Function reference • manynet

Making Functions for importing, exporting, constructing, and simulating directed and undirected, one-mode and two-mode networks. This includes functions for playing games upon networks, changing the distribution of nodal attributes.
`read_matrix()` `read_edgelist()` `read_nodelist()` `read_pajek()` `read_ucinet()` `read_dynetml()` `read_graphml()`	Making networks from external files
`write_matrix()` `write_edgelist()` `write_nodelist()` `write_pajek()` `write_ucinet()` `write_graphml()`	Making networks to external files
`create_empty()` `create_filled()` `create_ring()` `create_star()` `create_tree()` `create_lattice()` `create_components()` `create_core()` `create_explicit()`	Making networks with defined structures
`generate_random()` `generate_smallworld()` `generate_scalefree()` `generate_permutation()` `generate_utilities()`	Making networks with a stochastic element
`play_learning()` `play_segregation()`	Making learning models on networks
`play_diffusion()` `play_diffusions()`	Making diffusion models on networks
Modifying Functions for modifying networks into other classes or formats, or mofifying their properties or attributes. This includes functions for reformatting networks into networks of the same dimensions but a different type, e.g. from directed to undirected. It also includes functions for transforming networks into networks with other dimensions, such as from a two-mode network into a one-mode network. There are also functions for splitting networks, e.g. into a list of ego networks, and rejoining them from such lists. There are also tidy-style and igraph-style functions for adding or joining new data on nodes or ties to networks.
`as_edgelist()` `as_matrix()` `as_igraph()` `as_tidygraph()` `as_network()` `as_siena()` `as_graphAM()` `as_diffusion()`	Modifying network classes
`add_nodes()` `delete_nodes()` `add_node_attribute()` `mutate_nodes()` `mutate()` `bind_node_attributes()` `join_nodes()` `rename_nodes()` `rename()` `filter_nodes()`	Modifying node data
`add_ties()` `delete_ties()` `add_tie_attribute()` `mutate_ties()` `rename_ties()` `bind_ties()` `join_ties()` `filter_ties()` `select_ties()` `summarise_ties()`	Modifying tie data
`to_uniplex()` `to_undirected()` `to_directed()` `to_redirected()` `to_reciprocated()` `to_acyclic()` `to_unweighted()` `to_unsigned()` `to_unnamed()` `to_named()` `to_simplex()` `to_anti()`	Modifying network formats
`to_egos()` `to_subgraphs()` `to_components()` `to_waves()` `to_slices()`	Splitting networks into lists
`to_onemode()` `to_twomode()` `to_multilevel()`	Modifying network levels
`to_matching()` `to_mentoring()` `to_eulerian()` `to_tree()`	Modifying networks paths
`to_mode1()` `to_mode2()` `to_ties()` `to_galois()`	Modifying networks projection
`to_giant()` `to_no_isolates()` `to_subgraph()` `to_blocks()`	Modifying networks scope
`from_subgraphs()` `from_egos()` `from_waves()` `from_slices()` `from_ties()`	Joining lists of networks, graphs, and matrices
`na_to_zero()` `na_to_mean()`	Modifying missing tie data
Marking Functions for identifying properties of networks, nodes, or ties, all returning logical scalars or vectors. Note that all `node_` and `tie_` measures return a single vector so that they can be added directly to graph objects. `network_` measures return one or, in some cases of two-mode measures, two values. All `node_` and `tie_` measures return a single vector, the length of the nodes or ties in the network, respectively.
`is_connected()` `is_perfect_matching()` `is_eulerian()` `is_acyclic()` `is_aperiodic()`	Marking networks features
`is_manynet()` `is_graph()` `is_edgelist()` `is_list()` `is_longitudinal()` `is_dynamic()`	Marking networks classes
`is_twomode()` `is_weighted()` `is_directed()` `is_labelled()` `is_signed()` `is_complex()` `is_multiplex()` `is_uniplex()`	Marking networks formats
`node_is_latent()` `node_is_infected()` `node_is_recovered()` `node_is_exposed()`	Marking nodes based on diffusion properties
`node_is_isolate()` `node_is_cutpoint()` `node_is_core()` `node_is_fold()` `node_is_mentor()`	Marking nodes based on structural properties
`node_is_random()` `node_is_max()` `node_is_min()`	Marking nodes for selection based on measures
`tie_is_random()` `tie_is_max()` `tie_is_min()`	Marking ties for selection based on measures
`tie_is_multiple()` `tie_is_loop()` `tie_is_reciprocated()` `tie_is_feedback()` `tie_is_bridge()`	Marking ties based on structural properties
Mapping Functions for plotting and visualising graphs of different types. `autographr()` graphs any manynet-compatible class object automagically. `autographs()` and `autographt()` do the same for multiple networks and dynamic networks, respectively.
`network_nodes()` `network_ties()` `network_dims()` `network_node_attributes()` `network_tie_attributes()`	Describing network properties
`node_attribute()` `node_names()` `node_mode()` `tie_attribute()` `tie_weights()` `tie_signs()`	Describing attributes of nodes or ties in a network
`autographr()` `graphr()`	Easily graph networks with sensible defaults
`autographs()` `graphs()`	Easily graph a set of networks with sensible defaults
`autographt()` `autographd()` `grapht()`	Easily animate dynamic networks with sensible defaults
`layout_tbl_graph_configuration()` `layout_tbl_graph_triad()` `layout_tbl_graph_quad()`	Layout algorithms based on configurational positions
`layout_tbl_graph_hierarchy()` `layout_tbl_graph_alluvial()` `layout_tbl_graph_railway()` `layout_tbl_graph_ladder()` `layout_tbl_graph_concentric()` `layout_tbl_graph_multilevel()` `layout_tbl_graph_lineage()`	Layout algorithms based on bi- or other partitions
`theme_iheid()` `theme_ethz()` `theme_uzh()` `theme_rug()`	Many themes
`scale_fill_iheid()` `scale_colour_iheid()` `scale_color_iheid()` `scale_edge_colour_iheid()` `scale_edge_color_iheid()` `scale_fill_centres()` `scale_colour_centres()` `scale_color_centres()` `scale_edge_colour_centres()` `scale_edge_color_centres()` `scale_fill_sdgs()` `scale_colour_sdgs()` `scale_color_sdgs()` `scale_edge_colour_sdgs()` `scale_edge_color_sdgs()` `scale_fill_ethz()` `scale_colour_ethz()` `scale_color_ethz()` `scale_edge_colour_ethz()` `scale_edge_color_ethz()` `scale_fill_uzh()` `scale_colour_uzh()` `scale_color_uzh()` `scale_edge_colour_uzh()` `scale_edge_color_uzh()` `scale_fill_rug()` `scale_colour_rug()` `scale_color_rug()` `scale_edge_colour_rug()` `scale_edge_color_rug()`	Many scales
`many_palettes()`	Many palettes generator
Tutorials Functions for loading and extracting code from tutorials. There is also a function for tabulating the various network data included in the package, providing an overview of their properties.
`run_tute()` `extract_tute()` `pkg_data()`	Open and extract code from tutorials
Data The package contains a variety of networks useful for pedagogical purposes and used in the course ‘Social Networks Theories and Methods’ and other workshops. Each page documents the source of the data and its format. References are provided for further reading and citation.
`ison_adolescents`	One-mode subset of the adolescent society network (Coleman 1961)
`ison_algebra`	Multiplex graph object of friends, social, and task ties (McFarland 2001)
`ison_brandes`	One-mode and two-mode centrality demonstration networks
`ison_friends`	One-mode Friends character connections (McNulty, 2020)
`ison_hightech`	One-mode multiplex, directed network of managers of a high-tech company (Krackhardt 1987)
`ison_karateka`	One-mode karateka network (Zachary 1977)
`ison_koenigsberg`	One-mode Seven Bridges of Koenigsberg network (Euler 1741)
`ison_laterals`	Two-mode projection examples (Hollway 2021)
`ison_lawfirm`	One-mode lawfirm (Lazega 2001)
`ison_lotr`	One-mode network of Lord of the Rings character interactions
`ison_marvel_teams` `ison_marvel_relationships`	Multilevel two-mode affiliation, signed one-mode networks of Marvel comic book characters (Yuksel 2017)
`ison_monastery_like` `ison_monastery_esteem` `ison_monastery_influence` `ison_monastery_praise`	Three one-mode signed, weighted networks and a three-wave longitudinal network of monks (Sampson 1969)
`ison_networkers`	One-mode EIES dataset (Freeman and Freeman 1979)
`ison_physicians`	Four multiplex one-mode physician diffusion data (Coleman, Katz, and Menzel, 1966)
`ison_potter`	Six complex one-mode support data in Harry Potter books (Bossaert and Meidert 2013)
`ison_southern_women`	Two-mode southern women (Davis, Gardner and Gardner 1941)
`ison_starwars`	Seven one-mode Star Wars character interactions (Gabasova 2016)
`ison_usstates`	One-mode undirected network of US state contiguity (Meghanathan 2017)

Reference

Making

Modifying

Marking

Mapping

Tutorials

Data