View source: R/blockcv2rsample.R
| blockcv2rsample | R Documentation |
blockCV to an rsample objectThis function converts 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).
blockcv2rsample(x, data)
x |
a object created with a |
data |
the |
Note that currently only objects of type cv_spatial and cv_cluster are
supported.
an rsample object
library(blockCV)
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
sb1_rsample <- blockcv2rsample(sb1, pa_data)
class(sb1_rsample)
autoplot(sb1_rsample)
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