Nothing
context("vignette roi")
library(purrr)
test_that("test_searchlight works correctly", {
skip_on_cran()
# Load example volume
file_name <- system.file("extdata", "global_mask2.nii.gz", package="neuroim2")
vol <- read_vol(file_name)
# Test exhaustive searchlight with eager=TRUE
slist <- searchlight(vol, radius=8, eager=TRUE)
expect_true(is.list(slist))
expect_true(length(slist) > 0)
# Compute mean values in each searchlight
ret <- slist %>% purrr::map_dbl(~ mean(vol[coords(.)]))
expect_equal(length(ret), length(slist))
expect_true(all(!is.na(ret)))
# Test random searchlight
ret_random <- vol %>%
random_searchlight(radius=8) %>%
purrr::map_dbl(~ mean(vol[coords(.)]))
expect_true(length(ret_random) > 0)
expect_true(all(!is.na(ret_random)))
# Test clustered searchlight
grid <- index_to_coord(vol, which(vol > 0))
kres <- kmeans(grid, centers=50, iter.max=500)
kvol <- ClusteredNeuroVol(vol, kres$cluster)
ret_clustered <- vol %>%
clustered_searchlight(cvol=kvol) %>%
purrr::map_dbl(~ mean(vol[coords(.)]))
expect_equal(length(ret_clustered), 50)
expect_true(all(!is.na(ret_clustered)))
# Test searchlight_coords
coords_list <- searchlight_coords(vol, radius=4, nonzero=FALSE)
expect_true(inherits(coords_list, "deflist"))
# Force evaluation of a few elements to test
first_coords <- coords_list[[1]]
expect_true(is.matrix(first_coords))
expect_equal(ncol(first_coords), 3)
})
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