Encode point estimate output type IDs with null. #111
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zkamvar
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elray1
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Oct 25, 2024
elray1
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Oct 25, 2024
elray1
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Oct 25, 2024
zkamvar
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Oct 25, 2024
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I think setting required: null for the point estimates makes the most sense.
I also wanted to also provide context for what we can expect for adapting
hubValidations to work with this new format, becuase setting
required: null will make point estimates invisible to
expand_model_out_grid as demonstrated below.
Setup: creating three configurations:
v3the v3 config where mean hasrequired: ["NA"]array_nullthe v3 config, but the mean hasrequired: [null]solo_nullthe v3 config, but the mean hasrequired: null
hub_con <- hubData::connect_hub(
system.file("testhubs/simple", package = "hubUtils")
)
hp <- attributes(hub_con)$hub_path
# Get the tasks file which has a `mean` output type
tasks <- fs::path(hp, "hub-config", "tasks.json")
# copy the file to a new temp file
cfg <- readLines(tasks)
# change `required:` to a bare `null`
nullcfg <- sub('["NA"]', 'null', cfg, fixed = TRUE)
# change `required:` to a `[null]` array
null_array_cfg <- sub('["NA"]', '[null]', cfg, fixed = TRUE)
# convert to arrays
v3 <- jsonlite::fromJSON(cfg, simplifyDataFrame = FALSE)
array_null <- jsonlite::fromJSON(null_array_cfg, simplifyDataFrame = FALSE)
solo_null <- jsonlite::fromJSON(nullcfg, simplifyDataFrame = FALSE)null array matches our current infrastructure, but bare null is different
identical(v3, array_null)
#> [1] TRUE
identical(v3, solo_null)
#> [1] FALSEThe implication for this is that expand_model_out_grid() no longer detects
point estimates. The omission happens in expand_model_out_grid.R#214
with purrr::compact() throwing away list(mean = NULL). I think we can
address this by adding a v4 catch at that point that protects point estimates.
library("hubValidations")
head(expand_model_out_grid(v3, "2022-10-01"))
#> # A tibble: 6 × 6
#> origin_date target horizon location output_type output_type_id
#> <date> <chr> <int> <chr> <chr> <dbl>
#> 1 2022-10-01 wk inc flu hosp 1 US mean NA
#> 2 2022-10-01 wk inc flu hosp 2 US mean NA
#> 3 2022-10-01 wk inc flu hosp 3 US mean NA
#> 4 2022-10-01 wk inc flu hosp 4 US mean NA
#> 5 2022-10-01 wk inc flu hosp 1 01 mean NA
#> 6 2022-10-01 wk inc flu hosp 2 01 mean NA
head(expand_model_out_grid(array_null, "2022-10-01"))
#> # A tibble: 6 × 6
#> origin_date target horizon location output_type output_type_id
#> <date> <chr> <int> <chr> <chr> <dbl>
#> 1 2022-10-01 wk inc flu hosp 1 US mean NA
#> 2 2022-10-01 wk inc flu hosp 2 US mean NA
#> 3 2022-10-01 wk inc flu hosp 3 US mean NA
#> 4 2022-10-01 wk inc flu hosp 4 US mean NA
#> 5 2022-10-01 wk inc flu hosp 1 01 mean NA
#> 6 2022-10-01 wk inc flu hosp 2 01 mean NA
head(expand_model_out_grid(solo_null, "2022-10-01"))
#> # A tibble: 6 × 6
#> origin_date target horizon location output_type output_type_id
#> <date> <chr> <int> <chr> <chr> <dbl>
#> 1 2022-10-01 wk inc flu hosp 1 US quantile 0.01
#> 2 2022-10-01 wk inc flu hosp 2 US quantile 0.01
#> 3 2022-10-01 wk inc flu hosp 3 US quantile 0.01
#> 4 2022-10-01 wk inc flu hosp 4 US quantile 0.01
#> 5 2022-10-01 wk inc flu hosp 1 01 quantile 0.01
#> 6 2022-10-01 wk inc flu hosp 2 01 quantile 0.01Created on 2024-10-25 with reprex v2.1.1
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Thanks @zkamvar . None of the proposed schema changes work yet because the functionality to support it hasn't been developed yet. The usual development process is to queue up the new version in |
Co-authored-by: Evan Ray <[email protected]>
Co-authored-by: Evan Ray <[email protected]>
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Resolves #109