scoring.yml

name: Scoring

on:

  workflow_dispatch:
  schedule:
    - cron: "30 01 * * 4"

    
jobs:

  scoring_job:
    if: github.repository_owner == 'european-modelling-hubs'
    runs-on: ubuntu-latest
    env:
      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}

      
    steps:

    # Checkout the tools repo
    # -------------------------------------------      
    - name: checkout tools repo
      uses: actions/checkout@v3
      with:
        token: ${{ secrets.GITHUB_TOKEN }}
        repository: 'european-modelling-hubs/hub-tools'
        ref: 'main'
        path: './tools/'


    # Checkout the data repository
    # -------------------------------------------      
    - name: checkout data repo
      uses: actions/checkout@v3
      with:
        token: ${{ secrets.GITHUB_TOKEN }}
        repository: 'european-modelling-hubs/ari-forecast-hub'
        ref: 'main'
        path: './repo/'


    # Setup R env
    # -------------------------
    - uses: r-lib/actions/setup-r@v2
      with:
        install-r: false
        use-public-rspm: true
        
    # Eventually install R dependencies
    - name: Installing dependencies
      run: |
        install.packages("remotes")
        remotes::install_github("Infectious-Disease-Modeling-Hubs/hubData")
        install.packages("dplyr")
        install.packages('jsonlite')
        install.packages("optparse")
        install.packages("scoringutils")
      shell: Rscript {0}

    # Setup Python
    # -------------------------
    - uses: actions/setup-python@v4
      with:
        python-version: '3.10' 
    
    # eventually install additional packages
    - name: Installing python additional packages
      run: pip install pandas==1.2.5 numpy==1.22.4

    
    # Run R code to compute scoring and produce an output file (scoring_outfile)
    # ----------------------------------------------------------------------------
    - name: Generate Scoring
      id: generate_scoring
      run: |
        # call R script from tools
        Rscript ./tools/R-code/forecast_evaluation.R --hub_path "./repo" --truth_file_name "latest-ARI_incidence.csv" --subfolders "ERVISS"

    # Do the python manipulations and produce an output file (scoring_file)
    # ------------------------------------------------------------------------
    - name: format scoreing output
      id: format_scoring_output
      run: |
        python ./tools/code/format_evaluation_file.py --hub_path "./repo"

    # Commit the changes
    # -------------------------
    - name: Commit changes
      uses: EndBug/add-and-commit@v7
      with: 
          cwd: './repo'
          add: ${{ steps.format_scoring_output.outputs.scoring_file_latest }} ${{ steps.format_scoring_output.outputs.scoring_file_snapshot }} # put here file changes 
          message: "Update forecast scoring"
          default_author: github_actions
          push: true

    # Save changes to artifact for later persisting 
    - name: Save changes to artifact
      env:
        changed_files: ${{ steps.format_scoring_output.outputs.scoring_file_latest }} ${{ steps.format_scoring_output.outputs.scoring_file_snapshot }}
      run: |
        echo "{ \"pr-changes\" : \"$changed_files\" }" > pr_changes.json
          
    - name: Upload changes
      uses: actions/upload-artifact@v2
      with:
        name: pr_changes
        path: ./pr_changes.json