plot.fd: Plot a Functional Data Object

In fda: Functional Data Analysis

Plot a Functional Data Object

Description

Functional data observations, or a derivative of them, are plotted. These may be either plotted simultaneously, as matplot does for multivariate data, or one by one with a mouse click to move from one plot to another. The function also accepts the other plot specification arguments that the regular plot does. Calling plot with an fdSmooth or an fdPar object plots its fd component.

Usage

## S3 method for class 'fd'
  plot(x, y, Lfdobj=0, href=TRUE, titles=NULL,
                    xlim=NULL, ylim=NULL, xlab=NULL,
                    ylab=NULL, ask=FALSE, nx=NULL, axes=NULL, ...)
## S3 method for class 'fdPar'
plot(x, y, Lfdobj=0, href=TRUE, titles=NULL,
                    xlim=NULL, ylim=NULL, xlab=NULL,
                    ylab=NULL, ask=FALSE, nx=NULL, axes=NULL, ...)
## S3 method for class 'fdSmooth'
plot(x, y, Lfdobj=0, href=TRUE, titles=NULL,
                    xlim=NULL, ylim=NULL, xlab=NULL,
                    ylab=NULL, ask=FALSE, nx=NULL, axes=NULL, ...)

Arguments

x	functional data object(s) to be plotted.
y	sequence of points at which to evaluate the functions 'x' and plot on the horizontal axis. Defaults to seq(rangex[1], rangex[2], length = nx). NOTE: This will be the values on the horizontal axis, NOT the vertical axis.
Lfdobj	either a nonnegative integer or a linear differential operator object. If present, the derivative or the value of applying the operator is plotted rather than the functions themselves.
href	a logical variable: If TRUE, add a horizontal reference line at 0.
titles	a vector of strings for identifying curves
xlab	a label for the horizontal axis.
ylab	a label for the vertical axis.
xlim	a vector of length 2 containing axis limits for the horizontal axis.
ylim	a vector of length 2 containing axis limits for the vertical axis.
ask	a logical value: If TRUE, each curve is shown separately, and the plot advances with a mouse click
nx	the number of points to use to define the plot. The default is usually enough, but for a highly variable function more may be required.
axes	Either a logical or a list or NULL. logical whether axes should be drawn on the plot list a list used to create custom axes used to create axes via x$axes[[1]] and x$axes[-1]. The primary example of this uses list("axesIntervals", ...), e.g., with Fourier bases to create CanadianWeather plots
...	additional plotting arguments that can be used with function plot

Details

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

Value

'done'

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

lines.fd, plotfit.fd

Examples

oldpar <- par(no.readonly=TRUE)
##
## plot.fd
##
daybasis65 <- create.fourier.basis(c(0, 365), 65,
                    axes=list("axesIntervals"))
harmaccelLfd <- vec2Lfd(c(0,(2*pi/365)^2,0), c(0, 365))
harmfdPar    <- fdPar(fd(matrix(0, daybasis65$nbasis,1), daybasis65), 
                      harmaccelLfd, lambda=1e5)
daytempfd <- with(CanadianWeather, smooth.basis(day.5,
        dailyAv[,,"Temperature.C"], daybasis65)$fd)
#  plot all the temperature functions for the monthly weather data
plot(daytempfd, main="Temperature Functions")
if (!CRAN()) {
  # To plot one at a time:
  # The following pauses to request page changes.
  
  plot(daytempfd, ask=TRUE)
}

##
## plot.fdSmooth
##
b3.4 <- create.bspline.basis(nbasis=4, norder=3, breaks=c(0, .5, 1))
# 4 bases, order 3 = degree 2 =
# continuous, bounded, locally quadratic
fdPar3 <- fdPar(fd(matrix(0,4,1), b3.4), lambda=1)

# Penalize excessive slope Lfdobj=1;
# (Can not smooth on second derivative Lfdobj=2 at it is discontinuous.)
fd3.4s0 <- smooth.basis(0:1, 0:1, fdPar3)

# using plot.fd directly
plot(fd3.4s0$fd)




##
## with Date and POSIXct argvals
##
# Date
invasion1 <- as.Date('1775-09-04')
invasion2 <- as.Date('1812-07-12')
earlyUS.Canada <- as.numeric(c(invasion1, invasion2))
BspInvasion    <- create.bspline.basis(earlyUS.Canada)

earlyUSyears <- seq(invasion1, invasion2, length.out=7)
earlyUScubic <- (as.numeric(earlyUSyears-invasion1)/365.24)^3
earlyUSyears <- as.numeric(earlyUSyears)
fitCubic     <- smooth.basis(earlyUSyears, earlyUScubic, BspInvasion)$fd
plot(fitCubic)

# POSIXct
AmRev.ct    <- as.POSIXct1970(c('1776-07-04', '1789-04-30'))
AmRevYrs.ct <- seq(AmRev.ct[1], AmRev.ct[2], length.out=14)
AmRevLin.ct <- as.numeric(AmRevYrs.ct-AmRev.ct[2])
AmRevYrs.ct <- as.numeric(AmRevYrs.ct)
BspRev.ct   <- create.bspline.basis(AmRev.ct)
fitLin.ct   <- smooth.basis(AmRevYrs.ct, AmRevLin.ct, BspRev.ct)$fd
plot(fitLin.ct)
par(oldpar)

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