varying test cases for parsnip and recipes

Author: topepo

R/varying.R

@@ -109,11 +109,11 @@ varying_args.step <- function(x, id = NULL, ...) {
 
   exclude <-
     c("terms", "role", "trained", "skip", "na.rm", "impute_with", "seed",
-      "prefix", "naming", "denom", "outcome")
+      "prefix", "naming", "denom", "outcome", "id")
   x <- x[!(names(x) %in% exclude)]
   x <- x[!map_lgl(x, is.null)]
-  res <- map(x, is_varying)
-  res <- map_lgl(res, find_varying)
+  res <- map(x, find_varying)
+  res <- map_lgl(res, any)
   tibble(
     name = names(res),
     varying = unname(res),

tests/testthat/recipes_examples.RData

@@ -0,0 +1,125 @@
+library(testthat)
+library(parsnip)
+library(rlang)
+library(dplyr)
+
+context("varying parameters")
+
+load("recipes_examples.RData")
+
+test_that('main parsnip arguments', {
+  mod_1 <- 
+    rand_forest() %>% 
+    varying_args(id = "")
+  exp_1 <- 
+    tibble(
+      name = c("mtry", "trees", "min_n"),
+      varying = rep(FALSE, 3),
+      id = rep("", 3), 
+      type = rep("model_spec", 3)
+    )
+  expect_equal(mod_1, exp_1)
+  
+  mod_2 <- 
+    rand_forest(mtry = varying()) %>% 
+    varying_args(id = "")  
+  exp_2 <- exp_1
+  exp_2$varying[1] <- TRUE
+  expect_equal(mod_2, exp_2)
+  
+  mod_3 <- 
+    rand_forest(mtry = varying(), trees  = varying()) %>% 
+    varying_args(id = "wat")  
+  exp_3 <- exp_2
+  exp_3$varying[1:2] <- TRUE
+  exp_3$id <- "wat"
+  expect_equal(mod_3, exp_3)
+})
+
+
+test_that('other parsnip arguments', {
+  other_1 <-
+    rand_forest(others = list(sample.fraction = varying())) %>%
+    varying_args(id = "only others")
+  exp_1 <- 
+    tibble(
+      name = c("mtry", "trees", "min_n", "sample.fraction"),
+      varying = c(rep(FALSE, 3), TRUE),
+      id = rep("only others", 4), 
+      type = rep("model_spec", 4)
+    )
+  expect_equal(other_1, exp_1)
+  
+  other_2 <-
+    rand_forest(min_n = varying(), others = list(sample.fraction = varying())) %>%
+    varying_args(id = "only others")
+  exp_2 <- 
+    tibble(
+      name = c("mtry", "trees", "min_n", "sample.fraction"),
+      varying = c(rep(FALSE, 2), rep(TRUE, 2)),
+      id = rep("only others", 4), 
+      type = rep("model_spec", 4)
+    )
+  expect_equal(other_2, exp_2)  
+  
+  other_3 <- 
+    rand_forest(
+      others = list(
+        strata = expr(Class),
+        sampsize = c(varying(), varying())
+      )
+    ) %>%
+    varying_args(id = "add an expr")
+  exp_3 <- 
+    tibble(
+      name = c("mtry", "trees", "min_n", "strata", "sampsize"),
+      varying = c(rep(FALSE, 4), TRUE),
+      id = rep("add an expr", 5), 
+      type = rep("model_spec", 5)
+    )
+  expect_equal(other_3, exp_3)    
+  
+  other_4 <- 
+    rand_forest(
+      others = list(
+        strata = expr(Class),
+        sampsize = c(12, varying())
+      )
+    ) %>%
+    varying_args(id = "num and varying in vec")
+  exp_4 <- 
+    tibble(
+      name = c("mtry", "trees", "min_n", "strata", "sampsize"),
+      varying = c(rep(FALSE, 4), TRUE),
+      id = rep("num and varying in vec", 5), 
+      type = rep("model_spec", 5)
+    )
+  expect_equal(other_4, exp_4)    
+})
+
+
+test_that('recipe parameters', {
+  rec_res_1 <- varying_args(rec_1)
+  exp_1 <- 
+    tibble(
+      name = c("K", "num", "threshold", "options"),
+      varying = c(TRUE, TRUE, FALSE, FALSE),
+      id = c("step_knnimpute", rep("step_pca", 3)),
+      type = rep("step", 4)
+    )
+  expect_equal(rec_res_1, exp_1)
+  
+  rec_res_2 <- varying_args(rec_2)
+  exp_2 <- exp_1
+  expect_equal(rec_res_2, exp_2)
+  
+  rec_res_3 <- varying_args(rec_3)
+  exp_3 <- exp_1
+  exp_3$varying <- FALSE
+  expect_equal(rec_res_3, exp_3)
+  
+  rec_res_4 <- varying_args(rec_4)
+  exp_4 <- tibble()
+  expect_equal(rec_res_4, exp_4)
+})
+