Description Usage Arguments Value Author(s) References See Also Examples
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 plot.mat.nm
or plotMatNm
plots two matrices based on M, normalized by rows and columns, next to each other. The plot.array
or plotArray
plots an array.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 | plot.mat(x = M, M = x, clu = NULL,
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.col = "blue", 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, ...)
plotMat(x = M, M = x, clu = NULL,
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.col = "blue", 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, ...)
plot.mat.nm(x = M, M = x, ..., main.title = NULL,
title.row = "Row normalized",
title.col = "Column normalized",
main.title.line = -2, par.set = list(mfrow = c(1, 2)))
plotMatNm(x = M, M = x, ..., main.title = NULL,
title.row = "Row normalized",
title.col = "Column normalized",
main.title.line = -2, par.set = list(mfrow = c(1, 2)))
plot.array(x = M, M = x, ..., main.title = NULL, main.title.line
= -2, mfrow = NULL)
plotArray(x = M, M = x, ..., main.title = NULL, main.title.line
= -2, mfrow = NULL)
## S3 method for class 'mat'
plot(x = M, M = x, clu = NULL,
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.col = "blue", 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, ...)
## S3 method for class 'crit.fun'
plot(x, main = NULL, ...)
## S3 method for class 'opt.par'
plot(x, main = NULL, which = 1, ...)
## S3 method for class 'opt.par.mode'
plot(x, main = NULL, which = 1, ...)
## S3 method for class 'opt.more.par'
plot(x, main = NULL, which = 1, ...)
## S3 method for class 'opt.more.par.mode'
plot(x, main = NULL, which = 1, ...)
|
x |
A result from a corespodning function or a matrix or similar object representing a network. |
M |
A matrix or similar object representing a network - either |
clu |
A partition. Each unique value represents one cluster. If the network is one-mode, than this should be a vector, else a list of vectors, one for each mode. |
ylab |
Label for y axis. |
xlab |
Label for x axis. |
main |
Main title. |
main.title |
Main title in plot.array version. |
main.title.line |
The line in which main title is printed in |
mfrow |
|
print.val |
Should the values be printed in the matrix. |
print.0 |
If |
plot.legend |
Should the legend for shades be ploted. |
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 |
outer.title |
Should the title be printed on the 'inner' or 'outer' plot, default is |
title.line |
The line (from the top) where the title should be printed. The suitable values depend heavily on the displey type. |
mar |
A numerical vector of the form |
cex.val |
Size of the values printed. The default is |
val.y.coor.cor |
Correction for centering the values in the sqares in y direction. |
val.x.coor.cor |
Correction for centering the values in the sqares 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 |
print.x.axis.val |
Should the x axis values be printed. Default prints each axis if |
print.y.axis.val |
Should the y axis values be printed. Default prints each axis if |
x.axis.val.pos |
x coordiante of the y axis values. |
y.axis.val.pos |
y coordiante 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 seperates the partitions. |
par.line.col |
The color of the line that seperates the partitions. |
IM.dens |
The densitiey of shading lines for each block. |
IM |
The image (as obtaind with |
wnet |
Specifies which matrix (if more) should be ploted - used if |
wIM |
Specifies which IM (if more) should be used for ploting. The default value si set to |
use.IM |
Specifies if IM should be used for plotting. |
dens.leg |
It is used to translate the |
blackdens |
At which density should the values on dark colurs of lines be printed in white. |
plotLines |
Should the lines in the matrix be printed. The default value is set to |
frameMatrix |
Should the matrix be framed (if plotLines is |
x0ParLine |
Coordinates for lines seperating clusters. |
x1ParLine |
Coordinates for lines seperating clusters. |
y0ParLine |
Coordinates for lines seperating clusters. |
y1ParLine |
Coordinates for lines seperating clusters. |
colByUnits |
Coloring units 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 |
joinColOperator |
Function to join |
colTies |
If |
maxValPlot |
The value to use as maximum when computing colors (ties with maximal positive value are ploted as black). |
printMultipliedMessage |
Should the message '* all values in cells were multiplied by' be printed on the plot. The default value is set to |
replaceNAdiagWith0 |
If |
title.row |
Title for the row-normalized matrix in nm version |
title.col |
Title for the column-normalized matrix in nm version |
par.set |
A list of possible ploting paramters (to |
which |
Which (if there are more than one) of optimal solutions to plot. |
... |
Aditional arguments to |
The functions are used for their side affect - plotting.
Ale? ?iberna
?IBERNA, Ale? (2006): Generalized Blockmodeling of Valued Networks. Social Networks, Jan. 2007, vol. 29, no. 1, 105-126. http://dx.doi.org/10.1016/j.socnet.2006.04.002.
?IBERNA, Ale?. Direct and indirect approaches to blockmodeling of valued networks in terms of regular equivalence. J. math. sociol., 2008, vol. 32, no. 1, 57-84. http://www.informaworld.com/smpp/content?content=10.1080/00222500701790207.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ## 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 corespodning functions for examples for other plotting
## functions
## presented, that are esentially only the wrappers for "plot.max"
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.