autoplot.ResamplingSpCVCoords function

Visualization Functions for SpCV Coords Methods.

Visualization Functions for SpCV Coords Methods.

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

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

Arguments

  • object: [Resampling]

    mlr3 spatial resampling object of class ResamplingSpCVCoords or ResamplingRepeatedSpCVCoords .

  • task: [TaskClassifST]/[TaskRegrST]

    mlr3 task object.

  • fold_id: [numeric]

    Fold IDs to plot.

  • plot_as_grid: [logical(1)]

    Should a gridded plot using via list("patchwork") be created? If FALSE

    a list with of list("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 ResamplingSpCVCoords or ResamplingRepeatedSpCVCoords .

Examples

if (mlr3misc::require_namespaces(c("sf"), quietly = TRUE)) { library(mlr3) library(mlr3spatiotempcv) task = tsk("ecuador") resampling = rsmp("spcv_coords") 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)) }

See Also

  • mlr3book chapter on "Spatial Analysis"
  • autoplot.ResamplingSpCVBlock()
  • autoplot.ResamplingSpCVBuffer()
  • autoplot.ResamplingSpCVEnv()
  • autoplot.ResamplingSpCVDisc()
  • autoplot.ResamplingSpCVTiles()
  • autoplot.ResamplingCV()
  • autoplot.ResamplingSptCVCstf()