R CMD Check fixes

Author: topepo

DESCRIPTION

@@ -35,7 +35,7 @@ Suggests:
     rmarkdown,
     survival,
     keras,
-    C50,
     xgboost,
-    covr
+    covr,
+    sparklyr
 

R/misc.R

@@ -79,9 +79,14 @@ model_printer <- function(x, ...) {
   }
 }
 
-load_libs <- function(x, quiet) {
-  for (pkg in x$method$libs)
+load_libs <- function(x, quiet, attach = FALSE) {
+  for (pkg in x$method$libs) {
+    if(attach) {
     suppressPackageStartupMessages(requireNamespace(pkg, quietly = quiet))
+    } else {
+      library(pkg, character.only = TRUE)
+    }
+  }
   invisible(x)
 }
 
@@ -216,3 +221,22 @@ new_model_spec <- function(cls, args, eng_args, mode, method, engine) {
   class(out) <- make_classes(cls)
   out
 }
+
+# ------------------------------------------------------------------------------
+
+check_outcome <- function(y, spec) {
+  if (spec$mode == "unknown") {
+    return(invisible(NULL))
+  } else if (spec$mode == "regression") {
+    if (!is.numeric(y))
+      stop("The model outcome should be numeric for regression models.",
+           call. = FALSE)
+  } else if (spec$mode == "classification") {
+    if (!is.factor(y)) {
+      stop("The model outcome should be a factor for regression models.",
+           call. = FALSE)
+    }
+  }
+  invisible(NULL)
+}
+

tests/testthat/test_linear_reg_keras.R

@@ -10,25 +10,25 @@ source("helpers.R")
 
 # ------------------------------------------------------------------------------
 
-basic_mod <- 
-  linear_reg() %>% 
+basic_mod <-
+  linear_reg() %>%
   set_engine("keras", epochs = 50, verbose = 0)
 
-ridge_mod <- 
-  linear_reg(penalty = 0.1) %>% 
+ridge_mod <-
+  linear_reg(penalty = 0.1) %>%
   set_engine("keras", epochs = 50, verbose = 0)
 
 ctrl <- fit_control(verbosity = 0, catch = FALSE)
 
 # ------------------------------------------------------------------------------
 
 test_that('model fitting', {
-  
+  skip_on_cran()
   skip_if_not_installed("keras")
-  
+
   set.seed(257)
   expect_error(
-    fit1 <- 
+    fit1 <-
       fit_xy(
       basic_mod,
       control = ctrl,
@@ -37,10 +37,10 @@ test_that('model fitting', {
     ),
     regexp = NA
   )
-  
+
   set.seed(257)
   expect_error(
-    fit2 <- 
+    fit2 <-
       fit_xy(
         basic_mod,
         control = ctrl,
@@ -50,7 +50,7 @@ test_that('model fitting', {
     regexp = NA
   )
   expect_equal(fit1, fit2)
-  
+
   expect_error(
     fit(
       basic_mod,
@@ -60,9 +60,9 @@ test_that('model fitting', {
     ),
     regexp = NA
   )
-  
+
   expect_error(
-    fit1 <- 
+    fit1 <-
       fit_xy(
         ridge_mod,
         control = ctrl,
@@ -71,7 +71,7 @@ test_that('model fitting', {
       ),
     regexp = NA
   )
-  
+
   expect_error(
     fit(
       ridge_mod,
@@ -81,46 +81,46 @@ test_that('model fitting', {
     ),
     regexp = NA
   )
-  
+
 })
 
 
 test_that('regression prediction', {
-  
+  skip_on_cran()
   skip_if_not_installed("keras")
-  
+
   library(keras)
-  
+
   set.seed(257)
-  lm_fit <- 
+  lm_fit <-
     fit_xy(
       basic_mod,
       control = ctrl,
       x = iris[,2:4],
       y = iris$Sepal.Length
     )
-  
+
   keras_pred <-
     predict(lm_fit$fit, as.matrix(iris[1:3,2:4])) %>%
     as_tibble() %>%
     setNames(".pred")
   parsnip_pred <- predict(lm_fit, iris[1:3,2:4])
   expect_equal(as.data.frame(keras_pred), as.data.frame(parsnip_pred))
-  
+
   set.seed(257)
-  rr_fit <- 
+  rr_fit <-
     fit_xy(
       ridge_mod,
       control = ctrl,
       x = iris[,2:4],
       y = iris$Sepal.Length
     )
-  
+
   keras_pred <-
     predict(rr_fit$fit, as.matrix(iris[1:3,2:4])) %>%
     as_tibble() %>%
     setNames(".pred")
   parsnip_pred <- predict(rr_fit, iris[1:3,2:4])
   expect_equal(as.data.frame(keras_pred), as.data.frame(parsnip_pred))
-  
+
 })

tests/testthat/test_linear_reg_stan.R

@@ -20,8 +20,6 @@ quiet_ctrl <- fit_control(verbosity = 0L, catch = TRUE)
 test_that('stan_glm execution', {
   skip_if_not_installed("rstanarm")
 
-  library(rstanarm)
-
   expect_error(
     res <- fit(
       iris_basic,
@@ -55,7 +53,6 @@ test_that('stan_glm execution', {
 
 test_that('stan prediction', {
   skip_if_not_installed("rstanarm")
-  library(rstanarm)
 
   uni_stan <- stan_glm(Sepal.Length ~ Sepal.Width + Petal.Width + Petal.Length, data = iris, seed = 123)
   uni_pred <- unname(predict(uni_stan, newdata = iris[1:5, ]))
@@ -84,7 +81,6 @@ test_that('stan prediction', {
 
 test_that('stan intervals', {
   skip_if_not_installed("rstanarm")
-  library(rstanarm)
 
   res_xy <- fit_xy(
     linear_reg() %>%