plotMat: Functions for plotting a partitioned matrix (representing the...

In blockmodeling: Generalized and Classical Blockmodeling of Valued Networks

Functions for plotting a partitioned matrix (representing the network)

Description

The main function plot.mat or plotMat plots a (optionally partitioned) matrix. If the matrix is partitioned, the rows and columns of the matrix are rearranged according to the partitions. Other functions are only wrappers for plot.mat or plotMat for convenience when plotting the results of the corresponding functions. The plotMatNm plots two matrices based on M, normalized by rows and columns, next to each other. The plotArray plots an array. plot.mat.nm has been replaced by plotMatNm.

Usage

## S3 method for class 'critFun'
plot(x, main = NULL, ...)

## S3 method for class 'crit.fun'
plot(x, main = NULL, ...)

plotMatNm(
  M = x,
  x = M,
  ...,
  main.title = NULL,
  title.row = "Row normalized",
  title.col = "Column normalized",
  main.title.line = -2,
  par.set = list(mfrow = c(1, 2))
)

## S3 method for class 'optMorePar'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'opt.more.par'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'optMoreParMode'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'opt.more.par.mode'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'optPar'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'opt.par'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'optParMode'
plot(x, main = NULL, which = 1, ...)

## S3 method for class 'opt.par.mode'
plot(x, main = NULL, which = 1, ...)

plotMat(
  x = M,
  clu = NULL,
  orderClu = FALSE,
  M = x,
  ylab = "",
  xlab = "",
  main = NULL,
  print.val = !length(table(M)) <= 2,
  print.0 = FALSE,
  plot.legend = !print.val && !length(table(M)) <= 2,
  print.legend.val = "out",
  print.digits.legend = 2,
  print.digits.cells = 2,
  print.cells.mf = NULL,
  outer.title = FALSE,
  title.line = ifelse(outer.title, -1.5, 7),
  mar = c(0.5, 7, 8.5, 0) + 0.1,
  cex.val = "default",
  val.y.coor.cor = 0,
  val.x.coor.cor = 0,
  cex.legend = 1,
  legend.title = "Legend",
  cex.axes = "default",
  print.axes.val = NULL,
  print.x.axis.val = !is.null(colnames(M)),
  print.y.axis.val = !is.null(rownames(M)),
  x.axis.val.pos = 1.01,
  y.axis.val.pos = -0.01,
  cex.main = par()$cex.main,
  cex.lab = par()$cex.lab,
  yaxis.line = -1.5,
  xaxis.line = -1,
  legend.left = 0.4,
  legend.up = 0.03,
  legend.size = 1/min(dim(M)),
  legend.text.hor.pos = 0.5,
  par.line.width = 3,
  par.line.width.newSet = par.line.width[1] * 2,
  par.line.col = "blue",
  par.line.col.newSet = "red",
  IM.dens = NULL,
  IM = NULL,
  wnet = NULL,
  wIM = NULL,
  use.IM = length(dim(IM)) == length(dim(M)) | !is.null(wIM),
  dens.leg = c(null = 100, nul = 100),
  blackdens = 70,
  plotLines = FALSE,
  frameMatrix = TRUE,
  x0ParLine = -0.1,
  x1ParLine = 1,
  y0ParLine = 0,
  y1ParLine = 1.1,
  colByUnits = NULL,
  colByRow = NULL,
  colByCol = NULL,
  mulCol = 2,
  joinColOperator = "+",
  colTies = FALSE,
  maxValPlot = NULL,
  printMultipliedMessage = TRUE,
  replaceNAdiagWith0 = TRUE,
  colLabels = FALSE,
  MplotValues = NULL,
  ...
)

plotArray(
  x = M,
  M = x,
  IM = NULL,
  ...,
  main.title = NULL,
  main.title.line = -2,
  mfrow = NULL
)

## S3 method for class 'mat'
plot(
  x = M,
  clu = NULL,
  orderClu = FALSE,
  M = x,
  ylab = "",
  xlab = "",
  main = NULL,
  print.val = !length(table(M)) <= 2,
  print.0 = FALSE,
  plot.legend = !print.val && !length(table(M)) <= 2,
  print.legend.val = "out",
  print.digits.legend = 2,
  print.digits.cells = 2,
  print.cells.mf = NULL,
  outer.title = FALSE,
  title.line = ifelse(outer.title, -1.5, 7),
  mar = c(0.5, 7, 8.5, 0) + 0.1,
  cex.val = "default",
  val.y.coor.cor = 0,
  val.x.coor.cor = 0,
  cex.legend = 1,
  legend.title = "Legend",
  cex.axes = "default",
  print.axes.val = NULL,
  print.x.axis.val = !is.null(colnames(M)),
  print.y.axis.val = !is.null(rownames(M)),
  x.axis.val.pos = 1.01,
  y.axis.val.pos = -0.01,
  cex.main = par()$cex.main,
  cex.lab = par()$cex.lab,
  yaxis.line = -1.5,
  xaxis.line = -1,
  legend.left = 0.4,
  legend.up = 0.03,
  legend.size = 1/min(dim(M)),
  legend.text.hor.pos = 0.5,
  par.line.width = 3,
  par.line.width.newSet = par.line.width[1] * 2,
  par.line.col = "blue",
  par.line.col.newSet = "red",
  IM.dens = NULL,
  IM = NULL,
  wnet = NULL,
  wIM = NULL,
  use.IM = length(dim(IM)) == length(dim(M)) | !is.null(wIM),
  dens.leg = c(null = 100, nul = 100),
  blackdens = 70,
  plotLines = FALSE,
  frameMatrix = TRUE,
  x0ParLine = -0.1,
  x1ParLine = 1,
  y0ParLine = 0,
  y1ParLine = 1.1,
  colByUnits = NULL,
  colByRow = NULL,
  colByCol = NULL,
  mulCol = 2,
  joinColOperator = "+",
  colTies = FALSE,
  maxValPlot = NULL,
  printMultipliedMessage = TRUE,
  replaceNAdiagWith0 = TRUE,
  colLabels = FALSE,
  MplotValues = NULL,
  ...
)

Arguments

x	A result from a corresponding function or a matrix or similar object representing a network.
main	Main title.
...	Additional arguments to plot.default for plotMat and also to plotMat for other functions.
M	A matrix or similar object representing a network - either x or M must be supplied - both are here to make the code compatible with generic and with older functions.
main.title	Main title in plotArray version.
title.row	Title for the row-normalized matrix in nm version
title.col	Title for the column-normalized matrix in nm version
main.title.line	The line in which main title is printed in plotArray version.
par.set	A list of possible plotting parameters (to par) to be used in nm version
which	Which (if there are more than one) of optimal solutions to plot.
clu	A partition. Each unique value represents one cluster. If the network is one-mode, then this should be a vector, else a list of vectors, one for each mode/set.
orderClu	Should the partition be ordered before plotting. FALSE by default. If TRUE, orderClu is used (using default arguments) to order the clusters in a partition in "decreasing" (see orderClu for interpretation) order.
ylab	Label for y axis.
xlab	Label for x axis.
print.val	Should the values be printed in the matrix.
print.0	If print.val = TRUE Should the 0s be printed in the matrix.
plot.legend	Should the legend for shades be plotted.
print.legend.val	Should the values be printed in the legend.
print.digits.legend	The number of digits that should appear in the legend.
print.digits.cells	The number of digits that should appear in the cells (of the matrix and/or legend).
print.cells.mf	If not NULL, the above argument is ignored, the cell values are printed as the cell are multiplied by this factor and rounded.
outer.title	Should the title be printed on the 'inner' or 'outer' margin of the plot, default is 'inner' margin.
title.line	The line (from the top) where the title should be printed. The suitable values depend heavily on the displayed type.
mar	A numerical vector of the form c(bottom, left, top, right) which gives the lines of margin to be specified on the four sides of the plot. The R default for ordinary plots is c(5, 4, 4, 2) + 0.1, while this function default is c(0.5, 7, 8.5, 0) + 0.1.
cex.val	The size of the values printed. The default is 10 / 'number of units'.
val.y.coor.cor	Correction for centering the values in the squares in y direction.
val.x.coor.cor	Correction for centering the values in the squares in x direction.
cex.legend	Size of the text in the legend.
legend.title	The title of the legend.
cex.axes	Size of the characters in axes. Default makes the cex so small that all categories can be printed.
print.axes.val	Should the axes values be printed. Default prints each axis if rownames or colnames is not NULL.
print.x.axis.val	Should the x axis values be printed. Default prints each axis if rownames or colnames is not NULL.
print.y.axis.val	Should the y axis values be printed. Default prints each axis if rownames or colnames is not NULL.
x.axis.val.pos	The x coordinate of the y axis values.
y.axis.val.pos	The y coordinate of the x axis values.
cex.main	Size of the text in the main title.
cex.lab	Size of the text in matrix.
yaxis.line	The position of the y axis (the argument 'line').
xaxis.line	The position of the x axis (the argument 'line').
legend.left	How much left should the legend be from the matrix.
legend.up	How much up should the legend be from the matrix.
legend.size	Relative legend size.
legend.text.hor.pos	Horizontal position of the legend text (bottom) - 0 = bottom, 0.5 = middle,...
par.line.width	The width of the line that separates the partitions.
par.line.width.newSet	The width of the line that separates that separates the sets/modes - only used when clu is a list and par.line.width has length 1.
par.line.col	The color of the line that separates the partitions.
par.line.col.newSet	The color of the line that separates that separates the sets/modes - only used when clu is a list and par.line.col has length 1.
IM.dens	The density of shading lines in each block.
IM	The image (as obtained with critFunC) of the blockmodel. dens.leg is used to translate this image into IM.dens.
wnet	Specifies which matrix (if more) should be plotted - used if M is an array.
wIM	Specifies which IM (if more) should be used for plotting. The default value is set to wnet) - used if IM is an array.
use.IM	Specifies if IM should be used for plotting.
dens.leg	It is used to translate the IM into IM.dens.
blackdens	At which density should the values on dark colors of lines be printed in white.
plotLines	Should the lines in the matrix be printed. The default value is set to FALSE, best set to TRUE for very small networks.
frameMatrix	Should the matrix be framed (if plotLines is FALSE). The default value is set to TRUE.
x0ParLine	Coordinates for lines separating clusters.
x1ParLine	Coordinates for lines separating clusters.
y0ParLine	Coordinates for lines separating clusters.
y1ParLine	Coordinates for lines separating clusters.
colByUnits	Coloring units. It should be a vector of unit length.
colByRow	Coloring units by rows. It should be a vector of unit length.
colByCol	Coloring units by columns. It should be a vector of unit length.
mulCol	Multiply color when joining with row, column. Only used when when colByUnits is not NULL.
joinColOperator	Function to join colByRow and colByCol. The default value is set to "+".
colTies	If TRUE, ties are colored, if FALSE, 0-ties are colored.
maxValPlot	The value to use as a maximum when computing colors (ties with maximal positive value are plotted as black).
printMultipliedMessage	Should the message '* all values in cells were multiplied by' be printed on the plot. The default value is set to TRUE.
replaceNAdiagWith0	If replaceNAdiagWith0 = TRUE Should the NA values on the diagonal of a matrix be replaced with 0s.
colLabels	Should the labels of units be colored. If FALSE, these are not colored, if TRUE, they are colored with colors of clusters as defined by palette. This can be also a vector of colors (or integers) for one-mode networks or a list of two such vectors for two-mode networks.
MplotValues	A matrix to strings to plot in cells. Only to be used if other values than those in the original matrix (x or M arguments) should be used. Defaults to NULL, in which case the valued from original matrix are plotted (if this is not prevented by some other arguments). Overrides all other arguments that deal with cell values (e.g. print.digits.cells). Sets print.val to TRUE and plot.legend to FALSE.
mfrow	mfrow Argument to par - number of row and column plots to be plotted on one figure.

Value

The functions are used for their side effect - plotting.

Author(s)

Aleš Žiberna

References

Žiberna, A. (2007). Generalized Blockmodeling of Valued Networks. Social Networks, 29(1), 105-126. doi: 10.1016/j.socnet.2006.04.002

Žiberna, A. (2008). Direct and indirect approaches to blockmodeling of valued networks in terms of regular equivalence. Journal of Mathematical Sociology, 32(1), 57-84. doi: 10.1080/00222500701790207

See Also

critFunC, optRandomParC

Examples

# Generation of the network
n <- 20
net <- matrix(NA, ncol = n, nrow = n)
clu <- rep(1:2, times = c(5, 15))
tclu <- table(clu)
net[clu == 1, clu == 1] <- rnorm(n = tclu[1] * tclu[1], mean = 0, sd = 1)
net[clu == 1, clu == 2] <- rnorm(n = tclu[1] * tclu[2], mean = 4, sd = 1)
net[clu == 2, clu == 1] <- rnorm(n = tclu[2] * tclu[1], mean = 0, sd = 1)
net[clu == 2, clu == 2] <- rnorm(n = tclu[2] * tclu[2], mean = 0, sd = 1)

# Ploting the network
plotMat(M = net, clu = clu, print.digits.cells = 3)
class(net) <- "mat"
plot(net, clu = clu)
# See corresponding functions for examples for other ploting
# functions
# presented, that are essentially only the wrappers for "plot.max"

blockmodeling documentation built on Feb. 12, 2024, 3:01 a.m.