Function reference
-
igraph_options()
igraph_opt()
- Parameters for the igraph package
-
with_igraph_opt()
- Run code with a temporary igraph options setting
-
connect()
ego_size()
neighborhood_size()
ego()
neighborhood()
make_ego_graph()
make_neighborhood_graph()
- Neighborhood of graph vertices
-
make_()
- Make a new graph
-
is_bipartite()
make_bipartite_graph()
bipartite_graph()
- Create a bipartite graph
-
make_chordal_ring()
chordal_ring()
- Create an extended chordal ring graph
-
make_clusters()
- Creates a communities object.
-
make_de_bruijn_graph()
de_bruijn_graph()
- De Bruijn graphs
-
make_empty_graph()
empty_graph()
- A graph with no edges
-
make_from_prufer()
from_prufer()
- Create an undirected tree graph from its Prüfer sequence
-
make_full_bipartite_graph()
full_bipartite_graph()
- Create a full bipartite graph
-
make_full_citation_graph()
full_citation_graph()
- Create a complete (full) citation graph
-
make_full_graph()
full_graph()
- Create a full graph
-
make_graph()
make_directed_graph()
make_undirected_graph()
directed_graph()
undirected_graph()
- Create an igraph graph from a list of edges, or a notable graph
-
make_kautz_graph()
kautz_graph()
- Kautz graphs
-
make_lattice()
lattice()
- Create a lattice graph
-
make_line_graph()
line_graph()
- Line graph of a graph
-
make_ring()
ring()
- Create a ring graph
-
make_star()
star()
- Create a star graph, a tree with n vertices and n - 1 leaves
-
make_tree()
tree()
- Create tree graphs
-
realize_degseq()
- Creating a graph from a given degree sequence, deterministically
-
graph_from_atlas()
atlas()
- Create a graph from the Graph Atlas
-
graph_from_edgelist()
from_edgelist()
- Create a graph from an edge list matrix
-
graph_from_literal()
from_literal()
- Creating (small) graphs via a simple interface
-
graph_()
- Convert object to a graph
-
graph_from_lcf()
- Creating a graph from LCF notation
-
as_data_frame()
graph_from_data_frame()
from_data_frame()
- Creating igraph graphs from data frames or vice-versa
-
sample_()
- Sample from a random graph model
-
sample_bipartite()
bipartite()
- Bipartite random graphs
-
sample_correlated_gnp()
- Generate a new random graph from a given graph by randomly adding/removing edges
-
sample_correlated_gnp_pair()
- Sample a pair of correlated G(n,p) random graphs
-
sample_degseq()
degseq()
- Generate random graphs with a given degree sequence
-
sample_dot_product()
dot_product()
- Generate random graphs according to the random dot product graph model
-
sample_fitness()
- Random graphs from vertex fitness scores
-
sample_fitness_pl()
- Scale-free random graphs, from vertex fitness scores
-
sample_forestfire()
- Forest Fire Network Model
-
sample_gnm()
gnm()
- Generate random graphs according to the G(n,m) Erdős-Rényi model
-
sample_gnp()
gnp()
- Generate random graphs according to the G(n,p) Erdős-Rényi model
-
sample_grg()
grg()
- Geometric random graphs
-
sample_growing()
growing()
- Growing random graph generation
-
sample_hierarchical_sbm()
hierarchical_sbm()
- Sample the hierarchical stochastic block model
-
sample_islands()
- A graph with subgraphs that are each a random graph.
-
sample_k_regular()
- Create a random regular graph
-
sample_last_cit()
last_cit()
sample_cit_types()
cit_types()
sample_cit_cit_types()
cit_cit_types()
- Random citation graphs
-
sample_pa()
pa()
- Generate random graphs using preferential attachment
-
sample_pa_age()
pa_age()
- Generate an evolving random graph with preferential attachment and aging
-
sample_pref()
pref()
sample_asym_pref()
asym_pref()
- Trait-based random generation
-
sample_sbm()
sbm()
- Sample stochastic block model
-
sample_smallworld()
smallworld()
- The Watts-Strogatz small-world model
-
sample_traits_callaway()
traits_callaway()
sample_traits()
traits()
- Graph generation based on different vertex types
-
sample_tree()
- Sample trees randomly and uniformly
-
simplified()
- Constructor modifier to drop multiple and loop edges
-
with_edge_()
- Constructor modifier to add edge attributes
-
with_graph_()
- Constructor modifier to add graph attributes
-
with_vertex_()
- Constructor modifier to add vertex attributes
-
without_attr()
- Construtor modifier to remove all attributes from a graph
-
without_loops()
- Constructor modifier to drop loop edges
-
without_multiples()
- Constructor modifier to drop multiple edges
-
as.igraph()
- Conversion to igraph
-
graph_from_adjacency_matrix()
from_adjacency()
- Create graphs from adjacency matrices
-
add_layout_()
- Add layout to graph
-
component_wise()
- Component-wise layout
-
layout_as_bipartite()
as_bipartite()
- Simple two-row layout for bipartite graphs
-
layout_as_star()
as_star()
- Generate coordinates to place the vertices of a graph in a star-shape
-
layout_as_tree()
as_tree()
- The Reingold-Tilford graph layout algorithm
-
layout_in_circle()
in_circle()
- Graph layout with vertices on a circle.
-
layout_nicely()
nicely()
- Choose an appropriate graph layout algorithm automatically
-
layout_on_sphere()
on_sphere()
- Graph layout with vertices on the surface of a sphere
-
layout_randomly()
randomly()
- Randomly place vertices on a plane or in 3d space
-
layout_with_dh()
with_dh()
- The Davidson-Harel layout algorithm
-
layout_with_fr()
with_fr()
- The Fruchterman-Reingold layout algorithm
-
layout_with_gem()
with_gem()
- The GEM layout algorithm
-
layout_with_graphopt()
with_graphopt()
- The graphopt layout algorithm
-
layout_with_kk()
with_kk()
- The Kamada-Kawai layout algorithm
-
layout_with_lgl()
with_lgl()
- Large Graph Layout
-
layout_with_mds()
with_mds()
- Graph layout by multidimensional scaling
-
layout_with_sugiyama()
with_sugiyama()
- The Sugiyama graph layout generator
-
merge_coords()
layout_components()
- Merging graph layouts
-
norm_coords()
- Normalize coordinates for plotting graphs
-
normalize()
- Normalize layout
-
layout_with_drl()
with_drl()
- The DrL graph layout generator
-
categorical_pal()
- Palette for categories
-
diverging_pal()
- Diverging palette
-
r_pal()
- The default R palette
-
sequential_pal()
- Sequential palette
-
plot(<igraph>)
- Plotting of graphs
-
rglplot()
- 3D plotting of graphs with OpenGL
-
igraph.plotting
- Drawing graphs
-
plot_dendrogram(<igraphHRG>)
- HRG dendrogram plot
-
plot_dendrogram()
- Community structure dendrogram plots
-
curve_multiple()
- Optimal edge curvature when plotting graphs
-
shapes()
shape_noclip()
shape_noplot()
add_shape()
- Various vertex shapes when plotting igraph graphs
-
vertex.shape.pie
- Using pie charts as vertices in graph plots
-
greedy_vertex_coloring()
- Greedy vertex coloring
-
add_edges()
- Add edges to a graph
-
add_vertices()
- Add vertices to a graph
-
complementer()
- Complementer of a graph
-
compose()
- Compose two graphs as binary relations
-
contract()
- Contract several vertices into a single one
-
delete_edges()
- Delete edges from a graph
-
delete_vertices()
- Delete vertices from a graph
-
difference()
- Difference of two sets
-
difference(<igraph>)
- Difference of graphs
-
disjoint_union()
`%du%`
- Disjoint union of graphs
-
connect()
ego_size()
neighborhood_size()
ego()
neighborhood()
make_ego_graph()
make_neighborhood_graph()
- Neighborhood of graph vertices
-
`-`(<igraph>)
- Delete vertices or edges from a graph
-
intersection()
- Intersection of two or more sets
-
intersection(<igraph>)
- Intersection of graphs
-
path()
- Helper function to add or delete edges along a path
-
permute()
- Permute the vertices of a graph
-
`+`(<igraph>)
- Add vertices, edges or another graph to a graph
-
rep(<igraph>)
`*`(<igraph>)
- Replicate a graph multiple times
-
reverse_edges()
t(<igraph>)
- Reverse edges in a graph
-
simplify()
is_simple()
simplify_and_colorize()
- Simple graphs
-
union()
- Union of two or more sets
-
union(<igraph>)
- Union of graphs
-
vertex()
vertices()
- Helper function for adding and deleting vertices
-
each_edge()
- Rewires the endpoints of the edges of a graph to a random vertex
-
keeping_degseq()
- Graph rewiring while preserving the degree distribution
-
rewire()
- Rewiring edges of a graph
-
delete_edge_attr()
- Delete an edge attribute
-
delete_graph_attr()
- Delete a graph attribute
-
delete_vertex_attr()
- Delete a vertex attribute
-
`edge_attr<-`()
- Set one or more edge attributes
-
edge_attr()
- Query edge attributes of a graph
-
edge_attr_names()
- List names of edge attributes
-
`graph_attr<-`()
- Set all or some graph attributes
-
graph_attr()
- Graph attributes of a graph
-
graph_attr_names()
- List names of graph attributes
-
igraph-attribute-combination
attribute.combination
- How igraph functions handle attributes when the graph changes
-
`$`(<igraph>)
`$<-`(<igraph>)
- Getting and setting graph attributes, shortcut
-
`[[<-`(<igraph.vs>)
`[<-`(<igraph.vs>)
`$`(<igraph.vs>)
`$<-`(<igraph.vs>)
`V<-`()
- Query or set attributes of the vertices in a vertex sequence
-
set_edge_attr()
- Set edge attributes
-
set_graph_attr()
- Set a graph attribute
-
set_vertex_attr()
- Set vertex attributes
-
`vertex_attr<-`()
- Set one or more vertex attributes
-
vertex_attr()
- Query vertex attributes of a graph
-
vertex_attr_names()
- List names of vertex attributes
-
E()
- Edges of a graph
-
V()
- Vertices of a graph
-
as_ids()
- Convert a vertex or edge sequence to an ordinary vector
-
`[[<-`(<igraph.es>)
`[<-`(<igraph.es>)
`$`(<igraph.es>)
`$<-`(<igraph.es>)
`E<-`()
- Query or set attributes of the edges in an edge sequence
-
`[`(<igraph.es>)
- Indexing edge sequences
-
`[[`(<igraph.es>)
- Select edges and show their metadata
-
`[[<-`(<igraph.vs>)
`[<-`(<igraph.vs>)
`$`(<igraph.vs>)
`$<-`(<igraph.vs>)
`V<-`()
- Query or set attributes of the vertices in a vertex sequence
-
`[`(<igraph.vs>)
- Indexing vertex sequences
-
`[[`(<igraph.vs>)
- Select vertices and show their metadata
-
print(<igraph.es>)
- Print an edge sequence to the screen
-
print(<igraph.vs>)
- Show a vertex sequence on the screen
-
c(<igraph.es>)
- Concatenate edge sequences
-
c(<igraph.vs>)
- Concatenate vertex sequences
-
difference(<igraph.es>)
- Difference of edge sequences
-
difference(<igraph.vs>)
- Difference of vertex sequences
-
intersection(<igraph.es>)
- Intersection of edge sequences
-
intersection(<igraph.vs>)
- Intersection of vertex sequences
-
rev(<igraph.es>)
- Reverse the order in an edge sequence
-
rev(<igraph.vs>)
- Reverse the order in a vertex sequence
-
union(<igraph.es>)
- Union of edge sequences
-
union(<igraph.vs>)
- Union of vertex sequences
-
unique(<igraph.es>)
- Remove duplicate edges from an edge sequence
-
unique(<igraph.vs>)
- Remove duplicate vertices from a vertex sequence
-
graph_id()
- Get the id of a graph
-
identical_graphs()
- Decide if two graphs are identical
-
is_igraph()
- Is this object an igraph graph?
-
is_named()
- Named graphs
-
is_weighted()
- Weighted graphs
-
is_chordal()
- Chordality of a graph
-
as.directed()
as.undirected()
- Convert between directed and undirected graphs
-
as.matrix(<igraph>)
- Convert igraph objects to adjacency or edge list matrices
-
as_adj_list()
as_adj_edge_list()
- Adjacency lists
-
as_adjacency_matrix()
as_adj()
- Convert a graph to an adjacency matrix
-
as_biadjacency_matrix()
- Bipartite adjacency matrix of a bipartite graph
-
as_edgelist()
- Convert a graph to an edge list
-
as_graphnel()
- Convert igraph graphs to graphNEL objects from the graph package
-
as_long_data_frame()
- Convert a graph to a long data frame
-
graph_from_adj_list()
- Create graphs from adjacency lists
-
as_data_frame()
graph_from_data_frame()
from_data_frame()
- Creating igraph graphs from data frames or vice-versa
-
graph_from_graphnel()
- Convert graphNEL objects from the graph package to igraph
-
head_print()
- Print the only the head of an R object
-
indent_print()
- Indent a printout
-
print(<igraph>)
summary(<igraph>)
- Print graphs to the terminal
-
is_printer_callback()
- Is this a printer callback?
-
printer_callback()
- Create a printer callback function
-
sample_dirichlet()
- Sample from a Dirichlet distribution
-
sample_sphere_surface()
- Sample vectors uniformly from the surface of a sphere
-
sample_sphere_volume()
- Sample vectors uniformly from the volume of a sphere
-
convex_hull()
- Convex hull of a set of vertices
-
running_mean()
- Running mean of a time series
-
sample_seq()
- Sampling a random integer sequence
-
fit_power_law()
- Fitting a power-law distribution function to discrete data
-
bfs()
- Breadth-first search
-
component_distribution()
largest_component()
components()
is_connected()
count_components()
- Connected components of a graph
-
constraint()
- Burt's constraint
-
coreness()
- K-core decomposition of graphs
-
degree()
degree_distribution()
- Degree and degree distribution of the vertices
-
dfs()
- Depth-first search
-
distance_table()
mean_distance()
distances()
shortest_paths()
all_shortest_paths()
- Shortest (directed or undirected) paths between vertices
-
edge_density()
- Graph density
-
connect()
ego_size()
neighborhood_size()
ego()
neighborhood()
make_ego_graph()
make_neighborhood_graph()
- Neighborhood of graph vertices
-
feedback_arc_set()
- Finding a feedback arc set in a graph
-
girth()
- Girth of a graph
-
is_acyclic()
- Acyclic graphs
-
is_dag()
- Directed acyclic graphs
-
k_shortest_paths()
- Find the k shortest paths between two vertices
-
knn()
- Average nearest neighbor degree
-
laplacian_matrix()
- Graph Laplacian
-
reciprocity()
- Reciprocity of graphs
-
subcomponent()
- In- or out- component of a vertex
-
subgraph()
induced_subgraph()
subgraph.edges()
- Subgraph of a graph
-
topo_sort()
- Topological sorting of vertices in a graph
-
transitivity()
- Transitivity of a graph
-
unfold_tree()
- Convert a general graph into a forest
-
which_multiple()
any_multiple()
count_multiple()
which_loop()
any_loop()
- Find the multiple or loop edges in a graph
-
which_mutual()
- Find mutual edges in a directed graph
-
cocitation()
bibcoupling()
- Cocitation coupling
-
similarity()
- Similarity measures of two vertices
-
cohesive_blocks()
length(<cohesiveBlocks>)
blocks()
graphs_from_cohesive_blocks()
cohesion(<cohesiveBlocks>)
hierarchy()
parent()
print(<cohesiveBlocks>)
summary(<cohesiveBlocks>)
plot(<cohesiveBlocks>)
plot_hierarchy()
export_pajek()
max_cohesion()
- Calculate Cohesive Blocks
-
triangles()
count_triangles()
- Find triangles in graphs
-
assortativity()
assortativity_nominal()
assortativity_degree()
- Assortativity coefficient
-
spectrum()
- Eigenvalues and eigenvectors of the adjacency matrix of a graph
-
is_chordal()
- Chordality of a graph
-
max_cardinality()
- Maximum cardinality search
-
triangles()
count_triangles()
- Find triangles in graphs
-
transitivity()
- Transitivity of a graph
-
all_simple_paths()
- List all simple paths from one source
-
diameter()
get_diameter()
farthest_vertices()
- Diameter of a graph
-
distance_table()
mean_distance()
distances()
shortest_paths()
all_shortest_paths()
- Shortest (directed or undirected) paths between vertices
-
eccentricity()
- Eccentricity of the vertices in a graph
-
radius()
- Radius of a graph
-
bipartite_mapping()
- Decide whether a graph is bipartite
-
bipartite_projection()
bipartite_projection_size()
- Project a bipartite graph
-
is_bipartite()
make_bipartite_graph()
bipartite_graph()
- Create a bipartite graph
-
graph_from_biadjacency_matrix()
- Create graphs from a bipartite adjacency matrix
-
as_data_frame()
graph_from_data_frame()
from_data_frame()
- Creating igraph graphs from data frames or vice-versa
-
global_efficiency()
local_efficiency()
average_local_efficiency()
- Efficiency of a graph
-
similarity()
- Similarity measures of two vertices
-
is_forest()
- Decide whether a graph is a forest.
-
is_tree()
- Decide whether a graph is a tree.
-
make_from_prufer()
from_prufer()
- Create an undirected tree graph from its Prüfer sequence
-
sample_spanning_tree()
- Samples from the spanning trees of a graph randomly and uniformly
-
to_prufer()
- Convert a tree graph to its Prüfer sequence
-
mst()
- Minimum spanning tree
-
adjacent_vertices()
- Adjacent vertices of multiple vertices in a graph
-
are_adjacent()
- Are two vertices adjacent?
-
ends()
- Incident vertices of some graph edges
-
get.edge.ids()
- Find the edge ids based on the incident vertices of the edges
-
head_of()
- Head of the edge(s) in a graph
-
incident()
- Incident edges of a vertex in a graph
-
incident_edges()
- Incident edges of multiple vertices in a graph
-
is_directed()
- Check whether a graph is directed
-
neighbors()
- Neighboring (adjacent) vertices in a graph
-
`[`(<igraph>)
- Query and manipulate a graph as it were an adjacency matrix
-
`[[`(<igraph>)
- Query and manipulate a graph as it were an adjacency list
-
tail_of()
- Tails of the edge(s) in a graph
-
arpack_defaults()
arpack()
- ARPACK eigenvector calculation
-
alpha_centrality()
- Find Bonacich alpha centrality scores of network positions
-
betweenness()
edge_betweenness()
- Vertex and edge betweenness centrality
-
closeness()
- Closeness centrality of vertices
-
diversity()
- Graph diversity
-
eigen_centrality()
- Find Eigenvector Centrality Scores of Network Positions
-
harmonic_centrality()
- Harmonic centrality of vertices
-
hub_score()
authority_score()
- Kleinberg's hub and authority centrality scores.
-
page_rank()
- The Page Rank algorithm
-
power_centrality()
- Find Bonacich Power Centrality Scores of Network Positions
-
spectrum()
- Eigenvalues and eigenvectors of the adjacency matrix of a graph
-
strength()
- Strength or weighted vertex degree
-
subgraph_centrality()
- Find subgraph centrality scores of network positions
-
centr_betw()
- Centralize a graph according to the betweenness of vertices
-
centr_betw_tmax()
- Theoretical maximum for betweenness centralization
-
centr_clo()
- Centralize a graph according to the closeness of vertices
-
centr_clo_tmax()
- Theoretical maximum for closeness centralization
-
centr_degree()
- Centralize a graph according to the degrees of vertices
-
centr_degree_tmax()
- Theoretical maximum for degree centralization
-
centr_eigen()
- Centralize a graph according to the eigenvector centrality of vertices
-
centr_eigen_tmax()
- Theoretical maximum for betweenness centralization
-
centralize()
- Centralization of a graph
-
local_scan()
- Compute local scan statistics on graphs
-
scan_stat()
- Scan statistics on a time series of graphs
-
count_motifs()
- Graph motifs
-
dyad_census()
- Dyad census of a graph
-
motifs()
- Graph motifs
-
sample_motifs()
- Graph motifs
-
triad_census()
- Triad census, subgraphs with three vertices
-
canonical_permutation()
- Canonical permutation of a graph
-
count_isomorphisms()
- Count the number of isomorphic mappings between two graphs
-
count_subgraph_isomorphisms()
- Count the isomorphic mappings between a graph and the subgraphs of another graph
-
graph_from_isomorphism_class()
- Create a graph from an isomorphism class
-
isomorphic()
is_isomorphic_to()
- Decide if two graphs are isomorphic
-
isomorphism_class()
- Isomorphism class of a graph
-
isomorphisms()
- Calculate all isomorphic mappings between the vertices of two graphs
-
subgraph_isomorphic()
is_subgraph_isomorphic_to()
- Decide if a graph is subgraph isomorphic to another one
-
subgraph_isomorphisms()
- All isomorphic mappings between a graph and subgraphs of another graph
-
simplify()
is_simple()
simplify_and_colorize()
- Simple graphs
-
automorphism_group()
- Generating set of the automorphism group of a graph
-
count_automorphisms()
- Number of automorphisms
-
permute()
- Permute the vertices of a graph
-
match_vertices()
- Match Graphs given a seeding of vertex correspondences
-
dominator_tree()
- Dominator tree
-
edge_connectivity()
edge_disjoint_paths()
adhesion()
- Edge connectivity
-
is_min_separator()
- Minimal vertex separators
-
is_separator()
- Vertex separators
-
max_flow()
- Maximum flow in a graph
-
min_cut()
- Minimum cut in a graph
-
min_separators()
- Minimum size vertex separators
-
min_st_separators()
- Minimum size vertex separators
-
st_cuts()
- List all (s,t)-cuts of a graph
-
st_min_cuts()
- List all minimum (s,t)-cuts of a graph
-
vertex_connectivity()
vertex_disjoint_paths()
cohesion(<igraph>)
- Vertex connectivity
-
cliques()
largest_cliques()
max_cliques()
count_max_cliques()
clique_num()
largest_weighted_cliques()
weighted_clique_num()
clique_size_counts()
- Functions to find cliques, i.e. complete subgraphs in a graph
-
ivs()
largest_ivs()
maximal_ivs()
ivs_size()
- Independent vertex sets
-
weighted_cliques()
- Functions to find weighted cliques, i.e. vertex-weighted complete subgraphs in a graph
-
graphlet_basis()
graphlet_proj()
graphlets()
- Graphlet decomposition of a graph
-
as_membership()
- Declare a numeric vector as a membership vector
-
cluster_edge_betweenness()
- Community structure detection based on edge betweenness
-
cluster_fast_greedy()
- Community structure via greedy optimization of modularity
-
cluster_fluid_communities()
- Community detection algorithm based on interacting fluids
-
cluster_infomap()
- Infomap community finding
-
cluster_label_prop()
- Finding communities based on propagating labels
-
cluster_leading_eigen()
- Community structure detecting based on the leading eigenvector of the community matrix
-
cluster_leiden()
- Finding community structure of a graph using the Leiden algorithm of Traag, van Eck & Waltman.
-
cluster_louvain()
- Finding community structure by multi-level optimization of modularity
-
cluster_optimal()
- Optimal community structure
-
cluster_spinglass()
- Finding communities in graphs based on statistical meachanics
-
cluster_walktrap()
- Community structure via short random walks
-
membership()
print(<communities>)
modularity(<communities>)
length(<communities>)
sizes()
algorithm()
merges()
crossing()
code_len()
is_hierarchical()
as.dendrogram(<communities>)
as.hclust(<communities>)
cut_at()
show_trace()
plot(<communities>)
communities()
- Functions to deal with the result of network community detection
-
compare()
- Compares community structures using various metrics
-
groups()
- Groups of a vertex partitioning
-
make_clusters()
- Creates a communities object.
-
modularity(<igraph>)
modularity_matrix()
- Modularity of a community structure of a graph
-
plot_dendrogram()
- Community structure dendrogram plots
-
split_join_distance()
- Split-join distance of two community structures
-
feedback_arc_set()
- Finding a feedback arc set in a graph
-
girth()
- Girth of a graph
-
has_eulerian_path()
has_eulerian_cycle()
eulerian_path()
eulerian_cycle()
- Find Eulerian paths or cycles in a graph
-
is_acyclic()
- Acyclic graphs
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is_dag()
- Directed acyclic graphs
-
articulation_points()
bridges()
- Articulation points and bridges of a graph
-
biconnected_components()
- Biconnected components
-
component_distribution()
largest_component()
components()
is_connected()
count_components()
- Connected components of a graph
-
decompose()
- Decompose a graph into components
-
scg-method
- Spectral Coarse Graining
-
stochastic_matrix()
- Stochastic matrix of a graph
-
dim_select()
- Dimensionality selection for singular values using profile likelihood.
-
embed_adjacency_matrix()
- Spectral Embedding of Adjacency Matrices
-
embed_laplacian_matrix()
- Spectral Embedding of the Laplacian of a Graph
-
consensus_tree()
- Create a consensus tree from several hierarchical random graph models
-
fit_hrg()
- Fit a hierarchical random graph model
-
hrg-methods
- Hierarchical random graphs
-
hrg()
- Create a hierarchical random graph from an igraph graph
-
hrg_tree()
- Create an igraph graph from a hierarchical random graph model
-
predict_edges()
- Predict edges based on a hierarchical random graph model
-
print(<igraphHRG>)
- Print a hierarchical random graph model to the screen
-
print(<igraphHRGConsensus>)
- Print a hierarchical random graph consensus tree to the screen
-
sample_hrg()
- Sample from a hierarchical random graph model
-
is_degseq()
- Check if a degree sequence is valid for a multi-graph
-
is_graphical()
- Is a degree sequence graphical?
-
plot(<sir>)
- Plotting the results on multiple SIR model runs
-
time_bins()
median(<sir>)
quantile(<sir>)
sir()
- SIR model on graphs
-
random_walk()
random_edge_walk()
- Random walk on a graph
-
igraph_demo()
- Run igraph demos, step by step
-
graph_from_graphdb()
- Load a graph from the graph database for testing graph isomorphism.
-
read_graph()
- Reading foreign file formats
-
write_graph()
- Writing the graph to a file in some format
-
tkigraph()
- Experimental basic igraph GUI
-
tkplot()
tk_close()
tk_off()
tk_fit()
tk_center()
tk_reshape()
tk_postscript()
tk_coords()
tk_set_coords()
tk_rotate()
tk_canvas()
- Interactive plotting of graphs
-
console()
.igraph.progress()
.igraph.status()
- The igraph console
-
graph_version()
- igraph data structure versions
-
upgrade_graph()
- igraph data structure versions