## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(collapse = TRUE, comment = "#>")

## ----setup--------------------------------------------------------------------
library(coreval)

## ----one-dataset--------------------------------------------------------------
ae <- data.frame(
  STUDYID = "DEMO", DOMAIN = "AE", USUBJID = c("S1", "S1", "S2"),
  AESEQ = c(1, 2, 1), AETERM = c("Headache", "Nausea", "Rash"),
  AESTDTC = c("2024-01-10", "2024-02-30", "2024-01-12"),
  AEENDTC = c("2024-01-12", "2024-02-01", "")
)

result <- check_dataset(ae)
result

## ----one-dataset-date---------------------------------------------------------
result$findings[result$findings$Value == "2024-02-30", ]

## ----one-dataset-file, eval = FALSE-------------------------------------------
# result <- check_dataset("ae.xpt")

## ----one-dataset-skips--------------------------------------------------------
cross <- result$skipped[grepl("was not supplied", result$skipped$reason), ]
nrow(cross)
head(unique(cross$reason), 3)

## ----ct, eval = FALSE---------------------------------------------------------
# check_study(dir, ct_package = "sdtmct-2026-03-27")
# list_ct_packages("sdtm")   # every published version, pick the one you declare

## ----build-study--------------------------------------------------------------
dir <- tempfile("coreval_demo_")
dir.create(dir)

dm <- data.frame(
  STUDYID = "DEMO", DOMAIN = "DM", USUBJID = c("S1", "S2", "S3"),
  RFSTDTC = c("2024-01-05", "2024-01-06", ""),
  AGE = c(34, 61, 47), AGEU = c("YEARS", "YEARS", ""),
  SEX = c("M", "F", "F")
)

haven::write_xpt(dm, file.path(dir, "dm.xpt"))
haven::write_xpt(ae, file.path(dir, "ae.xpt"))

## ----check--------------------------------------------------------------------
study_result <- check_study(dir)

## ----read---------------------------------------------------------------------
study <- read_study(dir)
names(study$datasets)

## ----findings-head------------------------------------------------------------
head(study_result$findings)

## ----findings-filter----------------------------------------------------------
f <- study_result$findings
head(f[f$Dataset == "DM", ])
sort(table(f$rule_id), decreasing = TRUE)[1:3]

## ----filter-findings----------------------------------------------------------
worst <- filter_findings(study_result, triage = "wrong value")
nrow(worst$findings)
summary(worst)

## ----skipped------------------------------------------------------------------
head(study_result$skipped)

## ----export, eval = FALSE-----------------------------------------------------
# write_findings(study_result, "issues.xlsx")  # one workbook, a sheet per table
# write_findings(study_result, "issues.csv")   # issues.csv + _skipped + _about

## ----rules--------------------------------------------------------------------
rules <- list_rules()
nrow(rules)
table(rules$source)

attr(rules, "rules_version")

## ----rules-for-domain---------------------------------------------------------
nrow(list_rules(domain = "AE"))

rule <- list_rules(id = "CORE-000547")
rule$issue

## ----rule-ids-----------------------------------------------------------------
rule$legacy_ids

## ----narrow, eval = FALSE-----------------------------------------------------
# result <- check_dataset(dm, standard = "SDTMIG", version = "3.4")

## ----usdm, eval = FALSE-------------------------------------------------------
# result <- check_study("path/to/usdm")

## ----cleanup, include = FALSE-------------------------------------------------
unlink(dir, recursive = TRUE)