autoplot.ResamplingSptCVCstf {mlr3spatiotempcv} | R Documentation |
Visualization Functions for SptCV Cstf Methods.
Description
Generic S3 plot()
and autoplot()
(ggplot2) methods to
visualize mlr3 spatiotemporal resampling objects.
Usage
## S3 method for class 'ResamplingSptCVCstf'
autoplot(
object,
task,
fold_id = NULL,
plot_as_grid = TRUE,
train_color = "#0072B5",
test_color = "#E18727",
repeats_id = NULL,
tickformat_date = "%Y-%m",
nticks_x = 3,
nticks_y = 3,
point_size = 3,
axis_label_fontsize = 11,
static_image = FALSE,
show_omitted = FALSE,
plot3D = NULL,
plot_time_var = NULL,
sample_fold_n = NULL,
...
)
## S3 method for class 'ResamplingRepeatedSptCVCstf'
autoplot(
object,
task,
fold_id = NULL,
repeats_id = 1,
plot_as_grid = TRUE,
train_color = "#0072B5",
test_color = "#E18727",
tickformat_date = "%Y-%m",
nticks_x = 3,
nticks_y = 3,
point_size = 3,
axis_label_fontsize = 11,
plot3D = NULL,
plot_time_var = NULL,
...
)
## S3 method for class 'ResamplingSptCVCstf'
plot(x, ...)
## S3 method for class 'ResamplingRepeatedSptCVCstf'
plot(x, ...)
Arguments
object |
|
task |
|
fold_id |
|
plot_as_grid |
|
train_color |
|
test_color |
|
repeats_id |
|
tickformat_date |
|
nticks_x |
|
nticks_y |
|
point_size |
|
axis_label_fontsize |
|
static_image |
|
show_omitted |
|
plot3D |
|
plot_time_var |
|
sample_fold_n |
|
... |
Passed down to |
x |
|
Details
This method requires to set argument fold_id
.
No plot showing all folds in one plot can be created.
This is because the LLTO method does not make use of all observations but only
a subset of them (many observations are omitted).
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 be
misleading.
2D vs 3D plotting
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.
See Also
mlr3book chapter on "Spatiotemporal Visualization"
Vignette Spatiotemporal Visualization.
Examples
if (mlr3misc::require_namespaces(c("sf", "plotly"), quietly = TRUE)) {
library(mlr3)
library(mlr3spatiotempcv)
task_st = tsk("cookfarm_mlr3")
task_st$set_col_roles("SOURCEID", "space")
task_st$set_col_roles("Date", "time")
resampling = rsmp("sptcv_cstf", folds = 5)
resampling$instantiate(task_st)
# with both `"space"` and `"time"` column roles set (LLTO), the omitted
# observations per fold can be shown by setting `show_omitted = TRUE`
autoplot(resampling, task_st, fold_id = 1, show_omitted = TRUE)
}