Apply a Function to Vector Data

The function FUN is applied to f in bins specified by xbreaks. The division of data into bins is done with cut().

binApply1D(x, f, xbreaks, FUN, include.lowest = FALSE, ...)

Arguments

x

a vector of numerical values.

f

a vector of data to which FUN will be applied.

xbreaks

optional vector holding values of x at the boundaries between bins. If this is not given, it is computed by calling pretty() with n=20 segments.

FUN

function that is applied to the f values in each x bin. This must take a single numeric vector as input, and return a single numeric value.

include.lowest

logical value indicating whether to include x values that equal xbreaks[1]. See “Details”.

...

optional arguments to pass to FUN.

Value

A list with the following elements: xbreaks as used, xmids (the mid-points between those breaks) and result (the result of applying FUN to the f values in the designated bins).

Details

By default, the sub-intervals defined by the xbreaks argument are open on the left and closed on the right, to match the behaviour of cut(). An open interval does not include points on the boundary, and so any x values that exactly match the first breaks value will not be counted. To include such points in the calculation, set include.lowest to TRUE.

See also

Other bin-related functions: binApply2D(), binAverage(), binCount1D(), binCount2D(), binMean1D(), binMean2D()

Author

Dan Kelley

Examples

library(oce)
# salinity profile (black) with 1-dbar bin means (red)
data(ctd)
plotProfile(ctd, "salinity")
p <- ctd[["pressure"]]
S <- ctd[["salinity"]]
pbreaks <- seq(0, max(p), 1)
binned <- binApply1D(p, S, pbreaks, mean)
lines(binned$result, binned$xmids, lwd = 2, col = rgb(1, 0, 0, 0.9))