# im.apply

0th

Percentile

##### Apply Function Pixelwise to List of Images

Returns a pixel image obtained by applying a function to the values of corresponding pixels in several pixel images.

Keywords
manip, spatial, programming
##### Usage
im.apply(X, FUN, …, fun.handles.na=FALSE, check=TRUE)
##### Arguments
X

A list of pixel images (objects of class "im").

FUN

A function that can be applied to vectors, or a character string giving the name of such a function.

Additional arguments to FUN.

fun.handles.na

Logical value specifying what to do when the data include NA values. See Details.

check

Logical value specifying whether to check that the images in X are compatible (for example that they have the same grid of pixel locations) and to convert them to compatible images if necessary.

##### Details

The argument X should be a list of pixel images (objects of class "im"). If the images do not have identical pixel grids, they will be converted to a common grid using harmonise.im.

At each pixel location, the values of the images in X at that pixel will be extracted as a vector. The function FUN will be applied to this vector. The result (which should be a single value) becomes the pixel value of the resulting image.

The argument fun.handles.na specifies what to do when some of the pixel values are NA.

• If fun.handles.na=FALSE (the default), the function FUN is never applied to data that include NA values; the result is defined to be NA whenever the data contain NA.

• If fun.handles.na=TRUE, the function FUN will be applied to all pixel data, including those which contain NA values.

##### Value

A pixel image (object of class "im").

##### See Also

eval.im for algebraic operations with images.

• im.apply
##### Examples
# NOT RUN {
DA <- density(split(amacrine))
DA
im.apply(DA, max)
im.apply(DA, sum)

## Example with incompatible patterns of NA values
Z <- density(split(ants))
B <- owin(c(438, 666), c(80, 310))
Z[][B] <- NA
opa <- par(mfrow=c(2,2))
plot(Z[])
plot(Z[])
#' Default action: NA -> NA
plot(im.apply(Z, mean))
#' Use NA handling in mean.default
plot(im.apply(Z, mean, na.rm=TRUE, fun.handles.na=TRUE))
par(opa)
# }

Documentation reproduced from package spatstat, version 1.59-0, License: GPL (>= 2)

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