extras/Shiny.R

In OHDSI/PheValuator: Rapid Phenotype Evaluation

# Copyright 2022 Observational Health Data Sciences and Informatics
#
# This file is part of PheValuator
#
# 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 PheValuator Explorer Shiny app
#'
#' @param dataFolder       A folder where the prepared PheValuator results are stored. Use
#'                         the \code{\link{prepareForShiny}} function to generate this data file.
#' @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 PheValuator results.
#'
#' @export
launchPheValuatorExplorer <- function(dataFolder, launch.browser = FALSE) {
  ensure_installed("shiny")
  ensure_installed("shinydashboard")
  ensure_installed("DT")
  ensure_installed("htmltools")
  appDir <- system.file("shiny", "PheValuatorExplorer", package = "PheValuator")
  shinySettings <- list(dataFolder = dataFolder)
  .GlobalEnv$shinySettings <- shinySettings
  on.exit(rm(shinySettings, envir = .GlobalEnv))
  shiny::runApp(appDir)
}

#' Preprare results for Shiny viewer
#'
#' @description
#' Processes one or more zip files generated by the \code{\link{exportPheValuatorResults}} function, so they
#' can be viewed in a Shiny app.
#'
#' @param dataFolder  folder where the exported zip files are stored. Use
#'                         the \code{\link{exportPheValuatorResults}} function to generate these zip files.
#'                         Zip files containing results from multiple databases can be placed in the same
#'                         folder.
#'
#' @export
prepareForShiny <- function(dataFolder) {
  zipFiles <- list.files(dataFolder, pattern = ".zip", full.names = TRUE)
  env <- new.env()

  loadFile <- function(file, folder, overwrite, env) {
    # print(file)
    tableName <- gsub(".csv$", "", file)
    camelCaseName <- SqlRender::snakeCaseToCamelCase(tableName)
    data <- readr::read_csv(file = 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 = env)) {
      existingData <- get(camelCaseName, envir = env)
      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 = env)

    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), env = env)

    unlink(tempFolder, recursive = TRUE)
  }
  phevaluatorResult <- get("phevaluatorResult", envir = env)
  phevaluatorResult <- computePerformanceMetricsFromCounts(phevaluatorResult)
  assign("phevaluatorResult", phevaluatorResult, envir = env)

  cohort <- get("cohort", envir = env)
  cohort <- unique(cohort)
  assign("cohort", cohort, envir = env)

  phevaluatorAnalysis <- get("phevaluatorAnalysis", envir = env)
  phevaluatorAnalysis <- unique(phevaluatorAnalysis)
  assign("phevaluatorAnalysis", phevaluatorAnalysis, envir = env)

  save(list = ls(envir = env),
       file = file.path(dataFolder, "PreparedPheValuatorData.RData"),
       envir = env,
       compress = TRUE)
  ParallelLogger::logInfo("Prepared data saved in ", file.path(dataFolder, "PreparedPheValuatorData.RData"))
}

# 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)
    }
  }
}