Address reviewer comments (#17)

* Address reviewer comments

* Vignette doesn't need kableExtra anymore

* Trip dplyr lifecycle warning outside tests

* Bump min R version

.github/workflows/R-CMD-check.yaml

@@ -26,15 +26,13 @@ jobs:
 
           - {os: windows-latest, r: 'release'}
 
-          # Use older ubuntu to maximise backward compatibility
           - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
           - {os: ubuntu-latest,   r: 'release'}
           - {os: ubuntu-latest,   r: 'oldrel-1'}
           - {os: ubuntu-latest,   r: 'oldrel-2'}
-          # Until dplyr::summarize is swapped for dplyr::reframe
-#          - {os: ubuntu-latest,   r: 'oldrel-3'}
           # Uncomment this in 2023 (once current R is >= 4.3)
-          # The package requires R 3.6, I don't really remember why
+#          - {os: ubuntu-latest,   r: 'oldrel-3'}
+          # Uncomment this in 2024 (once current R is >= 4.4)
 #          - {os: ubuntu-latest,   r: 'oldrel-4'}
 
     env:
@@ -58,11 +56,6 @@ jobs:
           extra-packages: any::rcmdcheck, CAST=?ignore-before-r=4.1.0
           needs: check
 
-      - name: Update dependencies
-        run: |
-          install.packages("purrr", repos = 'https://cloud.r-project.org')
-        shell: Rscript {0}
-
       - uses: r-lib/actions/check-r-package@v2
         env:
           _R_CHECK_FORCE_SUGGESTS_: false

DESCRIPTION

@@ -35,7 +35,7 @@ URL: https://github.com/mikemahoney218/waywiser,
     https://mikemahoney218.github.io/waywiser/
 BugReports: https://github.com/mikemahoney218/waywiser/issues
 Depends: 
-    R (>= 3.6)
+    R (>= 4.0)
 Imports: 
     dplyr,
     fields,
@@ -58,7 +58,6 @@ Suggests:
     CAST,
     covr,
     ggplot2,
-    kableExtra,
     knitr,
     modeldata,
     recipes,
@@ -74,6 +73,7 @@ Suggests:
     withr
 Config/testthat/edition: 3
 Config/testthat/parallel: true
+Config/Needs/website: kableExtra
 Encoding: UTF-8
 LazyData: true
 Roxygen: list(markdown = TRUE, roclets = c("namespace", "rd", "srr::srr_stats_roclet"))

R/data.R

@@ -74,7 +74,7 @@
 #'
 #' This data is adapted from the CAST vignette
 #' `vignette("cast02-AOA-tutorial", package = "CAST")`.
-#' The original data is derived from the Worldclim global climate variables/
+#' The original data is derived from the Worldclim global climate variables.
 #'
 #' @srrstats {G5.1} Data used to test the package is exported.
 #'

R/global_geary.R

@@ -3,6 +3,10 @@
 #' Calculate the global Geary's C statistic for model residuals.
 #' `ww_global_geary_c()` returns the statistic itself, while
 #' `ww_global_geary_pvalue()` returns the associated p value.
+#' These functions are meant to help assess model predictions, for instance by
+#' identifying if there are clusters of higher residuals than expected. For
+#' statistical testing and inference applications, use
+#' [spdep::geary.test()] instead.
 #'
 #' These functions can be used for geographic or projected coordinate reference
 #' systems and expect 2D data.

R/global_moran.R

@@ -3,6 +3,10 @@
 #' Calculate the global Moran's I statistic for model residuals.
 #' `ww_global_moran_i()` returns the statistic itself, while
 #' `ww_global_moran_pvalue()` returns the associated p value.
+#' These functions are meant to help assess model predictions, for instance by
+#' identifying if there are clusters of higher residuals than expected. For
+#' statistical testing and inference applications, use
+#' [spdep::moran.test()] instead.
 #'
 #' These functions can be used for geographic or projected coordinate reference
 #' systems and expect 2D data.

R/local_geary.R

@@ -3,6 +3,9 @@
 #' Calculate the local Geary's C statistic for model residuals.
 #' `ww_local_geary_c()` returns the statistic itself, while
 #' `ww_local_geary_pvalue()` returns the associated p value.
+#' These functions are meant to help assess model predictions, for instance by
+#' identifying clusters of higher residuals than expected. For statistical
+#' testing and inference applications, use [spdep::localC_perm()] instead.
 #'
 #' These functions can be used for geographic or projected coordinate reference
 #' systems and expect 2D data.

R/local_getis.R

@@ -3,6 +3,9 @@
 #' Calculate the local Getis-Ord G and G* statistic for model residuals.
 #' `ww_local_getis_ord_g()` returns the statistic itself, while
 #' `ww_local_getis_ord_pvalue()` returns the associated p value.
+#' These functions are meant to help assess model predictions, for instance by
+#' identifying clusters of higher residuals than expected. For statistical
+#' testing and inference applications, use [spdep::localG_perm()] instead.
 #'
 #' These functions can be used for geographic or projected coordinate reference
 #' systems and expect 2D data.

R/local_moran.R

@@ -3,6 +3,9 @@
 #' Calculate the local Moran's I statistic for model residuals.
 #' `ww_local_moran_i()` returns the statistic itself, while
 #' `ww_local_moran_pvalue()` returns the associated p value.
+#' These functions are meant to help assess model predictions, for instance by
+#' identifying clusters of higher residuals than expected. For statistical
+#' testing and inference applications, use [spdep::localmoran_perm()] instead.
 #'
 #' These functions can be used for geographic or projected coordinate reference
 #' systems and expect 2D data.

inst/srr_template_spatial_yardstick.R

@@ -1,4 +1,5 @@
 test_that("srr: expected failures for {{{name}}}", {
+  trip_dplyr_warning()
   worldclim_predicted <- worldclim_simulation
   worldclim_predicted$predicted <- predict(
     lm(response ~ bio2 * bio10 * bio13 * bio19, data = worldclim_simulation),
@@ -226,6 +227,7 @@ test_that("srr: expected failures for {{{name}}}", {
 })
 
 test_that("other generic srr standards", {
+  trip_dplyr_warning()
   skip_if_not_installed("withr")
   worldclim_predicted <- worldclim_simulation
   worldclim_predicted$predicted <- predict(

tests/testthat/_snaps/local_geary.md

@@ -2,13 +2,6 @@
 
     Code
       df_local_c <- ww_local_geary_c(guerry_modeled, Crm_prs, predictions)
-    Warning <lifecycle_warning_deprecated>
-      Returning more (or less) than 1 row per `summarise()` group was deprecated in dplyr 1.1.0.
-      i Please use `reframe()` instead.
-      i When switching from `summarise()` to `reframe()`, remember that `reframe()` always returns an ungrouped data frame and adjust accordingly.
-      i The deprecated feature was likely used in the yardstick package.
-        Please report the issue at <https://github.com/tidymodels/yardstick/issues>.
-    Code
       df_local_c[1:3]
     Output
       # A tibble: 85 x 3

tests/testthat/_snaps/srr-ww_local_geary_c.md

@@ -726,12 +726,6 @@
 
     Code
       ww_local_geary_c(worldclim_simulation, response, response)
-    Warning <lifecycle_warning_deprecated>
-      Returning more (or less) than 1 row per `summarise()` group was deprecated in dplyr 1.1.0.
-      i Please use `reframe()` instead.
-      i When switching from `summarise()` to `reframe()`, remember that `reframe()` always returns an ungrouped data frame and adjust accordingly.
-      i The deprecated feature was likely used in the yardstick package.
-        Please report the issue at <https://github.com/tidymodels/yardstick/issues>.
     Output
       # A tibble: 10,000 x 3
          .metric       .estimator .estimate

tests/testthat/helper.R

@@ -0,0 +1,11 @@
+if (identical(Sys.getenv("NOT_CRAN"), "true")) {
+  Sys.setenv("waywiser_test_cast" = "true")
+}
+
+trip_dplyr_warning <- function() {
+  invisible(
+    suppressWarnings(
+      dplyr::summarise(dplyr::group_by(iris, Species), 1:2)
+    )
+  )
+}

tests/testthat/test-agreement_coefficient.R

@@ -1,4 +1,5 @@
 test_that("agreement coefficients match Ji and Gallo", {
+  trip_dplyr_warning()
   #' @srrstats {G5.7} Algorithm performs as expected
   x <- c(6, 8, 9, 10, 11, 14)
   y <- c(2, 3, 5, 5, 6, 8)
@@ -62,6 +63,7 @@ test_that("agreement coefficients match Ji and Gallo", {
 })
 
 test_that("agreement coefficients are the same across methods", {
+  trip_dplyr_warning()
   x <- c(6, 8, 9, 10, 11, 14)
   y <- c(2, 3, 5, 5, 6, 8)
   df <- data.frame(x = x, y = y)

tests/testthat/test-area_of_applicability.R

@@ -18,19 +18,22 @@ importance <- vip::vi_permute(
 )
 
 test_that("`ww_area_of_applicability` is properly classed", {
+  trip_dplyr_warning()
   model <- ww_area_of_applicability(y ~ ., train, test, importance)
   expect_s3_class(model, "ww_area_of_applicability")
   expect_s3_class(model, "hardhat_model")
 })
 
 
 test_that("`ww_area_of_applicability` is not defined for vectors", {
+  trip_dplyr_warning()
   expect_snapshot_error(
     ww_area_of_applicability(mtcars$mpg)
   )
 })
 
 test_that("`ww_area_of_applicability` finds 0 distance between identical data", {
+  trip_dplyr_warning()
   #' @srrstats {G3.0} Testing with appropriate tolerances.
   expect_equal(
     suppressWarnings(
@@ -43,7 +46,7 @@ test_that("`ww_area_of_applicability` finds 0 distance between identical data",
 })
 
 test_that("`ww_area_of_applicability` works with or without a testing set", {
-
+  trip_dplyr_warning()
   expect_error(
     ww_area_of_applicability(y ~ ., train, test, importance),
     NA
@@ -57,7 +60,7 @@ test_that("`ww_area_of_applicability` works with or without a testing set", {
 })
 
 test_that("`ww_area_of_applicability` methods are equivalent", {
-
+  trip_dplyr_warning()
   methods <- list(
     ww_area_of_applicability(y ~ ., train, test, importance),
     ww_area_of_applicability(train[2:11], test[2:11], importance),
@@ -117,7 +120,7 @@ test_that("`ww_area_of_applicability` methods are equivalent", {
 })
 
 test_that("`ww_area_of_applicability` can handle different column orders", {
-
+  trip_dplyr_warning()
   #' @srrstats {G3.0} Testing with appropriate tolerances.
   expect_equal(
     ww_area_of_applicability(train[2:11], test[2:11], importance)$aoa_threshold,
@@ -133,7 +136,7 @@ test_that("`ww_area_of_applicability` can handle different column orders", {
 })
 
 test_that("NAs are handled", {
-
+  trip_dplyr_warning()
   train[1, 2] <- NA
   test[1, 2] <- NA
   comb_rset <- rsample::make_splits(train, test)
@@ -216,6 +219,7 @@ test_that("NAs are handled", {
 })
 
 test_that("Expected errors", {
+  trip_dplyr_warning()
   expect_snapshot(
     ww_area_of_applicability(y ~ ., train, test[1:10], importance),
     error = TRUE
@@ -252,7 +256,7 @@ importance <- vip::vi_permute(
 aoa <- ww_area_of_applicability(y ~ ., train, test, importance)
 
 test_that("normal use", {
-
+  trip_dplyr_warning()
   expect_snapshot(
     predict(aoa, test)
   )
@@ -265,6 +269,7 @@ test_that("normal use", {
 })
 
 test_that("`new_ww_area_of_applicability` arguments are assigned correctly", {
+  trip_dplyr_warning()
   x <- ww_area_of_applicability(y ~ ., train, test, importance)
 
   skip_on_os("mac")
@@ -284,6 +289,7 @@ test_that("`new_ww_area_of_applicability` arguments are assigned correctly", {
 #' @srrstats {G5.4c} Data is derived originally from CAST and associated paper
 test_that("ww_area_of_applicability() is close-enough to CAST", {
   skip_on_cran()
+  trip_dplyr_warning()
   #' @srrstats {SP6.2} Testing with ~global data
   relevant_data <- head(as.data.frame(worldclim_simulation)[c(1:4, 6)], 1000)
 
@@ -331,6 +337,7 @@ test_that("ww_area_of_applicability() is close-enough to CAST", {
 })
 
 test_that("loaded data is equivalent", {
+  trip_dplyr_warning()
   importance <- data.frame(
     term = c("bio2", "bio10", "bio13", "bio19"),
     estimate = c(50.68727, 57.66859, 62.81009, 48.72391)

tests/testthat/test-global_geary.R

@@ -1,5 +1,5 @@
 test_that("Global Geary statistics are stable", {
-
+  trip_dplyr_warning()
   guerry_modeled <- guerry
   guerry_lm <- lm(Crm_prs ~ Litercy, guerry_modeled)
   guerry_modeled$predictions <- predict(guerry_lm, guerry_modeled)

tests/testthat/test-global_moran.R

@@ -1,5 +1,5 @@
 test_that("Global Moran statistics are stable", {
-
+  trip_dplyr_warning()
   guerry_modeled <- guerry
   guerry_lm <- lm(Crm_prs ~ Litercy, guerry_modeled)
   guerry_modeled$predictions <- predict(guerry_lm, guerry_modeled)

tests/testthat/test-local_geary.R

@@ -1,4 +1,5 @@
 test_that("Local geary statistics are stable", {
+  trip_dplyr_warning()
   set.seed(123)
 
   guerry_modeled <- guerry

tests/testthat/test-local_getis.R

@@ -1,6 +1,6 @@
 set.seed(123)
 test_that("Local Getis-Ord statistics are stable", {
-
+  trip_dplyr_warning()
   guerry_modeled <- guerry
   guerry_lm <- lm(Crm_prs ~ Litercy, guerry_modeled)
   guerry_modeled$predictions <- predict(guerry_lm, guerry_modeled)
@@ -61,7 +61,7 @@ test_that("Local Getis-Ord statistics are stable", {
 })
 
 test_that("Local Getis-Ord statistics are stable", {
-
+  trip_dplyr_warning()
   guerry_modeled <- guerry
   guerry_lm <- lm(Crm_prs ~ Litercy, guerry_modeled)
   guerry_modeled$predictions <- predict(guerry_lm, guerry_modeled)

tests/testthat/test-local_moran.R

@@ -1,6 +1,6 @@
 set.seed(123)
 test_that("Local Moran statistics are stable", {
-
+  trip_dplyr_warning()
   guerry_modeled <- guerry
   guerry_lm <- lm(Crm_prs ~ Litercy, guerry_modeled)
   guerry_modeled$predictions <- predict(guerry_lm, guerry_modeled)