Summarize variance cubes — summary.variance

This is a generic function. Parameters depend on the specific type of input.

Usage

# S3 method for class 'variance_cube'
summary(
  object,
  ...,
  intervals = 0.05,
  sample_size = 10000L,
  multicores = 2L,
  memsize = 2L,
  quantiles = c("75%", "80%", "85%", "90%", "95%", "100%")
)

Arguments

object: Object of class "class_cube"
...: Further specifications for summary.
intervals: Intervals to calculate the quantiles
sample_size: The approximate size of samples will be extracted from the variance cube (by tile).
multicores: Number of cores to summarize data (integer, min = 1, max = 2048).
memsize: Memory in GB available to summarize data (integer, min = 1, max = 16384).
quantiles: Quantiles to be shown

Value

A summary of a variance cube

Author

Gilberto Camara, gilberto.camara@inpe.br

Felipe Carlos, efelipecarlos@gmail.com

Felipe Souza, lipecaso@gmail.com

Examples

if (sits_run_examples()) {
    # 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
    )
    # create a random forest model
    rfor_model <- sits_train(samples_modis_ndvi, sits_rfor())
    # classify a data cube
    probs_cube <- sits_classify(
        data = cube, ml_model = rfor_model, output_dir = tempdir()
    )
    variance_cube <- sits_variance(
        data = probs_cube,
        output_dir = tempdir()
    )
    summary(variance_cube)
}