# focal: Focal values In raster: Geographic Data Analysis and Modeling

## Description

Calculate focal ("moving window") values for the neighborhood of focal cells using a matrix of weights, perhaps in combination with a function.

## Usage

 ```1 2``` ```## S4 method for signature 'RasterLayer' focal(x, w, fun, filename='', na.rm=FALSE, pad=FALSE, padValue=NA, NAonly=FALSE, ...) ```

## Arguments

 `x` RasterLayer `w` matrix of weights (the moving window), e.g. a 3 by 3 matrix with values 1; see Details. The matrix does not need to be square, but the sides must be odd numbers. If you need even sides, you can add a column or row with weights of zero `fun` function (optional). The function fun should take multiple numbers, and return a single number. For example mean, modal, min or max. It should also accept a `na.rm` argument (or ignore it, e.g. as one of the 'dots' arguments. For example, `length` will fail, but `function(x, ...){na.omit(length(x))}` works. `filename` character. Filename for a new raster (optional) `na.rm` logical. If `TRUE`, `NA` will be removed from focal computations. The result will only be `NA` if all focal cells are `NA`. Except for some special cases (weights of 1, functions like min, max, mean), using `na.rm=TRUE` is generally not a good idea in this function because it will unbalance the effect of the weights `pad` logical. If `TRUE`, additional 'virtual' rows and columns are padded to `x` such that there are no edge effects. This can be useful when a function needs to have access to the central cell of the filter `padValue` numeric. The value of the cells of the padded rows and columns `NAonly` logical. If `TRUE`, only cell values that are `NA` are replaced with the computed focal values `...` Additional arguments as for `writeRaster`

## Details

`focal` uses a matrix of weights for the neighborhood of the focal cells. The default function is `sum`. It is computationally much more efficient to adjust the weights-matrix than to use another function through the `fun` argument. Thus while the following two statements are equivalent (if there are no `NA` values), the first one is faster than the second one:

`a <- focal(x, w=matrix(1/9, nc=3, nr=3))`

`b <- focal(x, w=matrix(1,3,3), fun=mean)`

There is, however, a difference if `NA` values are considered. One can use the `na.rm=TRUE` option which may make sense when using a function like `mean`. However, the results would be wrong when using a weights matrix.

Laplacian filter: `filter=matrix(c(0,1,0,1,-4,1,0,1,0), nrow=3)`

Sobel filter: `filter=matrix(c(1,2,1,0,0,0,-1,-2,-1) / 4, nrow=3)`

see the `focalWeight` function to create distance based circular, rectangular, or Gaussian filters.

## Value

RasterLayer

`focalWeight`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59``` ```r <- raster(ncols=36, nrows=18, xmn=0) r[] <- runif(ncell(r)) # 3x3 mean filter r3 <- focal(r, w=matrix(1/9,nrow=3,ncol=3)) # 5x5 mean filter r5 <- focal(r, w=matrix(1/25,nrow=5,ncol=5)) # Gaussian filter gf <- focalWeight(r, 2, "Gauss") rg <- focal(r, w=gf) # The max value for the lower-rigth corner of a 3x3 matrix around a focal cell f = matrix(c(0,0,0,0,1,1,0,1,1), nrow=3) f rm <- focal(r, w=f, fun=max) # global lon/lat data: no 'edge effect' for the columns xmin(r) <- -180 r3g <- focal(r, w=matrix(1/9,nrow=3,ncol=3)) ## Not run: ## focal can be used to create a cellular automaton # Conway's Game of Life w <- matrix(c(1,1,1,1,0,1,1,1,1), nr=3,nc=3) gameOfLife <- function(x) { f <- focal(x, w=w, pad=TRUE, padValue=0) # cells with less than two or more than three live neighbours die x[f<2 | f>3] <- 0 # cells with three live neighbours become alive x[f==3] <- 1 x } # simulation function sim <- function(x, fun, n=100, pause=0.25) { for (i in 1:n) { x <- fun(x) plot(x, legend=FALSE, asp=NA, main=i) dev.flush() Sys.sleep(pause) } invisible(x) } # Gosper glider gun m <- matrix(0, nc=48, nr=34) m[c(40, 41, 74, 75, 380, 381, 382, 413, 417, 446, 452, 480, 486, 517, 549, 553, 584, 585, 586, 619, 718, 719, 720, 752, 753, 754, 785, 789, 852, 853, 857, 858, 1194, 1195, 1228, 1229)] <- 1 init <- raster(m) # run the model sim(init, gameOfLife, n=150, pause=0.05) ## End(Not run) ```