## ----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,
#                                    oracleTempSchema = NULL,
#                                    cdmDatabaseSchema,
#                                    cdmVersion = "5",
#                                    cohortTable = "#cohort_person",
#                                    cohortIds = c(-1),
#                                    rowIdField = "subject_id",
#                                    covariateSettings,
#                                    aggregated = FALSE,
#                                    minCharacterizationMean = 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
#  )