Adjust blueprint test

DESCRIPTION

@@ -23,7 +23,7 @@ Imports:
     generics,
     glue,
     hardhat (>= 0.1.4),
-    parsnip (>= 0.1.2),
+    parsnip (>= 0.1.3),
     rlang (>= 0.4.1)
 Suggests: 
     covr,

NEWS.md

@@ -1,5 +1,8 @@
 # workflows (development version)
 
+* A test has been updated to reflect a change in parsnip 0.1.3 regarding how
+  intercept columns are removed during prediction (#65).
+
 # workflows 0.1.2
 
 * When using a formula preprocessor with `add_formula()`, workflows now uses

tests/testthat/test-predict.R

@@ -95,25 +95,57 @@ test_that("`new_data` must have all of the original predictors", {
 })
 
 test_that("blueprint will get passed on to hardhat::forge()", {
+  train <- data.frame(
+    y = c(1L, 5L, 3L, 4L),
+    x = factor(c("x", "y", "x", "y"))
+  )
+
+  test <- data.frame(
+    x = factor(c("x", "y", "z"))
+  )
+
+  spec <- parsnip::linear_reg()
+  spec <- parsnip::set_engine(spec, "lm")
+
+  bp1 <- hardhat::default_formula_blueprint(intercept = TRUE, allow_novel_levels = FALSE)
+  bp2 <- hardhat::default_formula_blueprint(intercept = TRUE, allow_novel_levels = TRUE)
+
+  workflow <- workflow()
+  workflow <- add_model(workflow, spec)
+
+  workflow1 <- add_formula(workflow, y ~ x, blueprint = bp1)
+  workflow2 <- add_formula(workflow, y ~ x, blueprint = bp2)
+
+  mod1 <- fit(workflow1, train)
+  mod2 <- fit(workflow2, train)
+
+  expect_warning(pred1 <- predict(mod1, test))
+  expect_warning(pred2 <- predict(mod2, test), NA)
+
+  expect_identical(
+    pred1[[".pred"]],
+    c(2, 4.5, NA)
+  )
+
+  expect_identical(
+    pred2[[".pred"]],
+    c(2, 4.5, 2)
+  )
+})
+
+test_that("monitoring: known that parsnip removes blueprint intercept for some models (tidymodels/parsnip#353)", {
   mod <- parsnip::linear_reg()
   mod <- parsnip::set_engine(mod, "lm")
 
   # Pass formula explicitly to keep `lm()` from auto-generating an intercept
   workflow <- workflow()
   workflow <- add_model(workflow, mod, formula = mpg ~ . + 0)
 
-  blueprint_no_intercept <- hardhat::default_formula_blueprint(intercept = FALSE)
-  workflow_no_intercept <- add_formula(workflow, mpg ~ hp + disp, blueprint = blueprint_no_intercept)
-  fit_no_intercept <- fit(workflow_no_intercept, mtcars)
-  prediction_no_intercept <- predict(fit_no_intercept, mtcars)
-
   blueprint_with_intercept <- hardhat::default_formula_blueprint(intercept = TRUE)
   workflow_with_intercept <- add_formula(workflow, mpg ~ hp + disp, blueprint = blueprint_with_intercept)
   fit_with_intercept <- fit(workflow_with_intercept, mtcars)
-  prediction_with_intercept <- predict(fit_with_intercept, mtcars)
-
-  expect_false(fit_no_intercept$pre$mold$blueprint$intercept)
-  expect_true(fit_with_intercept$pre$mold$blueprint$intercept)
 
-  expect_false(identical(prediction_with_intercept, prediction_no_intercept))
+  # `parsnip:::prepare_data()` will remove the intercept, so it won't be
+  # there when the `lm()` `predict()` method is called.
+  expect_error(predict(fit_with_intercept, mtcars))
 })