updates for no-suggests checks (#160)

* add new GHA

* add skip

* update vignette

* protections for inline code

* many skips

* more test updates

* SKIP

* update docs

* another example

* more examples

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

@@ -0,0 +1,59 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+#
+# NOTE: This workflow only directly installs "hard" dependencies, i.e. Depends,
+# Imports, and LinkingTo dependencies. Notably, Suggests dependencies are never
+# installed, with the exception of testthat, knitr, and rmarkdown. The cache is
+# never used to avoid accidentally restoring a cache containing a suggested
+# dependency.
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+
+name: R-CMD-check-hard.yaml
+
+permissions: read-all
+
+jobs:
+  check-no-suggests:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: ubuntu-latest,   r: 'release'}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          dependencies: '"hard"'
+          cache: false
+          extra-packages: |
+            any::rcmdcheck
+            any::testthat
+            any::knitr
+            any::rmarkdown
+          needs: check
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'

R/cal-estimate-beta.R

@@ -15,9 +15,11 @@
 #' \url{https://www.tidymodels.org/learn/models/calibration/},
 #' [cal_validate_beta()]
 #' @examples
-#' # It will automatically identify the probability columns
-#' # if passed a model fitted with tidymodels
-#' cal_estimate_beta(segment_logistic, Class)
+#' if (rlang::is_installed("betacal")) {
+#'  # It will automatically identify the probability columns
+#'   # if passed a model fitted with tidymodels
+#'   cal_estimate_beta(segment_logistic, Class)
+#' }
 #' @export
 cal_estimate_beta <- function(.data,
                               truth = NULL,

R/cal-validate.R

@@ -297,10 +297,11 @@ cal_validate_isotonic_boot.tune_results <- function(.data,
 #'
 #' library(dplyr)
 #'
-#' segment_logistic %>%
-#'   rsample::vfold_cv() %>%
-#'   cal_validate_beta(Class)
-#'
+#' if (rlang::is_installed("betacal")) {
+#'   segment_logistic %>%
+#'     rsample::vfold_cv() %>%
+#'     cal_validate_beta(Class)
+#' }
 #' @export
 cal_validate_beta <- function(.data,
                               truth = NULL,

R/conformal_infer_cv.R

@@ -33,7 +33,7 @@
 #' Rina Foygel Barber, Emmanuel J. Candès, Aaditya Ramdas, Ryan J. Tibshirani
 #' "Predictive inference with the jackknife+," _The Annals of Statistics_,
 #' 49(1), 486-507, 2021
-#' @examplesIf !probably:::is_cran_check()
+#' @examplesIf !probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip"))
 #' library(workflows)
 #' library(dplyr)
 #' library(parsnip)

R/conformal_infer_quantile.R

@@ -31,7 +31,7 @@
 #' @references
 #' Romano, Yaniv, Evan Patterson, and Emmanuel Candes. "Conformalized quantile
 #' regression." _Advances in neural information processing systems_ 32 (2019).
-#' @examplesIf !probably:::is_cran_check()
+#' @examplesIf !probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip", "quantregForest"))
 #' library(workflows)
 #' library(dplyr)
 #' library(parsnip)

R/conformal_infer_split.R

@@ -28,7 +28,7 @@
 #' @references
 #' Lei, Jing, et al. "Distribution-free predictive inference for regression."
 #' _Journal of the American Statistical Association_ 113.523 (2018): 1094-1111.
-#' @examplesIf !probably:::is_cran_check()
+#' @examplesIf !probably:::is_cran_check() & rlang::is_installed(c("modeldata", "parsnip", "nnet"))
 #' library(workflows)
 #' library(dplyr)
 #' library(parsnip)

tests/testthat/_snaps/cal-estimate.md

@@ -213,7 +213,7 @@
       Type: Regression
       Source class: Data Frame
       Data points: 2,000
-      Unique Predicted Values: 43
+      Unique Predicted Values: 40
       Truth variable: `outcome`
       Estimate variables:
       `.pred` ==> predictions
@@ -229,7 +229,7 @@
       Type: Regression
       Source class: Data Frame
       Data points: 2,000, split in 10 groups
-      Unique Predicted Values: 11
+      Unique Predicted Values: 16
       Truth variable: `outcome`
       Estimate variables:
       `.pred` ==> predictions
@@ -373,7 +373,7 @@
 ---
 
     Code
-      print(mtnl_isotonic)
+      print(mtnl_beta)
     Message
       
       -- Probability Calibration 

tests/testthat/test-cal-apply.R

@@ -8,6 +8,8 @@ test_that("Logistic apply works - data.frame", {
 })
 
 test_that("Logistic apply works - tune_results", {
+  skip_if_not_installed("modeldata")
+
   tct <- testthat_cal_binary()
   tl_logistic <- cal_estimate_logistic(tct, smooth = FALSE)
   tap_logistic <- cal_apply(tct, tl_logistic)
@@ -27,6 +29,8 @@ test_that("Logistic spline apply works", {
 })
 
 test_that("Logistic spline apply works - tune_results", {
+  skip_if_not_installed("modeldata")
+
   tct <- testthat_cal_binary()
   tl_gam <- cal_estimate_logistic(tct)
   tap_gam <- cal_apply(tct, tl_gam)
@@ -90,6 +94,8 @@ test_that("Isotonic apply works - data.frame", {
 })
 
 test_that("Isotonic apply works - tune_results", {
+  skip_if_not_installed("modeldata")
+
   tct <- testthat_cal_binary()
   tl_isotonic <- cal_estimate_isotonic(tct)
   tap_isotonic <- cal_apply(tct, tl_isotonic)
@@ -107,6 +113,8 @@ test_that("Isotonic Bootstrapped apply works - data.frame", {
 })
 
 test_that("Isotonic Bootstrapped apply works - tune_results", {
+  skip_if_not_installed("modeldata")
+
   tct <- testthat_cal_binary()
   tl_boot <- cal_estimate_isotonic_boot(tct)
   tap_boot <- cal_apply(tct, tl_boot)
@@ -119,6 +127,7 @@ test_that("Isotonic Bootstrapped apply works - tune_results", {
 # ------------------------------------------------------------------------------
 
 test_that("Beta apply works - data.frame", {
+  skip_if_not_installed("betacal")
   sl_beta <- cal_estimate_beta(segment_logistic, Class)
   ap_beta <- cal_apply(segment_logistic, sl_beta)
 
@@ -128,6 +137,9 @@ test_that("Beta apply works - data.frame", {
 })
 
 test_that("Beta apply works - tune_results", {
+  skip_if_not_installed("betacal")
+  skip_if_not_installed("modeldata")
+
   tct <- testthat_cal_binary()
   tl_beta <- cal_estimate_beta(tct)
   tap_beta <- cal_apply(tct, tl_beta)
@@ -148,12 +160,16 @@ test_that("Passing the data frame first returns expected abort message", {
 })
 
 test_that("Passing a tune_results without saved predictions causes error", {
+  skip_if_not_installed("betacal")
+  skip_if_not_installed("modeldata")
+
   tct <- testthat_cal_binary()
   tl_beta <- cal_estimate_beta(tct)
   expect_error(cal_apply(tune::ames_grid_search, tl_beta))
 })
 
 test_that("Passing a calibration object as the first arg fails", {
+  skip_if_not_installed("betacal")
   sl_beta <- cal_estimate_beta(segment_logistic, Class)
   expect_error(cal_apply(sl_beta, segment_logistic))
 })