autoplot.ResamplingSpCVEnv: Visualization Functions for SpCV Env Methods.

In mlr-org/mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'

Visualization Functions for SpCV Env Methods.

Description

Generic S3 plot() and autoplot() (ggplot2) methods.

Usage

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

## S3 method for class 'ResamplingRepeatedSpCVEnv'
autoplot(
  object,
  task,
  fold_id = NULL,
  repeats_id = 1,
  plot_as_grid = TRUE,
  train_color = "#0072B5",
  test_color = "#E18727",
  sample_fold_n = NULL,
  ...
)

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

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

Arguments

object	⁠[Resampling]⁠ mlr3 spatial resampling object of class ResamplingSpCVEnv or ResamplingRepeatedSpCVEnv.
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.
sample_fold_n	⁠[integer]⁠ Number of points in a random sample stratified over partitions. This argument aims to keep file sizes of resulting plots reasonable and reduce overplotting in dense datasets.
...	Passed to geom_sf(). Helpful for adjusting point sizes and shapes.
repeats_id	⁠[numeric]⁠ Repetition ID to plot.
x	⁠[Resampling]⁠ mlr3 spatial resampling object of class ResamplingSpCVEnv or ResamplingRepeatedSpCVEnv.

See Also

• mlr3book chapter on "Spatial Analysis"

• autoplot.ResamplingSpCVBlock()

• autoplot.ResamplingSpCVBuffer()

• autoplot.ResamplingSpCVCoords()

• autoplot.ResamplingSpCVDisc()

• autoplot.ResamplingSpCVTiles()

• autoplot.ResamplingCV()

• autoplot.ResamplingSptCVCstf()

Examples

if (mlr3misc::require_namespaces(c("sf", "blockCV"), quietly = TRUE)) {
  library(mlr3)
  library(mlr3spatiotempcv)
  task = tsk("ecuador")
  resampling = rsmp("spcv_env", folds = 4, features = "dem")
  resampling$instantiate(task)

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

mlr-org/mlr3spatiotempcv documentation built on April 23, 2024, 6:50 a.m.