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Update snaps
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mikemahoney218 committed Apr 29, 2024
1 parent 8c022ef commit 9df933d
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Expand Up @@ -87,4 +87,4 @@ Encoding: UTF-8
Language: en-US
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
RoxygenNote: 7.3.1
5 changes: 5 additions & 0 deletions NEWS.md
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# waywiser (development version)

* `ww_multi_scale()`, when called with raster arguments (either to `data` or to `truth`
and `estimate`) and a classification metric set, will now convert `truth` and
`estimate`to factors before passing them to the metric set. Thanks to @nowosad
for the report in #60 (#61).

# waywiser 0.5.1

* `ww_multi_scale()` now warns if you provide `crs` as an argument to `sf::st_make_grid()` via `...`. Grids created by this function will always take their CRS from `data`.
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3 changes: 3 additions & 0 deletions tests/testthat/_snaps/misc.md
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Number of nonzero links: 85
Percentage nonzero weights: 1.176471
Average number of links: 1
25 disjoint connected subgraphs
Non-symmetric neighbours list

---
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Number of nonzero links: 85
Percentage nonzero weights: 1.176471
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Non-symmetric neighbours list

---
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Number of nonzero links: 85
Percentage nonzero weights: 1.176471
Average number of links: 1
25 disjoint connected subgraphs
Non-symmetric neighbours list
Weights style: W
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4 changes: 2 additions & 2 deletions tests/testthat/test-multi_scale.R
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Expand Up @@ -778,7 +778,7 @@ test_that("Passing arguments via `...` errors when using grids", {
)
})

test_that("ww_multi_scale with raster args can handle classification metrics", {
test_that("ww_multi_scale with raster args can handle classification metrics (#60)", {
l1 <- terra::rast(matrix(sample(1:10, 100, TRUE), nrow = 10))
l2 <- l1

Expand All @@ -794,7 +794,7 @@ test_that("ww_multi_scale with raster args can handle classification metrics", {

})

test_that("ww_multi_scale with raster data can handle classification metrics", {
test_that("ww_multi_scale with raster data can handle classification metrics (#60)", {
l1 <- terra::rast(matrix(sample(1:10, 100, TRUE), nrow = 10))
l2 <- l1

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