add mlr3 based imputation function

.github/workflows/test-coverage.yaml

@@ -4,9 +4,10 @@ on:
   push:
     branches: [main, master]
   pull_request:
-    branches: [main, master]
 
-name: test-coverage
+name: test-coverage.yaml
+
+permissions: read-all
 
 jobs:
   test-coverage:
@@ -15,36 +16,47 @@ jobs:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-r@v2
         with:
           use-public-rspm: true
 
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          extra-packages: any::covr
+          extra-packages: any::covr, any::xml2
           needs: coverage
 
       - name: Test coverage
         run: |
-          covr::codecov(
+          cov <- covr::package_coverage(
             quiet = FALSE,
             clean = FALSE,
             install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
           )
+          print(cov)
+          covr::to_cobertura(cov)
         shell: Rscript {0}
 
+      - uses: codecov/codecov-action@v5
+        with:
+          # Fail if error if not on PR, or if on PR and token is given
+          fail_ci_if_error: ${{ github.event_name != 'pull_request' || secrets.CODECOV_TOKEN }}
+          files: ./cobertura.xml
+          plugins: noop
+          disable_search: true
+          token: ${{ secrets.CODECOV_TOKEN }}
+
       - name: Show testthat output
         if: always()
         run: |
           ## --------------------------------------------------------------------
-          find ${{ runner.temp }}/package -name 'testthat.Rout*' -exec cat '{}' \; || true
+          find '${{ runner.temp }}/package' -name 'testthat.Rout*' -exec cat '{}' \; || true
         shell: bash
 
       - name: Upload test results
         if: failure()
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: coverage-test-failures
-          path: ${{ runner.temp }}/package
+          path: ${{ runner.temp }}/package

DESCRIPTION

@@ -1,13 +1,17 @@
 Package: VIM
-Version: 6.2.4
+Version: 7.0.0
 Title: Visualization and Imputation of Missing Values
 Authors@R: c(
   person("Matthias", "Templ", email = "[email protected]", role = c("aut","cre")),
   person("Alexander", "Kowarik", email = "[email protected]", role = c("aut"), comment=c(ORCID="0000-0001-8598-4130")),
   person("Andreas", "Alfons", role = c("aut")),
+  person("Johannes", "Gussenbauer", role = c("aut")),
+  person("Nina", "Niederhametner", role = c("aut")),
+  person("Eileen", "Vattheuer", role = c("aut")),
   person("Gregor", "de Cillia", email = "[email protected]", role = c("aut")),
   person("Bernd", "Prantner", role = c("ctb")),
-  person("Wolfgang", "Rannetbauer", role = c("aut")))
+  person("Wolfgang", "Rannetbauer", role = c("aut"))
+  )
 Depends:
     R (>= 4.1.0),colorspace,grid
 Imports:
@@ -27,15 +31,23 @@ Imports:
     ranger,
     MASS,
     xgboost,
-    data.table(>= 1.9.4)
+    data.table(>= 1.9.4),
+    mlr3,
+    mlr3pipelines,
+    R6,
+    paradox,
+    mlr3tuning,
+    mlr3learners,
+    future
 Suggests: 
     dplyr,
     tinytest,
     knitr,
     rmarkdown,
     reactable,
     covr,
-    withr
+    withr,
+    glmnet
 Description: New tools for the visualization of missing and/or imputed values
     are introduced, which can be used for exploring the data and the structure of
     the missing and/or imputed values. Depending on this structure of the missing
@@ -51,7 +63,7 @@ License: GPL (>= 2)
 URL: https://github.com/statistikat/VIM
 Repository: CRAN
 LinkingTo: Rcpp
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.3
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
 VignetteBuilder: knitr

NAMESPACE

@@ -50,6 +50,7 @@ export(scattMiss)
 export(scattmatrixMiss)
 export(spineMiss)
 export(tableMiss)
+export(vimpute)
 export(xgboostImpute)
 import(Rcpp)
 import(colorspace)
@@ -92,11 +93,36 @@ importFrom(graphics,text)
 importFrom(graphics,title)
 importFrom(laeken,weightedMean)
 importFrom(laeken,weightedMedian)
+importFrom(mlr3,LearnerClassif)
+importFrom(mlr3,LearnerRegr)
+importFrom(mlr3,PredictionClassif)
+importFrom(mlr3,PredictionRegr)
+importFrom(mlr3,TaskClassif)
+importFrom(mlr3,TaskRegr)
+importFrom(mlr3,as_task_classif)
+importFrom(mlr3,as_task_regr)
+importFrom(mlr3,lrn)
+importFrom(mlr3,msr)
+importFrom(mlr3,resample)
+importFrom(mlr3,rsmp)
+importFrom(mlr3learners,LearnerRegrCVGlmnet)
+importFrom(mlr3pipelines,"%>>%")
+importFrom(mlr3pipelines,GraphLearner)
+importFrom(mlr3pipelines,PipeOpModelMatrix)
+importFrom(mlr3pipelines,po)
+importFrom(mlr3tuning,TuningInstanceBatchSingleCrit)
+importFrom(mlr3tuning,tnr)
+importFrom(mlr3tuning,trm)
+importFrom(paradox,p_dbl)
+importFrom(paradox,p_fct)
+importFrom(paradox,p_int)
+importFrom(paradox,ps)
 importFrom(ranger,importance)
 importFrom(ranger,ranger)
 importFrom(utils,capture.output)
 importFrom(utils,flush.console)
 importFrom(utils,head)
+importFrom(utils,modifyList)
 importFrom(vcd,labeling_border)
 importFrom(vcd,mosaic)
 useDynLib(VIM)

NEWS.md

@@ -1,3 +1,6 @@
+# VIM 7.0.0
+ - new function vimpute that uses mlr3 backend for a flexible imputation method.
+
 # VIM 6.x.x
  - fix infinite loop in matchImpute in case all observations of a variable are missing
  - remove parameter metric from kNN because it was not used

R/VIM-package.R

@@ -17,12 +17,17 @@
 #' @importFrom laeken weightedMean
 #' @importFrom graphics Axis abline axTicks axis barplot box hist boxplot layout lcm lines locator par plot.new plot.window points
 #' @importFrom graphics polygon rect strheight strwidth text title
-#' @importFrom utils capture.output flush.console head
+#' @importFrom utils capture.output flush.console head modifyList
 #' @importFrom ranger ranger importance
 #' @importFrom MASS stepAIC lqs polr rlm
+#' @importFrom mlr3 LearnerRegr PredictionRegr LearnerClassif PredictionClassif lrn TaskRegr TaskClassif as_task_regr as_task_classif rsmp msr resample
+#' @importFrom mlr3pipelines PipeOpModelMatrix %>>% GraphLearner po
+#' @importFrom paradox ps p_fct p_dbl p_int
+#' @importFrom mlr3tuning tnr trm TuningInstanceBatchSingleCrit
+#' @importFrom mlr3learners LearnerRegrCVGlmnet
 #' @useDynLib VIM
 NULL
-
+utils::globalVariables(c("self", "super"))
 #' Animals_na
 #'
 #' @description Average log brain and log body weights for 28 Species
@@ -596,21 +601,16 @@ NULL
 #' handling of the plot methods.  In addition, `VIM` can be used for data
 #' from essentially any field.
 #'
-#' @name VIM-package
-#' @aliases VIM-package VIM
-#' @docType package
-#' @author Matthias Templ, Andreas Alfons, Alexander Kowarik, Bernd Prantner
-#'
-#' Maintainer: Matthias Templ <templ@@tuwien.ac.at>
+
 #' @references M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete
 #' data using visualization tools.  *Journal of Advances in Data Analysis
 #' and Classification*, Online first. DOI: 10.1007/s11634-011-0102-y.
 #'
 #' M. Templ, A. Kowarik, P. Filzmoser (2011) Iterative stepwise regression
 #' imputation using standard and robust methods.  *Journal of
 #' Computational Statistics and Data Analysis*, Vol. 55, pp. 2793-2806.
-#' @keywords package
-NULL
+#' @keywords internal
+"_PACKAGE"