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Forecast Checks
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header must only include
location
,target
,type
,quantile
,value
(required for zoltpy) andforecast_date
,target_end_date
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each row must have the same number of columns as header
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location
must be in "locations" column of locations.csv -
target
must be inpaste(1:20, "wk ahead inc death") paste(1:20, "wk ahead cum death") paste(0:130, "day ahead inc hosp") paste(1:8, "wk ahead inc case")
county locations should have only "case" targets
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forecast_date
andtarget_end_date
must be in YYYY-MM-DD format -
quantile
must be inc(0.01, 0.025, seq(0.05, 0.95, by = 0.05), 0.975, 0.99)
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quantile
for "case" targets must be inc(0.025, 0.100, 0.250, 0.500, 0.750, 0.900, 0.975)
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checks
quantile
must be an int or float in [0, 1] -
checks
value
must be an int or float and non-negative -
validates date alignment as documented in the issue add additional validations
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validates quantiles and values (i.e,. at the prediction level):
- checks that entries in
value
must be non-decreasing as quantiles increase - checks that elements in the
quantile
are unique
- checks that entries in
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validates quantiles as a group:
- there must be exactly one point prediction for each
location/target
pair
- there must be exactly one point prediction for each
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validates if the prediction
value
for a location is at least less than the population of that location.- this check is run for all forecast submissions for all targets (in/cum deaths/cases).
- the population truth data is present in the locations.csv file.
- To check which predictions are violating, check the logs in the Github Actions build do your PR and it should be printed.
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- Data Validation
- Truth Data
- Baseline model
- Weekly ensemble release
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