release: 0.2.1 (#38)

Author: be-marc

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: mlr3batchmark
 Title: Batch Experiments for 'mlr3'
-Version: 0.2.0.9000
+Version: 0.2.1
 Authors@R: c(
     person("Marc", "Becker", , "[email protected]", role = c("cre", "aut"),
            comment = c(ORCID = "0000-0002-8115-0400")),

NEWS.md

@@ -1,4 +1,4 @@
-# mlr3batchmark (development version)
+# mlr3batchmark 0.2.1
 
 * compatibility: mlr3 1.0.0
 

README.Rmd

@@ -8,7 +8,7 @@ output: github_document
 [![StackOverflow](https://img.shields.io/badge/stackoverflow-mlr3-orange.svg)](https://stackoverflow.com/questions/tagged/mlr3)
 [![Mattermost](https://img.shields.io/badge/chat-mattermost-orange.svg)](https://lmmisld-lmu-stats-slds.srv.mwn.de/mlr_invite/)
 
-A connector between [mlr3](https://github.com/mlr-org/mlr3) and [batchtools](https://mllg.github.io/batchtools/).
+A connector between [mlr3](https://github.com/mlr-org/mlr3) and [batchtools](http://batchtools.mlr-org.com/).
 This allows to run large-scale benchmark experiments on scheduled high-performance computing clusters.
 
 The package comes with two core functions for switching between `mlr3` and `batchtools` to perform a benchmark:

README.md

@@ -8,22 +8,22 @@ status](https://www.r-pkg.org/badges/version/mlr3batchmark)](https://CRAN.R-proj
 [![Mattermost](https://img.shields.io/badge/chat-mattermost-orange.svg)](https://lmmisld-lmu-stats-slds.srv.mwn.de/mlr_invite/)
 
 A connector between [mlr3](https://github.com/mlr-org/mlr3) and
-[batchtools](https://mllg.github.io/batchtools/). This allows to run
+[batchtools](http://batchtools.mlr-org.com/). This allows to run
 large-scale benchmark experiments on scheduled high-performance
 computing clusters.
 
 The package comes with two core functions for switching between `mlr3`
 and `batchtools` to perform a benchmark:
 
--   After creating a `design` object (as required for `mlr3`’s
-    `benchmark()` function), instead of `benchmark()` call `batchmark()`
-    which populates an `ExperimentRegistry` for the computational jobs
-    of the benchmark. You are now in the world of `batchtools` where you
-    can selectively submit jobs with different resources, monitor the
-    progress or resubmit as needed.
--   After the computations are finished, collect the results with
-    `reduceResultsBatchmark()` to return to `mlr3`. The resulting object
-    is a regular `BenchmarkResult`.
+- After creating a `design` object (as required for `mlr3`’s
+  `benchmark()` function), instead of `benchmark()` call `batchmark()`
+  which populates an `ExperimentRegistry` for the computational jobs of
+  the benchmark. You are now in the world of `batchtools` where you can
+  selectively submit jobs with different resources, monitor the progress
+  or resubmit as needed.
+- After the computations are finished, collect the results with
+  `reduceResultsBatchmark()` to return to `mlr3`. The resulting object
+  is a regular `BenchmarkResult`.
 
 ## Example
 
@@ -46,61 +46,86 @@ reg = makeExperimentRegistry(NA)
 
     ## No readable configuration file found
 
-    ## Created registry in '/tmp/Rtmp8DlMZQ/registry704553adf7a88' using cluster functions 'Interactive'
+    ## Created registry in '/tmp/RtmpbcuMc4/registry27b8961304f5da' using cluster functions 'Interactive'
 
 ``` r
 ids = batchmark(design, reg = reg)
 ```
 
     ## Adding algorithm 'run_learner'
 
-    ## Adding problem 'b39ef23a66b1f1ee'
+    ## Adding problem 'abc694dd29a7a8ce'
 
-    ## Exporting new objects: '5ec484de3f93431b' ...
+    ## Exporting new objects: '2da7eeb80b94fc3b' ...
 
-    ## Exporting new objects: '7c35d835f3dfae37' ...
+    ## Exporting new objects: 'c905990877a775af' ...
 
-    ## Exporting new objects: '70dd22724e5c724d' ...
+    ## Exporting new objects: '3acc41a799a260d8' ...
 
-    ## Adding 6 experiments ('b39ef23a66b1f1ee'[1] x 'run_learner'[2] x repls[3]) ...
+    ## Exporting new objects: 'ecf8ee265ec56766' ...
 
-    ## Adding problem '76c4fc7a533d41b7'
+    ## Overwriting previously exported object: 'ecf8ee265ec56766'
 
-    ## Exporting new objects: 'b209de197d6cbe75' ...
+    ## Adding 6 experiments ('abc694dd29a7a8ce'[1] x 'run_learner'[2] x repls[3]) ...
 
-    ## Adding 6 experiments ('76c4fc7a533d41b7'[1] x 'run_learner'[2] x repls[3]) ...
+    ## Adding problem 'f9791e97f9813150'
+
+    ## Exporting new objects: '62ac3bb85aabfbaf' ...
+
+    ## Adding 6 experiments ('f9791e97f9813150'[1] x 'run_learner'[2] x repls[3]) ...
 
 ``` r
 submitJobs()
 ```
 
     ## Submitting 12 jobs in 12 chunks using cluster functions 'Interactive' ...
 
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+    ## Error in workhorse(iteration = job$repl, task = data, learner = learner,  : 
+    ##   unused argument (lgr_threshold = lgr::get_logger("mlr3")$threshold)
+
 ``` r
 getStatus()
 ```
 
-    ## Status for 12 jobs at 2023-11-13 19:32:20:
+    ## Status for 12 jobs at 2025-05-26 09:23:22:
     ##   Submitted    : 12 (100.0%)
     ##   -- Queued    :  0 (  0.0%)
     ##   -- Started   : 12 (100.0%)
     ##   ---- Running :  0 (  0.0%)
-    ##   ---- Done    : 12 (100.0%)
-    ##   ---- Error   :  0 (  0.0%)
+    ##   ---- Done    :  0 (  0.0%)
+    ##   ---- Error   : 12 (100.0%)
     ##   ---- Expired :  0 (  0.0%)
 
 ``` r
 reduceResultsBatchmark()
 ```
 
-    ## <BenchmarkResult> of 12 rows with 4 resampling runs
-    ##  nr task_id          learner_id resampling_id iters warnings errors
-    ##   1    iris classif.featureless            cv     3        0      0
-    ##   2    iris       classif.rpart            cv     3        0      0
-    ##   3   sonar classif.featureless            cv     3        0      0
-    ##   4   sonar       classif.rpart            cv     3        0      0
+    ## 
+    ## ── <BenchmarkResult> of 0 rows with 0 resampling run ───────────────────────────
 
 ## Resources
 
--   The *Large-Scale Benchmarking* chapter of the [mlr3
-    book](https://mlr3book.mlr-org.com/)
+- The *Large-Scale Benchmarking* chapter of the [mlr3
+  book](https://mlr3book.mlr-org.com/)