406 hades weekly fail - hotfix (#410)

* fix because of addition of new parameter for decision trees in scikit-learn 1.3
* more consistent python environments in CI

.github/workflows/R_CMD_check_Hades.yaml

@@ -22,7 +22,7 @@ jobs:
         config:
           - {os: windows-latest, r: 'release'}  # Does not appear to have Java 32-bit, hence the --no-multiarch
           - {os: macOS-latest, r: 'release'}
-          - {os: ubuntu-20.04, r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
+          - {os: ubuntu-22.04, r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/jammy/latest"}
 
     env:
       GITHUB_PAT: ${{ secrets.GH_TOKEN }}
@@ -46,28 +46,14 @@ jobs:
 
     steps:
       - uses: actions/checkout@v2
-
-      - uses: conda-incubator/setup-miniconda@v2
-        with:
-          python-version: "3.7"
-          activate-environment: r-reticulate
-
-      - name: python main dependencies  
-        run: conda install --name r-reticulate numpy scipy scikit-learn pandas pydotplus joblib
-
-      - name: python json dependencies  
-        run: conda install --name r-reticulate -c conda-forge sklearn-json 
-
-      - name: python scikit-survival dependencies    
-        run: conda install --name r-reticulate -c sebp scikit-survival
 
       - uses: r-lib/actions/setup-r@v2
         with:
           r-version: ${{ matrix.config.r }}
 
-      - uses: r-lib/actions/setup-tinytex@v1
+      - uses: r-lib/actions/setup-tinytex@v2
 
-      - uses: r-lib/actions/setup-pandoc@v1
+      - uses: r-lib/actions/setup-pandoc@v2
 
       - name: Install system requirements
         if: runner.os == 'Linux'
@@ -77,17 +63,17 @@ jobs:
           while read -r cmd
           do
             eval sudo $cmd
-          done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "20.04"))')
+          done < <(Rscript -e 'writeLines(remotes::system_requirements("ubuntu", "22.04"))')
+          
+      - name: Setup conda
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+          activate-environment: "r-reticulate"
 
       - uses: r-lib/actions/setup-r-dependencies@v2
         with:
           extra-packages: any::rcmdcheck
           needs: check
-
-      - name: use r-reticulate environment
-        run: |
-          reticulate::use_condaenv("r-reticulate", required = TRUE)
-        shell: Rscript {0}
 
       - uses: r-lib/actions/check-r-package@v2
         with:

DESCRIPTION

@@ -2,7 +2,7 @@ Package: PatientLevelPrediction
 Type: Package
 Title: Developing patient level prediction using data in the OMOP Common Data
     Model
-Version: 6.3.4
+Version: 6.3.5
 Date: 2023-08-15
 Authors@R: c(
     person("Jenna", "Reps", email = "[email protected]", role = c("aut", "cre")),

NEWS.md

@@ -1,3 +1,9 @@
+PatientLevelPrediction 6.3.5
+======================
+- Fix sklearnToJson to be compatible with scikit-learn>=1.3
+- Fix github actions so it's not hardcoded to use python 3.7
+
+
 PatientLevelPrediction 6.3.4
 ======================
 - added spline feature engineering 

R/SklearnToJson.R

@@ -89,7 +89,11 @@ deSerializeTree <- function(tree_dict, nFeatures, nClasses, nOutputs) {
                             reticulate::tuple(reticulate::py_to_r(tree_dict["nodes"][i])))
   }
 
-  names = list("left_child", "right_child", "feature", "threshold", "impurity", "n_node_samples", "weighted_n_node_samples")
+  names <- list("left_child", "right_child", "feature", "threshold", "impurity", "n_node_samples", "weighted_n_node_samples")
+  if (length(tree_dict["nodes"][0])==8) {
+    # model used sklearn>=1.3 which added a parameter
+    names[[8]] <- "missing_go_to_left"
+  }
 
   sklearn <- reticulate::import("sklearn")
   np <- reticulate::import("numpy", convert = FALSE)

README.md

@@ -78,7 +78,7 @@ System Requirements
 Requires R (version 4.0 or higher). Installation on Windows requires [RTools](http://cran.r-project.org/bin/windows/Rtools/). Libraries used in PatientLevelPrediction require Java and Python.
 
 The python installation is required for some of the machine learning algorithms. We advise to
-install Python 3.7 using Anaconda (https://www.continuum.io/downloads). 
+install Python 3.8 or higher using Anaconda (https://www.continuum.io/downloads). 
 
 Getting Started
 ===============