library(tidyverse)

token=keyring::key_get("talos_redcap_api")
# keyring::key_set("talos_redcap_api")

# REDCapR::redcap_variables(redcap_uri = "https://redcap.au.dk/api/",token = token)
# inst <- REDCapR::redcap_instruments(redcap_uri = "https://redcap.au.dk/api/",token = token)

# REDCapR::redcap_read(redcap_uri = "https://redcap.au.dk/api/",token = token)

pase_raw <- REDCapR::redcap_read(redcap_uri = "https://redcap.au.dk/api/",token = token,fields = "record_id",forms = c("pase_0"))

## Selecting relevant variables only
## "(a)x_" variables are notes and excluded.
## "12_" is not used for scoring
pase_sel <- pase_raw[["data"]] |> select("record_id",
                                     contains("_pase"),
                                     -contains("x_"),
                                     -contains("12_"))

## Last subset to have relevant cleaned PASE data only
pase <- pase_sel[,c(3:23)] 

## Function
source("TALOS data workflow/pase_calc.R")




## No work adjustment (older method)
summary((pase |> pase_calc(adjust_work = FALSE))[,13])
## With work adjustment (newer method)
summary((scores <- pase |> pase_calc())[,13])

# pase <- pase[sample(seq_len(nrow(pase)),size = 200),]
# names(pase) <- sub("_0","",sub("talos","sample", names(pase)))
# saveRDS(pase,"pase.rds")