70 score 8 scripts 558 downloads 17 exports 28 dependencies

Last updated from:782212815d. Checks:6 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK170
linux-devel-x86_64OK156
source / vignettesOK230
linux-release-arm64OK194
linux-release-x86_64OK159
wasm-releaseOK155

Exports:adj_to_wdnetassortcoefcentralityclustcoefcvxr_controldprewiredprewire.rangeedgelist_to_wdnetigraph_to_wdnetis_wdnetrpa_control_edgeweightrpa_control_newedgerpa_control_preferencerpa_control_reciprocalrpa_control_scenariorpanetwdnet_to_igraph

Dependencies:backportscheckmateclarabelclicpp11CVXRgluegmphighsigraphlatticelifecyclemagrittrMatrixosqppkgconfigrARPACKRcppRcppArmadilloRcppEigenRcppXPtrUtilsrlangRSpectraS7scsslamvctrswdm