check with new paradox

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

@@ -25,6 +25,7 @@ jobs:
       matrix:
         config:
           - {os: ubuntu-latest, r: 'release', dev-package: 'mlr-org/mlr3'}
+          - {os: ubuntu-latest, r: 'release', dev-package: "mlr-org/mlr3viz', 'mlr-org/mlr3pipelines', 'mlr-org/paradox"}
 
     steps:
       - uses: actions/checkout@v4
@@ -41,7 +42,7 @@ jobs:
           needs: check
 
       - name: Install dev versions
-        run: pak::pkg_install('${{ matrix.config.dev-package }}')
+        run: pak::pkg_install(c('${{ matrix.config.dev-package }}'))
         shell: Rscript {0}
 
       - uses: r-lib/actions/check-r-package@v2

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mlr3proba
 Title: Probabilistic Supervised Learning for 'mlr3'
-Version: 0.6.0
+Version: 0.6.0-9000
 Authors@R:
     c(person(given = "Raphael",
              family = "Sonabend",

NEWS.md

@@ -1,3 +1,7 @@
+# mlr3proba 0.6.0-9000
+
+* Compatibility with upcoming 'paradox' release.
+
 # mlr3proba 0.6.0
 
 * Optimized `surv.logloss` and `calib_alpha` measures (bypassing `distr6`)

R/PipeOpBreslow.R

@@ -76,19 +76,21 @@ PipeOpBreslow = R6Class("PipeOpBreslow",
 
       # id of the PipeOp is the id of the learner
       private$.learner = as_learner(learner, clone = TRUE)
-      private$.learner$param_set$set_id = ""
       id = id %??% private$.learner$id
 
       # define `breslow.overwrite` parameter
       private$.breslow_ps = ps(
-        overwrite = p_lgl(default = FALSE, tags = c("predict", "required"))
+        overwrite = p_lgl(tags = c("predict", "required"))
       )
       private$.breslow_ps$values = list(overwrite = FALSE)
-      private$.breslow_ps$set_id = "breslow"
-
+      if ("set_id" %in% names(private$.learner$param_set)) {
+        # old paradox
+        private$.learner$param_set$set_id = ""
+        private$.breslow_ps$set_id = "breslow"
+      }
       super$initialize(
         id = id,
-        param_set = alist(private$.breslow_ps, private$.learner$param_set),
+        param_set = alist(breslow = private$.breslow_ps, private$.learner$param_set),
         param_vals = param_vals,
         input = data.table(name = "input", train = "TaskSurv", predict = "TaskSurv"),
         output = data.table(name = "output", train = "NULL", predict = "PredictionSurv"),

R/TaskGeneratorSimsurv.R

@@ -32,9 +32,9 @@ TaskGeneratorSimsurv = R6Class("TaskGeneratorSimsurv",
     initialize = function() {
       ps = ps(
         dist = p_fct(levels = c("weibull", "exponential", "gompertz"), default = "weibull"),
-        lambdas = p_dbl(lower = 0, default = 0.1, tags = "required"),
-        gammas = p_dbl(lower = 0, default = 1.5, tags = "required"),
-        maxt = p_dbl(lower = 0, default = 5, tags = "required")
+        lambdas = p_dbl(lower = 0, tags = "required"),
+        gammas = p_dbl(lower = 0, tags = "required"),
+        maxt = p_dbl(lower = 0, tags = "required")
       )
       ps$values = list(lambdas = 0.1, gammas = 1.5, maxt = 5)