autoplot.ResamplingSpCVDisc | R Documentation |
Generic S3 plot()
and autoplot()
(ggplot2) methods to
visualize mlr3 spatiotemporal resampling objects.
## S3 method for class 'ResamplingSpCVDisc'
autoplot(
object,
task,
fold_id = NULL,
plot_as_grid = TRUE,
train_color = "#0072B5",
test_color = "#E18727",
repeats_id = NULL,
show_omitted = FALSE,
sample_fold_n = NULL,
...
)
## S3 method for class 'ResamplingRepeatedSpCVDisc'
autoplot(
object,
task,
fold_id = NULL,
repeats_id = 1,
plot_as_grid = TRUE,
train_color = "#0072B5",
test_color = "#E18727",
show_omitted = FALSE,
sample_fold_n = NULL,
...
)
## S3 method for class 'ResamplingSpCVDisc'
plot(x, ...)
## S3 method for class 'ResamplingRepeatedSpCVDisc'
plot(x, ...)
object |
|
task |
|
fold_id |
|
plot_as_grid |
|
train_color |
|
test_color |
|
repeats_id |
|
show_omitted |
|
sample_fold_n |
|
... |
Passed to |
x |
|
This method requires to set argument fold_id
and no plot containing all
partitions can be created. This is because the method does not make use of
all observations but only a subset of them (many observations are left out).
Hence, train and test sets of one fold are not re-used in other folds as in
other methods and plotting these without a train/test indicator would not
make sense.
This method has both a 2D and a 3D plotting method.
The 2D method returns a ggplot with x and y axes representing the spatial
coordinates.
The 3D method uses plotly to create an interactive 3D plot.
Set plot3D = TRUE
to use the 3D method.
Note that spatiotemporal datasets usually suffer from overplotting in 2D mode.
mlr3book chapter on "Spatial Analysis"
Vignette Spatiotemporal Visualization.
autoplot.ResamplingSpCVBlock()
autoplot.ResamplingSpCVBuffer()
autoplot.ResamplingSpCVCoords()
autoplot.ResamplingSpCVTiles()
autoplot.ResamplingSpCVEnv()
autoplot.ResamplingCV()
if (mlr3misc::require_namespaces("sf", quietly = TRUE)) {
library(mlr3)
library(mlr3spatiotempcv)
task = tsk("ecuador")
resampling = rsmp("spcv_disc",
folds = 5, radius = 200L, buffer = 200L)
resampling$instantiate(task)
autoplot(resampling, task,
fold_id = 1,
show_omitted = TRUE, size = 0.7) *
ggplot2::scale_x_continuous(breaks = seq(-79.085, -79.055, 0.01))
}
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