inst/shiny/EvidenceExplorer/global.R

In ABMI/RanitidineCancerRisk: A Package to compare the risks of cancer between H2 blockers

source("DataPulls.R")
source("PlotsAndTables.R")

# shinySettings <- list(dataFolder = "c:/temp/shinyDataNoPcs", blind = FALSE)
dataFolder <- shinySettings$dataFolder
blind <- shinySettings$blind
connection <- NULL
positiveControlOutcome <- NULL

splittableTables <- c("covariate_balance", "preference_score_dist", "kaplan_meier_dist")

files <- list.files(dataFolder, pattern = ".rds")

# Remove data already in global environment:
tableNames <- gsub("(_t[0-9]+_c[0-9]+)|(_)[^_]*\\.rds", "", files) 
camelCaseNames <- SqlRender::snakeCaseToCamelCase(tableNames)
camelCaseNames <- unique(camelCaseNames)
camelCaseNames <- camelCaseNames[!(camelCaseNames %in% SqlRender::snakeCaseToCamelCase(splittableTables))]
rm(list = camelCaseNames)

# Load data from data folder:
loadFile <- function(file) {
  # file = files[13]
  tableName <- gsub("(_t[0-9]+_c[0-9]+)|(_)[^_]*\\.rds", "", file) 
  camelCaseName <- SqlRender::snakeCaseToCamelCase(tableName)
  if (!(tableName %in% splittableTables)) {
    newData <- readRDS(file.path(dataFolder, file))
    colnames(newData) <- SqlRender::snakeCaseToCamelCase(colnames(newData))
    if (exists(camelCaseName, envir = .GlobalEnv)) {
      existingData <- get(camelCaseName, envir = .GlobalEnv)
      newData <- rbind(existingData, newData)
    }
    assign(camelCaseName, newData, envir = .GlobalEnv)
  }
  invisible(NULL)
}
lapply(files, loadFile)

tcos <- unique(cohortMethodResult[, c("targetId", "comparatorId", "outcomeId")])
tcos <- tcos[tcos$outcomeId %in% outcomeOfInterest$outcomeId, ]