Plots a variance cube, useful to understand how local smoothing will work.
Usage
# S3 method for class 'variance_cube'
plot(
x,
...,
tile = x[["tile"]][[1L]],
roi = NULL,
labels = NULL,
palette = "YlGnBu",
rev = FALSE,
type = "map",
quantile = 0.75,
scale = 1,
max_cog_size = 1024L,
legend_position = "inside",
legend_title = "logvar"
)Arguments
- x
Object of class "variance_cube".
- ...
Further specifications for plot.
- tile
Tile to be plotted.
- roi
Spatial extent to plot in WGS 84 - named vector with either (lon_min, lon_max, lat_min, lat_max) or (xmin, xmax, ymin, ymax)
- labels
Labels to plot.
- palette
RColorBrewer palette
- rev
Reverse order of colors in palette?
- type
Type of plot ("map" or "hist")
- quantile
Minimum quantile to plot
- scale
Scale to plot map (0.4 to 1.0)
- max_cog_size
Maximum size of COG overviews (lines or columns)
- legend_position
Where to place the legend (default = "inside")
- legend_title
Title of legend (default = "probs")
Value
A plot containing local variances associated to the logit probability for each pixel and each class.
Author
Gilberto Camara, gilberto.camara@inpe.br
Examples
if (sits_run_examples()) {
# create a random forest model
rfor_model <- sits_train(samples_modis_ndvi, sits_rfor())
# create a data cube from local files
data_dir <- system.file("extdata/raster/mod13q1", package = "sits")
cube <- sits_cube(
source = "BDC",
collection = "MOD13Q1-6.1",
data_dir = data_dir
)
# classify a data cube
probs_cube <- sits_classify(
data = cube, ml_model = rfor_model, output_dir = tempdir()
)
# obtain a variance cube
var_cube <- sits_variance(probs_cube, output_dir = tempdir())
# plot the variance cube
plot(var_cube)
}