add back the s3 test, but order cols correctly

Author: dajmcdon

tests/testthat/test-check_enough_train_data.R

@@ -74,7 +74,8 @@ test_that("check_enough_train_data outputs the correct recipe values", {
 
   expect_equal(nrow(p), 2 * n)
   expect_equal(ncol(p), 4L)
-  expect_named(p, c("time_value", "geo_value", "x", "y"))
+  expect_s3_class(p, "epi_df")
+  expect_named(p, c("geo_value", "time_value", "x", "y")) # order in epiprocess::new_epi_df
   expect_equal(
     p$time_value,
     rep(seq(as.Date("2020-01-01"), by = 1, length.out = n), times = 2)

tests/testthat/test-step_training_window.R

@@ -16,8 +16,8 @@ test_that("step_training_window works with default n_recent", {
 
   expect_equal(nrow(p), 100L)
   expect_equal(ncol(p), 4L)
-
-  expect_named(p, c("time_value", "geo_value", "x", "y"))
+  expect_s3_class(p, "epi_df")
+  expect_named(p, c("geo_value", "time_value", "x", "y")) # order in epiprocess::new_epi_df
   expect_equal(
     p$time_value,
     rep(seq(as.Date("2020-02-20"), as.Date("2020-04-09"), by = 1), times = 2)
@@ -33,8 +33,8 @@ test_that("step_training_window works with specified n_recent", {
 
   expect_equal(nrow(p2), 10L)
   expect_equal(ncol(p2), 4L)
-
-  expect_named(p2, c("time_value", "geo_value", "x", "y"))
+  expect_s3_class(p2, "epi_df")
+  expect_named(p2, c("geo_value", "time_value", "x", "y")) # order in epiprocess::new_epi_df
   expect_equal(
     p2$time_value,
     rep(seq(as.Date("2020-04-05"), as.Date("2020-04-09"), by = 1), times = 2)
@@ -53,9 +53,9 @@ test_that("step_training_window does not proceed with specified new_data", {
 
   expect_equal(nrow(p3), 10L)
   expect_equal(ncol(p3), 4L)
-
+  expect_s3_class(p3, "epi_df")
   # cols will be predictors, outcomes, time_value, geo_value
-  expect_named(p3, c("x", "y", "time_value", "geo_value"))
+  expect_named(p3, c("geo_value", "time_value", "x", "y")) # order in epiprocess::new_epi_df
   expect_equal(
     p3$time_value,
     rep(seq(as.Date("2020-01-01"), as.Date("2020-01-10"), by = 1), times = 1)
@@ -83,8 +83,8 @@ test_that("step_training_window works with multiple keys", {
 
   expect_equal(nrow(p4), 12L)
   expect_equal(ncol(p4), 5L)
-
-  expect_named(p4, c("time_value", "geo_value", "additional_key", "x", "y"))
+  expect_s3_class(p4, "epi_df")
+  expect_named(p4, c("geo_value", "time_value", "additional_key", "x", "y"))
   expect_equal(
     p4$time_value,
     rep(c(