R/Shiny.R

In mi-erasmusmc/RanitidineStudy: Ranitidine drug utilization study generating statistics against the OMOP CDM

# Copyright 2020 Observational Health Data Sciences and Informatics
#
# This file is part of CohortDiagnostics
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
#     http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

#' Launch the Diagnostics Explorer Shiny app
#'
#' @param dataFolder       A folder where the exported zip files with the results are stored.  
#'                         Zip files containing results from multiple databases can be placed in the same
#'                         folder.
#' @param launch.browser   Should the app be launched in your default browser, or in a Shiny window.
#'                         Note: copying to clipboard will not work in a Shiny window.
#'
#' @details
#' Launches a Shiny app that allows the user to explore the diagnostics
#'
#' @export
launchResultsExplorer <- function(dataFolder, launch.browser = FALSE) {
  ensure_installed("DT")
  appDir <- system.file("shiny", "ResultsExplorer", package = "DrugUtilization")
  shinySettings <- list(dataFolder = dataFolder)
  .GlobalEnv$shinySettings <- shinySettings
  on.exit(rm(shinySettings, envir = .GlobalEnv))
  shiny::runApp(appDir)
}


# Borrowed from devtools:
# https://github.com/hadley/devtools/blob/ba7a5a4abd8258c52cb156e7b26bb4bf47a79f0b/R/utils.r#L44
is_installed <- function(pkg, version = 0) {
  installed_version <- tryCatch(utils::packageVersion(pkg), error = function(e) NA)
  !is.na(installed_version) && installed_version >= version
}

# Borrowed and adapted from devtools:
# https://github.com/hadley/devtools/blob/ba7a5a4abd8258c52cb156e7b26bb4bf47a79f0b/R/utils.r#L74
ensure_installed <- function(pkg) {
  if (!is_installed(pkg)) {
    msg <- paste0(sQuote(pkg), " must be installed for this functionality.")
    if (interactive()) {
      message(msg, "\nWould you like to install it?")
      if (menu(c("Yes", "No")) == 1) {
        install.packages(pkg)
      } else {
        stop(msg, call. = FALSE)
      }
    } else {
      stop(msg, call. = FALSE)
    }
  }
}

#' Premerge Shiny diagnostics files
#' 
#' @description 
#' If there are many diagnostics files, starting the Shiny app may take a very long time. This function 
#' already does most of the preprocessing, increasing loadding speed.
#' 
#' The merged data will be stored in the same folder, and will automatically be recognized by the Shiny app.
#'
#' @param dataFolder  folder where the exported zip files for the diagnostics are stored. Use
#'                         the \code{\link{execute}} function to generate these zip files. 
#'                         Zip files containing results from multiple databases can be placed in the same
#'                         folder.
#'                         
#' @export
preMergeDiagnosticsFiles <- function(dataFolder) {
  zipFiles <- list.files(dataFolder, pattern = ".zip", full.names = TRUE)
  
  loadFile <- function(file, folder, overwrite) {
    tableName <- gsub(".csv$", "", file)
    camelCaseName <- SqlRender::snakeCaseToCamelCase(tableName)
    data <- readr::read_csv(file.path(folder, file), col_types = readr::cols(), guess_max = 1e7, locale = readr::locale(encoding = "UTF-8"))
    colnames(data) <- SqlRender::snakeCaseToCamelCase(colnames(data))
    
    if (!overwrite && exists(camelCaseName, envir = .GlobalEnv)) {
      existingData <- get(camelCaseName, envir = .GlobalEnv)
      if (nrow(existingData) > 0) {
        if (nrow(data) > 0 &&
            all(colnames(existingData) %in% colnames(data)) &&
            all(colnames(data) %in% colnames(existingData))) {
          data <- data[, colnames(existingData)]
        }
        
        if (!isTRUE(all.equal(colnames(data), colnames(existingData), check.attributes = FALSE))) {
          stop("Table columns do no match previously seen columns. Columns in ", 
               file, 
               ":\n", 
               paste(colnames(data), collapse = ", "), 
               "\nPrevious columns:\n",
               paste(colnames(existingData), collapse = ", "))
        }
      }
      data <- rbind(existingData, data)
    }
    assign(camelCaseName, data, envir = .GlobalEnv)
    
    invisible(NULL)
  }
  tableNames <- c()
  for (i in 1:length(zipFiles)) {
    writeLines(paste("Processing", zipFiles[i]))
    tempFolder <- tempfile()
    dir.create(tempFolder)
    unzip(zipFiles[i], exdir = tempFolder)
    
    csvFiles <- list.files(tempFolder, pattern = ".csv")
    tableNames <- c(tableNames, csvFiles)
    lapply(csvFiles, loadFile, folder = tempFolder, overwrite = (i == 1))
    
    unlink(tempFolder, recursive = TRUE)
  }
  
  tableNames <- unique(tableNames)
  tableNames <- gsub(".csv$", "", tableNames)
  tableNames <- SqlRender::snakeCaseToCamelCase(tableNames)
  save(list = tableNames, file = file.path(dataFolder, "PreMerged.RData"), compress = TRUE)
  ParallelLogger::logInfo("Merged data saved in ", file.path(dataFolder, "PreMerged.RData"))
}