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Job request: 5974

Organisation:
University of Manchester
Workspace:
hosp_pred_popul
ID:
i2aq26eigiamc7vj
View repo View project.yaml

This page shows the technical details of what happened when authorised researcher ali requested one or more actions to be run against real patient data in the project, within a secure environment.

By cross-referencing the indicated Requested Actions with the Pipeline section below, you can infer what security level various outputs were written to. Outputs marked as highly_sensitive can never be viewed directly by a researcher; they can only request that code runs against them. Outputs marked as moderately_sensitive can be viewed by an approved researcher by logging into a highly secure environment. Only outputs marked as moderately_sensitive can be requested for release to the public, via a controlled output review service.

Jobs

Pipeline

Show project.yaml 
version: '3.0'

expectations:
  population_size: 10000

actions:

  # generate_study_population:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition --index-date-range "2019-01-01 to today by month" --skip-existing --output-dir=output/measures --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/measures/input_*.csv.gz

  generate_study_population_hospitalisation:
    run: cohortextractor:latest generate_cohort --study-definition study_definition_hospitalisation --index-date-range "2019-01-01 to 2021-08-01 by month" --skip-existing --output-dir=output/hospitalisation_data --output-format=csv.gz
    outputs:
      highly_sensitive:
        cohort: output/hospitalisation_data/input_hospitalisation_*.csv.gz

  # generate_study_population_elderly:
  #   run: cohortextractor:latest generate_cohort --study-definition study_definition_elderly 
  #     --output-format=csv.gz
  #   outputs:
  #     highly_sensitive:
  #       cohort: output/input_elderly.csv.gz

  # generate_measures:
  #   run: cohortextractor:latest generate_measures --study-definition study_definition --skip-existing --output-dir=output/measures
  #   needs: [generate_study_population]
  #   outputs:
  #     moderately_sensitive:
  #       measure_csv: output/measures/measure_*.csv
        
  # describe_elderly_agedis:
  #   run: r:latest analysis/tables/gen_csv_age_check.R
  #   needs: [generate_study_population_elderly]
  #   outputs:
  #     moderately_sensitive:
  #       agetable: output/age_quant.csv

  # describe:
  #   run: r:latest analysis/plot/overall_ab_prescribing.R
  #   needs: [generate_measures]
  #   outputs:
  #     moderately_sensitive:
  #       cohort: output/overall.png
  #       boxplot: output/overallbox.png

  # describe_percentile:
  #   run: r:latest analysis/plot/overall_ab_prescribing_2575percentile.R
  #   needs: [generate_measures]
  #   outputs:
  #     moderately_sensitive:
  #       percentile: output/overall_25th_75th_percentile.png

  # describe_starpu:
  #   run: r:latest analysis/plot/starpu_ab_prescribing.R
  #   needs: [generate_measures]
  #   outputs:
  #     moderately_sensitive:
  #       cohort: output/starpuline.png
  #       boxplot: output/starpubox.png
  
  #generate_notebook_starpu:
  #  run: jupyter:latest jupyter nbconvert /workspace/analysis/starpu.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #  needs: [generate_measures]
  #  outputs:
  #    moderately_sensitive:
  #      notebook: output/hospitalisation_risk/starpu.html 
  #      figures: output/hospitalisation_risk/*
        #tables: output/tables/*
        #csvs: output/*/* # two possible subfolders
        #text: output/text/*

  # generate_notebook_hospitalisation_analysis:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_analysis.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_risk --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population_hospitalisation]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_risk/hospitalisation_analysis.html 
  #       figures: output/hospitalisation_risk/*

  generate_notebook_hospitalisation_prediction_uti:
    run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction_uti.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction_uti --ExecutePreprocessor.timeout=86400
    needs: [generate_study_population_hospitalisation]
    outputs:
      moderately_sensitive:
        notebook: output/hospitalisation_prediction_uti/hospitalisation_prediction_uti.html 
        figures: output/hospitalisation_prediction_uti/*
  
  # generate_notebook_hospitalisation_prediction:
  #   run: jupyter:latest jupyter nbconvert /workspace/analysis/hospitalisation_prediction.ipynb --execute --to html --output-dir=/workspace/output/hospitalisation_prediction --ExecutePreprocessor.timeout=86400
  #   needs: [generate_study_population_hospitalisation]
  #   outputs:
  #     moderately_sensitive:
  #       notebook: output/hospitalisation_prediction/hospitalisation_prediction.html 
  #       figures: output/hospitalisation_prediction/*

  # describe_infection_ab_UTI:
  #   run: r:latest analysis/plot/infection_ab_UTI.R
  #   needs: [generate_study_population, generate_measures]
  #   outputs:
  #      moderately_sensitive:
  #       plot: output/UTI.png

Timeline

  • Created:

  • Started:

  • Finished:

  • Runtime: 03:13:54

These timestamps are generated and stored using the UTC timezone on the TPP backend.

Job information

Status
Failed
Backend
TPP
Workspace
hosp_pred_popul
Requested by
ali
Branch
hospitalisation
Force run dependencies
No
Git commit hash
cf1da32
Requested actions
  • generate_study_population_hospitalisation

Code comparison

Compare the code used in this Job Request