Package index

Base R plotting

splot.net_bootstrap() splot.tna_communities() splot.cograph_communities() splot.net_mlvar() splot.netobject() splot.boot_glasso() splot.wtna_mixed() splot.net_permutation() splot(): Plot Nestimate Bootstrap Results
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

Wrangling

Reshaping a network: selecting, thresholding, restructuring and editing. Every verb takes any supported input and returns a cograph_network.

network_wrangling: Network Wrangling Verbs
as.data.frame(<cograph_network>): Cograph Network as a Data Frame
filter_edges() subset_edges(): Filter Edges by Metadata
filter_nodes() subset_nodes(): Filter Nodes by Metadata or Centrality
select_nodes(): Select Nodes with Lazy Centrality Computation
select_edges(): Select Edges with Lazy Computation
select_neighbors(): Select Node Neighbors (Ego Network)
select_component(): Select Connected Component
select_top(): Select Top N Nodes by Centrality
select_bridges(): Select Bridge Edges
select_top_edges(): Select Top N Edges
select_edges_involving(): Select Edges Involving Nodes
select_edges_between(): Select Edges Between Node Sets
select_k_core(): Select the k-Core of a Network
split_components(): Split a Network into Its Connected Components
threshold_edges(): Threshold Edges by Weight, Count, Proportion or Density
binarize(): Binarize Edge Weights
symmetrize(): Symmetrize a Directed Network
normalize_weights(): Normalize Edge Weights
invert_weights(): Invert Edge Weights (Similarity to Distance and Back)
to_undirected(): Convert a Directed Network to Undirected
to_directed(): Convert an Undirected Network to Directed
reverse_edges(): Reverse Edge Direction
remove_isolates(): Remove Isolated Nodes
contract_nodes(): Contract Nodes into Groups
spanning_tree(): Minimum or Maximum Spanning Tree
complement_network(): Complement of a Network
reorder_nodes(): Reorder the Nodes of a Network
rename_nodes(): Rename Nodes
add_nodes(): Add Nodes to a Network
remove_nodes(): Remove Nodes from a Network
add_edges(): Add Edges to a Network
remove_edges(): Remove Edges from a Network
mutate_nodes(): Add or Change Node Attributes
mutate_edges(): Add or Change Edge Attributes
bind_networks(): Combine Two Networks
simplify(): Simplify a Network

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_access_information() centrality_hide_information(): Access and Hide Information
centrality_adaptive_leaderrank(): Adaptive LeaderRank centrality
centrality_alpha(): Alpha (Katz) Centrality
centrality_authority() centrality_hub(): HITS Authority and Hub Scores
centrality_average_distance(): Average Distance Centrality
centrality_barycenter(): Barycenter Centrality
centrality_beta_measure(): BG-index or beta power measure
centrality_betweenness(): Betweenness Centrality
centrality_bottleneck(): Bottleneck Centrality
centrality_bridging(): Bridging Centrality
centrality_bridging_capital(): Bridging capital from lost information walks
centrality_brokerage_coordinator(): Gould-Fernandez Brokerage — Coordinator Role
centrality_brokerage_gatekeeper(): Gould-Fernandez Brokerage — Gatekeeper Role
centrality_brokerage_itinerant(): Gould-Fernandez Brokerage — Itinerant (Consultant) Role
centrality_brokerage_liaison(): Gould-Fernandez Brokerage — Liaison Role
centrality_brokerage_representative(): Gould-Fernandez Brokerage — Representative Role
centrality_cda(): Clustering degree algorithm centrality
centrality_centroid(): Centroid Value
centrality_closeness() centrality_incloseness() centrality_outcloseness(): Closeness Centrality
centrality_closeness_vitality(): Closeness Vitality
centrality_clusterrank(): ClusterRank Centrality
centrality_coleman_theil(): Coleman-Theil hierarchy index
centrality_communicability(): Communicability Centrality
centrality_communicability_betweenness(): Communicability Betweenness Centrality
centrality_community_based() centrality_comm_centrality() centrality_community_mediator(): Community-Based Centrality, Comm Centrality and Community-Based Mediator
centrality_community_hub_bridge(): Community Hub-Bridge Centrality
centrality_constraint(): Burt's Constraint
centrality_controlrank(): ControlRank centrality
centrality_coreness(): K-Core Decomposition (Coreness)
centrality_cross_clique(): Cross-Clique Connectivity
centrality_current_flow_betweenness(): Current Flow Betweenness Centrality
centrality_current_flow_closeness(): Current Flow Closeness Centrality
centrality_dangalchev(): Dangalchev Closeness Centrality
centrality_decay(): Decay Centrality
centrality_degree() centrality_indegree() centrality_outdegree(): Degree Centrality
centrality_degree_discount() centrality_single_discount(): DegreeDiscountIC and SingleDiscount Rankings
centrality_diffusion(): Diffusion Centrality
centrality_diffusion_centrality(): Finite-horizon diffusion centrality
centrality_dil(): Degree and Importance of Lines
centrality_distance_entropy(): Distance Entropy
centrality_diversity(): Diversity Centrality
centrality_dkgm(): DK-based gravity model
centrality_dmnc(): Density of Maximum Neighborhood Component (DMNC)
centrality_dynamical_importance(): Dynamical importance by exact vertex deletion
centrality_dynamics_sensitive(): Dynamics-sensitive centrality
centrality_eccentricity() centrality_ineccentricity() centrality_outeccentricity(): Eccentricity
centrality_effective_size(): Effective Size (Burt's)
centrality_ehcc(): Extended hybrid characteristic centrality
centrality_eigenvector(): Eigenvector Centrality
centrality_entropy(): Entropy Centrality
centrality_entropy_variation(): Entropy Variation
centrality_exogenous(): Exogenous centrality
centrality_expected(): Expected Centrality
centrality_expected_force(): Expected Force centrality
centrality_expected_influence_1(): Expected Influence (one-step)
centrality_expected_influence_2(): Expected Influence (two-step)
centrality_extended_coreness(): Extended neighborhood coreness
centrality_extended_gravity(): Extended gravity centrality
centrality_extended_local_bridging(): Extended local bridging centrality
centrality_extended_mixed_gravity(): Extended mixed gravitational centrality
centrality_flow_betweenness(): Flow Betweenness Centrality
centrality_gateway(): Gateway Coefficient
centrality_generalized_closeness(): Generalized Closeness Centrality
centrality_gilschmidt(): Gil-Schmidt Power Index
centrality_global_structure(): Global structure model centrality
centrality_graph_regularization(): Graph regularization centrality
centrality_gravity(): Gravity centrality
centrality_harary(): Harary Centrality
centrality_harmonic() centrality_inharmonic() centrality_outharmonic(): Harmonic Centrality
centrality_hcc(): Hybrid characteristic centrality
centrality_heatmap() centrality_flow_coefficient() centrality_local_entropy() centrality_weighted_h_index() centrality_redundancy(): Heatmap, Flow Coefficient, Local Entropy, Weighted h-index, Redundancy
centrality_hubbell(): Hubbell Centrality
centrality_hybrid_global_structure(): Hybrid global structure model centrality
centrality_iec(): Immediate Effects Centrality
centrality_iira(): Improved iterative resource allocation (IIRA)
centrality_improved_closeness(): Improved closeness centrality
centrality_improved_global_structure(): Improved global structure model centrality
centrality_information(): Information Centrality (Stephenson-Zelen)
centrality_integration(): Integration Centrality
centrality_ira(): Iterative resource allocation (IRA)
centrality_katz(): Katz Centrality
centrality_ked(): KED method centrality
centrality_kreach(): Geodesic K-Path Centrality
centrality_lac(): Local Average Connectivity (LAC)
centrality_laplacian(): Laplacian Centrality
centrality_leaderrank(): LeaderRank Centrality
centrality_length_scaled_betweenness() centrality_delta_betweenness() centrality_ego_betweenness() centrality_delta_closeness(): Betweenness and closeness variants that carry a tuning parameter
centrality_leverage(): Leverage Centrality
centrality_lhc(): Lhc Index
centrality_lin(): Lin Centrality
centrality_linerank(): LineRank centrality
centrality_lnc(): Local neighbor contribution centrality
centrality_load(): Load Centrality
centrality_lobby(): Lobby Index (H-Index of Neighborhood)
centrality_local_bridging(): Local Bridging Centrality
centrality_local_dimension(): Local Dimension
centrality_local_dimension_fixed() centrality_fuzzy_local_dimension() centrality_local_volume_dimension(): Fixed-Radius, Fuzzy and Volume Local Dimensions
centrality_local_efficiency() centrality_s_core() centrality_fragmentation() centrality_kpath() centrality_epc(): Local efficiency, s-core, fragmentation, k-path census and EPC
centrality_local_information_dimension(): Local Information Dimensionality
centrality_localized_bridging(): Localized bridging centrality from ego betweenness
centrality_malatya(): Malatya centrality
centrality_map_equation(): Map equation centrality with explicit coding and flow conventions
centrality_markov(): Markov Centrality
centrality_mcc(): Maximal clique centrality
centrality_mcgm(): Multi-characteristics gravity model
centrality_mixed_gravity(): Mixed gravitational centrality
centrality_mnc(): Maximum Neighborhood Component (MNC)
centrality_modified_expected_force(): Modified Expected Force centrality
centrality_modularity_vitality(): Modularity Vitality
centrality_ncvoterank(): NCVoteRank
centrality_neighbor_distance(): Neighborhood centrality, and its neighbor distance special case
centrality_neighborhood_connectivity(): Neighborhood Connectivity
centrality_ninl(): Node and Neighbor Layer Information centrality
centrality_node_contraction() centrality_node_contraction_improved(): Node Contraction Centrality (IMC and IIMC)
centrality_pagerank(): PageRank Centrality
centrality_pairwisedis(): Pairwise Disconnectivity (Potapov et al. 2008)
centrality_participation(): Participation Coefficient
centrality_percolation(): Percolation Centrality
centrality_power(): Bonacich Power Centrality
centrality_prestige_domain(): Domain Prestige
centrality_prestige_domain_proximity(): Domain Proximity Prestige
centrality_proximal_betweenness(): Proximal betweenness centrality
centrality_radiality(): Radiality Centrality
centrality_random_walk(): Random Walk Centrality
centrality_random_walk_decay(): Random walk decay centrality
centrality_reaching_local(): Local Reaching Centrality (Mones, Vicsek & Vicsek 2012)
centrality_relative_entropy(): Relative-Entropy Integrated Evaluation
centrality_residual_closeness(): Residual Closeness Centrality
centrality_resistance_curvature(): Node resistance curvature
centrality_rsp_betweenness(): Randomized Shortest Paths Betweenness Centrality
centrality_rumor(): Rumor Centrality
centrality_s_shell(): s-shell Index
centrality_salsa(): SALSA Authority Centrality
centrality_semilocal(): Semi-Local Centrality
centrality_shapley_game1() centrality_shapley_game2() centrality_shapley_game3(): Shapley Value Centrality (Games 1, 2 and 3)
centrality_spectralrank(): SpectralRank with optional diagonal prior information
centrality_strength() centrality_instrength() centrality_outstrength(): Strength Centrality (Weighted Degree)
centrality_stress(): Stress Centrality
centrality_subgraph(): Subgraph Centrality
centrality_topological_coefficient(): Topological Coefficient
centrality_transitivity(): Local Transitivity (Clustering Coefficient)
centrality_truss() centrality_mdd() centrality_bridging_coefficient() centrality_godfather() centrality_support(): Truss, mixed-degree decomposition and local social-capital measures
centrality_trust_pagerank(): Trust-PageRank
centrality_two_way_rw(): Two-Way Random Walk Betweenness
centrality_volume(): Volume centrality
centrality_voterank(): VoteRank Centrality
centrality_weighted_kshell() centrality_renewed_coreness() centrality_geodesic_kpath(): Weighted k-shell, Renewed Coreness and Geodesic k-path
centrality_weighted_leaderrank(): Weighted LeaderRank centrality
centrality_wiener(): Wiener Index Centrality
centrality_within_module_z(): Within-Module Degree Z-Score
centrality_wvoterank() centrality_enrenew() centrality_voterank_plus(): WVoteRank, EnRenew and VoteRank++
centrality_x_degree(): X-degree 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_k_core(): Select the k-Core of a Network
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
network_wrangling: Network Wrangling Verbs
as_cograph() to_cograph(): Convert to Cograph Network
to_data_frame() to_df(): Export Network as Edge List Data Frame
to_directed(): Convert an Undirected Network to Directed
to_igraph(): Convert Network to igraph Object
to_matrix(): Convert Network to Adjacency Matrix
to_network(): Convert Network to statnet network Object
to_undirected(): Convert a Directed Network to Undirected
plot_alluvial(): Plot Alluvial Diagram
plot_bootstrap_forest(): Forest Plot for Bootstrap Network Results
plot_centrality(): Plot Centrality
plot_centrality_compare(): Plot Centrality Comparison
plot_centrality_distribution(): Plot Centrality Distribution
plot_centrality_heatmap(): Plot Centrality Heatmap
plot_chord(): Chord Diagram
plot_compare(): Plot Network Difference (alias of plot_difference)
plot_comparison_heatmap(): Plot Comparison Heatmap
plot_degree_correlation(): Plot Degree-Degree Correlation
plot_difference(): Plot Network Difference
plot_edge_diff_forest(): Forest Plot for Bootstrap Edge Differences
plot_edge_weights(): Plot Edge Weight Distribution
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_motifs(): Plot a motif/subgraph result
plot_mtna() mtna(): Multi-Cluster TNA Network Plot
plot_net_bootstrap_group() plot(<net_bootstrap_group>): Plot a Group Bootstrap Result
plot_net_stability(): Plot Centrality Stability Results
plot_netobject_group() plot(<netobject_group>): Plot a Group of Nestimate netobjects
plot_netobject_ml() plot(<netobject_ml>): Plot a Multilevel Nestimate netobject
plot_network_evolution(): Plot Network Evolution (Small Multiples)
splot.tna_permutation() plot_permutation(): Plot Permutation Test Results
plot_robustness(): Plot Network Robustness
plot_simplicial(): Simplicial Complex Visualization
plot_temporal(): Temporal Network Prism (3D Glass Box)
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
csum(): Cluster Summary Statistics
summarize_clusters(): Build MCML from Raw Transition Data
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(): Get Community Membership
mcml(): mcml - Deprecated alias for csum
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
extract_motifs() print(<cograph_motif_analysis>): Extract Motifs from Network Data
motif_census() print(<cograph_motifs>): Network Motif Analysis
motifs() print(<cograph_motif_result>) plot(<cograph_motif_result>): Network Motif Analysis
print(<cograph_communities>): Print Community Structure
print(<cograph_degree_fit>): Print method for cograph_degree_fit
print(<cograph_network>): Print cograph_network Object
plot(<cograph_cluster_significance>): Plot Cluster Significance
plot(<cograph_communities>): Plot Community Structure
plot(<cograph_core_periphery>): Plot Core-Periphery Structure
plot(<cograph_degree_fit>): Plot method for cograph_degree_fit
plot(<cograph_motif_analysis>): Plot Motif Analysis Results
plot(<cograph_motifs>): Plot Network Motifs
plot(<cograph_network>): Plot cograph_network Object
plot(<cograph_rich_club>): Plot Rich Club Results
plot(<cograph_vulnerability>): Plot Node Vulnerability
plot(<tna_disparity>): Plot Disparity Filter Result
plot(<tna_bootstrap>) splot.tna_bootstrap(): Plot Bootstrap Results
summary(<cograph_network>): Summary of cograph_network Object
splot.net_bootstrap() splot.tna_communities() splot.cograph_communities() splot.net_mlvar() splot.netobject() splot.boot_glasso() splot.wtna_mixed() splot.net_permutation() splot(): Plot Nestimate Bootstrap Results
splot.tna_disparity(): Plot Disparity Results with splot
abbrev_label() label_abbrev(): Abbreviate Labels
add_edges(): Add Edges to a Network
add_nodes(): Add Nodes to a Network
as.data.frame(<cograph_network>): Cograph Network as a Data Frame
as_mcml(): Convert to mcml
as_tna(): Convert cluster_summary to tna Objects
assortativity(): Degree Assortativity Coefficient
assortativity_attribute() homophily(): Attribute Assortativity (Homophily)
binarize(): Binarize Edge Weights
bind_networks(): Combine Two Networks
centralization(): Centralization index
cluster_significance() csig(): Test Significance of Community Structure
cograph(): Create a Network Visualization
complement_network(): Complement of a Network
contract_nodes(): Contract Nodes into Groups
core_periphery(): Detect Core-Periphery Structure
disparity_filter(): Disparity Filter
dispersion(): Dispersion (Backstrom-Kleinberg 2014)
dyad_census(): Dyad Census
edge_reciprocity(): Edge Reciprocity
ego_networks(): Ego-Network Metrics
estrada_index(): Estrada Index
extract_triads(): Extract Triads with Node Labels
fit_degree_distribution(): Fit Statistical Distributions to Degree Sequence
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
group_centrality(): Group Centrality (Everett-Borgatti 1999)
coding coding_detailed ai_coding ai_detailed human_ai human_ai_detailed: Human-AI Interaction Coding Sequences
invert_weights(): Invert Edge Weights (Similarity to Distance and Back)
is_bipartite(): Check if a Matrix Could Be Bipartite
k_shortest_paths(): Find K Shortest Loopless Paths (Yen's Algorithm)
layout_circle(): Circular Layout
layout_groups(): Group-based Layout
layout_oval(): Oval Layout
layout_saqr(): Saqr Layout (Start/End transition flow)
layout_spring(): Fruchterman-Reingold Spring Layout
layout_target(): Target Layout (focal-node, topological)
list_centralities(): Catalogue of the Centrality Measures
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
mutate_edges(): Add or Change Edge Attributes
mutate_nodes(): Add or Change Node Attributes
n_edges(): Get Number of Edges
n_nodes(): Get Number of Nodes
neighborhood_overlap(): Neighborhood Overlap (Jaccard) for Each Edge
normalize_weights(): Normalize Edge Weights
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
panel_layout(): Configure a custom multi-panel layout
project_bipartite(): Project Bipartite Network to One-Mode
reaching_global(): Global Reaching Centrality (Mones, Vicsek & Vicsek 2012)
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
remove_edges(): Remove Edges from a Network
remove_isolates(): Remove Isolated Nodes
remove_nodes(): Remove Nodes from a Network
rename_nodes(): Rename Nodes
render-ggplot: ggplot2 Conversion
render-grid: Grid Rendering
reorder_nodes(): Reorder the Nodes of a Network
reverse_edges(): Reverse Edge Direction
rich_club(): Rich Club Coefficient
rich_club_local(): Local Rich Club Score
set_edges(): Set Edges in Cograph Network
set_layout(): Set Layout in Cograph Network
set_nodes(): Set Nodes in Cograph Network
shortest_paths(): Compute Shortest Path Distances
simmelian_strength(): Simmelian Strength (Triangle Count per Edge)
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
spanning_tree(): Minimum or Maximum Spanning Tree
split_components(): Split a Network into Its Connected Components
student_interactions: Student Interaction Edge List
subgraphs(): Extract Specific Motif Instances (Subgraphs)
summarize_network() cnet(): Summarize Network by Clusters
symmetrize(): Symmetrize a Directed Network
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
threshold_edges(): Threshold Edges by Weight, Count, Proportion or Density
triad_census(): Triad Census
trophic_incoherence(): Trophic Incoherence Parameter
unregister_svg_shape(): Unregister SVG Shape
vulnerability(): Node Vulnerability

Base R plotting

Plotting based on ggplot2

Transition Network Analysis

Multi-Cluster TNA Network Plot

Multilevel Network Visualization

Wrangling

Network functions

Palettes

Shapes

Themes

Layouts

Motif Analysis

All Other Functions

Plotting based on `ggplot2`