binMean1D {oce}

Bin-average f=f(x)

Description

Average the values of a vector f in bins defined on another vector x. The values are broken up into bins using cut().

Usage

binMean1D(x, f, xbreaks, include.lowest = FALSE, na.rm = FALSE)

Arguments

x

vector of numerical values that will be categorized into bins via the xbreaks parameter.

f

vector of numerical values that are associated with the x values.

xbreaks

vector of values of x at the boundaries between bins, calculated using pretty() if not supplied.

include.lowest

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

na.rm

logical value indicating whether to remove NA values before doing the computation of the average. This is passed to mean(), which does the work of the present function.

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.

Value

A list with the following elements: the breaks (xbreaks, midpoints (xmids) between those breaks, the count (number) of x values between successive breaks, and the resultant average (result) of f, classified by the x breaks.

Author(s)

Dan Kelley

See Also

Other bin-related functions: binApply1D(), binApply2D(), binAverage(), binCount1D(), binCount2D(), binMean2D()

Examples

# Plot raw temperature profile as circles, with lines indicating
# the result of averaging in 1-metre depth intervals.
library(oce)
data(ctd)
z <- ctd[["z"]]
T <- ctd[["temperature"]]
plot(T, z, cex = 0.3)
TT <- binMean1D(z, T, seq(-100, 0, 1))
lines(TT$result, TT$xmids, col = rgb(1, 0, 0, 0.9), lwd = 2)