Visualization Functions for SpCV Block Methods.

Generic S3 plot() and autoplot() (ggplot2) methods to visualize mlr3 spatiotemporal resampling objects.

# S3 method for ResamplingSpCVBlock
autoplot(
  object,
  task,
  fold_id = NULL,
  plot_as_grid = TRUE,
  train_color = "#0072B5",
  test_color = "#E18727",
  crs = NULL,
  show_blocks = FALSE,
  show_labels = FALSE,
  ...
)

# S3 method for ResamplingRepeatedSpCVBlock
autoplot(
  object,
  task,
  fold_id = NULL,
  repeats_id = 1,
  plot_as_grid = TRUE,
  train_color = "#0072B5",
  test_color = "#E18727",
  crs = NULL,
  show_blocks = FALSE,
  show_labels = FALSE,
  ...
)

# S3 method for ResamplingSpCVBlock
plot(x, ...)

# S3 method for ResamplingRepeatedSpCVBlock
plot(x, ...)

Arguments

object	[Resampling] mlr3 spatial resampling object of class ResamplingSpCVBlock or ResamplingRepeatedSpCVBlock.
task	[TaskClassifST]/[TaskRegrST] mlr3 task object.
fold_id	[numeric] Fold IDs to plot.
plot_as_grid	[logical(1)] Should a gridded plot using via patchwork be created? If FALSE a list with of ggplot2 objects is returned. Only applies if a numeric vector is passed to argument fold_id.
train_color	[character(1)] The color to use for the training set observations.
test_color	[character(1)] The color to use for the test set observations.
crs	[character] EPSG code of the CRS for x and y axes.
show_blocks	[logical(1)] Whether to show an overlay of the spatial blocks polygons.
show_labels	[logical(1)] Whether to show an overlay of the spatial block IDs.
...	Passed to geom_sf(). Helpful for adjusting point sizes and shapes.
repeats_id	[numeric] Repetition ID to plot.
x	[Resampling] mlr3 spatial resampling object. One of class ResamplingSpCVBuffer, ResamplingSpCVBlock, ResamplingSpCVCoords, ResamplingSpCVEnv.

Value

ggplot() or list of ggplot2 objects.

Details

By default a plot is returned; if fold_id is set, a gridded plot is created. If plot_as_grid = FALSE, a list of plot objects is returned. This can be used to align the plots individually.

When no single fold is selected, the ggsci::scale_color_ucscgb() palette is used to display all partitions. If you want to change the colors, call <plot> + <color-palette>().

See also

• mlr3book chapter on on "Spatiotemporal Visualization".

• autoplot.ResamplingSpCVBuffer()

• autoplot.ResamplingSpCVCoords()

• autoplot.ResamplingSpCVEnv()

• autoplot.ResamplingCV()

• autoplot.ResamplingSptCVCstf()

• autoplot.ResamplingSptCVCluto()

Examples

if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) {
  library(mlr3)
  library(mlr3spatiotempcv)
  task = tsk("ecuador")
  resampling = rsmp("spcv_block", range = 1000L)
  resampling$instantiate(task)

  ## list of ggplot2 resamplings
  plot_list = autoplot(resampling, task,
    crs = 4326,
    fold_id = c(1, 2), plot_as_grid = FALSE)

  ## Visualize all partitions
  autoplot(resampling, task, crs = 4326) +
    ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01))

  ## Visualize the train/test split of a single fold
  autoplot(resampling, task, fold_id = 1, crs = 4326) +
    ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01))

  ## Visualize train/test splits of multiple folds
  autoplot(resampling, task,
    fold_id = c(1, 2), crs = 4326,
    show_blocks = TRUE) *
    ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01))
}