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#' @title Create a Spatiotemporal Classification Task
#'
#' @description This task specializes [Task] and [TaskSupervised] for
#' spatiotemporal classification problems. The target column is assumed to be a
#' factor. The `task_type` is set to `"classif"` and `"spatiotemporal"`.
#'
#' A spatial example task is available via `tsk("ecuador")`, a spatiotemporal
#' one via `tsk("cookfarm_mlr3")`.
#'
#' The coordinate reference system passed during initialization must match the
#' one which was used during data creation, otherwise offsets of multiple meters
#' may occur. By default, coordinates are not used as features. This can be
#' changed by setting `coords_as_features = TRUE`.
#'
#' @template rox_param_id
#' @template rox_param_backend
#' @template rox_param_target
#' @template rox_param_positive
#' @template rox_param_label
#' @template rox_param_coords_as_features
#' @template rox_param_crs
#' @template rox_param_coordinate_names
#' @template rox_param_extra_args
#'
#' @family Task
#' @export
#' @examples
#' \donttest{
#' if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) {
#' task = as_task_classif_st(ecuador,
#' target = "slides",
#' positive = "TRUE", coordinate_names = c("x", "y")
#' )
#'
#' # passing objects of class 'sf' is also supported
#' data_sf = sf::st_as_sf(ecuador, coords = c("x", "y"))
#' task = as_task_classif_st(data_sf, target = "slides", positive = "TRUE")
#'
#' task$task_type
#' task$formula()
#' task$class_names
#' task$positive
#' task$negative
#' task$coordinates()
#' task$coordinate_names
#' }
#' }
TaskClassifST = R6::R6Class("TaskClassifST",
inherit = TaskClassif,
public = list(
#' @description
#' Create a new spatiotemporal resampling Task
initialize = function(id, backend, target, positive = NULL,
label = NA_character_, coordinate_names, crs = NA_character_,
coords_as_features = FALSE, extra_args = list()) {
if (inherits(backend, "sf")) {
stopf("Creating tasks from `sf` objects is not supported anymore since >= v2.0.0. Use `as_task_classif_st()` to convert sf objects into a task.") # nolint
}
super$initialize(
id = id, backend = backend, target = target, label = label,
positive = positive, extra_args = extra_args
)
self$crs = crs
self$coordinate_names = coordinate_names
walk(coordinate_names, function(x) {
assert_numeric(self$backend$head(1)[[x]], .var.name = x)
})
if (packageVersion("mlr3") > "0.13.4") {
# adjust classif task
self$task_type = "classif_st"
new_col_roles = named_list(setdiff(
mlr_reflections$task_col_roles[["classif_st"]],
names(private$.col_roles)), character(0))
private$.col_roles = insert_named(private$.col_roles, new_col_roles)
}
# add coordinates as features
self$coords_as_features = assert_flag(coords_as_features)
},
#' @description
#' Returns coordinates of observations.
#'
#' @param row_ids (`integer()`)\cr
#' Vector of rows indices as subset of `task$row_ids`.
#'
#' @return [data.table::data.table()]
coordinates = function(row_ids = NULL) {
if (is.null(row_ids)) row_ids = self$row_ids
self$backend$data(rows = row_ids, cols = self$coordinate_names)
},
#' @description
#' Print the task.
#' @param ... Arguments passed to the `$print()` method of the superclass.
print = function(...) {
super$print(...)
cat("* Coordinates:\n")
print(self$coordinates(), nrows = 10)
if (length(self$col_roles$time) && length(self$col_roles$space)) {
catn(c(
"* Column roles:",
sprintf(" - Time: %s", self$col_roles$time),
sprintf(" - Space: %s", self$col_roles$space)
))
} else if (length(self$col_roles$time)) {
catn(c(
"* Column roles:",
sprintf(" - Time: %s", self$col_roles$time)
))
} else if (length(self$col_roles$space)) {
catn(c(
"* Column roles:",
sprintf(" - Space: %s", self$col_roles$space)
))
}
}
),
active = list(
#' @field crs (`character(1)`)\cr
#' Returns coordinate reference system of task.
crs = function(rhs) {
if (missing(rhs)) {
return(self$extra_args$crs)
}
self$extra_args$crs = rhs
},
#' @field coordinate_names (`character()`)\cr
#' Coordinate names.
coordinate_names = function(rhs) {
if (missing(rhs)) {
return(self$extra_args$coordinate_names)
}
self$extra_args$coordinate_names = assert_character(rhs,
len = 2,
all.missing = FALSE, any.missing = FALSE
)
},
#' @field coords_as_features (`logical(1)`)\cr
#' If `TRUE`, coordinates are used as features.
#' This is a shortcut for
#' `task$set_col_roles(c("x", "y"), role = "feature")` with the assumption
#' that the coordinates in the data are named `"x"` and `"y"`.
coords_as_features = function(rhs) {
if (missing(rhs)) {
return(self$extra_args$coords_as_features)
}
self$extra_args$coords_as_features = assert_flag(rhs)
if (rhs) {
self$set_col_roles(self$coordinate_names, add_to = "coordinate")
} else {
self$set_col_roles(self$coordinate_names, roles = "coordinate")
}
}
)
)
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