Package 'simplegraph'

Title: Simple Graph Data Types and Basic Algorithms
Description: Simple classic graph algorithms for simple graph classes. Graphs may possess vertex and edge attributes. 'simplegraph' has no dependencies and it is written entirely in R, so it is easy to install.
Authors: Gabor Csardi
Maintainer: Gabor Csardi <[email protected]>
License: MIT + file LICENSE
Version: 1.0.1.9000
Built: 2024-12-31 06:03:35 UTC
Source: https://github.com/gaborcsardi/simplegraph

Help Index

Adjacent vertices for all vertices in a graph

Description

A vertex is adjacent is it is either a successor, or a predecessor.

Usage

adjacent_vertices(graph)

Arguments

graph

The graph.

Value

A named list of character vectors, the adjacent vertices for each vertex.

See Also

Other simple queries: edges(), order(), vertices()

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
adjacent_vertices(G)

Breadth-first search of a graph

Description

Breadth-first search of a graph

Usage

bfs(graph, from = vertex_ids(graph))

Arguments

graph

Input graph.
from

Character vector, which vertices to start the search from. By default all vertices are attempted.

Value

Character vector of the named of the visited vertices, in the order of their visit.

Examples

funcs <- graph(list(
  drop_internal = character(0),
  get_deps = c("get_description", "parse_deps",
    "%||%", "drop_internal"),
  get_description = "pkg_from_filename",
  parse_deps = "str_trim",
  cran_file = c("get_pkg_type", "r_minor_version", "cran_file"),
  download_urls = c("split_pkg_names_versions", "cran_file"),
  filename_from_url = character(0),
  get_pkg_type = character(0),
  pkg_download = c("dir_exists", "download_urls",
    "filename_from_url", "try_download"),
  r_minor_version = character(0),
  try_download = character(0),
  drop_missing_deps = character(0),
  install_order = character(0),
  restore = c("pkg_download", "drop_missing_deps",
    "install_order", "get_deps"),
  snap = character(0),
  `%||%` = character(0),
  data_frame = character(0),
  dir_exists = character(0),
  pkg_from_filename = character(0),
  split_pkg_names_versions = "data_frame",
  str_trim = character(0)
))
bfs(funcs)

Degree of vertices

Description

Degree of vertices

Usage

degree(graph, mode = c("out", "in", "total", "all"))

Arguments

graph

Input graph.
mode

Whether to calculate out-degree, in-degree, or the total degree.

Value

Named numeric vector of degrees.

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
degree(G, mode = "out")
degree(G, mode = "in")
degree(G, mode = "total")

Edges of a graph

Description

Edges of a graph

Usage

edges(graph)

Arguments

graph

The graph

Value

Data frame of edge data and metadata. The tail and head vertices are in the fist two columns. The rest of the columns are metadata.

See Also

Other simple queries: adjacent_vertices(), order(), vertices()

Examples

bridges <- graph(list(
  "Altstadt-Loebenicht" = c(
    "Kneiphof",
    "Kneiphof",
    "Lomse"
  ),
  "Kneiphof" = c(
    "Altstadt-Loebenicht",
    "Altstadt-Loebenicht",
    "Vorstadt-Haberberg",
    "Vorstadt-Haberberg",
    "Lomse"
  ),
  "Vorstadt-Haberberg" = c(
    "Kneiphof",
    "Kneiphof",
    "Lomse"
  ),
  "Lomse" = c(
    "Altstadt-Loebenicht",
    "Kneiphof",
    "Vorstadt-Haberberg"
  )
))
edges(bridges)

Create a graph

Description

Graphs can be specified as adjacency lists or (two) data frames.

Usage

graph(x, ...)

Arguments

x

A data frame, or a named list of character vectors. See details below.
...

Additional arguments, see details below.

Details

If the first argument is a data frame, then it is interpreted as vertex data, and a second data frame must be supplied as edge data. The first column of the vertex data must contain (character) vertex ids. The first two columns of the edge data frame must contain the directed edges of the graph, in the order of tail and head, as characters referring to the nodes ids. Other columns are kept as metadata.

If the first argument is not a data frame, but a list, then it is interpreted as an adjacency list. It must be named, and the names will be used as vertex ids. Each list element must be a character vector containing the successors of each vertex.

Value

A graph object.

Examples

funcs <- graph(list(
  drop_internal = character(0),
  get_deps = c("get_description", "parse_deps",
    "%||%", "drop_internal"),
  get_description = "pkg_from_filename",
  parse_deps = "str_trim",
  cran_file = c("get_pkg_type", "r_minor_version", "cran_file"),
  download_urls = c("split_pkg_names_versions", "cran_file"),
  filename_from_url = character(0),
  get_pkg_type = character(0),
  pkg_download = c("dir_exists", "download_urls",
    "filename_from_url", "try_download"),
  r_minor_version = character(0),
  try_download = character(0),
  drop_missing_deps = character(0),
  install_order = character(0),
  restore = c("pkg_download", "drop_missing_deps",
    "install_order", "get_deps"),
  snap = character(0),
  `%||%` = character(0),
  data_frame = character(0),
  dir_exists = character(0),
  pkg_from_filename = character(0),
  split_pkg_names_versions = "data_frame",
  str_trim = character(0)
))
funcs

vertices <- data.frame(
  stringsAsFactors = FALSE,
  name = c("Tom Hanks", "Cate Blanchett", "Matt Damon", "Kate Winslet",
    "Saving Private Ryan", "Contagion", "The Talented Mr. Ripley"),
  what = c("actor", "actor", "actor", "actor", "movie", "movie", "movie"),
  born = c("1956-07-09", "1966-05-26", "1970-10-08", "1975-10-05",
    NA, NA, NA),
  gender = c("M", "F", "M", "F", NA, NA, NA),
  year = c(NA, NA, NA, NA, 1998, 2011, 1999)
)

edges <- data.frame(
  stringsAsFactors = FALSE,
  actor = c("Tom Hanks", "Cate Blanchett", "Matt Damon", "Matt Damon",
    "Kate Winslet"),
  movie = c("Saving Private Ryan", "The Talented Mr. Ripley",
    "Saving Private Ryan", "The Talented Mr. Ripley", "Contagion")
)
actors <- graph(vertices, edges)
actors

Incident edges

Description

Incident edges

Usage

incident_edges(graph, mode = c("out", "in", "all", "total"))

Arguments

graph

Input graph.
mode

Whether to use out edges, in edges or all edges.

Value

A list of data frames, each a set of edges.

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
incident_edges(G, mode = "out")
incident_edges(G, mode = "in")
incident_edges(G, mode = "all")

Is this a loopy graph?

Description

A loopy graph has at least one loop edge: an edge from a vertex to itself.

Usage

is_loopy(graph)

Arguments

graph

The input graph.

Value

Logical scalar.

See Also

Other multigraphs: is_multigraph(), is_simple(), remove_loops(), remove_multiple(), simplify()

Examples

G <- graph(list(A = c("A", "B", "B"), B = c("A", "C"), C = "A"))
is_loopy(G)

G2 <- simplify(G)
is_loopy(G2)

Is this a multigraph?

Description

A multigraph has at least one pair or multiple edges, edges connecting the same (ordered) pair of vertices.

Usage

is_multigraph(graph)

Arguments

graph

Input graph.

Value

Logical scalar.

See Also

Other multigraphs: is_loopy(), is_simple(), remove_loops(), remove_multiple(), simplify()

Examples

G <- graph(list(A = c("A", "B", "B"), B = c("A", "C"), C = "A"))
is_multigraph(G)

G2 <- simplify(G)
is_multigraph(G2)

Is this a simple graph?

Description

A simple graph contains no loop and multiple edges.

Usage

is_simple(graph)

Arguments

graph

The input graph.

Value

Logical scalar.

See Also

Other multigraphs: is_loopy(), is_multigraph(), remove_loops(), remove_multiple(), simplify()

Examples

G <- graph(list(A = c("A", "B", "B"), B = c("A", "C"), C = "A"))
is_simple(G)

G2 <- simplify(G)
is_simple(G2)

Is the graph weighted?

Description

Is the graph weighted?

Usage

is_weighted(graph)

Arguments

graph

The graph.

Examples

G <- graph(
  data.frame(
    stringsAsFactors = FALSE,
    id = c("a", "b", "c", "d")
  ),
  data.frame(
    stringsAsFactors = FALSE,
    from   = c("a", "a", "b", "b", "c"),
    to     = c("b", "d", "d", "c", "a"),
    weight = c( 1 ,  2 ,  1 ,  3 ,  2 )
  )
)
is_weighted(G)

G2 <- graph(
  data.frame(
    stringsAsFactors = FALSE,
    id = c("a", "b", "c", "d")
  ),
  data.frame(
    stringsAsFactors = FALSE,
    from   = c("a", "a", "b", "b", "c"),
    to     = c("b", "d", "d", "c", "a")
  )
)
is_weighted(G2)

Order of a graph

Description

The order of the graph is the number of vertices.

Usage

order(graph)

Arguments

graph

The graph.

Value

Numeric scalar, the number of vertices.

See Also

Other simple queries: adjacent_vertices(), edges(), vertices()

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
order(G)

Predecessors and successors

Description

Predecessors and successors

Usage

predecessors(graph)

successors(graph)

Arguments

graph

Input graph

Value

Named list of character vectors, the predecessors or the successors of each vertex.

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
predecessors(G)
successors(G)

Remove loop edges from a graph

Description

Remove loop edges from a graph

Usage

remove_loops(graph)

Arguments

graph

Input graph

Value

Graph, with loop edges removed.

See Also

Other multigraphs: is_loopy(), is_multigraph(), is_simple(), remove_multiple(), simplify()

Examples

G <- graph(list(A = c("A", "B", "B"), B = c("A", "C"), C = "A"))
is_loopy(G)
is_loopy(remove_loops(G))

Remove multiple edges from a graph

Description

Remove multiple edges from a graph

Usage

remove_multiple(graph)

Arguments

graph

Input graph.

Value

Graph, without the multiple edges. (More precisely, from each set of multiple edges, only one, the first one, is kept.)

See Also

Other multigraphs: is_loopy(), is_multigraph(), is_simple(), remove_loops(), simplify()

Examples

G <- graph(list(A = c("A", "B", "B"), B = c("A", "C"), C = "A"))
is_multigraph(G)
is_multigraph(remove_multiple(G))

Check the validity of a graph data structure

Description

This is mainly for internal checks, but occasionally it might be useful externally.

Usage

sanitize(x, ...)

Arguments

x

Graph.
...

Extra arguments are curently ignored.

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
sanitize(G)

G <- c(G, list("this is not good" = c(1, 2, 3)))
try(sanitize(G))

Simple Graph Data Types and Basic Algorithms

Description

Simple classic graph algorithms for simple graph classes. Graphs may possess vertex and edge attributes. 'simplegraph' has no dependencies and it is writting entirely in R, so it is easy to install.

See Also

Useful links:

Remove multiple and loop edges from a graph

Description

Remove multiple and loop edges from a graph

Usage

simplify(graph)

Arguments

graph

Input graph.

Value

Another graph, with the multiple and loop edges removed.

See Also

Other multigraphs: is_loopy(), is_multigraph(), is_simple(), remove_loops(), remove_multiple()

Examples

G <- graph(list(A = c("A", "B", "B"), B = c("A", "C"), C = "A"))
is_simple(G)

G2 <- simplify(G)
is_simple(G2)

The size of the graph is the number of edges

Description

The size of the graph is the number of edges

Usage

size(graph)

Arguments

graph

The graph.

Value

Numeric scalar, the number of edges.

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
size(G)

Vertex strength: sum of weights of incident edges

Description

This is also called weighed degree.

Usage

strength(graph, mode = c("out", "in", "total", "all"))

Arguments

graph

Input graph.
mode

Whether to consider incoming (in), outgoing (out) or all (total) edges.

Details

For non-weighted graphs, the degree is returned as a fallback.

Value

Named numeric vector.

Examples

G <- graph(
  data.frame(
    stringsAsFactors = FALSE,
    id = c("a", "b", "c", "d")
  ),
  data.frame(
    stringsAsFactors = FALSE,
    from   = c("a", "a", "b", "b", "c"),
    to     = c("b", "d", "d", "c", "a"),
    weight = c( 1 ,  2 ,  1 ,  3 ,  2 )
  )
)
strength(G)

G2 <- graph(
  data.frame(
    stringsAsFactors = FALSE,
    id = c("a", "b", "c", "d")
  ),
  data.frame(
    stringsAsFactors = FALSE,
    from   = c("a", "a", "b", "b", "c"),
    to     = c("b", "d", "d", "c", "a")
  )
)
strength(G2)

Topological sorting of a graph

Description

Topological sorting of a graph

Usage

topological_sort(graph)

Arguments

graph

Input graph.

Value

Character vector of vertex ids, in topological order.

Examples

funcs <- graph(list(
  drop_internal = character(0),
  get_deps = c("get_description", "parse_deps",
    "%||%", "drop_internal"),
  get_description = "pkg_from_filename",
  parse_deps = "str_trim",
  cran_file = c("get_pkg_type", "r_minor_version", "cran_file"),
  download_urls = c("split_pkg_names_versions", "cran_file"),
  filename_from_url = character(0),
  get_pkg_type = character(0),
  pkg_download = c("dir_exists", "download_urls",
    "filename_from_url", "try_download"),
  r_minor_version = character(0),
  try_download = character(0),
  drop_missing_deps = character(0),
  install_order = character(0),
  restore = c("pkg_download", "drop_missing_deps",
    "install_order", "get_deps"),
  snap = character(0),
  `%||%` = character(0),
  data_frame = character(0),
  dir_exists = character(0),
  pkg_from_filename = character(0),
  split_pkg_names_versions = "data_frame",
  str_trim = character(0)
))
topological_sort(remove_loops(funcs))

Transpose a graph

Description

The transposed graph have the same vertices, and the same number of edges, but all edge directions are opposite comparated to the original graph.

Usage

transpose(graph)

Arguments

graph

Input graph

Value

Transposed graph.

Examples

funcs <- graph(list(
  drop_internal = character(0),
  get_deps = c("get_description", "parse_deps",
    "%||%", "drop_internal"),
  get_description = "pkg_from_filename",
  parse_deps = "str_trim",
  cran_file = c("get_pkg_type", "r_minor_version", "cran_file"),
  download_urls = c("split_pkg_names_versions", "cran_file"),
  filename_from_url = character(0),
  get_pkg_type = character(0),
  pkg_download = c("dir_exists", "download_urls",
    "filename_from_url", "try_download"),
  r_minor_version = character(0),
  try_download = character(0),
  drop_missing_deps = character(0),
  install_order = character(0),
  restore = c("pkg_download", "drop_missing_deps",
    "install_order", "get_deps"),
  snap = character(0),
  `%||%` = character(0),
  data_frame = character(0),
  dir_exists = character(0),
  pkg_from_filename = character(0),
  split_pkg_names_versions = "data_frame",
  str_trim = character(0)
))
edges(transpose(funcs))

Vertex ids of a graph

Description

Vertex ids of a graph

Usage

vertex_ids(graph)

Arguments

graph

The graph.

Value

Character vector of vertex ids.

Examples

G <- graph(list(A = c("B", "C"), B = "C", C = "A"))
vertex_ids(G)

Vertices of a graph, with metadata

Description

Vertices of a graph, with metadata

Usage

vertices(graph)

Arguments

graph

The graph.

Value

Character vector of vertex names.

See Also

Other simple queries: adjacent_vertices(), edges(), order()

Examples

bridges <- graph(list(
  "Altstadt-Loebenicht" = c(
    "Kneiphof",
    "Kneiphof",
    "Lomse"
  ),
  "Kneiphof" = c(
    "Altstadt-Loebenicht",
    "Altstadt-Loebenicht",
    "Vorstadt-Haberberg",
    "Vorstadt-Haberberg",
    "Lomse"
  ),
  "Vorstadt-Haberberg" = c(
    "Kneiphof",
    "Kneiphof",
    "Lomse"
  ),
  "Lomse" = c(
    "Altstadt-Loebenicht",
    "Kneiphof",
    "Vorstadt-Haberberg"
  )
))
vertices(bridges)