fda (version 2.4.8)

plot.fd: 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 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 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 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 do.call(x$axes[[1]], x$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

Value

'done'

Side Effects

a plot of the functional observations

Details

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

See Also

lines.fd, plotfit.fd

Examples

# NOT RUN {
##
## plot.fd
##

daybasis65 <- create.fourier.basis(c(0, 365), 65,
                    axes=list("axesIntervals"))
# }
# NOT RUN {
<!-- %harmaccelLfd <- vec2Lfd(c(0,(2*pi/365)^2,0), c(0, 365)) -->
# }
# NOT RUN {
<!-- %harmfdPar     <- fdPar(daybasis65, harmaccelLfd, lambda=1e5) -->
# }
# NOT RUN {
daytempfd <- with(CanadianWeather, Data2fd(day.5,
        dailyAv[,,"Temperature.C"], daybasis65))

#  plot all the temperature functions for the monthly weather data
plot(daytempfd, main="Temperature Functions")

# }
# NOT RUN {
# To plot one at a time:
# The following pauses to request page changes.
plot(daytempfd, ask=TRUE)
# }
# NOT RUN {
# test plot(fd with NA)
daytempfd$coefs[,1] <- NA
plot(daytempfd, main="Temperature Functions")

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

# same plot via plot.fdSmooth
plot(fd3.4s0)
##
## with Date and POSIXct argvals
##
# Date
invasion1 <- as.Date('1775-09-04')
invasion2 <- as.Date('1812-07-12')
earlyUS.Canada <- c(invasion1, invasion2)
BspInvasion <- create.bspline.basis(earlyUS.Canada)

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

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

# }

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