value_seq() and value_sample() respect inclusive

NEWS.md

@@ -11,6 +11,8 @@
 
 * For space-filling designs for $p$ parameters, there is a higher likelihood of finding a space-filling design for `1 < size <= p`. Also, single-point designs now default to a random grid (#363).
 
+* `value_seq()` and `value_sample()` now respect the `inclusive` argument of quantitative parameters (#347).
+
 ## Breaking changes
 
 * The `grid_*()` functions now error instead of warn when provided with the wrong argument to control the grid size. So `grid_space_filling()`, `grid_random()`, `grid_max_entropy()`, and `grid_latin_hypercube()` now error if used with a `levels` argument and `grid_regular()` now errors if used with a `size` argument (#368).

R/aaa_values.R

@@ -143,9 +143,19 @@
     n_safely <- min(length(object$values), n)
     res <- object$values[seq_len(n_safely)]
   } else {
+    range_lower <- min(unlist(object$range))
+    if (!object$inclusive["lower"]) {
+      range_lower <- range_lower + .Machine$double.eps
+    }
+
+    range_upper <- max(unlist(object$range))
+    if (!object$inclusive["upper"]) {
+      range_upper <- range_upper - .Machine$double.eps
+    }
+
     res <- seq(
-      from = min(unlist(object$range)),
-      to = max(unlist(object$range)),
+      from = range_lower,
+      to = range_upper,
       length.out = n
     )
   }
@@ -161,9 +171,19 @@
     n_safely <- min(length(object$values), n)
     res <- object$values[seq_len(n_safely)]
   } else {
+    range_lower <- min(unlist(object$range))
+    if (!object$inclusive["lower"]) {
+      range_lower <- range_lower + 1L
+    }
+
+    range_upper <- max(unlist(object$range))
+    if (!object$inclusive["upper"]) {
+      range_upper <- range_upper - 1L
+    }
+
     res <- seq(
-      from = min(unlist(object$range)),
-      to = max(unlist(object$range)),
+      from = range_lower,
+      to = range_upper,
       length.out = n
     )
   }
@@ -202,10 +222,20 @@
 
 value_samp_dbl <- function(object, n, original = TRUE) {
   if (is.null(object$values)) {
+    range_lower <- min(unlist(object$range))
+    if (!object$inclusive["lower"]) {
+      range_lower <- range_lower + .Machine$double.eps
+    }
+
+    range_upper <- max(unlist(object$range))
+    if (!object$inclusive["upper"]) {
+      range_upper <- range_upper - .Machine$double.eps
+    }
+
     res <- runif(
       n,
-      min = min(unlist(object$range)),
-      max = max(unlist(object$range))
+      min = range_lower,
+      max = range_upper
     )
   } else {
     res <- sample(
@@ -223,8 +253,18 @@
 value_samp_int <- function(object, n, original = TRUE) {
   if (is.null(object$trans)) {
     if (is.null(object$values)) {
+      range_lower <- min(unlist(object$range))
+      if (!object$inclusive["lower"]) {
+        range_lower <- range_lower + 1L
+      }
+
+      range_upper <- max(unlist(object$range))
+      if (!object$inclusive["upper"]) {
+        range_upper <- range_upper - 1L
+      }
+
       res <- sample(
-        min(unlist(object$range)):max(unlist(object$range)),
+        seq(from = range_lower, to = range_upper),
         size = n,
         replace = TRUE
       )
@@ -237,10 +277,20 @@
     }
   } else {
     if (is.null(object$values)) {
+      range_lower <- min(unlist(object$range))
+      if (!object$inclusive["lower"]) {
+        range_lower <- range_lower + .Machine$double.eps
+      }
+
+      range_upper <- max(unlist(object$range))
+      if (!object$inclusive["upper"]) {
+        range_upper <- range_upper - .Machine$double.eps
+      }
+
       res <- runif(
         n,
-        min = min(unlist(object$range)),
-        max = max(unlist(object$range))
+        min = range_lower,
+        max = range_upper
       )
     } else {
       res <- sample(

tests/testthat/test-aaa_values.R

@@ -276,3 +276,59 @@ test_that("value_set() checks inputs", {
     value_set(cost_complexity(), numeric(0))
   })
 })
+
+test_that("`value_seq()` respects `inclusive` #347", {
+  double_non_incl <- new_quant_param(
+    type = "double",
+    range = c(0, 1),
+    inclusive = c(FALSE, FALSE),
+    trans = NULL,
+    label = c(param_non_incl = "some label"),
+    finalize = NULL
+  )
+
+  vals_double <- value_seq(double_non_incl, 10)
+  expect_gt(min(vals_double), 0)
+  expect_lt(max(vals_double), 1)
+
+  int_non_incl <- new_quant_param(
+    type = "integer",
+    range = c(0, 2),
+    inclusive = c(FALSE, FALSE),
+    trans = NULL,
+    label = c(param_non_incl = "some label"),
+    finalize = NULL
+  )
+
+  vals_int <- value_seq(int_non_incl, 10)
+  expect_gt(min(vals_int), 0)
+  expect_lt(max(vals_int), 2)
+})
+
+test_that("`value_sample()` respects `inclusive` #347", {
+  int_non_incl <- new_quant_param(
+    type = "integer",
+    range = c(0, 2),
+    inclusive = c(FALSE, FALSE),
+    trans = NULL,
+    label = c(param_non_incl = "some label"),
+    finalize = NULL
+  )
+
+  vals_int <- value_sample(int_non_incl, 10)
+  expect_gt(min(vals_int), 0)
+  expect_lt(max(vals_int), 2)
+
+  int_non_incl_trans <- new_quant_param(
+    type = "integer",
+    range = c(0, 2),
+    inclusive = c(FALSE, FALSE),
+    trans = scales::transform_log(),
+    label = c(param_non_incl = "some label"),
+    finalize = NULL
+  )
+
+  vals_int <- value_sample(int_non_incl_trans, n = 10, original = FALSE)
+  expect_gt(min(vals_int), 0)
+  expect_lt(max(vals_int), 2)
+})