Package index

Base R plotting

splot(): Base R Graphics Network Plotting
sn_save(): Save Network Visualization

Plotting based on `ggplot2`

soplot() sn_render(): Plot Cograph Network
sn_ggplot(): Convert Network to ggplot2
sn_save_ggplot(): Save as ggplot2

Transition Network Analysis

from_tna(): Convert a tna object to cograph parameters
plot_tna() tplot(): TNA-Style Network Plot (qgraph Compatible)
plot_htna() htna(): Plot Heterogeneous TNA Network (Multi-Group Layout)

Multi-Cluster TNA Network Plot

plot_mtna() mtna(): Multi-Cluster TNA Network Plot

Multilevel Network Visualization

plot_mlna() mlna(): Multilevel Network Visualization

Network functions

cograph(): Create a Network Visualization
as_cograph() to_cograph(): Convert to Cograph Network
n_nodes(): Get Number of Nodes
n_edges(): Get Number of Edges
get_edges(): Get Edges from Cograph Network
get_labels(): Get Labels from Cograph Network
get_nodes(): Get Nodes from Cograph Network
set_edges(): Set Edges in Cograph Network
set_nodes(): Set Nodes in Cograph Network
sn_edges(): Set Edge Aesthetics
sn_ggplot(): Convert Network to ggplot2
sn_nodes(): Set Node Aesthetics
sn_save(): Save Network Visualization
aes-nodes: Node Aesthetics
aes-edges: Edge Aesthetics
output-save: Output and Saving
from_qgraph(): Convert a qgraph object to cograph parameters

Palettes

list_palettes(): List Available Color Palettes
sn_palette(): Apply Color Palette to Network
palette_blues(): Blues Palette
palette_colorblind(): Colorblind-friendly Palette
palette_diverging(): Diverging Palette
palette_pastel(): Pastel Palette
palette_rainbow(): Rainbow Palette
palette_reds(): Reds Palette
palette_viridis(): Viridis Palette
palettes: Color Palettes

Shapes

get_shape(): Get a Registered Shape
list_shapes(): List Available Shapes
list_svg_shapes(): List Registered SVG Shapes
register_shape(): Register a Custom Shape
register_svg_shape(): Register Custom SVG Shape
unregister_svg_shape(): Unregister SVG Shape

Themes

get_theme(): Get a Registered Theme
list_themes(): List Available Themes
sn_theme(): Apply Theme to Network
register_theme(): Register a Custom Theme
theme_cograph_classic(): Classic Theme
theme_cograph_colorblind(): Colorblind-friendly Theme
theme_cograph_dark(): Dark Theme
theme_cograph_gray(): Grayscale Theme
theme_cograph_minimal(): Minimal Theme
theme_cograph_nature(): Nature Theme
theme_cograph_viridis(): Viridis Theme

Layouts

get_layout(): Get a Registered Layout
set_layout(): Set Layout in Cograph Network
sn_layout(): Apply Layout to Network
layout-circle: Circular Layout
layout-groups: Group-based Layout
layout-oval: Oval/Ellipse Layout
layout-spring: Fruchterman-Reingold Spring Layout
layout_circle(): Circular Layout
layout_groups(): Group-based Layout
layout_oval(): Oval Layout
layout_spring(): Fruchterman-Reingold Spring Layout
list_layouts(): List Available Layouts
register_layout(): Register a Custom Layout

Motif Analysis

motif_census() print(<cograph_motifs>): Network Motif Analysis
extract_motifs() print(<cograph_motif_analysis>): Extract Motifs from Network Data
extract_triads(): Extract Triads with Node Labels
triad_census(): Triad Census

All Other Functions

centrality(): Calculate Network Centrality Measures
centrality_alpha(): Alpha (Katz) Centrality
centrality_authority() centrality_hub(): HITS Authority and Hub Scores
centrality_betweenness(): Betweenness Centrality
centrality_closeness() centrality_incloseness() centrality_outcloseness(): Closeness Centrality
centrality_constraint(): Burt's Constraint
centrality_coreness(): K-Core Decomposition (Coreness)
centrality_current_flow_betweenness(): Current Flow Betweenness Centrality
centrality_current_flow_closeness(): Current Flow Closeness Centrality
centrality_degree() centrality_indegree() centrality_outdegree(): Degree Centrality
centrality_diffusion(): Diffusion Centrality
centrality_eccentricity() centrality_ineccentricity() centrality_outeccentricity(): Eccentricity
centrality_eigenvector(): Eigenvector Centrality
centrality_harmonic() centrality_inharmonic() centrality_outharmonic(): Harmonic Centrality
centrality_kreach(): Geodesic K-Path Centrality
centrality_laplacian(): Laplacian Centrality
centrality_leverage(): Leverage Centrality
centrality_load(): Load Centrality
centrality_pagerank(): PageRank Centrality
centrality_percolation(): Percolation Centrality
centrality_power(): Bonacich Power Centrality
centrality_strength() centrality_instrength() centrality_outstrength(): Strength Centrality (Weighted Degree)
centrality_subgraph(): Subgraph Centrality
centrality_transitivity(): Local Transitivity (Clustering Coefficient)
centrality_voterank(): VoteRank Centrality
community_consensus() com_consensus(): Consensus Community Detection
community_edge_betweenness() com_eb(): Edge Betweenness Community Detection
community_fast_greedy() com_fg(): Fast Greedy Community Detection
community_fluid() com_fl(): Fluid Communities Detection
community_infomap() com_im(): Infomap Community Detection
community_label_propagation() com_lp(): Label Propagation Community Detection
community_leading_eigenvector() com_le(): Leading Eigenvector Community Detection
community_leiden() com_ld(): Leiden Community Detection
community_louvain() com_lv(): Louvain Community Detection
community_optimal() com_op(): Optimal Community Detection
community_sizes(): Get Community Sizes
community_spinglass() com_sg(): Spinglass Community Detection
community_walktrap() com_wt(): Walktrap Community Detection
select_bridges(): Select Bridge Edges
select_component(): Select Connected Component
select_edges(): Select Edges with Lazy Computation
select_edges_between(): Select Edges Between Node Sets
select_edges_involving(): Select Edges Involving Nodes
select_neighbors(): Select Node Neighbors (Ego Network)
select_nodes(): Select Nodes with Lazy Centrality Computation
select_top(): Select Top N Nodes by Centrality
select_top_edges(): Select Top N Edges
filter_edges() subset_edges(): Filter Edges by Metadata
filter_nodes() subset_nodes(): Filter Nodes by Metadata or Centrality
network_bridges(): Bridge Edges
network_clique_size(): Largest Clique Size
network_cut_vertices(): Cut Vertices (Articulation Points)
network_girth(): Network Girth (Shortest Cycle Length)
network_global_efficiency(): Global Efficiency
network_local_efficiency(): Local Efficiency
network_radius(): Network Radius
network_rich_club(): Rich Club Coefficient
network_small_world(): Small-World Coefficient (Sigma)
network_summary(): Network-Level Summary Statistics
network_vertex_connectivity(): Network Vertex Connectivity
as_cograph() to_cograph(): Convert to Cograph Network
to_data_frame() to_df(): Export Network as Edge List Data Frame
to_igraph(): Convert Network to igraph Object
to_matrix(): Convert Network to Adjacency Matrix
to_network(): Convert Network to statnet network Object
plot_alluvial(): Plot Alluvial Diagram
plot_chord(): Chord Diagram
plot_compare(): Plot Network Difference
plot_comparison_heatmap(): Plot Comparison Heatmap
plot_edge_diff_forest(): Forest Plot for Bootstrap Edge Differences
splot.group_tna_permutation() plot_group_permutation(): Plot Group Permutation Test Results
plot_heatmap(): Plot Network as Heatmap
plot_htna() htna(): Plot Heterogeneous TNA Network (Multi-Group Layout)
plot_mcml(): Plot Multi-Cluster Multi-Layer Network
plot_mixed_network(): Plot Mixed Network
plot_ml_heatmap(): Multilayer Network Heatmap
plot_mlna() mlna(): Multilevel Network Visualization
plot_mtna() mtna(): Multi-Cluster TNA Network Plot
plot_netobject_group() plot(<netobject_group>): Plot a Group of Nestimate netobjects
plot_netobject_ml() plot(<netobject_ml>): Plot a Multilevel Nestimate netobject
splot.tna_permutation() plot_permutation(): Plot Permutation Test Results
plot_robustness(): Plot Network Robustness
plot_simplicial(): Simplicial Complex Visualization
plot_tna() tplot(): TNA-Style Network Plot (qgraph Compatible)
plot_trajectories(): Plot Individual Trajectories
plot_transitions(): Plot Transitions Between States
CographLayout: CographLayout R6 Class
CographNetwork: CographNetwork R6 Class
CographTheme: CographTheme R6 Class
aggregate_layers() lagg(): Aggregate Layers
aggregate_weights() wagg(): Aggregate Edge Weights
cluster_quality() cqual(): Cluster Quality Metrics
cluster_summary() csum(): Cluster Summary Statistics
cograph-main: Main Entry Point
cograph-package: cograph: Modern Network Visualization for R
color_communities(): Color Nodes by Community
communities(): Community Detection
compare_communities(): Compare Community Structures
degree_distribution(): Degree Distribution Visualization
detect_communities(): Detect Communities in a Network
edge_centrality() edge_betweenness(): Calculate Edge Centrality Measures
get_edge_list(): Extract Raw Edge List from TNA Model
get_groups(): Get Node Groups from Cograph Network
get_shape(): Get a Registered Shape
ggplot_robustness(): Compare Network Robustness (ggplot2)
is_directed(): Check if Network is Directed
is_tna_network(): Check if Network is TNA-based
membership.cograph_communities(): Get Community Membership
modularity.cograph_communities(): Get Modularity Score
mcml() deprecated: mcml - Deprecated alias for cluster_summary
n_communities(): Get Number of Communities
nodes(): Get Nodes from Cograph Network (Deprecated)
robustness(): Network Robustness Analysis
robustness_auc(): Calculate Area Under Robustness Curve (AUC)
robustness_summary(): Summary of Robustness Analysis
set_groups(): Set Node Groups
supra_adjacency() supra(): Supra-Adjacency Matrix
supra_interlayer() extract_interlayer(): Extract Inter-Layer Block
supra_layer() extract_layer(): Extract Layer from Supra-Adjacency Matrix
verify_with_igraph() verify_igraph(): Verify Against igraph
layer_degree_correlation() ldegcor(): Degree Correlation Between Layers
layer_similarity() lsim(): Layer Similarity
layer_similarity_matrix() lsim_matrix(): Pairwise Layer Similarities
themes-builtin: Built-in Themes
motifs() print(<cograph_motif_result>) plot(<cograph_motif_result>): Network Motif Analysis
print(<cograph_communities>): Print Community Structure
print(<cograph_network>): Print cograph_network Object
plot(<cograph_cluster_significance>): Plot Cluster Significance
plot(<cograph_communities>): Plot Community Structure
plot(<cograph_motif_analysis>): Plot Motif Analysis Results
plot(<cograph_motifs>): Plot Network Motifs
plot(<cograph_network>): Plot cograph_network Object
plot(<tna_disparity>): Plot Disparity Filter Result
summary(<cograph_network>): Summary of cograph_network Object
splot.tna_bootstrap(): Plot Bootstrap Results
splot.tna_disparity(): Plot Disparity Results with splot
abbrev_label() label_abbrev(): Abbreviate Labels
as_mcml(): Convert to mcml
as_tna(): Convert cluster_summary to tna Objects
build_mcml(): Build MCML from Raw Transition Data
cluster_significance() csig(): Test Significance of Community Structure
cograph(): Create a Network Visualization
disparity_filter(): Disparity Filter
from_qgraph(): Convert a qgraph object to cograph parameters
from_tna(): Convert a tna object to cograph parameters
get_data(): Get Original Data from Cograph Network
get_edges(): Get Edges from Cograph Network
get_labels(): Get Labels from Cograph Network
get_layout(): Get a Registered Layout
get_meta(): Get Metadata from Cograph Network
get_nodes(): Get Nodes from Cograph Network
get_source(): Get Source Type from Cograph Network
get_theme(): Get a Registered Theme
coding coding_detailed ai_coding ai_detailed human_ai human_ai_detailed: Human-AI Interaction Coding Sequences
layout_circle(): Circular Layout
layout_groups(): Group-based Layout
layout_oval(): Oval Layout
layout_spring(): Fruchterman-Reingold Spring Layout
list_layouts(): List Available Layouts
list_palettes(): List Available Color Palettes
list_shapes(): List Available Shapes
list_svg_shapes(): List Registered SVG Shapes
list_themes(): List Available Themes
n_edges(): Get Number of Edges
n_nodes(): Get Number of Nodes
overlay_communities(): Overlay Community Blobs on a Network Plot
palette_blues(): Blues Palette
palette_colorblind(): Colorblind-friendly Palette
palette_diverging(): Diverging Palette
palette_pastel(): Pastel Palette
palette_rainbow(): Rainbow Palette
palette_reds(): Reds Palette
palette_viridis(): Viridis Palette
palettes: Color Palettes
register_layout(): Register a Custom Layout
register_shape(): Register a Custom Shape
register_svg_shape(): Register Custom SVG Shape
register_theme(): Register a Custom Theme
render-ggplot: ggplot2 Conversion
render-grid: Grid Rendering
set_edges(): Set Edges in Cograph Network
set_layout(): Set Layout in Cograph Network
set_nodes(): Set Nodes in Cograph Network
simplify(): Simplify a Network
sn_edges(): Set Edge Aesthetics
sn_ggplot(): Convert Network to ggplot2
sn_layout(): Apply Layout to Network
sn_nodes(): Set Node Aesthetics
sn_palette(): Apply Color Palette to Network
sn_save(): Save Network Visualization
sn_save_ggplot(): Save as ggplot2
sn_theme(): Apply Theme to Network
soplot() sn_render(): Plot Cograph Network
splot(): Base R Graphics Network Plotting
student_interactions: Student Interaction Edge List
subgraphs(): Extract Specific Motif Instances (Subgraphs)
summarize_network() cluster_network() cnet(): Summarize Network by Clusters
theme_cograph_classic(): Classic Theme
theme_cograph_colorblind(): Colorblind-friendly Theme
theme_cograph_dark(): Dark Theme
theme_cograph_gray(): Grayscale Theme
theme_cograph_minimal(): Minimal Theme
theme_cograph_nature(): Nature Theme
theme_cograph_viridis(): Viridis Theme
unregister_svg_shape(): Unregister SVG Shape

Base R plotting

Plotting based on ggplot2

Transition Network Analysis

Multi-Cluster TNA Network Plot

Multilevel Network Visualization

Network functions

Palettes

Shapes

Themes

Layouts

Motif Analysis

All Other Functions

Plotting based on `ggplot2`