القائمة
R dynamic/temporal networks with ndtv, networkDynamic, tsna. Use for time-varying networks and network evolution.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
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")