dnet (version 1.1.7)

visNetReorder: Function to visualise the multiple graph colorings reorded within a sheet-shape rectangle grid

Description

visNetReorder is supposed to visualise the multiple graph colorings reorded within a sheet-shape rectangle grid

Usage

visNetReorder(
g,
data,
sReorder,
height = 7,
margin = rep(0.1, 4),
border.color = "#EEEEEE",
colormap = c("bwr", "jet", "gbr", "wyr", "br", "yr", "rainbow", "wb"),
ncolors = 40,
zlim = NULL,
colorbar = T,
colorbar.fraction = 0.5,
newpage = T,
glayout = layout.fruchterman.reingold,
mtext.side = 3,
mtext.adj = 0,
mtext.cex = 1,
mtext.font = 2,
mtext.col = "black",
...
)

Arguments

g

an object of class "igraph" or "graphNEL"

data

an input data matrix used to color-code vertices/nodes. One column corresponds to one graph node coloring. The input matrix must have row names, and these names should include all node names of input graph, i.e. V(g)$name, since there is a mapping operation. After mapping, the length of the pattern vector should be the same as the number of nodes of input graph. The way of how to color-code is to map values in the pattern onto the whole colormap (see the next arguments: colormap, ncolors, zlim and colorbar)

sReorder

an object of class "sReorder"

height

a numeric value specifying the height of device

margin

margins as units of length 4 or 1

border.color

the border color of each figure

colormap

short name for the colormap. It can be one of "jet" (jet colormap), "bwr" (blue-white-red colormap), "gbr" (green-black-red colormap), "wyr" (white-yellow-red colormap), "br" (black-red colormap), "yr" (yellow-red colormap), "wb" (white-black colormap), and "rainbow" (rainbow colormap, that is, red-yellow-green-cyan-blue-magenta). Alternatively, any hyphen-separated HTML color names, e.g. "blue-black-yellow", "royalblue-white-sandybrown", "darkgreen-white-darkviolet". A list of standard color names can be found in http://html-color-codes.info/color-names

ncolors

the number of colors specified over the colormap

zlim

the minimum and maximum z/patttern values for which colors should be plotted, defaulting to the range of the finite values of z. Each of the given colors will be used to color an equispaced interval of this range. The midpoints of the intervals cover the range, so that values just outside the range will be plotted

colorbar

logical to indicate whether to append a colorbar. If pattern is null, it always sets to false

colorbar.fraction

the relative fraction of colorbar block against the figure block

newpage

logical to indicate whether to open a new page. By default, it sets to true for opening a new page

glayout

either a function or a numeric matrix configuring how the vertices will be placed on the plot. If layout is a function, this function will be called with the graph as the single parameter to determine the actual coordinates. This function can be one of "layout.auto", "layout.random", "layout.circle", "layout.sphere", "layout.fruchterman.reingold", "layout.kamada.kawai", "layout.spring", "layout.reingold.tilford", "layout.fruchterman.reingold.grid", "layout.lgl", "layout.graphopt", "layout.svd" and "layout.norm". A full explanation of these layouts can be found in http://igraph.org/r/doc/layout_nicely.html

mtext.side

on which side of the mtext plot (1=bottom, 2=left, 3=top, 4=right)

mtext.adj

the adjustment for mtext alignment (0 for left or bottom alignment, 1 for right or top alignment)

mtext.cex

the font size of mtext labels

mtext.font

the font weight of mtext labels

mtext.col

the color of mtext labels

...

additional graphic parameters. See http://igraph.org/r/doc/plot.common.html for the complete list.

Value

invisible

See Also

visNet, dNetReorder

Examples

# NOT RUN {
# 1) generate a random graph according to the ER model
g <- erdos.renyi.game(100, 1/100)

# 2) produce the induced subgraph only based on the nodes in query
subg <- dNetInduce(g, V(g), knn=0)

# 3) reorder the module with vertices being color-coded by input data
nnodes <- vcount(subg)
nsamples <- 10
data <- matrix(runif(nnodes*nsamples), nrow=nnodes, ncol=nsamples)
rownames(data) <- V(subg)$name
sReorder <- dNetReorder(g=subg, data, feature="node",
node.normalise="none")

# 4) visualise the module with vertices being color-coded by input data
visNetReorder(g=subg, colormap="bwr", data=data, sReorder)
# }