matplot: Plot Columns of Matrices

In fda: Functional Data Analysis

Plot Columns of Matrices

Description

Plot the columns of one matrix against the columns of another.

Usage

matplot(x, ...)
## Default S3 method:
matplot(x, y, type = "p", lty = 1:5, lwd = 1,
    lend = par("lend"), pch = NULL, col = 1:6, cex = NULL, bg = NA,
    xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL, ..., add = FALSE,
    verbose = getOption("verbose"))
## S3 method for class 'Date'
matplot(x, y, type = "p", lty = 1:5, lwd = 1,
    lend = par("lend"), pch = NULL, col = 1:6, cex = NULL, bg = NA,
    xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL, ..., add = FALSE,
    verbose = getOption("verbose"))
## S3 method for class 'POSIXct'
matplot(x, y, type = "p", lty = 1:5, lwd = 1,
    lend = par("lend"), pch = NULL, col = 1:6, cex = NULL, bg = NA,
    xlab = NULL, ylab = NULL, xlim = NULL, ylim = NULL, ..., add = FALSE,
    verbose = getOption("verbose"))

Arguments

x, y	vectors or matrices of data for plotting. The number of rows should match. If one of them are missing, the other is taken as 'y' and an 'x' vector of '1:n' is used. Missing values ('NA's) are allowed.
type	character string (length 1 vector) or vector of 1-character strings indicating the type of plot for each column of 'y', see 'plot' for all possible 'type's. The first character of 'type' defines the first plot, the second character the second, etc. Characters in 'type' are cycled through; e.g., '"pl"' alternately plots points and lines.
lty, lwd, lend	vector of line types, widths, and end styles. The first element is for the first column, the second element for the second column, etc., even if lines are not plotted for all columns. Line types will be used cyclically until all plots are drawn.
pch	character string or vector of 1-characters or integers for plotting characters, see 'points'. The first character is the plotting-character for the first plot, the second for the second, etc. The default is the digits (1 through 9, 0) then the lowercase and uppercase letters.
col	vector of colors. Colors are used cyclically.
cex	vector of character expansion sizes, used cyclically. This works as a multiple of 'par("cex")'. 'NULL' is equivalent to '1.0'.
bg	vector of background (fill) colors for the open plot symbols given by 'pch=21:25' as in 'points'. The default 'NA' corresponds to the one of the underlying function 'plot.xy'.
xlab, ylab	titles for x and y axes, as in 'plot'.
xlim, ylim	ranges of x and y axes, as in 'plot'.
...	Graphical parameters (see 'par') and any further arguments of 'plot', typically 'plot.default', may also be supplied as arguments to this function. Hence, the high-level graphics control arguments described under 'par' and the arguments to 'title' may be supplied to this function.
add	logical. If 'TRUE', plots are added to current one, using 'points' and 'lines'.
verbose	logical. If 'TRUE', write one line of what is done.

Details

Note that for multivariate data, a suitable array must first be defined using the par function.

matplot.default calls matplot. The other methods are needed, because the default methods ignore the Date or POSIXct character of x, labeling the horizontal axis as numbers, thereby placing it on the user to translate the numbers of days or seconds since the start of the epoch into dates (and possibly times for POSIXct x).

Side Effects

a plot of the functional observations

References

Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.

See Also

matplot, plot, points, lines, matrix, par

Examples

oldpar <- par(no.readonly=TRUE)
##
## matplot.Date, matplot.POSIXct
##
# Date
invasion1 <- as.Date('1775-09-04')
invasion2 <- as.Date('1812-07-12')
earlyUS.Canada <- c(invasion1, invasion2)
Y <- matrix(1:4, 2, 2)
matplot(earlyUS.Canada, Y)

# POSIXct
AmRev.ct <- as.POSIXct1970(c('1776-07-04', '1789-04-30'))
matplot(AmRev.ct, Y)

##
## matplot.default (copied from matplot{graphics})
##
matplot((-4:5)^2, main = "Quadratic") # almost identical to plot(*)
sines <- outer(1:20, 1:4, function(x, y) sin(x / 20 * pi * y))
matplot(sines, pch = 1:4, type = "o", col = rainbow(ncol(sines)))
matplot(sines, type = "b", pch = 21:23, col = 2:5, bg = 2:5,
             main = "matplot(...., pch = 21:23, bg = 2:5)")

x <- 0:50/50
matplot(x, outer(x, 1:8, function(x, k) sin(k*pi * x)),
             ylim = c(-2,2), type = "plobcsSh",
             main= "matplot(,type = \"plobcsSh\" )")
## pch & type =  vector of 1-chars :
matplot(x, outer(x, 1:4, function(x, k) sin(k*pi * x)),
             pch = letters[1:4], type = c("b","p","o"))

lends <- c("round","butt","square")
matplot(matrix(1:12, 4), type="c", lty=1, lwd=10, lend=lends)
text(cbind(2.5, 2*c(1,3,5)-.4), lends, col= 1:3, cex = 1.5)

table(iris$Species) # is data.frame with 'Species' factor
iS <- iris$Species == "setosa"
iV <- iris$Species == "versicolor"
op <- par(bg = "bisque")
matplot(c(1, 8), c(0, 4.5), type= "n", xlab = "Length", ylab = "Width",
             main = "Petal and Sepal Dimensions in Iris Blossoms")
matpoints(iris[iS,c(1,3)], iris[iS,c(2,4)], pch = "sS", col = c(2,4))
matpoints(iris[iV,c(1,3)], iris[iV,c(2,4)], pch = "vV", col = c(2,4))
legend(1, 4, c("    Setosa Petals", "    Setosa Sepals",
                    "Versicolor Petals", "Versicolor Sepals"),
            pch = "sSvV", col = rep(c(2,4), 2))

nam.var <- colnames(iris)[-5]
nam.spec <- as.character(iris[1+50*0:2, "Species"])
iris.S <- array(NA, dim = c(50,4,3),
                     dimnames = list(NULL, nam.var, nam.spec))
for(i in 1:3) iris.S[,,i] <- data.matrix(iris[1:50+50*(i-1), -5])

matplot(iris.S[,"Petal.Length",], iris.S[,"Petal.Width",], pch="SCV",
             col = rainbow(3, start = .8, end = .1),
             sub = paste(c("S", "C", "V"), dimnames(iris.S)[[3]],
                         sep = "=", collapse= ",  "),
             main = "Fisher's Iris Data")
par(op)
par(oldpar)

fda documentation built on Sept. 30, 2024, 9:19 a.m.