Job request: 5581

version: "3.0"

expectations:
  population_size: 5000

actions:
  generate_study_population_1:
    run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-09-01 to 2020-05-01 by month" --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 "2020-06-01 to 2021-02-01 by month" --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 "2021-03-01 to 2021-09-01 by month" --output-format csv.gz
    outputs:
      highly_sensitive:
        cohort: output/inpu*.csv.gz

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

  # join_ethnicity_region:
  #   run: python:latest python analysis/join_ethnicity_region.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

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

  calculate_numerators:
    run: python:latest python analysis/calculate_numerators.py
    needs: [filter_population]
    outputs:
      highly_sensitive:
        cohort: output/indicator_e_f_*.feather

  # calculate_composite_indicators:
  #   run: python:latest python analysis/composite_indicators.py
  #   needs: [calculate_numerators, filter_population]
  #   outputs:
  #     moderately_sensitive:
  #       counts: output/*_composite_measure.csv

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

  # generate_measures_demographics:
  #   run: python:latest python analysis/calculate_measures.py
  #   needs: [calculate_numerators, filter_population]
  #   outputs:
  #     moderately_sensitive:
  #       counts: output/indicator_measure_*.csv
  #       measure_csv: output/measure*_rate.csv
  #       demographics: output/demographics_summary_*.csv

  # generate_summary_counts:
  #   run: python:latest python analysis/summary_statistics.py
  #   needs:
  #     [
  #       filter_population,
  #       generate_measures,
  #       generate_measures_demographics,
  #       calculate_numerators,
  #     ]
  #   outputs:
  #     moderately_sensitive:
  #       patient_count: output/patient_count_*.json
  #       practice_count: output/practice_count_*.json
  #       summary: output/indicator_summary_statistics_*.json

  # generate_plots:
  #   run: python:latest python analysis/plot_measures.py
  #   needs:
  #     [
  #       generate_measures,
  #       generate_measures_demographics,
  #       calculate_composite_indicators,
  #     ]
  #   outputs:
  #     moderately_sensitive:
  #       counts: output/figures/plot_*.jpeg
  #       combined: output/figures/combined_plot_*.png
  #       demographics: output/demographic_aggregates.csv
  #       medians: output/medians.json

  # generate_notebook:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/report.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
  #   needs: [generate_plots, generate_summary_counts]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/report.html

  # generate_dem_notebook:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/demographic_report.ipynb --execute --to html --template basic --output-dir=/workspace/output --ExecutePreprocessor.timeout=86400 --no-input
  #   needs: [generate_plots]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/demographic_report.html

  # plot_Q1_comparisons:
  #   run: r:latest analysis/generate_demographic_slope_plot.R
  #   needs: [generate_plots]
  #   outputs:
  #     moderately_sensitive:
  #       plots: output/figures/SLOPE_*.png

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

  # test_population:
  #   run: python:latest python analysis/test_population.py
  #   needs: [filter_population]
  #   outputs:
  #     moderately_sensitive:
  #       counts: output/population_counts.csv
  #       count: output/patient_count_check.json