Package 'geotargets'

Title: 'Targets' Extensions for Geospatial Formats
Description: Provides extensions for various geospatial file formats, such as shapefiles and rasters. Currently provides support for the 'terra' geospatial formats. See the vignettes for worked examples, demonstrations, and explanations of how to use the various package extensions.
Authors: Nicholas Tierney [aut, cre] , Eric Scott [aut] , Andrew Brown [aut]
Maintainer: Nicholas Tierney <[email protected]>
License: MIT + file LICENSE
Version: 0.2.0.9000
Built: 2024-12-19 01:39:42 UTC
Source: https://github.com/njtierney/geotargets

Help Index

Get or Set geotargets Options

Description

Get or set behavior for geospatial data target stores using geotargets-specific global options.

Usage

geotargets_option_set(
  gdal_raster_driver = NULL,
  gdal_raster_creation_options = NULL,
  gdal_vector_driver = NULL,
  gdal_vector_creation_options = NULL,
  terra_preserve_metadata = NULL
)

geotargets_option_get(name)

Arguments

gdal_raster_driver

character, length 1; set the driver used for raster data in target store (default: "GTiff"). Options for driver names can be found here: https://gdal.org/drivers/raster/index.html.
gdal_raster_creation_options

character; set the GDAL creation options used when writing raster files to target store (default: ""). You may specify multiple values e.g. c("COMPRESS=DEFLATE", "TFW=YES"). Each GDAL driver supports a unique set of creation options. For example, with the default "GTiff" driver: https://gdal.org/drivers/raster/gtiff.html#creation-options.
gdal_vector_driver

character, length 1; set the file type used for vector data in target store (default: "GeoJSON").
gdal_vector_creation_options

character; set the GDAL layer creation options used when writing vector files to target store (default: "ENCODING=UTF-8"). You may specify multiple values e.g. c("WRITE_BBOX=YES", "COORDINATE_PRECISION=10"). Each GDAL driver supports a unique set of creation options. For example, with the default "GeoJSON" driver: https://gdal.org/drivers/vector/geojson.html#layer-creation-options
terra_preserve_metadata

character. When "drop" (default), any auxiliary files that would be written by terra::writeRaster() containing raster metadata such as units and datetimes are lost (note that this does not include layer names set with ⁠names() <-⁠). When "zip", these metadata are retained by archiving all written files as a zip file upon writing and unzipping them upon reading. This adds extra overhead and will slow pipelines.
name

character; option name to get.

Details

These options can also be set using options(). For example, geotargets_options_set(gdal_raster_driver = "GTiff") is equivalent to options("geotargets.gdal.raster.driver" = "GTiff").

Value

Specific options, such as "gdal.raster.driver". See "Details" for more information.

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({ # tar_dir() runs code from a temporary directory.
    library(geotargets)
    op <- getOption("geotargets.gdal.raster.driver")
    withr::defer(options("geotargets.gdal.raster.driver" = op))
    geotargets_option_set(gdal_raster_driver = "COG")
    targets::tar_script({
      list(
        geotargets::tar_terra_rast(
          terra_rast_example,
          system.file("ex/elev.tif", package = "terra") |> terra::rast()
        )
      )
    })
    targets::tar_make()
    x <- targets::tar_read(terra_rast_example)
  })
}

geotargets_option_get("gdal.raster.driver")
geotargets_option_get("gdal.raster.creation.options")

Copy a raster within a window

Description

Create a new SpatRaster object as specified by a window (area of interest) over the original SpatRaster. This is a wrapper around terra::window() which, rather than modifying the SpatRaster in place, returns a new SpatRaster leaving the original unchanged.

Usage

set_window(raster, window)

Arguments

raster

a SpatRaster object.
window

a SpatExtent object defining the area of interest.

Value

SpatRaster

Note

While this may have general use, it was created primarily for use within tar_terra_tiles().

Author(s)

Eric Scott

Examples

f <- system.file("ex/elev.tif", package="terra")
r <- terra::rast(f)
e <- terra::ext(c(5.9, 6,49.95, 50))
r2 <- set_window(r, e)
terra::ext(r)
terra::ext(r2)

Create a stars stars Target

Description

[Experimental]

Provides a target format for stars objects. Note that most or all stars objects work with ordinary tar_target() and do not necessarily need geotargets target factories the way terra objects do. Currently tar_stars() has the same limitations as stars::write_stars(), so use with caution.

Usage

tar_stars(
  name,
  command,
  pattern = NULL,
  proxy = FALSE,
  mdim = FALSE,
  ncdf = FALSE,
  driver = geotargets_option_get("gdal.raster.driver"),
  options = geotargets_option_get("gdal.raster.creation.options"),
  ...,
  tidy_eval = targets::tar_option_get("tidy_eval"),
  packages = targets::tar_option_get("packages"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

tar_stars_proxy(
  name,
  command,
  pattern = NULL,
  mdim = FALSE,
  ncdf = FALSE,
  driver = geotargets_option_get("gdal.raster.driver"),
  options = geotargets_option_get("gdal.raster.creation.options"),
  ...,
  tidy_eval = targets::tar_option_get("tidy_eval"),
  packages = targets::tar_option_get("packages"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

Arguments

name

Symbol, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. See targets::tar_target() for more information.
command

R code to run the target.
pattern

Code to define a dynamic branching pattern for a target. See targets::tar_target() for more information.
proxy

logical. Passed to stars::read_stars(). If TRUE the target will be read as an object of class stars_proxy. Otherwise, the object is class stars.
mdim

logical. Use the Multidimensional Raster Data Model via stars::write_mdim()? Default: FALSE. Only supported for some drivers, e.g. "netCDF" or "Zarr".
ncdf

logical. Use the NetCDF library directly to read data via stars::read_ncdf()? Default: FALSE. Only supported for driver="netCDF".
driver

character. File format expressed as GDAL driver names passed to stars::write_stars(). See sf::st_drivers().
options

character. GDAL driver specific datasource creation options passed to stars::write_stars().
...

Additional arguments not yet used.
tidy_eval

Logical, whether to enable tidy evaluation when interpreting command and pattern. If TRUE, you can use the "bang-bang" operator ⁠!!⁠ to programmatically insert the values of global objects.
packages

Character vector of packages to load right before the target runs or the output data is reloaded for downstream targets. Use tar_option_set() to set packages globally for all subsequent targets you define.
library

Character vector of library paths to try when loading packages.
repository

Character of length 1, remote repository for target storage. Choices:

Note: if repository is not "local" and format is "file" then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.
error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "null": The errored target continues and returns NULL. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.

  • "abridge": any currently running targets keep running, but no new targets launch after that.

  • "trim": all currently running targets stay running. A queued target is allowed to start if:

    1. It is not downstream of the error, and

    2. It is not a sibling branch from the same tar_target() call (if the error happened in a dynamic branch).

    The idea is to avoid starting any new work that the immediate error impacts. error = "trim" is just like error = "abridge", but it allows potentially healthy regions of the dependency graph to begin running. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g. format = "file" with repository = "aws"), this memory strategy applies to the temporary local copy of the file: "persistent" means it remains until the end of the pipeline and is then deleted, and "transient" means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.
garbage_collection

Logical, whether to run base::gc() just before the target runs.
deployment

Character of length 1. If deployment is "main", then the target will run on the central controlling R process. Otherwise, if deployment is "worker" and you set up the pipeline with distributed/parallel computing, then the target runs on a parallel worker. For more on distributed/parallel computing in targets, please visit https://books.ropensci.org/targets/crew.html.
priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get dispatched earlier (and polled earlier in tar_make_future()).
resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.
storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file") it is the responsibility of the user to write to the data store from inside the target.

    The distinguishing feature of storage = "none" (as opposed to format = "file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target runs.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.
description

Character of length 1, a custom free-form human-readable text description of the target. Descriptions appear as target labels in functions like tar_manifest() and tar_visnetwork(), and they let you select subsets of targets for the names argument of functions like tar_make(). For example, tar_manifest(names = tar_described_as(starts_with("survival model"))) lists all the targets whose descriptions start with the character string "survival model".

Value

target class "tar_stem" for use in a target pipeline

Note

The iteration argument is unavailable because it is hard-coded to "list", the only option that works currently.

See Also

targets::tar_target()

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({ # tar_dir() runs code from a temporary directory.
    library(geotargets)
    targets::tar_script({
      list(
        geotargets::tar_stars(
          stars_example,
          stars::read_stars(system.file("tif", "olinda_dem_utm25s.tif", package = "stars"))
        )
      )
    })
    targets::tar_make()
    x <- targets::tar_read(stars_example)
  })
}

Create a terra SpatRaster target

Description

Provides a target format for terra::SpatRaster objects.

Usage

tar_terra_rast(
  name,
  command,
  pattern = NULL,
  filetype = geotargets_option_get("gdal.raster.driver"),
  gdal = geotargets_option_get("gdal.raster.creation.options"),
  preserve_metadata = geotargets_option_get("terra.preserve.metadata"),
  ...,
  tidy_eval = targets::tar_option_get("tidy_eval"),
  packages = targets::tar_option_get("packages"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

Arguments

name

Symbol, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. See targets::tar_target() for more information.
command

R code to run the target.
pattern

Code to define a dynamic branching pattern for a target. See targets::tar_target() for more information.
filetype

character. File format expressed as GDAL driver names passed to terra::writeRaster()
gdal

character. GDAL driver specific datasource creation options passed to terra::writeRaster()
preserve_metadata

character. When "drop" (default), any auxiliary files that would be written by terra::writeRaster() containing raster metadata such as units and datetimes are lost (note that this does not include layer names set with ⁠names() <-⁠). When "zip", these metadata are retained by archiving all written files as a zip file upon writing and unzipping them upon reading. This adds extra overhead and will slow pipelines.
...

Additional arguments not yet used
tidy_eval

Logical, whether to enable tidy evaluation when interpreting command and pattern. If TRUE, you can use the "bang-bang" operator ⁠!!⁠ to programmatically insert the values of global objects.
packages

Character vector of packages to load right before the target runs or the output data is reloaded for downstream targets. Use tar_option_set() to set packages globally for all subsequent targets you define.
library

Character vector of library paths to try when loading packages.
repository

Character of length 1, remote repository for target storage. Choices:

Note: if repository is not "local" and format is "file" then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.
error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "null": The errored target continues and returns NULL. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.

  • "abridge": any currently running targets keep running, but no new targets launch after that.

  • "trim": all currently running targets stay running. A queued target is allowed to start if:

    1. It is not downstream of the error, and

    2. It is not a sibling branch from the same tar_target() call (if the error happened in a dynamic branch).

    The idea is to avoid starting any new work that the immediate error impacts. error = "trim" is just like error = "abridge", but it allows potentially healthy regions of the dependency graph to begin running. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g. format = "file" with repository = "aws"), this memory strategy applies to the temporary local copy of the file: "persistent" means it remains until the end of the pipeline and is then deleted, and "transient" means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.
garbage_collection

Logical, whether to run base::gc() just before the target runs.
deployment

Character of length 1. If deployment is "main", then the target will run on the central controlling R process. Otherwise, if deployment is "worker" and you set up the pipeline with distributed/parallel computing, then the target runs on a parallel worker. For more on distributed/parallel computing in targets, please visit https://books.ropensci.org/targets/crew.html.
priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get dispatched earlier (and polled earlier in tar_make_future()).
resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.
storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file") it is the responsibility of the user to write to the data store from inside the target.

    The distinguishing feature of storage = "none" (as opposed to format = "file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target runs.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.
description

Character of length 1, a custom free-form human-readable text description of the target. Descriptions appear as target labels in functions like tar_manifest() and tar_visnetwork(), and they let you select subsets of targets for the names argument of functions like tar_make(). For example, tar_manifest(names = tar_described_as(starts_with("survival model"))) lists all the targets whose descriptions start with the character string "survival model".

Details

terra::SpatRaster objects do not contain raster data directly—they contain a C++ pointer to memory where the data is stored. As a result, these objects are not portable between R sessions without special handling, which causes problems when including them in targets pipelines with tar_target(). tar_terra_rast() handles this issue by writing and reading the target as a geospatial file (specified by filetype) rather than saving the SpatRaster object itself.

Value

target class "tar_stem" for use in a target pipeline

Note

The iteration argument is unavailable because it is hard-coded to "list", the only option that works currently.

See Also

targets::tar_target()

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({ # tar_dir() runs code from a temporary directory.
    library(geotargets)
    targets::tar_script({
      list(
        geotargets::tar_terra_rast(
          terra_rast_example,
          system.file("ex/elev.tif", package = "terra") |> terra::rast()
        )
      )
    })
    targets::tar_make()
    x <- targets::tar_read(terra_rast_example)
  })
}

Create a terra SpatRasterDataset target

Description

Provides a target format for terra::SpatRasterDataset objects, which hold sub-datasets, each a SpatRaster that can have multiple layers.

Usage

tar_terra_sds(
  name,
  command,
  pattern = NULL,
  filetype = geotargets_option_get("gdal.raster.driver"),
  gdal = geotargets_option_get("gdal.raster.creation.options"),
  ...,
  tidy_eval = targets::tar_option_get("tidy_eval"),
  packages = targets::tar_option_get("packages"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

Arguments

name

Symbol, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. See targets::tar_target() for more information.
command

R code to run the target.
pattern

Code to define a dynamic branching pattern for a target. See targets::tar_target() for more information.
filetype

character. File format expressed as GDAL driver names passed to terra::writeRaster().
gdal

character. GDAL driver specific datasource creation options. passed to terra::writeRaster()
...

Additional arguments not yet used.
tidy_eval

Logical, whether to enable tidy evaluation when interpreting command and pattern. If TRUE, you can use the "bang-bang" operator ⁠!!⁠ to programmatically insert the values of global objects.
packages

Character vector of packages to load right before the target runs or the output data is reloaded for downstream targets. Use tar_option_set() to set packages globally for all subsequent targets you define.
library

Character vector of library paths to try when loading packages.
repository

Character of length 1, remote repository for target storage. Choices:

Note: if repository is not "local" and format is "file" then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.
error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "null": The errored target continues and returns NULL. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.

  • "abridge": any currently running targets keep running, but no new targets launch after that.

  • "trim": all currently running targets stay running. A queued target is allowed to start if:

    1. It is not downstream of the error, and

    2. It is not a sibling branch from the same tar_target() call (if the error happened in a dynamic branch).

    The idea is to avoid starting any new work that the immediate error impacts. error = "trim" is just like error = "abridge", but it allows potentially healthy regions of the dependency graph to begin running. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g. format = "file" with repository = "aws"), this memory strategy applies to the temporary local copy of the file: "persistent" means it remains until the end of the pipeline and is then deleted, and "transient" means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.
garbage_collection

Logical, whether to run base::gc() just before the target runs.
deployment

Character of length 1. If deployment is "main", then the target will run on the central controlling R process. Otherwise, if deployment is "worker" and you set up the pipeline with distributed/parallel computing, then the target runs on a parallel worker. For more on distributed/parallel computing in targets, please visit https://books.ropensci.org/targets/crew.html.
priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get dispatched earlier (and polled earlier in tar_make_future()).
resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.
storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file") it is the responsibility of the user to write to the data store from inside the target.

    The distinguishing feature of storage = "none" (as opposed to format = "file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target runs.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.
description

Character of length 1, a custom free-form human-readable text description of the target. Descriptions appear as target labels in functions like tar_manifest() and tar_visnetwork(), and they let you select subsets of targets for the names argument of functions like tar_make(). For example, tar_manifest(names = tar_described_as(starts_with("survival model"))) lists all the targets whose descriptions start with the character string "survival model".

Value

target class "tar_stem" for use in a target pipeline

Note

The iteration argument is unavailable because it is hard-coded to "list", the only option that works currently.

Author(s)

Andrew Gene Brown

Nicholas Tierney

Eric R. Scott

See Also

targets::tar_target_raw(), tar_terra_sprc()

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({ # tar_dir() runs code from a temporary directory.
    library(geotargets)
    targets::tar_script({
      elev_scale <- function(z = 1) {
        terra::rast(system.file("ex", "elev.tif", package = "terra")) * z
      }
      list(
        tar_terra_sds(
          raster_elevs,
          # two rasters, one unaltered, one scaled by factor of 2
          command = terra::sds(list(
            elev_scale(1),
            elev_scale(2)
          ))
        )
      )
    })
    targets::tar_make()
    targets::tar_read(raster_elevs)
  })
}

Create a terra SpatRasterCollection target

Description

Provides a target format for terra::SpatRasterCollection objects, which have no restriction in the extent or other geometric parameters.

Usage

tar_terra_sprc(
  name,
  command,
  pattern = NULL,
  filetype = geotargets_option_get("gdal.raster.driver"),
  gdal = geotargets_option_get("gdal.raster.creation.options"),
  ...,
  tidy_eval = targets::tar_option_get("tidy_eval"),
  packages = targets::tar_option_get("packages"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

Arguments

name

Symbol, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. See targets::tar_target() for more information.
command

R code to run the target.
pattern

Code to define a dynamic branching pattern for a target. See targets::tar_target() for more information.
filetype

character. File format expressed as GDAL driver names passed to terra::writeRaster().
gdal

character. GDAL driver specific datasource creation options. passed to terra::writeRaster()
...

Additional arguments not yet used.
tidy_eval

Logical, whether to enable tidy evaluation when interpreting command and pattern. If TRUE, you can use the "bang-bang" operator ⁠!!⁠ to programmatically insert the values of global objects.
packages

Character vector of packages to load right before the target runs or the output data is reloaded for downstream targets. Use tar_option_set() to set packages globally for all subsequent targets you define.
library

Character vector of library paths to try when loading packages.
repository

Character of length 1, remote repository for target storage. Choices:

Note: if repository is not "local" and format is "file" then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.
error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "null": The errored target continues and returns NULL. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.

  • "abridge": any currently running targets keep running, but no new targets launch after that.

  • "trim": all currently running targets stay running. A queued target is allowed to start if:

    1. It is not downstream of the error, and

    2. It is not a sibling branch from the same tar_target() call (if the error happened in a dynamic branch).

    The idea is to avoid starting any new work that the immediate error impacts. error = "trim" is just like error = "abridge", but it allows potentially healthy regions of the dependency graph to begin running. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g. format = "file" with repository = "aws"), this memory strategy applies to the temporary local copy of the file: "persistent" means it remains until the end of the pipeline and is then deleted, and "transient" means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.
garbage_collection

Logical, whether to run base::gc() just before the target runs.
deployment

Character of length 1. If deployment is "main", then the target will run on the central controlling R process. Otherwise, if deployment is "worker" and you set up the pipeline with distributed/parallel computing, then the target runs on a parallel worker. For more on distributed/parallel computing in targets, please visit https://books.ropensci.org/targets/crew.html.
priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get dispatched earlier (and polled earlier in tar_make_future()).
resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.
storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file") it is the responsibility of the user to write to the data store from inside the target.

    The distinguishing feature of storage = "none" (as opposed to format = "file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target runs.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.
description

Character of length 1, a custom free-form human-readable text description of the target. Descriptions appear as target labels in functions like tar_manifest() and tar_visnetwork(), and they let you select subsets of targets for the names argument of functions like tar_make(). For example, tar_manifest(names = tar_described_as(starts_with("survival model"))) lists all the targets whose descriptions start with the character string "survival model".

Value

target class "tar_stem" for use in a target pipeline

Note

The iteration argument is unavailable because it is hard-coded to "list", the only option that works currently.

Author(s)

Andrew Gene Brown

Nicholas Tierney

See Also

targets::tar_target_raw()

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({ # tar_dir() runs code from a temporary directory.
    library(geotargets)
    targets::tar_script({
      elev_scale <- function(z = 1, projection = "EPSG:4326") {
        terra::project(
          terra::rast(system.file("ex", "elev.tif", package = "terra")) * z,
          projection
        )
      }
      list(
        tar_terra_sprc(
          raster_elevs,
          # two rasters, one unaltered, one scaled by factor of 2 and
          # reprojected to interrupted good homolosine
          command = terra::sprc(list(
            elev_scale(1),
            elev_scale(2, "+proj=igh")
          ))
        )
      )
    })
    targets::tar_make()
    x <- targets::tar_read(raster_elevs)
  })
}

Split a raster into tiles that can be iterated over with dynamic branching

Description

This target factory is useful when a raster is too large or too high resolution to work on in-memory. It can instead be split into tiles that can be iterated over using dynamic branching.

Usage

tar_terra_tiles(
  name,
  raster,
  tile_fun,
  filetype = geotargets_option_get("gdal.raster.driver"),
  gdal = geotargets_option_get("gdal.raster.creation.options"),
  ...,
  packages = targets::tar_option_get("packages"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

Arguments

name

Symbol, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. See targets::tar_target() for more information.
raster

a SpatRaster object to be split into tiles.
tile_fun

a helper function that returns a list of numeric vectors such as tile_grid(), tile_n() or tile_blocksize specified in one of the following ways:

  • A named function, e.g. tile_blocksize or "tile_blocksize".

  • An anonymous function, e.g. ⁠\(x) tile_grid(x, nrow = 2, ncol = 2)⁠.

filetype

character. File format expressed as GDAL driver names passed to terra::makeTiles().
gdal

character. GDAL driver specific datasource creation options passed to terra::makeTiles().
...

additional arguments not yet used.
packages

Character vector of packages to load right before the target runs or the output data is reloaded for downstream targets. Use tar_option_set() to set packages globally for all subsequent targets you define.
library

Character vector of library paths to try when loading packages.
repository

Character of length 1, remote repository for target storage. Choices:

Note: if repository is not "local" and format is "file" then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.
error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "null": The errored target continues and returns NULL. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.

  • "abridge": any currently running targets keep running, but no new targets launch after that.

  • "trim": all currently running targets stay running. A queued target is allowed to start if:

    1. It is not downstream of the error, and

    2. It is not a sibling branch from the same tar_target() call (if the error happened in a dynamic branch).

    The idea is to avoid starting any new work that the immediate error impacts. error = "trim" is just like error = "abridge", but it allows potentially healthy regions of the dependency graph to begin running. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g. format = "file" with repository = "aws"), this memory strategy applies to the temporary local copy of the file: "persistent" means it remains until the end of the pipeline and is then deleted, and "transient" means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.
garbage_collection

Logical, whether to run base::gc() just before the target runs.
deployment

Character of length 1. If deployment is "main", then the target will run on the central controlling R process. Otherwise, if deployment is "worker" and you set up the pipeline with distributed/parallel computing, then the target runs on a parallel worker. For more on distributed/parallel computing in targets, please visit https://books.ropensci.org/targets/crew.html.
priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get dispatched earlier (and polled earlier in tar_make_future()).
resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.
storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file") it is the responsibility of the user to write to the data store from inside the target.

    The distinguishing feature of storage = "none" (as opposed to format = "file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target runs.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.
description

Character of length 1, a custom free-form human-readable text description of the target. Descriptions appear as target labels in functions like tar_manifest() and tar_visnetwork(), and they let you select subsets of targets for the names argument of functions like tar_make(). For example, tar_manifest(names = tar_described_as(starts_with("survival model"))) lists all the targets whose descriptions start with the character string "survival model".

Value

a list of two targets: an upstream target that creates a list of extents and a downstream pattern that maps over these extents to create a list of SpatRaster objects.

Note

The iteration argument is unavailable because it is hard-coded to "list", the only option that works currently.

When using the tile_blocksize() helper function, you may need to set memory = "transient" on the upstream target provided to the raster argument of tar_terra_tiles(). More details are in the help file for tile_blocksize().

Author(s)

Eric Scott

See Also

tile_n(), tile_grid(), tile_blocksize(), tar_terra_rast()

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({
    targets::tar_script({
        library(targets)
        library(geotargets)
        library(terra)
        list(
            tar_target(
                my_file,
                system.file("ex/elev.tif", package="terra"),
                format = "file"
            ),
            tar_terra_rast(
                my_map,
                terra::rast(my_file)
            ),
            tar_terra_tiles(
                name = rast_split,
                raster = my_map,
                ncol = 2,
                nrow = 2
            )
        )
    })
    targets::tar_manifest()
  })
}

Create a terra SpatVector target

Description

Provides a target format for terra::SpatVector objects.

Usage

tar_terra_vect(
  name,
  command,
  pattern = NULL,
  filetype = geotargets_option_get("gdal.vector.driver"),
  gdal = geotargets_option_get("gdal.vector.creation.options"),
  ...,
  packages = targets::tar_option_get("packages"),
  tidy_eval = targets::tar_option_get("tidy_eval"),
  library = targets::tar_option_get("library"),
  repository = targets::tar_option_get("repository"),
  error = targets::tar_option_get("error"),
  memory = targets::tar_option_get("memory"),
  garbage_collection = targets::tar_option_get("garbage_collection"),
  deployment = targets::tar_option_get("deployment"),
  priority = targets::tar_option_get("priority"),
  resources = targets::tar_option_get("resources"),
  storage = targets::tar_option_get("storage"),
  retrieval = targets::tar_option_get("retrieval"),
  cue = targets::tar_option_get("cue"),
  description = targets::tar_option_get("description")
)

Arguments

name

Symbol, name of the target. A target name must be a valid name for a symbol in R, and it must not start with a dot. See targets::tar_target() for more information.
command

R code to run the target.
pattern

Code to define a dynamic branching pattern for a target. See targets::tar_target() for more information.
filetype

character. File format expressed as GDAL driver names passed to terra::writeVector(). See 'Note' for more details.
gdal

character. GDAL driver specific datasource creation options passed to terra::writeVector().
...

Additional arguments not yet used.
packages

Character vector of packages to load right before the target runs or the output data is reloaded for downstream targets. Use tar_option_set() to set packages globally for all subsequent targets you define.
tidy_eval

Logical, whether to enable tidy evaluation when interpreting command and pattern. If TRUE, you can use the "bang-bang" operator ⁠!!⁠ to programmatically insert the values of global objects.
library

Character vector of library paths to try when loading packages.
repository

Character of length 1, remote repository for target storage. Choices:

Note: if repository is not "local" and format is "file" then the target should create a single output file. That output file is uploaded to the cloud and tracked for changes where it exists in the cloud. The local file is deleted after the target runs.
error

Character of length 1, what to do if the target stops and throws an error. Options:

  • "stop": the whole pipeline stops and throws an error.

  • "continue": the whole pipeline keeps going.

  • "null": The errored target continues and returns NULL. The data hash is deliberately wrong so the target is not up to date for the next run of the pipeline.

  • "abridge": any currently running targets keep running, but no new targets launch after that.

  • "trim": all currently running targets stay running. A queued target is allowed to start if:

    1. It is not downstream of the error, and

    2. It is not a sibling branch from the same tar_target() call (if the error happened in a dynamic branch).

    The idea is to avoid starting any new work that the immediate error impacts. error = "trim" is just like error = "abridge", but it allows potentially healthy regions of the dependency graph to begin running. (Visit https://books.ropensci.org/targets/debugging.html to learn how to debug targets using saved workspaces.)

memory

Character of length 1, memory strategy. If "persistent", the target stays in memory until the end of the pipeline (unless storage is "worker", in which case targets unloads the value from memory right after storing it in order to avoid sending copious data over a network). If "transient", the target gets unloaded after every new target completes. Either way, the target gets automatically loaded into memory whenever another target needs the value. For cloud-based dynamic files (e.g. format = "file" with repository = "aws"), this memory strategy applies to the temporary local copy of the file: "persistent" means it remains until the end of the pipeline and is then deleted, and "transient" means it gets deleted as soon as possible. The former conserves bandwidth, and the latter conserves local storage.
garbage_collection

Logical, whether to run base::gc() just before the target runs.
deployment

Character of length 1. If deployment is "main", then the target will run on the central controlling R process. Otherwise, if deployment is "worker" and you set up the pipeline with distributed/parallel computing, then the target runs on a parallel worker. For more on distributed/parallel computing in targets, please visit https://books.ropensci.org/targets/crew.html.
priority

Numeric of length 1 between 0 and 1. Controls which targets get deployed first when multiple competing targets are ready simultaneously. Targets with priorities closer to 1 get dispatched earlier (and polled earlier in tar_make_future()).
resources

Object returned by tar_resources() with optional settings for high-performance computing functionality, alternative data storage formats, and other optional capabilities of targets. See tar_resources() for details.
storage

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's return value is sent back to the host machine and saved/uploaded locally.

  • "worker": the worker saves/uploads the value.

  • "none": almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language. If you do use it, then the return value of the target is totally ignored when the target ends, but each downstream target still attempts to load the data file (except when retrieval = "none").

    If you select storage = "none", then the return value of the target's command is ignored, and the data is not saved automatically. As with dynamic files (format = "file") it is the responsibility of the user to write to the data store from inside the target.

    The distinguishing feature of storage = "none" (as opposed to format = "file") is that in the general case, downstream targets will automatically try to load the data from the data store as a dependency. As a corollary, storage = "none" is completely unnecessary if format is "file".

retrieval

Character of length 1, only relevant to tar_make_clustermq() and tar_make_future(). Must be one of the following values:

  • "main": the target's dependencies are loaded on the host machine and sent to the worker before the target runs.

  • "worker": the worker loads the targets dependencies.

  • "none": the dependencies are not loaded at all. This choice is almost never recommended. It is only for niche situations, e.g. the data needs to be loaded explicitly from another language.

cue

An optional object from tar_cue() to customize the rules that decide whether the target is up to date.
description

Character of length 1, a custom free-form human-readable text description of the target. Descriptions appear as target labels in functions like tar_manifest() and tar_visnetwork(), and they let you select subsets of targets for the names argument of functions like tar_make(). For example, tar_manifest(names = tar_described_as(starts_with("survival model"))) lists all the targets whose descriptions start with the character string "survival model".

Details

terra::SpatVector objects do not contain vector data directly—they contain a C++ pointer to memory where the data is stored. As a result, these objects are not portable between R sessions without special handling, which causes problems when including them in targets pipelines with tar_target(). tar_terra_rast() handles this issue by writing and reading the target as a geospatial file (specified by filetype) rather than saving the SpatVector object itself.

Value

target class "tar_stem" for use in a target pipeline

Note

The iteration argument is unavailable because it is hard-coded to "list", the only option that works currently.

Although you may pass any supported GDAL vector driver to the filetype argument, not all formats are guaranteed to work with geotargets. At the moment, we have tested GeoJSON and ⁠ESRI Shapefile⁠ which both appear to work generally.

Examples

if (Sys.getenv("TAR_LONG_EXAMPLES") == "true") {
  targets::tar_dir({ # tar_dir() runs code from a temporary directory.
    targets::tar_script({
      lux_area <- function(projection = "EPSG:4326") {
        terra::project(
          terra::vect(system.file("ex", "lux.shp",
            package = "terra"
          )),
          projection
        )
      }
      list(
        geotargets::tar_terra_vect(
          terra_vect_example,
          lux_area()
        )
      )
    })
    targets::tar_make()
    x <- targets::tar_read(terra_vect_example)
  })
}

Helper functions to create tiles

Description

Wrappers around terra::getTileExtents() that return a list of named numeric vectors describing the extents of tiles rather than SpatExtent objects. While these may have general use, they are intended primarily for supplying to the tile_fun argument of tar_terra_tiles().

Usage

tile_grid(raster, ncol, nrow)

tile_blocksize(raster, n_blocks_row = 1, n_blocks_col = 1)

tile_n(raster, n)

Arguments

raster

a SpatRaster object.
ncol

integer; number of columns to split the SpatRaster into.
nrow

integer; number of rows to split the SpatRaster into.
n_blocks_row

integer; multiple of blocksize to include in each tile vertically.
n_blocks_col

integer; multiple of blocksize to include in each tile horizontally.
n

integer; total number of tiles to split the SpatRaster into.

Details

tile_blocksize() creates extents using the raster's native block size (see terra::fileBlocksize()), which should be more memory efficient. Create tiles with multiples of the raster's blocksize with n_blocks_row and n_blocks_col. We strongly suggest the user explore how many tiles are created by tile_blocksize() before creating a dynamically branched target using this helper. Note that block size is a property of files and does not apply to in-memory SpatRasters. Therefore, if you want to use this helper in tar_terra_tiles() you may need to ensure the upstream target provided to the raster argument is not in memory by setting memory = "transient".

tile_grid() allows specification of a number of rows and columns to split the raster into. E.g. nrow = 2 and ncol = 2 would create 4 tiles (because it specifies a 2x2 matrix, which has 4 elements).

tile_n() creates (about) n tiles and prints the number of rows, columns, and total tiles created.

Value

list of named numeric vectors with xmin, xmax, ymin, and ymax values that can be coerced to SpatExtent objects with terra::ext().

Author(s)

Eric Scott

Examples

f <- system.file("ex/elev.tif", package="terra")
r <- terra::rast(f)
tile_grid(r, ncol = 2, nrow = 2)
tile_blocksize(r)
tile_n(r, 8)

## Not run: 
#usage with tar_terra_tiles
list(
    tar_terra_rast(
        my_map,
        terra::rast(system.file("ex/logo.tif", package = "terra"))
    ),
    tar_terra_tiles(
        name = rast_split,
        raster = my_map,
        tile_fun = tile_blocksize,
        description = "Each tile is 1 block"
    ),
    tar_terra_tiles(
        name = rast_split_2blocks,
        raster = my_map,
        tile_fun = \(x) tile_blocksize(x, n_blocks_row = 2, n_blocks_col = 1),
        description = "Each tile is 2 blocks tall, 1 block wide"
    )
    tar_terra_tiles(
        name = rast_split_grid,
        raster = my_map,
        tile_fun = \(x) tile_grid(x, ncol = 2, nrow = 2),
        description = "Split into 4 tiles in a 2x2 grid"
    ),
    tar_terra_tiles(
        name = rast_split_n,
        raster = my_map,
        tile_fun = \(x) tile_n(x, n = 6),
        description = "Split into 6 tiles"
    )
)

## End(Not run)