## ----echo=FALSE,message=FALSE,warning=FALSE,eval=TRUE-------------------------
library(FeatureExtraction)

## ----eval=FALSE---------------------------------------------------------------
# createLooCovariateSettings <- function(useLengthOfObs = TRUE) {
#   covariateSettings <- list(useLengthOfObs = useLengthOfObs)
#   attr(covariateSettings, "fun") <- "getDbLooCovariateData"
#   class(covariateSettings) <- "covariateSettings"
#   return(covariateSettings)
# }

## ----eval=FALSE---------------------------------------------------------------
# getDbLooCovariateData <- function(connection,
#                                   tempEmulationSchema = NULL,
#                                   cdmDatabaseSchema,
#                                   cdmVersion = "5",
#                                   cohortTable = "#cohort_person",
#                                   cohortIds = c(-1),
#                                   rowIdField = "subject_id",
#                                   covariateSettings,
#                                   targetCovariateTable = NULL,
#                                   targetCovariateContinuousTable = NULL,
#                                   targetCovariateRefTable = NULL,
#                                   targetAnalysisRefTable = NULL,
#                                   targetTimeRefTable = NULL,
#                                   aggregated = FALSE,
#                                   minCharacterizationMean = 0,
#                                   minCharacterizationCount = 0) {
#   writeLines("Constructing length of observation covariates")
#   if (covariateSettings$useLengthOfObs == FALSE) {
#     return(NULL)
#   }
#   if (aggregated) {
#     stop("Aggregation not supported")
#   }
# 
#   # Some SQL to construct the covariate:
#   sql <- paste(
#     "SELECT @row_id_field AS row_id, 1 AS covariate_id,",
#     "DATEDIFF(DAY, observation_period_start_date, cohort_start_date)",
#     "AS covariate_value",
#     "FROM @cohort_table c",
#     "INNER JOIN @cdm_database_schema.observation_period op",
#     "ON op.person_id = c.subject_id",
#     "WHERE cohort_start_date >= observation_period_start_date",
#     "AND cohort_start_date <= observation_period_end_date",
#     "{@cohort_ids != -1} ? {AND cohort_definition_id IN (@cohort_ids)}"
#   )
#   sql <- SqlRender::render(sql,
#     cohort_table = cohortTable,
#     cohort_ids = cohortIds,
#     row_id_field = rowIdField,
#     cdm_database_schema = cdmDatabaseSchema
#   )
#   sql <- SqlRender::translate(sql, targetDialect = attr(connection, "dbms"))
# 
#   # Retrieve the covariate:
#   covariates <- DatabaseConnector::querySql(connection, sql, snakeCaseToCamelCase = TRUE)
# 
#   # Construct covariate reference:
#   covariateRef <- data.frame(
#     covariateId = 1,
#     covariateName = "Length of observation",
#     analysisId = 1,
#     conceptId = 0
#   )
# 
#   # Construct analysis reference:
#   analysisRef <- data.frame(
#     analysisId = 1,
#     analysisName = "Length of observation",
#     domainId = "Demographics",
#     startDay = 0,
#     endDay = 0,
#     isBinary = "N",
#     missingMeansZero = "Y"
#   )
# 
#   # Construct analysis reference:
#   metaData <- list(sql = sql, call = match.call())
#   result <- Andromeda::andromeda(
#     covariates = covariates,
#     covariateRef = covariateRef,
#     analysisRef = analysisRef
#   )
#   attr(result, "metaData") <- metaData
#   class(result) <- "CovariateData"
#   return(result)
# }

## ----eval=FALSE---------------------------------------------------------------
# looCovSet <- createLooCovariateSettings(useLengthOfObs = TRUE)
# 
# covariates <- getDbCovariateData(
#   connectionDetails = connectionDetails,
#   cdmDatabaseSchema = cdmDatabaseSchema,
#   cohortDatabaseSchema = resultsDatabaseSchema,
#   cohortTable = "rehospitalization",
#   cohortIds = c(1),
#   covariateSettings = looCovSet
# )

## ----eval=FALSE---------------------------------------------------------------
# covariateSettings <- createCovariateSettings(
#   useDemographicsGender = TRUE,
#   useDemographicsAgeGroup = TRUE,
#   useDemographicsRace = TRUE,
#   useDemographicsEthnicity = TRUE,
#   useDemographicsIndexYear = TRUE,
#   useDemographicsIndexMonth = TRUE
# )
# 
# looCovSet <- createLooCovariateSettings(useLengthOfObs = TRUE)
# 
# covariateSettingsList <- list(covariateSettings, looCovSet)
# 
# covariates <- getDbCovariateData(
#   connectionDetails = connectionDetails,
#   cdmDatabaseSchema = cdmDatabaseSchema,
#   cohortDatabaseSchema = resultsDatabaseSchema,
#   cohortTable = "rehospitalization",
#   cohortIds = c(1),
#   covariateSettings = covariateSettingsList
# )

