Convert an object created with blockCV to an rsample object

This function creates objects created with blockCV to rsample objects that can be used by tidysdm. BlockCV provides more sophisticated sampling options than the spatialsample library. For example, it is possible to stratify the sampling to ensure that presences and absences are evenly distributed among the folds (see the example below).

Usage

blockcv2rsample(x, data)

Arguments

x

a object created with a blockCV function

data

the sf object used to create x

Value

an rsample object

Details

Note that currently only objects of type cv_spatial and cv_cluster are supported.

Examples

# \donttest{
library(blockCV)
#> blockCV 3.1.5
points <- read.csv(system.file("extdata/", "species.csv", package = "blockCV"))
pa_data <- sf::st_as_sf(points, coords = c("x", "y"), crs = 7845)
sb1 <- cv_spatial(
  x = pa_data,
  column = "occ", # the response column to balance the folds
  k = 5, # number of folds
  size = 350000, # size of the blocks in metres
  selection = "random", # random blocks-to-fold
  iteration = 10
) # find evenly dispersed folds
#> 
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#>   train_0 train_1 test_0 test_1
#> 1     172     207     85     36
#> 2     218     202     39     41
#> 3     218     192     39     51
#> 4     217     171     40     72
#> 5     203     200     54     43

sb1_rsample <- blockcv2rsample(sb1, pa_data)
class(sb1_rsample)
#> [1] "spatial_rset" "rset"         "tbl_df"       "tbl"          "data.frame"  
autoplot(sb1_rsample)

# }