plot.uncertainty_cube {sits} | R Documentation |
Plot uncertainty cubes
Description
plots a probability cube using stars
Usage
## S3 method for class 'uncertainty_cube'
plot(
x,
...,
tile = x[["tile"]][[1]],
palette = "RdYlGn",
rev = TRUE,
scale = 1,
first_quantile = 0.02,
last_quantile = 0.98,
max_cog_size = 1024
)
Arguments
x |
Object of class "probs_image". |
... |
Further specifications for plot. |
tile |
Tiles to be plotted. |
palette |
An RColorBrewer palette |
rev |
Reverse the color order in the palette? |
scale |
Scale to plot map (0.4 to 1.0) |
first_quantile |
First quantile for stretching images |
last_quantile |
Last quantile for stretching images |
max_cog_size |
Maximum size of COG overviews (lines or columns) |
Value
A plot object produced by the stars package with a map showing the uncertainty associated to each classified pixel.
Note
The following optional parameters are available to allow for detailed control over the plot output:
-
graticules_labels_size
: size of coordinates labels (default = 0.7) -
legend_title_size
: relative size of legend title (default = 1.0) -
legend_text_size
: relative size of legend text (default = 1.0) -
legend_bg_color
: color of legend background (default = "white") -
legend_bg_alpha
: legend opacity (default = 0.5)
Author(s)
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()
)
# calculate uncertainty
uncert_cube <- sits_uncertainty(probs_cube, output_dir = tempdir())
# plot the resulting uncertainty cube
plot(uncert_cube)
}