animation (version 2.0-0)

moving.block: Cycle through an R object and plot each subset of elements.

Description

Cycle through an R object and plot each subset of elements. For a long numeric vector or matrix (or data frame), we can plot only a subset of its elements to take a closer look at its structure. With a moving ``block'' from the beginning to the end of a vector or matrix or any R objects to which we can apply subset, all elements inside the block are plotted as a line or scatter plot or any customized plots.

Usage

moving.block(dat = runif(100), block, FUN, ...)

Arguments

dat

a numeric vector or two-column matrix

block

block length (i.e. how many elements are to be plotted in each step)

FUN

a plot function to be applied to the subset of data

...

other arguments passed to FUN

Value

• NULL

Details

For a vector, the elments from i + 1 to i + block will be plotted in the i-th step; similarly for a matrix or data frame, a (scatter) plot will be created from the i + 1-th row to i + block-th row. However, this function is not limited to scatter plots or lines -- we can customize the function FUN as we wish.

Examples

## (1) Brownian motion
#  block length: 101 (i.e. 300-200+1)
oopt = ani.options(nmax = ifelse(interactive(), 200, 
    2), interval = 0.1)
#  plot y = dat against x = i + 1:block
#  customize xlab and ylab with 'i' and 'block'
#  restrict ylim using the range of 'dat'
moving.block(dat = cumsum(rnorm(300)), FUN = function(..., 
    dat = dat, i = i, block = block) {
    plot(..., x = i + 1:block, xlab = sprintf("block length = %d", 
        block), ylim = range(dat), ylab = sprintf("x[%s:%s]", 
        i + 1, i + block))
}, type = "o", pch = 20)


## (2) Word counts of Hu's speech (block = 10; length(HuSpeech) = 75)
#  see any pattern in the President's speech?
ani.options(nmax = ifelse(interactive(), 66, 2), interval = 0.5)
data(HuSpeech)
moving.block(dat = HuSpeech, FUN = function(..., dat = dat, 
    i = i, block = block) {
    plot(..., x = i + 1:block, xlab = "paragraph index", ylim = range(dat), 
        ylab = sprintf("HuSpeech[%s:%s]", i + 1, i + block))
}, type = "o", pch = 20)


## (3) sunspot data: observe the 11-year cycles
#  block = 11 years x 12 months/year = 132
#  set interval greater than 0 if your computer really rocks!
ani.options(nmax = ifelse(interactive(), 2857, 2), 
    interval = 0)
spt.att = tsp(sunspot.month)
#  the time index (we need it to correctly draw the ticks of x-axis)
ts.idx = seq(spt.att[1], spt.att[2], 1/spt.att[3])
moving.block(dat = sunspot.month, block = 132, FUN = function(..., 
    dat = dat, i = i, block = block) {
    plot(..., x = ts.idx[i + 1:block], xlab = sprintf("block length = %d", 
        block), ylim = range(dat), ylab = sprintf("sunspot.month[%s:%s]", 
        i + 1, i + block))
}, type = "o", pch = 20)


## (4) earth quake: order the data by 'depth' first
#  see how the locations change as 'depth' increases
ani.options(nmax = ifelse(interactive(), 900, 2), 
    interval = 0.01)
#  compute the mean depth for each block of data
moving.block(quakes[order(quakes$depth), c("long", 
    "lat")], FUN = function(..., dat = dat, i = i, block = block) {
    plot(..., xlab = sprintf("%s[%s:%s]", colnames(dat)[1], i + 
        1, i + block), ylab = sprintf("%s[%s:%s]", colnames(dat)[2], 
        i + 1, i + block), xlim = range(dat[, 1]), ylim = range(dat[, 
        2]), main = sprintf("Mean Depth = %.3f", mean(sort(quakes$depth)[i + 
        1:block])))
}, pch = 20, col = rgb(0, 0, 0, 0.5))

ani.options(oopt)