test with new paradox (#43)

* test with new paradox

* a required parameter can not have a default.

* custom_check functions should return a string, not stop()

* workflow file

* dev cmd check with paradox master

.github/workflows/dev-cmd-check.yml

@@ -0,0 +1,68 @@
+# Workflow sets WEKA_HOME and installs XMeans
+# r cmd check workflow of the mlr3 ecosystem v0.3.1
+# https://github.com/mlr-org/actions
+on:
+  workflow_dispatch:
+    inputs:
+      debug_enabled:
+        type: boolean
+        description: 'Run the build with tmate debugging enabled'
+        required: false
+        default: false
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - main
+
+name: dev-check
+
+env:
+   WEKA_HOME: /home/runner/work/mlr3cluster
+
+jobs:
+  check-package:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.dev-package }}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: ubuntu-latest,   r: 'release', dev-package: 'mlr-org/paradox'}
+
+    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 }}
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+
+      - uses: mxschmitt/action-tmate@v3
+        if: ${{ github.event_name == 'workflow_dispatch' && inputs.debug_enabled }}
+        with:
+          limit-access-to-actor: true
+
+      - name: Install XMeans
+        run: |
+          RWeka::WPM("refresh-cache")
+          RWeka::WPM("install-package", "XMeans")
+        shell: Rscript {0}
+
+      - name: Install dev versions
+        run: pak::pkg_install(c('${{ matrix.config.dev-package }}'))
+        shell: Rscript {0}
+
+      - uses: r-lib/actions/check-r-package@v2

NEWS.md

@@ -3,6 +3,7 @@
 * Add DBSCAN learner from 'fpc' package
 * Add HDBSCAN learner from 'dbscan' package
 * Add OPTICS learner from 'dbscan' package
+* Compatibility with upcoming 'paradox' release
 
 # mlr3cluster 0.1.8
 

R/LearnerClustCMeans.R

@@ -26,7 +26,7 @@ LearnerClustCMeans = R6Class("LearnerClustCMeans",
     initialize = function() {
       param_set = ps(
         centers = p_uty(
-          tags = c("required", "train"), default = 2L, custom_check = check_centers
+          tags = c("required", "train"), custom_check = check_centers
         ),
         iter.max = p_int(1L, default = 100L, tags = "train"),
         verbose = p_lgl(default = FALSE, tags = "train"),

R/LearnerClustFanny.R

@@ -27,7 +27,7 @@ LearnerClustFanny = R6Class("LearnerClustFanny",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       param_set = ps(
-        k = p_int(1L, default = 2L, tags = c("required", "train")),
+        k = p_int(1L, tags = c("required", "train")),
         memb.exp = p_dbl(1, default = 2, tags = "train"),
         metric = p_fct(default = "euclidean", levels = c("euclidean", "manhattan", "SqEuclidean"), tags = "train"),
         stand = p_lgl(default = FALSE, tags = "train"),

R/LearnerClustFeatureless.R

@@ -18,7 +18,7 @@ LearnerClustFeatureless = R6Class("LearnerClustFeatureless",
     #' @description
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
-      param_set = ps(num_clusters = p_int(1L, default = 1L, tags = c("required", "train", "predict")))
+      param_set = ps(num_clusters = p_int(1L, tags = c("required", "train", "predict")))
       param_set$set_values(num_clusters = 1L)
 
       super$initialize(

R/LearnerClustKKMeans.R

@@ -27,7 +27,7 @@ LearnerClustKKMeans = R6Class("LearnerClustKKMeans",
     initialize = function() {
       param_set = ps(
         centers = p_uty(
-          tags = c("required", "train"), default = 2L, custom_check = check_centers
+          tags = c("required", "train"), custom_check = check_centers
         ),
         kernel = p_fct(
           default = "rbfdot",

R/LearnerClustKMeans.R

@@ -26,7 +26,7 @@ LearnerClustKMeans = R6Class("LearnerClustKMeans",
     initialize = function() {
       param_set = ps(
         centers = p_uty(
-          tags = c("required", "train"), default = 2L, custom_check = check_centers
+          tags = c("required", "train"), custom_check = check_centers
         ),
         iter.max = p_int(1L, default = 10L, tags = "train"),
         algorithm = p_fct(

R/LearnerClustPAM.R

@@ -26,7 +26,7 @@ LearnerClustPAM = R6Class("LearnerClustPAM",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       param_set = ps(
-        k = p_int(1L, default = 2L, tags = c("required", "train")),
+        k = p_int(1L, tags = c("required", "train")),
         metric = p_fct(levels = c("euclidian", "manhattan"), tags = "train"),
         medoids = p_uty(
           default = NULL, tags = "train", custom_check = crate(function(x) check_integerish(x, null.ok = TRUE))