Job request: 12436

version: "3.0"

expectations:
  population_size: 1000

actions:
  generate_study_population_population:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_population --index-date-range "2019-01-01 to 2022-05-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_population*.feather

  join_ethnicity_population:
    run: >
      cohort-joiner:v0.0.46
        --lhs output/input_population_20*.feather
        --rhs output/input_ethnicity.feather
        --output-dir output/joined
    needs: [generate_study_population_population, generate_study_population_ethnicity]
    outputs:
      highly_sensitive:
        cohort: output/joined/input_population_20*.feather

  get_moved_count:
    run: python:latest python analysis/population_count.py
    needs: [join_ethnicity_population]
    outputs:
      moderately_sensitive:
        text: output/move*.json


  generate_study_population_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to 2019-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_*.feather

  generate_study_population_2:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2020-01-01 to 2020-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input*.feather

  generate_study_population_3:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-01-01 to 2021-06-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/inpu*.feather

  generate_study_population_4:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2021-07-01 to 2021-12-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/in*.feather

  generate_study_population_5:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2022-01-01 to 2022-05-01 by month" --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/i*.feather


  get_patient_count:
    run: python:latest python analysis/get_patients_counts.py
    needs: [generate_study_population_4, generate_study_population_5, join_ethnicity]
    outputs:
      moderately_sensitive:
        text: output/patient_count.json

  generate_study_population_ethnicity:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_ethnicity --output-dir=output --output-format=feather
    outputs:
      highly_sensitive:
        cohort: output/input_ethnicity.feather

  join_ethnicity:
    run: python:latest python analysis/join_ethnicity.py
    needs:
      [
        generate_study_population_1,
        generate_study_population_2,
        generate_study_population_3,
        generate_study_population_ethnicity,
      ]
    outputs:
      highly_sensitive:
        cohort: output/inp*.feather

  get_practice_count:
    run: python:latest python analysis/get_practice_count.py
    needs: [join_ethnicity, generate_study_population_4, generate_study_population_5]
    outputs:
      moderately_sensitive:
        text: output/practice_count.json

  generate_measures:
    run: cohortextractor:latest generate_measures --study-definition study_definition --output-dir=output
    needs: [join_ethnicity, generate_study_population_4, generate_study_population_5]
    outputs:
      moderately_sensitive:
        measure_csv: output/measure_*_rate.csv

  generate_measures_cleaned:
    run: python:latest python analysis/clean_measures.py
    needs: [generate_measures]
    outputs:
      moderately_sensitive:
        measure_csv: output/measure_cleaned_*.csv


  generate_notebook:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs:
      [
        generate_measures,
        generate_measures_cleaned,
        get_practice_count,
        get_patient_count,
      ]
    outputs:
      moderately_sensitive:
        notebook: output/sentinel_measures.html
        subplots: output/sentinel_measures_subplots.png
        code_tables: output/code_table_*.csv
        events_count: output/event_count.json

  generate_notebook_updating:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/sentinel_measures_updating.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
    needs:
      [
        generate_measures,
        generate_measures_cleaned,
        get_practice_count,
        get_patient_count,
      ]
    outputs:
      moderately_sensitive:
        notebook: output/sentinel_measures_updating.html
        code_tables: output/code_table*.csv
        practices: output/num_practices_included*.csv

  run_tests_population_count:
    run: python:latest python -m pytest tests/test_population_count.py --junit-xml=output/pytest.xml --verbose
    outputs:
      moderately_sensitive:
        log: output/pytest.xml

  # run_tests:
  #   run: python:latest python -m pytest --junit-xml=output/pytest.xml --verbose
  #   outputs:
  #     moderately_sensitive:
  #       log: output/pytest.xml