prepInputs error : [mask] too many values for writing

[achubaty]

using latest development version:

devtools::load_all("~/GitHub/PredictiveEcology/reproducible")
#> ℹ Loading reproducible

cacheDir <- file.path(tempdir(), "reprex_maskTo", "cache")
inputDir <- file.path(tempdir(), "reprex_maskTo", "inputs")
outputDir <- file.path(tempdir(), "reprex_maskTo", "outputs")

targetCRS <- paste("+proj=lcc +lat_1=49 +lat_2=77 +lat_0=0 +lon_0=-95",
                   "+x_0=0 +y_0=0 +units=m +no_defs +ellps=GRS80 +towgs84=0,0,0")

## get studyArea (Ontario forest management units)
studyArea <- {
  prepInputs(
    url = "https://www.gisapplication.lrc.gov.on.ca/fmedatadownload/Packages/FORMGMT.zip",
    destinationPath = asPath(inputDir),
    targetFile = "FOREST_MANAGEMENT_UNIT.shp",
    alsoExtract = "similar",
    fun = "sf::st_read"
  ) |>
    sf::st_transform(crs = targetCRS) |>
    sf::st_union()
} |>
  Cache()
#> No cachePath supplied and getOption('reproducible.cachePath') is inside a temporary directory;
#>   this will not persist across R sessions.
#> Running `prepInputs`
#> Running `preProcess`
#> Preparing: FOREST_MANAGEMENT_UNIT.shp
#> ...downloading...
#>    Downloading
#>      https://www.gisapplication.lrc.gov.on.ca/fmedatadownload/Packages/FORMGMT.zip
#>      ...
#> Hardlinked version of file(s) created:
#> ... no copy/copies made.
#> User supplied files don't correctly specify the files in the archive (likely because of sub-folders); 
#> using items in archive with same basenames. Renaming to these: 
#> LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.shp
#> From:
#> /tmp/RtmpKGaOHk/reprex_maskTo/inputs/FORMGMT.zip  
#> Extracting
#> files
#>                                        <char>
#>  1: LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.dbf
#>  2: LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.prj
#>  3: LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.shp
#>  4: LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.shx
#> ... Done extracting 6 files
#>    Appending checksums to CHECKSUMS.txt. If you see this message repeatedly,
#>      you can specify targetFile (and optionally alsoExtract) so it knows what
#>      to look for.
#> `preProcess` done; took 43.41183 secs
#> Running `process` (i.e., loading file into R)
#> targetFile located at:
#> /tmp/RtmpKGaOHk/reprex_maskTo/inputs/LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.shp
#> Loading object into R
#> Reading layer `FOREST_MANAGEMENT_UNIT' from data source 
#>   `/tmp/RtmpKGaOHk/reprex_maskTo/inputs/LIO-2023-08-19/FOREST_MANAGEMENT_UNIT.shp' 
#>   using driver `ESRI Shapefile'
#> Simple feature collection with 39 features and 14 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: -95.15363 ymin: 44.31563 xmax: -75.81624 ymax: 52.39881
#> Geodetic CRS:  NAD83
#>    Saving large object (fn: sf::st_read , cacheId: 677ef02367f902c4 ) to Cache
#>      : 73.9 Mb
#> � Done!
#> Saved! Cache file: 677ef02367f902c4.rds; fn: sf::st_read
#> `prepInputs` done; took 51.21939 secs
#> Saving large object (fn: sf::st_union , cacheId: f85b7d2a0cd7dd6b ) to Cache :
#>   23.4 Mb
#> � Done!
#> Saved! Cache file: f85b7d2a0cd7dd6b.rds; fn: sf::st_union

## prep LCC for studyArea and write to outputDir
LCC <- Cache(
  prepInputs,
  url = paste0(
    "https://ftp.maps.canada.ca/pub/nrcan_rncan/",
    "Land-cover_Couverture-du-sol/canada-landcover_canada-couverture-du-sol/",
    "CanadaLandcover2010.zip"
  ),
  destinationPath = asPath(inputDir),
  to = studyArea,
  method = "near",
  datatype = "INT2U",
  fun = "terra::rast",
  targetFile = asPath("CAN_LC_2010_CAL.tif"),
  writeTo = asPath(file.path(outputDir, "LCC_ON_FMU.tif"))
)
#> No cachePath supplied and getOption('reproducible.cachePath') is inside a temporary directory;
#>   this will not persist across R sessions.
#> Running `prepInputs`
#> Running `preProcess`
#> Preparing: CAN_LC_2010_CAL.tif
#> alsoExtract is unspecified; assuming that all files must be extracted
#> Checksumming all files in archive
#> ...downloading...
#>    Downloading
#>      https://ftp.maps.canada.ca/pub/nrcan_rncan/Land-cover_Couverture-du-sol/canada-landcover_canada-couverture-du-sol/CanadaLandcover2010.zip
#>      ...
#> Hardlinked version of file(s) created:
#> ... no copy/copies made.
#> From:
#> /tmp/RtmpKGaOHk/reprex_maskTo/inputs/CanadaLandcover2010.zip  
#> Extracting
#> files
#>                  <char>
#>  1: CAN_LC_2010_CAL.tif
#> ... Done extracting 2 files
#>    Appending checksums to CHECKSUMS.txt. If you see this message repeatedly,
#>      you can specify targetFile (and optionally alsoExtract) so it knows what
#>      to look for.
#> `preProcess` done; took 42.43514 secs
#> Running `process` (i.e., loading file into R)
#> targetFile located at:
#> /tmp/RtmpKGaOHk/reprex_maskTo/inputs/CAN_LC_2010_CAL.tif
#> Loading object into R
#> Running `postProcessTo`
#> cropping...
#> |---------|---------|---------|---------|=========================================                                          
#> �done! took:  23.1 secs
#> projecting...
#> 
#> projectTo is a Vector dataset, which does not define all metadata required.
#> Using original resolution (30x30m)
#>    Using the origin and extent from `ext(from)` in the projection from
#>      `crs(projectTo)`.
#>    If this is not correct, create a template gridded object and pass that to
#>      `projectTo`...
#> |---------|---------|---------|---------|=========================================                                          |---------|---------|---------|---------|=========================================                                          
#> �done! took:  9.25 mins
#> masking...
#> |---------|---------|---------|---------|
#> maskTo resulted in following error: 
#>     - [mask] too many values for writing: 1214009477 > 151528274
#>     --> attempting to fix
#> |---------|---------|---------|---------|
#> Error in maskTo(from, maskTo, ..., overwrite = overwrite): Error : [mask] too many values for writing: 1214009477 > 246297134

try(unlink(file.path(tempdir(), "reprex_maskTo"), recursive = TRUE))

^{Created on 2025-01-08 with reprex v2.1.1}