autoplot.ResamplingSpCVBuffer: Visualization Functions for SpCV Buffer Methods.

In mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'

Visualization Functions for SpCV Buffer Methods.

Description

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

Usage

## S3 method for class 'ResamplingSpCVBuffer'
autoplot(
  object,
  task,
  fold_id = NULL,
  plot_as_grid = TRUE,
  train_color = "#0072B5",
  test_color = "#E18727",
  show_omitted = FALSE,
  ...
)

## S3 method for class 'ResamplingSpCVBuffer'
plot(x, ...)

Arguments

object	⁠[Resampling]⁠ mlr3 spatial resampling object of class ResamplingSpCVBuffer.
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.
show_omitted	⁠[logical]⁠ Whether to show points not used in train or test set for the current fold.
...	Passed to geom_sf(). Helpful for adjusting point sizes and shapes.
x	⁠[Resampling]⁠ mlr3 spatial resampling object of class ResamplingSpCVBuffer.

See Also

• mlr3book chapter on "Spatiotemporal Visualization"

• autoplot.ResamplingSpCVBlock()

• autoplot.ResamplingSpCVCoords()

• autoplot.ResamplingSpCVEnv()

• autoplot.ResamplingCV()

• autoplot.ResamplingSptCVCstf()

Examples

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

  ## single fold
  autoplot(resampling, task, fold_id = 1) +
    ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01))

  ## multiple folds
  autoplot(resampling, task, fold_id = c(1, 2)) *
    ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01))
}

mlr3spatiotempcv documentation built on Oct. 24, 2023, 5:07 p.m.