/
project.yaml
107 lines (95 loc) · 4.18 KB
/
project.yaml
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version: '3.0'
expectations:
population_size: 1000
actions:
generate_study_population_ethnicity_01H170K13SCPCZBQ1GJEYTYED2:
run: cohortextractor:latest generate_cohort
--study-definition study_definition_ethnicity
--output-dir output/01H170K13SCPCZBQ1GJEYTYED2 --output-format=feather
outputs:
highly_sensitive:
cohort: output/01H170K13SCPCZBQ1GJEYTYED2/input_ethnicity.feather
generate_study_population_weekly_01H170K13SCPCZBQ1GJEYTYED2:
run: cohortextractor:latest generate_cohort
--study-definition study_definition
--param codelist_1_frequency="weekly"
--param breakdowns=""
--index-date_range="2023-05-08 to 2023-05-08 by week"
--output-dir=output/01H170K13SCPCZBQ1GJEYTYED2
--output-format=feather
--output-file=output/01H170K13SCPCZBQ1GJEYTYED2/input_weekly_2023-05-08.feather
outputs:
highly_sensitive:
cohort: output/01H170K13SCPCZBQ1GJEYTYED2/input_weekly_2023-05-08.feather
generate_study_population_01H170K13SCPCZBQ1GJEYTYED2:
run: cohortextractor:latest generate_cohort
--study-definition study_definition
--index-date-range="2019-09-01 to 2023-04-30 by month"
--output-dir=output/01H170K13SCPCZBQ1GJEYTYED2
--output-format=feather
outputs:
highly_sensitive:
cohort: output/01H170K13SCPCZBQ1GJEYTYED2/input_*.feather
join_cohorts_01H170K13SCPCZBQ1GJEYTYED2:
run: >
cohort-joiner:v0.0.38
--lhs output/01H170K13SCPCZBQ1GJEYTYED2/input_20*.feather
--rhs output/01H170K13SCPCZBQ1GJEYTYED2/input_ethnicity.feather
--output-dir output/01H170K13SCPCZBQ1GJEYTYED2/joined
needs: [generate_study_population_01H170K13SCPCZBQ1GJEYTYED2, generate_study_population_ethnicity_01H170K13SCPCZBQ1GJEYTYED2]
outputs:
highly_sensitive:
cohort: output/01H170K13SCPCZBQ1GJEYTYED2/joined/input_20*.feather
generate_measures_01H170K13SCPCZBQ1GJEYTYED2:
run: >
python:latest -m analysis.measures
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--input-dir="output/01H170K13SCPCZBQ1GJEYTYED2/joined"
needs: [join_cohorts_01H170K13SCPCZBQ1GJEYTYED2]
outputs:
moderately_sensitive:
measure: output/01H170K13SCPCZBQ1GJEYTYED2/joined/measure_all.csv
decile_measure: output/01H170K13SCPCZBQ1GJEYTYED2/joined/measure_practice_rate_deciles.csv
top_5_table_01H170K13SCPCZBQ1GJEYTYED2:
run: >
python:latest python analysis/top_5.py
--codelist-1-path="interactive_codelists/codelist_1.csv"
--codelist-2-path="interactive_codelists/codelist_2.csv"
--output-dir="output/01H170K13SCPCZBQ1GJEYTYED2"
needs: [generate_measures_01H170K13SCPCZBQ1GJEYTYED2]
outputs:
moderately_sensitive:
tables: output/01H170K13SCPCZBQ1GJEYTYED2/joined/top_5*.csv
plot_measure_01H170K13SCPCZBQ1GJEYTYED2:
run: >
python:latest python analysis/plot_measures.py
--breakdowns=sex
--breakdowns=age
--breakdowns=ethnicity
--breakdowns=imd
--breakdowns=region
--output-dir output/01H170K13SCPCZBQ1GJEYTYED2
needs: [generate_measures_01H170K13SCPCZBQ1GJEYTYED2]
outputs:
moderately_sensitive:
measure: output/01H170K13SCPCZBQ1GJEYTYED2/plot_measure*.png
deciles: output/01H170K13SCPCZBQ1GJEYTYED2/deciles_chart.png
event_counts_01H170K13SCPCZBQ1GJEYTYED2:
run: >
python:latest -m analysis.event_counts --input-dir="output/01H170K13SCPCZBQ1GJEYTYED2" --output-dir="output/01H170K13SCPCZBQ1GJEYTYED2"
needs: [join_cohorts_01H170K13SCPCZBQ1GJEYTYED2, generate_study_population_weekly_01H170K13SCPCZBQ1GJEYTYED2]
outputs:
moderately_sensitive:
measure: output/01H170K13SCPCZBQ1GJEYTYED2/event_counts.json
generate_report_01H170K13SCPCZBQ1GJEYTYED2:
run: >
python:latest python analysis/render_report.py
--output-dir="output/01H170K13SCPCZBQ1GJEYTYED2"
needs: [event_counts_01H170K13SCPCZBQ1GJEYTYED2, top_5_table_01H170K13SCPCZBQ1GJEYTYED2, plot_measure_01H170K13SCPCZBQ1GJEYTYED2]
outputs:
moderately_sensitive:
notebook: output/01H170K13SCPCZBQ1GJEYTYED2/report.html