RC 1.1.3

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: embed
 Title: Extra Recipes for Encoding Predictors
-Version: 1.1.2.9000
+Version: 1.1.3.9000
 Authors@R: c(
     person("Emil", "Hvitfeldt", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-0679-1945")),

NAMESPACE

@@ -81,7 +81,6 @@ S3method(tunable,step_woe)
 export(add_woe)
 export(dictionary)
 export(embed_control)
-export(is_tf_available)
 export(required_pkgs)
 export(step_collapse_cart)
 export(step_collapse_stringdist)

NEWS.md

@@ -1,6 +1,10 @@
 # embed (development version)
 
-* `step_collapse_stringdist()` will now return predictors as factors.
+# embed 1.1.3
+
+* `step_collapse_stringdist()` will now return predictors as factors. (#204)
+
+* Fixed regression from 1.1.2 in `step_lencode_glm()` where it couldn't be used on multiple columns.
 
 # embed 1.1.2
 

R/aaa.R

@@ -12,4 +12,13 @@ utils::globalVariables(
   )
 )
 
+# adapted from ps:::is_cran_check()
+is_cran_check <- function() {
+  if (identical(Sys.getenv("NOT_CRAN"), "true")) {
+    FALSE
+  }
+  else {
+    Sys.getenv("_R_CHECK_PACKAGE_NAME_", "") != ""
+  }
+}
 # nocov end

R/embed.R

@@ -122,7 +122,7 @@
 #' "Concatenate Embeddings for Categorical Variables with Keras"
 #' \url{https://flovv.github.io/Embeddings_with_keras_part2/}
 #'
-#' @examplesIf is_tf_available() && rlang::is_installed("modeldata")
+#' @examplesIf !embed:::is_cran_check() && rlang::is_installed("modeldata")
 #' data(grants, package = "modeldata")
 #'
 #' set.seed(1)
@@ -531,12 +531,6 @@ class2ind <- function(x) {
   y
 }
 
-#' Test to see if tensorflow is available
-#'
-#' @return A logical
-#' @examples
-#' is_tf_available()
-#' @export
 is_tf_available <- function() {
   if (!rlang::is_installed("tensorflow")) {
     return(FALSE)

R/feature_hash.R

@@ -50,7 +50,7 @@
 #' Approach for Predictive Models_. CRC/Chapman Hall
 #' \url{https://bookdown.org/max/FES/encoding-predictors-with-many-categories.html}
 #' @seealso [recipes::step_dummy()], [recipes::step_zv()]
-#' @examplesIf is_tf_available() && rlang::is_installed("modeldata")
+#' @examplesIf !embed:::is_cran_check() && rlang::is_installed("modeldata")
 #' data(grants, package = "modeldata")
 #' rec <-
 #'   recipe(class ~ sponsor_code, data = grants_other) %>%

R/lencode_glm.R

@@ -203,7 +203,7 @@ bake.step_lencode_glm <- function(object, new_data, ...) {
   for (col_name in col_names) {
     new_data[[col_name]] <- map_glm_coef(
       dat = new_data[, col_name], # map_glm_coef() expects a tibble
-      mapping = object$mapping[[col_names]]
+      mapping = object$mapping[[col_name]]
     )
   }
 

_pkgdown.yml

@@ -38,7 +38,6 @@ reference:
 - title: miscellaneous
   contents:
     - dictionary
-    - is_tf_available
 - title: Tidy Methods
   contents:
     - tidy.recipe

revdep/README.md

@@ -1,38 +1,37 @@
 # Platform
 
-|field    |value                                                                                      |
-|:--------|:------------------------------------------------------------------------------------------|
-|version  |R version 4.3.0 (2023-04-21)                                                               |
-|os       |macOS Ventura 13.5                                                                         |
-|system   |aarch64, darwin20                                                                          |
-|ui       |RStudio                                                                                    |
-|language |(EN)                                                                                       |
-|collate  |en_US.UTF-8                                                                                |
-|ctype    |en_US.UTF-8                                                                                |
-|tz       |America/Los_Angeles                                                                        |
-|date     |2023-08-14                                                                                 |
-|rstudio  |2023.09.0-daily+310 Desert Sunflower (desktop)                                             |
-|pandoc   |3.1.1 @ /Applications/RStudio.app/Contents/Resources/app/quarto/bin/tools/ (via rmarkdown) |
+|field    |value                                                        |
+|:--------|:------------------------------------------------------------|
+|version  |R version 4.3.1 (2023-06-16)                                 |
+|os       |macOS Ventura 13.6                                           |
+|system   |aarch64, darwin20                                            |
+|ui       |X11                                                          |
+|language |(EN)                                                         |
+|collate  |en_US.UTF-8                                                  |
+|ctype    |en_US.UTF-8                                                  |
+|tz       |America/Los_Angeles                                          |
+|date     |2023-10-17                                                   |
+|pandoc   |3.1.3 @ /Users/emilhvitfeldt/miniforge3/bin/ (via rmarkdown) |
 
 # Dependencies
 
 |package      |old        |new        |Δ  |
 |:------------|:----------|:----------|:--|
-|embed        |1.1.1      |1.1.1.9000 |*  |
+|embed        |1.1.2      |1.1.2.9000 |*  |
 |backports    |1.4.1      |1.4.1      |   |
 |base64enc    |0.1-3      |0.1-3      |   |
 |BH           |1.81.0-1   |1.81.0-1   |   |
 |cli          |3.6.1      |3.6.1      |   |
 |clock        |0.7.0      |0.7.0      |   |
-|config       |0.3.1      |0.3.1      |   |
+|config       |0.3.2      |0.3.2      |   |
 |cpp11        |0.4.6      |0.4.6      |   |
 |data.table   |1.14.8     |1.14.8     |   |
 |diagram      |1.6.5      |1.6.5      |   |
 |digest       |0.6.33     |0.6.33     |   |
-|dplyr        |1.1.2      |1.1.2      |   |
-|dqrng        |0.3.0      |0.3.0      |   |
+|dplyr        |1.1.3      |1.1.3      |   |
+|dqrng        |0.3.1      |0.3.1      |   |
 |ellipsis     |0.3.2      |0.3.2      |   |
-|fansi        |1.0.4      |1.0.4      |   |
+|fansi        |1.0.5      |1.0.5      |   |
 |FNN          |1.1.3.2    |1.1.3.2    |   |
 |furrr        |0.3.1      |0.3.1      |   |
 |future       |1.33.0     |1.33.0     |   |
@@ -46,19 +45,19 @@
 |ipred        |0.9-14     |0.9-14     |   |
 |irlba        |2.3.5.1    |2.3.5.1    |   |
 |jsonlite     |1.8.7      |1.8.7      |   |
-|keras        |2.11.1     |2.11.1     |   |
+|keras        |2.13.0     |2.13.0     |   |
 |lava         |1.7.2.1    |1.7.2.1    |   |
 |lifecycle    |1.0.3      |1.0.3      |   |
 |listenv      |0.9.0      |0.9.0      |   |
-|lubridate    |1.9.2      |1.9.2      |   |
+|lubridate    |1.9.3      |1.9.3      |   |
 |magrittr     |2.0.3      |2.0.3      |   |
 |numDeriv     |2016.8-1.1 |2016.8-1.1 |   |
 |parallelly   |1.36.0     |1.36.0     |   |
 |pillar       |1.9.0      |1.9.0      |   |
 |pkgconfig    |2.0.3      |2.0.3      |   |
 |png          |0.1-8      |0.1-8      |   |
 |processx     |3.8.2      |3.8.2      |   |
-|prodlim      |2023.03.31 |2023.03.31 |   |
+|prodlim      |2023.08.28 |2023.08.28 |   |
 |progressr    |0.14.0     |0.14.0     |   |
 |ps           |1.7.5      |1.7.5      |   |
 |purrr        |1.0.2      |1.0.2      |   |
@@ -68,19 +67,19 @@
 |RcppAnnoy    |0.0.21     |0.0.21     |   |
 |RcppProgress |0.4.2      |0.4.2      |   |
 |RcppTOML     |0.2.2      |0.2.2      |   |
-|recipes      |1.0.7      |1.0.7      |   |
-|reticulate   |1.31       |1.31       |   |
+|recipes      |1.0.8      |1.0.8      |   |
+|reticulate   |1.34.0     |1.34.0     |   |
 |rlang        |1.1.1      |1.1.1      |   |
 |rprojroot    |2.0.3      |2.0.3      |   |
-|rsample      |1.1.1      |1.1.1      |   |
+|rsample      |1.2.0      |1.2.0      |   |
 |rstudioapi   |0.15.0     |0.15.0     |   |
 |shape        |1.4.6      |1.4.6      |   |
 |sitmo        |2.0.2      |2.0.2      |   |
-|slider       |0.3.0      |0.3.0      |   |
+|slider       |0.3.1      |0.3.1      |   |
 |SQUAREM      |2021.1     |2021.1     |   |
 |stringi      |1.7.12     |1.7.12     |   |
 |stringr      |1.5.0      |1.5.0      |   |
-|tensorflow   |2.11.0     |2.11.0     |   |
+|tensorflow   |2.14.0     |2.14.0     |   |
 |tfautograph  |0.3.2      |0.3.2      |   |
 |tfruns       |1.5.1      |1.5.1      |   |
 |tibble       |3.2.1      |3.2.1      |   |
@@ -91,10 +90,10 @@
 |tzdb         |0.4.0      |0.4.0      |   |
 |utf8         |1.2.3      |1.2.3      |   |
 |uwot         |0.1.16     |0.1.16     |   |
-|vctrs        |0.6.3      |0.6.3      |   |
+|vctrs        |0.6.4      |0.6.4      |   |
 |warp         |0.2.0      |0.2.0      |   |
 |whisker      |0.4.1      |0.4.1      |   |
-|withr        |2.5.0      |2.5.0      |   |
+|withr        |2.5.1      |2.5.1      |   |
 |yaml         |2.3.7      |2.3.7      |   |
 |zeallot      |0.1.0      |0.1.0      |   |
 

tests/testthat/test-embed.R

@@ -10,7 +10,7 @@ withr::local_envvar(TF_CPP_MIN_LOG_LEVEL = "2")
 
 test_that("factor encoded predictor", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   class_test <- recipe(x2 ~ ., data = ex_dat) %>%
     step_embed(x3, outcome = vars(x2), options = embed_control(verbose = 0), id = "id") %>%
@@ -80,7 +80,7 @@ test_that("factor encoded predictor", {
 
 test_that("character encoded predictor", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   class_test <- recipe(x2 ~ ., data = ex_dat_ch) %>%
     step_embed(x3, outcome = vars(x2), options = embed_control(verbose = 0)) %>%
@@ -148,7 +148,7 @@ test_that("character encoded predictor", {
 
 test_that("factor encoded predictor", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   class_test <- recipe(x1 ~ ., data = ex_dat) %>%
     step_embed(x3, outcome = vars(x1), options = embed_control(verbose = 0)) %>%
@@ -217,7 +217,7 @@ test_that("factor encoded predictor", {
 
 test_that("character encoded predictor", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   class_test <- recipe(x1 ~ ., data = ex_dat_ch) %>%
     step_embed(x3, outcome = vars(x1), num_terms = 5, options = embed_control(verbose = 0)) %>%
@@ -285,7 +285,7 @@ test_that("character encoded predictor", {
 
 test_that("bad args", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   three_class <- iris
   three_class$fac <- rep(letters[1:3], 50)
@@ -301,7 +301,7 @@ test_that("bad args", {
 
 test_that("check_name() is used", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   dat <- ex_dat
   dat$x3_embed_1 <- dat$x3
@@ -334,7 +334,7 @@ test_that("tunable", {
 
 test_that("bake method errors when needed non-standard role columns are missing", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
   rec <- recipe(x2 ~ ., data = ex_dat) %>%
     step_embed(
       x3,
@@ -355,7 +355,7 @@ test_that("bake method errors when needed non-standard role columns are missing"
 
 test_that("empty printing", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   rec <- recipe(mpg ~ ., mtcars)
   rec <- step_embed(rec, outcome = vars(mpg))
@@ -400,7 +400,7 @@ test_that("empty selection tidy method works", {
 
 test_that("keep_original_cols works", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   new_names <- c("x2", "x3_embed_1", "x3_embed_2")
 
@@ -431,7 +431,7 @@ test_that("keep_original_cols works", {
 
 test_that("keep_original_cols - can prep recipes with it missing", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   rec <- recipe(x2 ~ x3, data = ex_dat) %>%
     step_embed(x3, outcome = vars(x2), options = embed_control(verbose = 0))
@@ -450,7 +450,7 @@ test_that("keep_original_cols - can prep recipes with it missing", {
 
 test_that("printing", {
   skip_on_cran()
-  skip_if(!is_tf_available())
+  skip_if(!embed:::is_tf_available())
 
   rec <- recipe(x2 ~ ., data = ex_dat_ch) %>%
     step_embed(x3, outcome = vars(x2))

tests/testthat/test-helpers.R

@@ -2,4 +2,4 @@ library(embed)
 library(dplyr)
 library(testthat)
 
-is_tf_available()
+embed:::is_tf_available()