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R dynamic/temporal networks with ndtv, networkDynamic, tsna. Use for time-varying networks and network evolution.
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R language data analysis and visualization skill. Use when user asks to (1) run R scripts or code, (2) install/update R packages, (3) perform data analysis with R, (4) create visualizations with ggplot2/plotly, (5) statistical analysis, (6) data manipulation with tidyverse/dplyr/data.table. Triggers on keywords like "R语言", "R脚本", "ggplot", "tidyverse", "数据分析", "可视化".
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| name | r-network-dynamic |
| description | R dynamic/temporal networks with ndtv, networkDynamic, tsna. Use for time-varying networks and network evolution. |
Temporal and evolving networks.
library(networkDynamic)
# Create dynamic network
dnet <- networkDynamic(
network.list = list(net_t1, net_t2, net_t3),
onsets = c(0, 1, 2),
termini = c(1, 2, 3)
)
# Add/remove edges over time
activate.edges(dnet, onset = 1, terminus = 3, e = 1:5)
deactivate.edges(dnet, onset = 2, terminus = 3, e = 3)
# Query at time point
network.extract(dnet, at = 1.5)
network.extract(dnet, onset = 0, terminus = 2)
# Edge/vertex activity
is.active(dnet, at = 1, e = 1:10)
get.edge.activity(dnet, e = 1)
library(ndtv)
# Compute animation
compute.animation(dnet, animation.mode = "kamadakawai")
# Render animation
render.d3movie(dnet, filename = "network.html")
render.animation(dnet, filename = "network.gif")
# Customize
render.d3movie(dnet,
vertex.col = "blue",
edge.col = "gray",
displaylabels = TRUE
)
library(tsna)
# Temporal paths
tPath(dnet, v = 1, start = 0, end = 10)
# Reachability
tReach(dnet, direction = "fwd")
# Temporal metrics
tDegree(dnet)
tSnaStats(dnet, snafun = "betweenness")