binMean2D | R Documentation |
Average the values of a vector f(x,y)
in bins defined on vectors
x
and y
. A common example might be averaging spatial data into
location bins.
binMean2D(
x,
y,
f,
xbreaks,
ybreaks,
flatten = FALSE,
fill = FALSE,
fillgap = -1,
include.lowest = FALSE,
na.rm = FALSE,
debug = getOption("oceDebug")
)
x |
vector of numerical values. |
y |
vector of numerical values. |
f |
Matrix of numerical values, a matrix f=f(x,y). |
xbreaks |
Vector of values of |
ybreaks |
Vector of values of |
flatten |
a logical value indicating whether the return value
also contains equilength vectors |
fill , fillgap |
values controlling whether to attempt to fill
gaps (that is, regions of NA values) in the matrix. If |
include.lowest |
logical value indicating whether to include
|
na.rm |
logical value indicating whether to remove NA values before
doing the computation of the average. This is passed to |
debug |
an integer specifying whether debugging information is
to be printed during the processing. This is a general parameter that
is used by many |
By default, i.e. with flatten
being FALSE, binMean2D()
returns a list with the following elements: xmids
, a vector
holding the x-bin midpoints; ymids
, a vector holding the y-bin
midpoints; number
, a matrix holding the number the points in each
bin; and result
, a matrix holding the mean value in each bin. If
flatten
is TRUE, the number
and result
matrices are renamed
as n
and f
and transformed to vectors, while the bin midpoints
are renamed as x
and y
and extended to match the length of n
and f
.
Dan Kelley
Other bin-related functions:
binApply1D()
,
binApply2D()
,
binAverage()
,
binCount1D()
,
binCount2D()
,
binMean1D()
library(oce)
x <- runif(500, 0, 0.5)
y <- runif(500, 0, 0.5)
f <- x^2 + y^2
xb <- seq(0, 0.5, 0.1)
yb <- seq(0, 0.5, 0.1)
m <- binMean2D(x, y, f, xb, yb)
cm <- colormap(f, col = oceColorsTurbo)
opar <- par(no.readonly = TRUE)
drawPalette(colormap = cm)
plot(x, y, col = cm$zcol, pch = 20, cex = 1.4)
contour(m$xmids, m$ymids, m$result, add = TRUE, labcex = 1.4)
par(opar)
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