Package index • netify

Creating Networks

Functions for constructing netify objects

netify(): Create network object from various data types
new_netify(): low-level constructor for netify objects
layer_netify(): Create multilayer networks from multiple netify objects
bind_netifies(): Combine multiple netify objects
merge(<netify>): merge method for netify objects (s3 alias for bind_netifies)
ego_netify(): Create ego network from a netify object
to_netify(): Convert igraph, network, or matrix objects to netify format
pivot_dyad_to_network(): Pivot a dyadic variable to become the network
netify_workflows: Common netify workflows – index of patterns

Adding Attributes

Add nodal and dyadic attributes

add_node_vars() add_vertex_attributes(): Add nodal variables to a netify object
add_dyad_vars() add_edge_attributes(): Add dyadic variables to a netify object

Manipulating Networks

Subset, transform, reshape, and clean networks

subset_netify(): internal subset function for netify objects
subset(<netify>): Subset netify objects
mutate_weights(): Mutate edge weights in a netify object
aggregate_dyad(): Aggregate dyadic event data by actor pairs
binarize(): Binarize a netify object at a threshold
decompose_netify(): Decompose a netify object into edge and node data frames
drop_na_actors(): Drop actors with NA covariates from a netify object
gen_symm_id(): generate symmetric identifiers for dyadic data

Analysis

Network statistics and comparisons

summary(<netify>): Calculate graph-level statistics for netify objects
summary(<netify_comparison>): summary method for netify_comparison objects
summary_actor(): Calculate actor-level network statistics
netify_measurements() measurements(): Extract measurements and dimensions from a netify object
compare_networks(): Compare networks across time, layers, or attributes
print(<netify_comparison>): Print method for netify_comparison objects
homophily(): Analyze homophily in network data
mixing_matrix(): Create attribute mixing matrices for network data
dyad_correlation(): Analyze correlations between dyadic attributes and network ties
attribute_report(): Summary of network-attribute relationships
get_actor_time_info(): Extract actor time range information

Inference

Bootstrap, null comparison, and simulation

bootstrap_netlet(): Bootstrap any user-supplied function of a netify object
compare_to_null(): Test an observed network statistic against a NULL distribution
simulate(<netify>): Simulate NULL-model networks from a netify object

Visualization

Plot networks and statistics

plot(<netify>): Plotting method for netify objects
plot(<netify_comparison>): Plot method for netify_comparison objects
plot(<summary.netify>): plot graph-level summary statistics
plot(<summary_actor>): plot method for summary_actor output
plot_actor_stats(): Visualize actor-level network statistics
plot_graph_stats(): Visualize network-level statistics
plot_homophily(): Visualize homophily analysis results
plot_mixing_matrix(): Visualize attribute mixing matrix results
plot_mixing_matrix_facet(): create a multi-panel mixing matrix visualization
animate_netify(): Animate a longitudinal netify object with gganimate
theme_netify(): theme_netify function
theme_stat_netify(): theme_stat_netify function
theme_publication_netify(): ggplot theme for netify network plots
theme_publication_netify_ts(): ggplot theme for netify time-series / stat plots
list_network_styles(): list available network styles
list_palettes(): list available color palettes

Plot Styles

Pre-built visual style presets

style_random(): apply random network style
style_rose(): rose network style
style_red_blue(): red and blue network style
style_orange_teal(): orange and teal network style
style_solarized(): solarized-inspired network style
style_navy_maroon(): navy and maroon network style
style_scientific_blue(): scientific blue network style
style_cyberpunk(): cyberpunk-inspired network style
style_tufte(): minimal tufte-inspired network style
style_pastel(): pastel rainbow network style
style_retro80s(): retro 80s-inspired network style
style_dark2(): colorbrewer dark2-based network style
style_crimson_silver(): crimson and silver network style
style_green_gold(): green and gold network style
style_slate_silver(): slate and silver network style
style_bronze_block(): bronze block network style
style_lime_magenta(): lime and magenta network style
style_black_yellow(): black and yellow network style
style_sunburst(): sunburst network style
style_racing_blue(): racing blue network style
style_bipartite_network(): preset style for bipartite networks
style_temporal_network(): preset style for temporal/longitudinal networks

Plot Components

Low-level plot building blocks

net_plot_data(): Prepare netify data for network visualization
get_node_layout(): Calculate node layout positions for netify visualization
get_edge_layout(): Generate edge layout coordinates for netify visualization
get_ego_layout(): Calculate ego-centric layout positions for network visualization
create_hierarchical_ego_layout() create_radial_ego_layout() create_ego_centric_layout(): Create ego-centric layouts for ego networks
remove_ego_edges(): remove ego-alter edges from ego network
assemble_netify_plot(): assemble netify plot from components
netify_edge(): Extract edges layer from netify plot components
netify_node(): extract nodes layer from netify plot components
netify_text(): extract text layer from netify plot components
netify_label(): extract label layer from netify plot components
netify_text_repel(): extract text_repel layer from netify plot components
netify_label_repel(): extract label_repel layer from netify plot components
netify_scale_labels(): set scale labels for netify plots
reset_scales(): reset aesthetic scales in ggplot
plot_with_style(): Apply style to netify plot
validate_plot_params(): Validate plot parameters and warn about common mistakes
print(<netify_plot_components>): print netify plot components
ggplot_add(<netify_edge>): add netify_edge to ggplot
ggplot_add(<netify_node>): add netify_node to ggplot
ggplot_add(<netify_text>): add netify_text to ggplot
ggplot_add(<netify_label>): add netify_label to ggplot
ggplot_add(<netify_text_repel>): add netify_text_repel to ggplot
ggplot_add(<netify_label_repel>): add netify_label_repel to ggplot
ggplot_add(<netify_scale_reset>): add scale resets to ggplot
ggplot_add(<netify_labels>): add netify scale labels to ggplot

Conversion

Convert between netify and other formats

netify_to_igraph() to_igraph(): Convert netify objects to igraph format
netify_to_statnet() netify_to_network() to_statnet() to_network(): Convert netify objects to statnet network format
netify_to_amen() to_amen(): Convert netify objects to amen format
netify_to_lame() to_lame(): Convert a netify object to the format expected by lame::ame()
netify_to_dbn() to_dbn(): Convert netify objects to dbn format
from_lame_fit(): Convert a fitted lame/amen AME object back into a netify
unnetify() netify_to_df(): Convert netify objects back to dyadic data frames
melt(): Melt methods for netify objects
decompose_igraph(): decompose an igraph object into base r components
decompose_statnet() decompose_network(): decompose a network object into base r components
read_graphml() read_pajek() read_gml(): Read a network from common file formats into a netify object
as.matrix(<netify>): coerce a netify object to a plain matrix
as.igraph.netify(): as.igraph method for netify objects
as.network.netify(): as.network method for netify objects
as_tibble.netify(): convert a netify object to a tibble (long edge frame)
as_tibble.netify_comparison(): Convert a netify_comparison to a tibble
tidy.netify(): Tidy a netify object into a long edge data frame
glance.netify(): one-row-per-network summary of a netify object (broom style)

Inspection

Examine and query netify objects

print(<netify>): Print method for netify objects
peek(): Preview subsets of network data from netify objects
get_raw(): get raw network data without netify attributes
get_adjacency(): Create a netify matrix from cross-sectional dyadic data
get_adjacency_array(): Create a netify array from longitudinal dyadic data
get_adjacency_list(): Create a netify list from longitudinal dyadic data
is_netify(): is this object a netify object?
is_binary() nodal_data() is_bipartite() is_bipartite_netify() is_directed_netify() is_longitudinal() is_multilayer() is_symmetric_netify() n_actors() n_periods() n_layers(): Type predicates and convenience accessors for netify objects
validate_netify(): Deep coherence check on a netify object

Data

Example datasets

icews: Event data slice from ICEWS
mexico: Event data slice from UCDP on Mexico
myanmar: event data slice from ucdp on myanmar
classroom_edges: synthetic high-school friendship edgelist
classroom_nodes: Synthetic high-school friendship roster (nodes)