app | R Documentation |

Apply a function to the values of each cell of a SpatRaster. Similar to `apply`

– think of each layer in a SpatRaster as a column (or row) in a matrix.

This is generally used to summarize the values of multiple layers into one layer; but this is not required.

`app`

calls function `fun`

with the raster data as first argument. Depending on the function supplied, the raster data is represented as either a matrix in which each layer is a column, or a vector representing a cell. The function should return a vector or matrix that is divisible by ncell(x). Thus, both "sum" and "rowSums" can be used, but "colSums" cannot be used.

You can also apply a function `fun`

across datasets by layer of a `SpatRasterDataset`

. In that case, summarization is by layer across SpatRasters.

## S4 method for signature 'SpatRaster' app(x, fun, ..., cores=1, filename="", overwrite=FALSE, wopt=list()) ## S4 method for signature 'SpatRasterDataset' app(x, fun, ..., cores=1, filename="", overwrite=FALSE, wopt=list())

`x` |
SpatRaster or SpatRasterDataset |

`fun` |
a function that operates on a vector or matrix. This can be a function that is defined in base-R or in a package, or a function you write yourself (see examples). Functions that return complex output (e.g. a list) may need to be wrapped in your own function to simplify the output to a vector or matrix. The following functions have been re-implemented in C++ for speed: "sum", "mean", "median", "modal", "which", "which.min", "which.max", "min", "max", "prod", "any", "all", "sd", "std", "first". To use the base-R function for say, "min", you could use something like |

`...` |
additional arguments for |

`cores` |
positive integer. If |

`filename` |
character. Output filename |

`overwrite` |
logical. If |

`wopt` |
list with named options for writing files as in |

To speed things up, parallelization is supported, but this is often not helpful, and it may actually be slower. There is only a speed gain if you have many cores (> 8) and/or a very complex (slow) function `fun`

. If you write `fun`

yourself, consider supplying a `cppFunction`

made with the Rcpp package instead (or go have a cup of tea while the computer works for you).

SpatRaster

`lapp`

, `tapp`

, `Math-methods`

r <- rast(ncols=10, nrows=10) values(r) <- 1:ncell(r) x <- c(r, sqrt(r), r+50) s <- app(x, fun=sum) s # for a few generic functions like # "sum", "mean", and "max" you can also do sum(x) ## SpatRasterDataset sd <- sds(x, x*2, x/3) a <- app(sd, max) a # same as max(x, x*2, x/3) # and as (but slower) b <- app(sd, \(i) max(i)) ## also works for a single layer f <- function(i) (i+1) * 2 * i + sqrt(i) s <- app(r, f) # same as above, but that is not memory-safe # and has no filename argument s <- f(r) ## Not run: #### multiple cores test0 <- app(x, sqrt) test1 <- app(x, sqrt, cores=2) testfun <- function(i) { 2 * sqrt(i) } test2 <- app(x, fun=testfun, cores =2) ## this fails because testfun is not exported to the nodes # test3 <- app(x, fun=function(i) testfun(i), cores=2) ## to export it, add it as argument to fun test3 <- app(x, fun=function(i, ff) ff(i), cores =3, ff=testfun) ## End(Not run)

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