Package {ggbipart}

A package to plot bipartite interaction networks in R.

Description

Bipartite networks

Details

The ggbipart package includes a series of R functions aimed to plot bipartite networks within the ggplot2 environment. The library relies heavily on code developed by Francois Briatte for the ggnet library. Bipartite networks are a special type of network where nodes are of two distinct types or sets, so that connections (links) only exist among nodes of the different sets. As in other types of network, bipartite structures can be binary (only the presence/absence of the links is mapped) or quantitative (weighted), where the links can have variable importance or weight. To plot, we start with an adjacency or incidence matrix. Using matrices that illustrate ecological interactions among species, such as the mutualisttic interactions of animal pollinators and plant flowers. The two sets (modes) of these bipartite networks are animals (e.g., pollinators) and plants species. From any adjacency matrix we can get a network object or an igraph object for plotting and analysis.

Installation.

'# devtools::install_github("pedroj/bipartite_plots")'

'# library(ggbipart)'

Suggested references:

Pocock, M.J.O., Evans, D.M., Fontaine, C., Harvey, M., Julliard, R., McLaughlin, O., Silvertown, J., Tamaddoni-Nezhad, A., White, P.C.L. and Bohan, D.A. (2016) The visualisation of ecological networks, and their use as a tool for engagement, advocacy and management. Advances in Ecological Research, 1st ed, pp. 41-85. Elsevier Ltd.

Bascompte, J., Jordano, P. (2014) Mutualistic Networks. Princeton University Press, Princeton, NJ.

Author(s)

Pedro Jordano

See Also

Useful links:

• http://pjordanolab.ebd.csic.es/resources/

• Report bugs at https://github.com/pedroj/bipartite_plots/issues

Function bip_binplot, to plot a network object corresponding to a binary adjacency matrix.

Description

mymat is the adjacency matrix, to get the dimensions from. net is a network object corresponding to mymat. The object net can be initialized with function bip_netinit.R

Usage

bip_binplot(
  mymat,
  net,
  usearrows = FALSE,
  mode = "kamadakawai",
  displaylabels = TRUE,
  label.cex = 0.6,
  vertex.cex = 1,
  edge.lty = 0.7
)

Arguments

Details

Plot of a network object corresponding to a binary adjacency matrix (qualitative, presence-absence, data.

Value

A plot object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
net <- bip_init_network(mat)
bip_binplot(mat, net)

Function to compute scaled edge weights for plotting.

Description

Function to compute scaled edge weights for plotting.

Usage

bip_edgewt(M, x = 30)

Arguments

Value

A vector of scaled edge weights for plotting.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
# One scaled weight per non-zero interaction; the largest equals x.
wt <- bip_edgewt(mat, x = 30)
summary(wt)

Plotting bipartite networks from adjacency matrix of a two-mode network.

Description

Plotting bipartite networks from adjacency matrix of a two-mode network.

Usage

bip_ggnet(
  net,
  mat,
  mode = "fruchtermanreingold",
  size = 9,
  palette = c(A = "grey", P = "gold"),
  color = "mode",
  label.size = 3,
  label = FALSE,
  shape = "mode",
  edge.label = NULL,
  layout.exp = 0,
  mode1 = "P",
  mode2 = "A"
)

Arguments

Details

Inputs are a net object and its corresponding adjacency matrix. It uses the adjacency matrix to compute scaled weighted edges with function edgewt. Part of the code from Francois Briatte, using package ggnet. DATE: 15Jul2013. Updated to ggnet 11/11/2016. ggnet2 automatically detects two-mode graphs from their bipartite network attribute. To simplify the plotting of each mode, it understands arguments of the form [alpha, color, shape, size] = "mode", which will mark the primary mode as "actor" and the secondary mode as "event". #—————————————————————————- Detect and color the mode To use the mode of the nodes as the basis for their colors, all the user has to do is to pass the color = "mode" argument, and then to style the "actor" and "event" values. #—————————————————————————

Value

A ggplot object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
net <- bip_init_network(mat)
bip_ggnet(net, mat)
# igraph input works too, and the matrix can be omitted
g <- bip_init_igraph(mat)
bip_ggnet(g)

Plotting bipartite networks from adjacency matrix of a two-mode network.

Description

Plotting bipartite networks from adjacency matrix of a two-mode network.

Usage

bip_igplot(mymat, g)

Arguments

Details

Plotting bipartite networks from adjacency weighted matrix of two-mode network. A modified version of the plotting, with package igraph. Requires input of the weighted "mymmat" matrix and its graph object, "g". #—————————————————————————

Value

An igraph graph object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
g <- bip_init_igraph(mat)
bip_igplot(mat, g)

Function to initialize a bipartite web for library igraph (type igraph).

Description

Function to initialize a bipartite web for library igraph (type igraph).

Usage

bip_init_igraph(mat)

Arguments

Details

Function to initialize a bipartite web for library igraph (type igraph), starting from a weighted adjacency matrix. Create the graph object (a bipartite, weighted graph) for igraph.

Value

A graph object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
g <- bip_init_igraph(mat)
g

Function to initialize a bipartite web for library network (type network).

Description

Function to initialize a bipartite web for library network (type network).

Usage

bip_init_network(mymat, mode1 = "P", mode2 = "A")

Arguments

Details

Function to initialize a bipartite web for library network (type network),

Value

A network object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
net <- bip_init_network(mat)
net

Function to plot a bipartite weighted network.

Description

Function to plot a bipartite weighted network.

Usage

bip_qtplot(mat)

Arguments

Details

Plotting a bipartite network from the weighted (quantitative) adjacency matrix of a two-mode network. Uses objects of type network and a traditional plot.

Value

A plot object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
bip_qtplot(mat)

Function to plot layout coordinates for railway network plot.

Description

Function to plot layout coordinates for railway network plot.

Usage

bip_railway(mymat, nodesize = 9, label = FALSE)

Arguments

Details

Plotting a bipartite network from the weighted (quantitative) adjacency matrix of a two-mode network.

# Code for separately nudging and rotating labels of modes. geom_text(aes(label= network.vertex.names(test.net)), angle<- ifelse(network.vertex.names(test.net)[1:dim(mymat)[1]], 0, 45), nudge_x<- ifelse(network.vertex.names(test.net)[1:dim(mymat)[1]], 0.5, -0.5))

Value

A plot object.

Examples

mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
bip_railway(mat, label = TRUE)

Function to vectorze an adjacency matrix.

Description

Function to vectorze an adjacency matrix.

Usage

vectorize(mat)

Arguments

Details

Like in STACK: Turn table (C) into (D): The input matrix should be read with row.names=1 option and a blank entry at the upper left corner.

C a b c d A 3 2 . . B . . 1 1

D A a 3 A b 2 A c . A d . B a . B b . B c 1 B d 1 #————————————————————-

Value

A vector object.

Examples

# A weighted plant-frugivore adjacency matrix shipped with the package.
mat <- as.matrix(read.csv(
    system.file("extdata", "sdw02_adj_fru.csv", package = "ggbipart"),
    comment.char = "#", row.names = 1, check.names = FALSE))
edges <- vectorize(mat)
head(edges)