cv_plot: Visualising folds created by blockCV in ggplot

In rvalavi/blockCV: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation

Visualising folds created by blockCV in ggplot

Description

This function visualises the folds create by blockCV. It also accepts a raster layer to be used as background in the output plot.

Usage

cv_plot(
  cv,
  x,
  r = NULL,
  nrow = NULL,
  ncol = NULL,
  num_plots = 1:10,
  max_pixels = 3e+05,
  remove_na = TRUE,
  raster_colors = gray.colors(10, alpha = 1),
  points_colors = c("#E69F00", "#56B4E9"),
  points_alpha = 0.7,
  label_size = 4
)

Arguments

cv	a blockCV cv_* object; a cv_spatial, cv_cluster, cv_buffer or cv_nndm
x	a simple features (sf) or SpatialPoints object of the spatial sample data used for creating the cv object. This could be empty when cv is a cv_spatial object.
r	a terra SpatRaster object (optional). If provided, it will be used as background of the plots. It also supports stars, raster, or path to a raster file on disk.
nrow	integer; number of rows for facet plot
ncol	integer; number of columns for facet plot
num_plots	a vector of indices of folds; by default the first 10 are shown (if available). You can choose any of the folds to be shown e.g. 1:3 or c(2, 7, 16, 22)
max_pixels	integer; maximum number of pixels used for plotting r
remove_na	logical; whether to remove excluded points in cv_buffer from the plot
raster_colors	character; a character vector of colours for raster background e.g. terrain.colors(20)
points_colors	character; two colours to be used for train and test points
points_alpha	numeric; the opacity of points
label_size	integer; size of fold labels when a cv_spatial object is used.

Value

a ggplot object

Examples

library(blockCV)

# import presence-absence species data
points <- read.csv(system.file("extdata/", "species.csv", package = "blockCV"))
pa_data <- sf::st_as_sf(points, coords = c("x", "y"), crs = 7845)

# spatial clustering
sc <- cv_cluster(x = pa_data, k = 5)

# now plot the create folds
cv_plot(cv = sc,
        x = pa_data, # sample points
        nrow = 2,
        points_alpha = 0.5)

rvalavi/blockCV documentation built on Feb. 3, 2024, 7:26 a.m.