Merge pull request #418 from tidymodels:jarl

Try out Jarl

Author: hfrick

R/aaa_ranges.R

@@ -98,7 +98,7 @@ range_validate <- function(
         call = call
       )
     }
-    if (any(!is_num[!is_unk])) {
+    if (!all(is_num[!is_unk])) {
       cli::cli_abort(
         c("Value ranges must be numeric.", ukn_txt),
         call = call

R/constructors.R

@@ -160,7 +160,7 @@ new_quant_param <- function(
 
   check_label(label, call = call)
   if (is.null(label)) {
-    label = "Unlabeled parameter"
+    label <- "Unlabeled parameter"
     names(label) <- "Unlabeled parameter"
   }
 
@@ -223,7 +223,7 @@ new_qual_param <- function(
 
   check_label(label, call = call)
   if (is.null(label)) {
-    label = "Unlabeled parameter"
+    label <- "Unlabeled parameter"
     names(label) <- "Unlabeled parameter"
   }
 

R/misc.R

@@ -182,7 +182,7 @@ check_inclusive <- function(x, ..., arg = caller_arg(x), call = caller_env()) {
 
   check_logical(x, arg = arg, call = call)
 
-  if (any(is.na(x))) {
+  if (anyNA(x)) {
     cli::cli_abort("{.arg {arg}} can't contain missing values.", call = call)
   }
 

R/parameters.R

@@ -45,7 +45,7 @@ parameters.list <- function(x, ...) {
   check_dots_empty()
 
   elem_param <- purrr::map_lgl(x, inherits, "param")
-  if (any(!elem_param)) {
+  if (!all(elem_param)) {
     cli::cli_abort("The objects should all be {.cls param} objects.")
   }
   elem_name <- purrr::map_chr(x, \(.x) names(.x$label))
@@ -98,7 +98,7 @@ check_list_of_param <- function(x, ..., call = caller_env()) {
     )
   }
   is_good_boi <- map_lgl(x, param_or_na)
-  if (any(!is_good_boi)) {
+  if (!all(is_good_boi)) {
     offenders <- which(!is_good_boi)
 
     cli::cli_abort(
@@ -141,10 +141,7 @@ parameters_constr <- function(
   check_character(component_id, call = call)
   check_list_of_param(object, call = call)
 
-  n_elements <- map_int(
-    list(name, id, source, component, component_id, object),
-    length
-  )
+  n_elements <- lengths(list(name, id, source, component, component_id, object))
   n_elements_unique <- unique(n_elements)
   if (length(n_elements_unique) > 1) {
     cli::cli_abort(

tests/testthat/test-constructors.R

@@ -133,7 +133,7 @@ test_that("printing", {
   expect_snapshot(surv_dist())
 
   expect_snapshot(
-    value_set(cost_complexity(), log10(c(.09, .0001)))
+    value_set(cost_complexity(), log10(c(0.09, 0.0001)))
   )
 
   expect_snapshot({
@@ -177,9 +177,9 @@ test_that("bad ranges", {
   expect_snapshot(error = TRUE, mixture(c(1L, unknown())))
   expect_snapshot(error = TRUE, mixture(c(unknown(), 1L)))
   expect_snapshot(error = TRUE, mixture(letters[1:2]))
-  expect_snapshot(error = TRUE, mtry(c(.1, .5)))
-  expect_snapshot(error = TRUE, mtry(c(.1, unknown())))
-  expect_snapshot(error = TRUE, mtry(c(unknown(), .5)))
+  expect_snapshot(error = TRUE, mtry(c(0.1, 0.5)))
+  expect_snapshot(error = TRUE, mtry(c(0.1, unknown())))
+  expect_snapshot(error = TRUE, mtry(c(unknown(), 0.5)))
 })
 
 test_that("can supply `values` without `range` and `inclusive` (#87)", {

tests/testthat/test-encode_unit.R

@@ -26,7 +26,7 @@ test_that("to [0, 1] for quantitative values", {
 
   x_back <- encode_unit(
     x,
-    c(0.000001, 1 / 3, .99999, 1),
+    c(0.000001, 1 / 3, 0.99999, 1),
     direction = "backward"
   )
   expect_equal(x_back, c(2L, 4L, 7L, 7L))

tests/testthat/test-finalize.R

@@ -72,7 +72,7 @@ test_that("estimate rows", {
 
 test_that("`get_batch_size() is deprecated", {
   expect_snapshot(
-    bsizes <- get_batch_sizes(batch_size(), iris, frac = c(.3, .7))
+    bsizes <- get_batch_sizes(batch_size(), iris, frac = c(0.3, 0.7))
   )
 })
 

tests/testthat/test-grids.R

@@ -88,16 +88,16 @@ test_that("wrong argument name", {
 test_that("filter arg yields same results", {
   p <- parameters(penalty(), mixture())
   expect_equal(
-    filter(with_seed(36L, grid_random(p)), penalty < .01),
-    with_seed(36L, grid_random(p, filter = penalty < .01))
+    filter(with_seed(36L, grid_random(p)), penalty < 0.01),
+    with_seed(36L, grid_random(p, filter = penalty < 0.01))
   )
   expect_equal(
-    filter(with_seed(36L, grid_random(p)), penalty > .001),
-    with_seed(36L, grid_random(p, filter = penalty > .001))
+    filter(with_seed(36L, grid_random(p)), penalty > 0.001),
+    with_seed(36L, grid_random(p, filter = penalty > 0.001))
   )
   expect_equal(
-    filter(with_seed(36L, grid_random(p)), mixture == .01),
-    with_seed(36L, grid_random(p, filter = mixture == .01))
+    filter(with_seed(36L, grid_random(p)), mixture == 0.01),
+    with_seed(36L, grid_random(p, filter = mixture == 0.01))
   )
 })
 

tests/testthat/test-params.R

@@ -3,7 +3,7 @@ test_that("param ranges", {
   expect_equal(sample_size(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(learn_rate(c(.1, .9))$range, list(lower = 0.1, upper = 0.9))
   expect_equal(loss_reduction(c(.1, .9))$range, list(lower = 0.1, upper = 0.9))
-  expect_equal(buffer(c(0, .25))$range, list(lower = 0, upper = .25))
+  expect_equal(buffer(c(0, 0.25))$range, list(lower = 0, upper = 0.25))
   expect_equal(cost_complexity(c(.1, .9))$range, list(lower = 0.1, upper = 0.9))
   expect_equal(epochs(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(degree()$range, list(lower = 1, upper = 3))
@@ -15,14 +15,14 @@ test_that("param ranges", {
   expect_equal(num_comp(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(cost(c(-2.0, -1.0))$range, list(lower = -2, upper = -1))
   expect_equal(scale_factor(c(-2.0, -1.0))$range, list(lower = -2, upper = -1))
-  expect_equal(svm_margin(c(.1, .15))$range, list(lower = .1, upper = .15))
+  expect_equal(svm_margin(c(0.1, 0.15))$range, list(lower = 0.1, upper = 0.15))
   expect_equal(deg_free(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(hidden_units(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(hidden_units_2(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(batch_size(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(Laplace(c(.1, .9))$range, list(lower = 0.1, upper = 0.9))
   expect_equal(dist_power(c(.1, .9))$range, list(lower = 0.1, upper = 0.9))
-  expect_equal(threshold(c(.1, .15))$range, list(lower = .1, upper = .15))
+  expect_equal(threshold(c(0.1, 0.15))$range, list(lower = 0.1, upper = 0.15))
   expect_equal(weight(c(-2.0, -1.0))$range, list(lower = -2, upper = -1))
   expect_equal(max_times(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(min_times(1:2)$range, list(lower = 1L, upper = 2L))
@@ -36,36 +36,45 @@ test_that("param ranges", {
   expect_equal(min_unique(1:2)$range, list(lower = 1L, upper = 2L))
   expect_equal(freq_cut(c(1.0, 2.0))$range, list(lower = 1, upper = 2))
   expect_equal(unique_cut(c(1.0, 2.0))$range, list(lower = 1, upper = 2))
-  expect_equal(over_ratio(c(.5, 1.5))$range, list(lower = .5, upper = 1.5))
-  expect_equal(under_ratio(c(.5, 1.5))$range, list(lower = .5, upper = 1.5))
+  expect_equal(over_ratio(c(0.5, 1.5))$range, list(lower = 0.5, upper = 1.5))
+  expect_equal(under_ratio(c(0.5, 1.5))$range, list(lower = 0.5, upper = 1.5))
   expect_equal(rbf_sigma(c(-2.0, -1.0))$range, list(lower = -2, upper = -1))
   expect_equal(kernel_offset(c(0.0, 1.0))$range, list(lower = 0, upper = 1))
   expect_equal(min_dist(c(-2.0, -1.0))$range, list(lower = -2, upper = -1))
-  expect_equal(sample_prop(c(.5, .6))$range, list(lower = .5, upper = .6))
+  expect_equal(sample_prop(c(0.5, 0.6))$range, list(lower = 0.5, upper = 0.6))
   expect_equal(num_hash(1:2)$range, list(lower = 1, upper = 2))
-  expect_equal(smoothness(c(.25, 1.75))$range, list(lower = .25, upper = 1.75))
-  expect_equal(predictor_prop(c(.1, .5))$range, list(lower = .1, upper = .5))
+  expect_equal(
+    smoothness(c(0.25, 1.75))$range,
+    list(lower = 0.25, upper = 1.75)
+  )
+  expect_equal(
+    predictor_prop(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
+  )
   expect_equal(
     num_random_splits(c(7L, 15L))$range,
     list(lower = 7L, upper = 15L)
   )
-  expect_equal(lower_quantile(c(.1, .5))$range, list(lower = .1, upper = .5))
+  expect_equal(
+    lower_quantile(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
+  )
   expect_equal(
     significance_threshold(c(-3, -2))$range,
     list(lower = -3, upper = -2)
   )
   expect_equal(
-    regularization_factor(c(.1, .5))$range,
-    list(lower = .1, upper = .5)
+    regularization_factor(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
   )
   expect_equal(
-    confidence_factor(c(-1, -.5))$range,
-    list(lower = -1, upper = -.5)
+    confidence_factor(c(-1, -0.5))$range,
+    list(lower = -1, upper = -0.5)
   )
   expect_equal(rule_bands(c(5L, 10L))$range, list(lower = 5L, upper = 10L))
   expect_equal(max_rules(c(5L, 10L))$range, list(lower = 5L, upper = 10L))
   expect_equal(extrapolation(c(1, 10))$range, list(lower = 1, upper = 10))
-  expect_equal(momentum(c(.1, .5))$range, list(lower = .1, upper = .5))
+  expect_equal(momentum(c(0.1, 0.5))$range, list(lower = 0.1, upper = 0.5))
   expect_equal(stop_iter(c(7L, 15L))$range, list(lower = 7L, upper = 15L))
   expect_equal(
     conditional_min_criterion(c(1, 2))$range,
@@ -81,27 +90,27 @@ test_that("param ranges", {
   )
   expect_equal(prior_slab_dispersion(c(1, 2))$range, list(lower = 1, upper = 2))
   expect_equal(
-    prior_mixture_threshold(c(.1, .5))$range,
-    list(lower = .1, upper = .5)
+    prior_mixture_threshold(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
   )
   expect_equal(
-    shrinkage_correlation(c(.1, .5))$range,
-    list(lower = .1, upper = .5)
+    shrinkage_correlation(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
   )
   expect_equal(
-    shrinkage_variance(c(.1, .5))$range,
-    list(lower = .1, upper = .5)
+    shrinkage_variance(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
   )
   expect_equal(
-    shrinkage_frequencies(c(.1, .5))$range,
-    list(lower = .1, upper = .5)
+    shrinkage_frequencies(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
   )
   expect_equal(penalty_L1(c(-5, 3))$range, list(lower = -5, upper = 3))
   expect_equal(penalty_L2(c(-5, 3))$range, list(lower = -5, upper = 3))
   expect_equal(class_weights(c(1, 5))$range, list(lower = 1, upper = 5))
   expect_equal(
-    prior_terminal_node_coef(c(.1, .5))$range,
-    list(lower = .1, upper = .5)
+    prior_terminal_node_coef(c(0.1, 0.5))$range,
+    list(lower = 0.1, upper = 0.5)
   )
   expect_equal(
     prior_terminal_node_expo(c(1, 2))$range,
@@ -140,9 +149,9 @@ test_that("param ranges", {
   expect_equal(max_num_terms(c(31, 100))$range, list(lower = 31, upper = 100))
   expect_equal(max_nodes(c(31, 100))$range, list(lower = 31, upper = 100))
   expect_equal(num_tokens(c(31, 100))$range, list(lower = 31, upper = 100))
-  expect_equal(mtry_prop(c(.1, .2))$range, list(lower = .1, upper = .2))
-  expect_equal(dropout(c(.1, .2))$range, list(lower = .1, upper = .2))
-  expect_equal(prop_terms(c(.1, .2))$range, list(lower = .1, upper = .2))
+  expect_equal(mtry_prop(c(0.1, 0.2))$range, list(lower = 0.1, upper = 0.2))
+  expect_equal(dropout(c(0.1, 0.2))$range, list(lower = 0.1, upper = 0.2))
+  expect_equal(prop_terms(c(0.1, 0.2))$range, list(lower = 0.1, upper = 0.2))
   expect_equal(num_estimators(c(1L, 10L))$range, list(lower = 1L, upper = 10L))
   expect_equal(
     softmax_temperature(c(0.1, 2.0))$range,