R/autoplot.R
autoplot.ResamplingSpCVBlock.Rd
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, ...)
object |
|
---|---|
task |
|
fold_id |
|
plot_as_grid |
|
train_color |
|
test_color |
|
crs |
|
show_blocks |
|
show_labels |
|
... | Passed to |
repeats_id |
|
x |
|
ggplot()
or list of ggplot2 objects.
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>()
.
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)) }