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R ndtv package for network animation. Use for visualizing and animating dynamic networks.
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Basé sur la classification professionnelle SOC
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 | ndtv |
| description | R ndtv package for network animation. Use for visualizing and animating dynamic networks. |
Network dynamic temporal visualization.
library(ndtv)
# Compute layout for animation
compute.animation(dnet,
animation.mode = "kamadakawai",
slice.par = list(
start = 0,
end = 10,
interval = 1,
aggregate.dur = 1
))
# HTML/D3 animation
render.d3movie(dnet, filename = "network.html")
# GIF animation
render.animation(dnet, filename = "network.gif")
# Video
render.animation(dnet, filename = "network.mp4",
ani.options = list(interval = 0.1))
render.d3movie(dnet,
# Vertex appearance
vertex.col = "blue",
vertex.cex = 1.5,
vertex.sides = 50, # Circle
# Edge appearance
edge.col = "gray",
edge.lwd = 1,
# Labels
displaylabels = TRUE,
label.cex = 0.8,
label.col = "black",
# Output
filename = "network.html",
output.mode = "htmlWidget"
)
# Color by attribute
render.d3movie(dnet,
vertex.col = function(slice) {
get.vertex.attribute(slice, "group")
})
# Size by degree
render.d3movie(dnet,
vertex.cex = function(slice) {
degree(slice) / 5
})
# Add timeline
timeline(dnet,
slice.par = list(start = 0, end = 10, interval = 1))
# Filmstrip view
filmstrip(dnet, displaylabels = TRUE)
# Available modes
compute.animation(dnet, animation.mode = "kamadakawai")
compute.animation(dnet, animation.mode = "MDSJ")
compute.animation(dnet, animation.mode = "Graphviz")
compute.animation(dnet, animation.mode = "useAttribute")
# Proximity timeline plot
proximity.timeline(dnet,
default.dist = 10,
mode = "sammon")
# Export individual frames
for (t in 0:10) {
net_t <- network.extract(dnet, at = t)
png(paste0("frame_", t, ".png"))
plot(net_t)
dev.off()
}