test Euclidean weights and weight standardisation for control_for_euc()

tests/testthat/test-generate.R

@@ -188,7 +188,7 @@ testthat::test_that("no id_col given", {
       eg_df %>%
         split_by(a, -5:0 ~ 0:5) %>%
         control_for(b, -2.5:2.5) %>%
-        generate(17) %>%
+        generate(17, silent=TRUE) %>%
         nrow()
     ),
     17
@@ -198,7 +198,7 @@ testthat::test_that("no id_col given", {
     eg_df %>%
       split_by(a, -5:0 ~ 0:5) %>%
       control_for(b, -2.5:2.5) %>%
-      generate(17),
+      generate(17, silent=TRUE),
     "No id_col detected; will use row numbers."
   )
   # since eg_df's id column is just the row numbers anyway, these should be identical
@@ -777,4 +777,98 @@ testthat::test_that("control_for_euc", {
       dplyr::filter(gen_euc_dist == man_euc_dist) %>%
       nrow()
   }, 20)
+  # test weighted Euclidean distance is calculated as expected
+  testthat::expect_equal({
+    weights <- runif(2, 0.1, 100)
+    weights_std <- weights / mean(weights)
+
+    wide_res <- eg_df %>%
+      set_options(id_col = "id") %>%
+      split_by(a, -5:0 ~ 0:5) %>%
+      control_for_euc(
+        c(b, e),
+        0:1.5,
+        name = "gen_euc_dist",
+        weights = weights
+      ) %>%
+      generate(20, silent=TRUE)
+
+    manual_euc_dist <- wide_res %>%
+      dplyr::left_join(
+        eg_df %>%
+          dplyr::select(id, b, e) %>%
+          dplyr::mutate(b = weights_std[1]*scale(b), e = weights_std[2]*scale(e)) %>%
+          dplyr::rename(A1_b = b, A1_e = e),
+        by = c("A1" = "id")
+      ) %>%
+      dplyr::left_join(
+        eg_df %>%
+          dplyr::select(id, b, e) %>%
+          dplyr::mutate(b = weights_std[1]*scale(b), e = weights_std[2]*scale(e)) %>%
+          dplyr::rename(A2_b = b, A2_e = e),
+        by = c("A2" = "id")
+      ) %>%
+      dplyr::mutate(
+        dist_b = A1_b - A2_b,
+        dist_e = A1_e - A2_e,
+        man_euc_dist = sqrt(dist_b**2 + dist_e**2)
+      )
+
+    wide_res %>%
+      long_format() %>%
+      dplyr::filter(condition != match_null) %>%
+      dplyr::left_join(
+        dplyr::select(manual_euc_dist, item_nr, man_euc_dist),
+        by = "item_nr"
+      ) %>%
+      dplyr::filter(gen_euc_dist == man_euc_dist) %>%
+      nrow()
+  }, 20)
+  # test that weight standardisation can be disabled
+  testthat::expect_equal({
+    weights <- runif(2, 0.1, 100)
+
+    wide_res <- eg_df %>%
+      set_options(id_col = "id") %>%
+      split_by(a, -5:0 ~ 0:5) %>%
+      control_for_euc(
+        c(b, e),
+        0:10,
+        name = "gen_euc_dist",
+        weights = weights,
+        standardise_weights = FALSE
+      ) %>%
+      generate(20, silent=TRUE)
+
+    manual_euc_dist <- wide_res %>%
+      dplyr::left_join(
+        eg_df %>%
+          dplyr::select(id, b, e) %>%
+          dplyr::mutate(b = weights[1]*scale(b), e = weights[2]*scale(e)) %>%
+          dplyr::rename(A1_b = b, A1_e = e),
+        by = c("A1" = "id")
+      ) %>%
+      dplyr::left_join(
+        eg_df %>%
+          dplyr::select(id, b, e) %>%
+          dplyr::mutate(b = weights[1]*scale(b), e = weights[2]*scale(e)) %>%
+          dplyr::rename(A2_b = b, A2_e = e),
+        by = c("A2" = "id")
+      ) %>%
+      dplyr::mutate(
+        dist_b = A1_b - A2_b,
+        dist_e = A1_e - A2_e,
+        man_euc_dist = sqrt(dist_b**2 + dist_e**2)
+      )
+
+    wide_res %>%
+      long_format() %>%
+      dplyr::filter(condition != match_null) %>%
+      dplyr::left_join(
+        dplyr::select(manual_euc_dist, item_nr, man_euc_dist),
+        by = "item_nr"
+      ) %>%
+      dplyr::filter(gen_euc_dist == man_euc_dist) %>%
+      nrow()
+  }, 20)
 })