butcher version 0.3.4 (#274)

* Release candidate 0.3.4

* Update custom model to use `new_model_spec()`

* Add `set_encoding()`

* Update DESCRIPTION

* Increment version number to 0.3.4

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: butcher
 Title: Model Butcher
-Version: 0.3.3.9000
+Version: 0.3.4
 Authors@R: c(
     person("Joyce", "Cahoon", , "joyceyu48@gmail.com", role = "aut",
            comment = c(ORCID = "0000-0001-7217-4702")),
@@ -76,9 +76,9 @@ Suggests:
     xrf
 VignetteBuilder: 
     knitr
-Config/Needs/check:bioc::mixOmics
-Config/Needs/website:tidyverse/tidytemplate
+Config/Needs/check: bioc::mixOmics
+Config/Needs/website: tidyverse/tidytemplate
 Config/testthat/edition: 3
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(as.character,dev_topic)
 S3method(axe_call,C5.0)
 S3method(axe_call,KMeansCluster)
 S3method(axe_call,NaiveBayes)

NEWS.md

@@ -1,4 +1,6 @@
-# butcher (development version)
+# butcher 0.3.4
+
+* Submit to CRAN for new HTML reference manuals.
 
 # butcher 0.3.3
 

R/docs.R

@@ -132,6 +132,8 @@ locate_help_doc <- function(x, package) {
   }
 }
 
+#' @export
+#' @keywords internal
 as.character.dev_topic <- function(x, ...) {
   sub("[.]Rd$", "", x$path)
 }

README.Rmd

@@ -120,7 +120,7 @@ Check out the `vignette("available-axe-methods")` to see butcher's current cover
 
 This project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). By contributing to this project, you agree to abide by its terms.
 
-- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
+- For questions and discussions about tidymodels packages, modeling, and machine learning, please [post on RStudio Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).
 
 - If you think you have encountered a bug, please [submit an issue](https://github.com/tidymodels/butcher/issues).
 

README.md

@@ -149,11 +149,11 @@ weigh(small_lm)
 To make the most of your memory available, this package provides five S3
 generics for you to remove parts of a model object:
 
--   `axe_call()`: To remove the call object.
--   `axe_ctrl()`: To remove controls associated with training.
--   `axe_data()`: To remove the original training data.
--   `axe_env()`: To remove environments.
--   `axe_fitted()`: To remove fitted values.
+- `axe_call()`: To remove the call object.
+- `axe_ctrl()`: To remove controls associated with training.
+- `axe_data()`: To remove the original training data.
+- `axe_env()`: To remove environments.
+- `axe_fitted()`: To remove fitted values.
 
 When you run `butcher()`, you execute all of these axing functions at
 once. Any kind of axing on the object will append a butchered class to
@@ -183,18 +183,18 @@ This project is released with a [Contributor Code of
 Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html).
 By contributing to this project, you agree to abide by its terms.
 
--   For questions and discussions about tidymodels packages, modeling,
-    and machine learning, please [post on RStudio
-    Community](https://community.rstudio.com/new-topic?category_id=15&tags=tidymodels,question).
+- For questions and discussions about tidymodels packages, modeling, and
+  machine learning, please [post on RStudio
+  Community](https://forum.posit.co/new-topic?category_id=15&tags=tidymodels,question).
 
--   If you think you have encountered a bug, please [submit an
-    issue](https://github.com/tidymodels/butcher/issues).
+- If you think you have encountered a bug, please [submit an
+  issue](https://github.com/tidymodels/butcher/issues).
 
--   Either way, learn how to create and share a
-    [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html)
-    (a minimal, reproducible example), to clearly communicate about your
-    code.
+- Either way, learn how to create and share a
+  [reprex](https://reprex.tidyverse.org/articles/articles/learn-reprex.html)
+  (a minimal, reproducible example), to clearly communicate about your
+  code.
 
--   Check out further details on [contributing guidelines for tidymodels
-    packages](https://www.tidymodels.org/contribute/) and [how to get
-    help](https://www.tidymodels.org/help/).
+- Check out further details on [contributing guidelines for tidymodels
+  packages](https://www.tidymodels.org/contribute/) and [how to get
+  help](https://www.tidymodels.org/help/).

revdep/README.md

@@ -1,24 +1,2 @@
-# Platform
-
-|field    |value                                    |
-|:--------|:----------------------------------------|
-|version  |R version 4.2.2 (2022-10-31)             |
-|os       |macOS Ventura 13.2.1                     |
-|system   |aarch64, darwin20                        |
-|ui       |RStudio                                  |
-|language |(EN)                                     |
-|collate  |en_US.UTF-8                              |
-|ctype    |en_US.UTF-8                              |
-|tz       |America/Denver                           |
-|date     |2023-03-07                               |
-|rstudio  |2022.12.0+353 Elsbeth Geranium (desktop) |
-|pandoc   |2.17.1.1 @ /usr/local/bin/pandoc         |
-
-# Dependencies
-
-|package |old   |new   |Δ  |
-|:-------|:-----|:-----|:--|
-|butcher |0.3.1 |0.3.2 |*  |
-
 # Revdeps
 

revdep/cran.md

@@ -1,6 +1,6 @@
 ## revdepcheck results
 
-We checked 6 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
+We checked 8 reverse dependencies, comparing R CMD check results across CRAN and dev versions of this package.
 
  * We saw 0 new problems
  * We failed to check 0 packages

tests/testthat/test-mda.R

@@ -46,13 +46,14 @@ test_that("mda + custom parsnip model + predict() works", {
       stop("`mode` should be 'classification'", call. = FALSE)
     }
     args <- list(sub_classes = rlang::enquo(sub_classes))
-    out <- list(args = args,
-                eng_args = NULL,
-                mode = mode,
-                method = NULL,
-                engine = NULL)
-    class(out) <- make_classes("mixture_da")
-    out
+    new_model_spec(
+      "mixture_da",
+      args = args,
+      eng_args = NULL,
+      mode = mode,
+      method = NULL,
+      engine = NULL
+    )
   }
   set_fit(
     model = "mixture_da",
@@ -65,6 +66,17 @@ test_that("mda + custom parsnip model + predict() works", {
       defaults = list()
     )
   )
+  set_encoding(
+    model = "mixture_da",
+    eng = "mda",
+    mode = "classification",
+    options = list(
+      predictor_indicators = "traditional",
+      compute_intercept = TRUE,
+      remove_intercept = TRUE,
+      allow_sparse_x = FALSE
+    )
+  )
   mda_fit <- mixture_da(sub_classes = 2) %>%
     set_engine("mda") %>%
     fit(Species ~ ., data = iris)