Fix glmnet penalty check (#1262)

* update snap

* changes for #1261

* use cran reticulate

Author: topepo

.github/workflows/R-CMD-check.yaml

@@ -61,8 +61,8 @@ jobs:
           extra-packages: any::rcmdcheck
           needs: check
 
-      - name: Install dev reticulate
-        run: pak::pkg_install('rstudio/reticulate')
+      - name: Install reticulate
+        run: pak::pkg_install('reticulate')
         shell: Rscript {0}
 
       - name: Install Miniconda

NEWS.md

@@ -1,5 +1,9 @@
 # parsnip (development version)
 
+## Bug Fixes
+
+* Fixed a bug that errored when tidying a glmnet object with a penalty value greater than one (#1261).
+
 # parsnip 1.3.0
 
 ## New Features

R/tidy_glmnet.R

@@ -48,7 +48,10 @@ get_glmn_coefs <- function(x, penalty = 0.01) {
   res <- tibble::as_tibble(res) %>% mutate(term = rn, penalty = penalty)
   res <- dplyr::select(res, term, estimate, penalty)
   if (is.list(res$estimate)) {
-    res$estimate <- purrr::map(res$estimate, ~ as_tibble(as.matrix(.x), rownames = "term"))
+    res$estimate <- purrr::map(
+      res$estimate,
+      ~ as_tibble(as.matrix(.x), rownames = "term")
+    )
     res <- tidyr::unnest(res, cols = c(estimate), names_repair = "minimal")
     names(res) <- c("class", "term", "estimate", "penalty")
   }
@@ -61,6 +64,6 @@ tidy_glmnet <- function(x, penalty = NULL, ..., call = caller_env()) {
   if (is.null(penalty)) {
     penalty <- x$spec$args$penalty
   }
-  check_number_decimal(penalty, min = 0, max = 1, allow_null = TRUE, call = call)
+  check_number_decimal(penalty, min = 0, allow_null = TRUE, call = call)
   get_glmn_coefs(x$fit, penalty = penalty)
 }

tests/testthat/_snaps/mlp_keras.md

@@ -1,11 +1,3 @@
-# keras execution, classification
-
-    Code
-      res <- parsnip::fit(hpc_keras, class ~ novar, data = hpc, control = ctrl)
-    Condition
-      Error:
-      ! object 'novar' not found
-
 # all keras activation functions
 
     Code
@@ -14,4 +6,5 @@
         Class ~ A + B, data = modeldata::two_class_dat)
     Condition
       Error in `parsnip::keras_mlp()`:
-      ! `activation` should be one of: elu, exponential, gelu, hard_sigmoid, linear, relu, selu, sigmoid, softmax, softplus, softsign, swish, and tanh, not "invalid".
+      ! `activation` should be one of: elu, exponential, gelu, hardsigmoid, linear, relu, selu, sigmoid, softmax, softplus, softsign, swish, and tanh, not "invalid".
+