These functions offer tools for transforming manynet-consistent objects (matrices, igraph, tidygraph, or network objects). Transforming means that the returned object may have different dimensions than the original object.
to_ego() scopes a network into the local neighbourhood of a given node.
to_giant() scopes a network into one including only the main component and no smaller components or isolates.
to_no_isolates() scopes a network into one excluding all nodes without ties
to_subgraph() scopes a network into a subgraph by filtering on some node-related logical statement.
to_blocks() reduces a network to ties between a given partition membership vector.
to_ego(.data, node, max_dist = 1, min_dist = 0, direction = c("out", "in"))
to_giant(.data)
to_no_isolates(.data)
to_subgraph(.data, ...)
to_blocks(.data, membership, FUN = mean)An object of a manynet-consistent class:
matrix (adjacency or incidence) from {base} R
edgelist, a data frame from {base} R or tibble from {tibble}
igraph, from the {igraph} package
network, from the {network} package
tbl_graph, from the {tidygraph} package
Name or index of node.
The maximum breadth of the neighbourhood. By default 1.
The minimum breadth of the neighbourhood. By default 0. Increasing this to 1 excludes the ego, and 2 excludes ego's direct alters.
String, either "out" or "in".
Arguments passed on to dplyr::filter
A vector of partition memberships.
A function for summarising block content.
By default mean.
Other recommended options include median, sum,
min or max.
All to_ functions return an object of the same class as that provided.
So passing it an igraph object will return an igraph object
and passing it a network object will return a network object,
with certain modifications as outlined for each function.
Not all functions have methods available for all object classes. Below are the currently implemented S3 methods:
| data.frame | igraph | list | matrix | network | tbl_graph | |
| to_blocks | 1 | 1 | 0 | 1 | 1 | 1 |
| to_ego | 0 | 1 | 0 | 0 | 0 | 1 |
| to_giant | 1 | 1 | 0 | 1 | 1 | 1 |
| to_no_isolates | 1 | 1 | 1 | 1 | 1 | 1 |
| to_subgraph | 1 | 1 | 0 | 1 | 1 | 1 |
to_blocks()Reduced graphs provide summary representations of network structures by collapsing groups of connected nodes into single nodes while preserving the topology of the original structures.
Other modifications:
manip_as,
manip_correlation,
manip_from,
manip_levels,
manip_miss,
manip_nodes,
manip_paths,
manip_permutation,
manip_project,
manip_reformat,
manip_split,
manip_ties
ison_adolescents %>%
mutate_ties(wave = sample(1995:1998, 10, replace = TRUE)) %>%
to_waves(attribute = "wave") %>%
to_no_isolates()
#> $`1997`
#> # The Adolescent Society
#> # A longitudinal, labelled, undirected network of 4 adolescents and 2
#> friendships ties
#> # A tibble: 4 × 1
#> name
#> <chr>
#> 1 Betty
#> 2 Sue
#> 3 Alice
#> 4 Jane
#> # A tibble: 2 × 3
#> from to wave
#> <int> <int> <int>
#> 1 1 2 1997
#> 2 3 4 1997
#>
#> $`1998`
#> # The Adolescent Society
#> # A longitudinal, labelled, undirected network of 6 adolescents and 4
#> friendships ties
#> # A tibble: 6 × 1
#> name
#> <chr>
#> 1 Sue
#> 2 Alice
#> 3 Dale
#> 4 Pam
#> 5 Carol
#> 6 Tina
#> # A tibble: 4 × 3
#> from to wave
#> <int> <int> <int>
#> 1 1 2 1998
#> 2 2 3 1998
#> 3 4 5 1998
#> 4 5 6 1998
#>
#> $`1995`
#> # The Adolescent Society
#> # A longitudinal, labelled, undirected network of 4 adolescents and 3
#> friendships ties
#> # A tibble: 4 × 1
#> name
#> <chr>
#> 1 Sue
#> 2 Jane
#> 3 Dale
#> 4 Pam
#> # A tibble: 3 × 3
#> from to wave
#> <int> <int> <int>
#> 1 1 3 1995
#> 2 2 3 1995
#> 3 1 4 1995
#>
#> $`1996`
#> # The Adolescent Society
#> # A longitudinal, labelled, undirected network of 2 adolescents and 1
#> friendships ties
#> # A tibble: 2 × 1
#> name
#> <chr>
#> 1 Alice
#> 2 Pam
#> # A tibble: 1 × 3
#> from to wave
#> <int> <int> <int>
#> 1 1 2 1996
#>