[](https://travis-ci.org/hypertidy/ffraster) [](https://ci.appveyor.com/project/mdsumner/ffraster) [](https://codecov.io/github/hypertidy/ffraster?branch=master) ffraster allows loading a file-backed raster as an `ff` object, and some wrappers to deal with the [rasterfile format](https://cran.r-project.org/web/packages/raster/vignettes/rasterfile.pdf) using ff’s array abstractions linked to a file on disk. ``` r library(raster) b <- brick("/some/huge/brick.grd") library(ffraster) ff_object(b) ``` ffraster tries to solve the following problem, posed by raster’s native binary “rasterfile” format for long time series. - a multilayer rasterfile can only be created from an existing multi-layer raster - setting the values of a rasterfile for a given layer reads all the data into memory and cuts the link to the rasterfile # Applications Create a brick by instantiating the file with an `ff` “out of memory” array and populating the data layer by layer using ff’s array methods. First, obtain the SST data use in `rasterVis::hovmoller`, we end up with several file paths to NetCDF files in `files`. ``` r td <- tempdir() curl::curl_download('https://raw.github.com/oscarperpinan/spacetime-vis/master/data/SISmm2008_CMSAF.zip', destfile = file.path(td, 'SISmm2008_CMSAF.zip')) unzip(file.path(td, 'SISmm2008_CMSAF.zip'), exdir = td) files <- file.path(td, list.files(td, pattern = "SISmm.*UD.nc$")) ``` Now set up the .grd metadata file and a ff-array as an interface to the raw binary data in the .gri file. ``` r library(raster) #> Loading required package: sp ## we'll create a brick layer by layer in this file (.grd/.gri) r_brickfile <- rasterTmpFile() ## we need the first layer to initiate the target as a template r0 <- raster(files[1]) #> Loading required namespace: ncdf4 library(ffraster) ffraster:::.writeGRD(r0, dataType = "FLT4S", filename = r_brickfile, nbands = length(files), ## if dates are known, input them here for each file dates = NULL) #> [1] TRUE ## use mode "single", float32 (or double, float64) ff_array <- ffrarr(c(nrow(r0), ncol(r0), length(files)), mode = "single", filename = r_brickfile, readonly = FALSE) ## now loop and populate for (i in seq_along(files)) { ## in the loop we read each layer from file (or whatever source of layers we have) r <- raster(files[i]) ## the ff array can be written to by treating like a slice in a 3D array ## the default is transpose, but note other layouts are possible for rasterfile and in ff ff_array[,,i] <- values(t(r)) } plot(brick(r_brickfile), zlim = c(36, 365)) ```  ``` r ## show that we get the same result plot(stack(files), zlim = c(36, 365)) ```  See related work in library mmap, in GDAL virtualmem, VRT-linked binary, GDAL driver for R-raster, R packages ff, matter, spatial.tools, mmap, bigmemory, rasterfaster, Manifold’s Raw Binary surface. Please note that this project is released with a [Contributor Code of Conduct](CONDUCT.md). By participating in this project you agree to abide by its terms.