Functions for plotting a partitioned matrix (representing the network)
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 plot.mat.nm has been replaced by plotMatNm.
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## 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, ... )
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 versiontitle.col: Title for the column-normalized matrix in nm versionmain.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 versionwhich: 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.The functions are used for their side effect - plotting.
# 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"
(2007). Generalized Blockmodeling of Valued Networks. Social Networks, 29(1), 105-126. doi: 10.1016/j.socnet.2006.04.002
(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
critFunC, optRandomParC
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