shinypkv: shinypkv

#if(!require(devtools)) {install.packages("devtools"); require(devtools)}


#detach("package:roxygen2", unload=TRUE)
#install.packages("Rcpp", dependencies=TRUE, INSTALL_opts = c('--no-lock'))
#if(!require(roxygen2)) {install.packages("roxygen2"); require(roxygen2)}
if(!require(devtools)) {install.packages("devtools"); require(devtools)}
if(!require(Rcpp)) {    install.packages("Rcpp");     require(Rcpp)}
if(!require(roxygen2)) {install.packages("roxygen2"); require(roxygen2)}
if(!require(shiny)) {   install.packages("shiny");    require(shiny)}
if(!require(miniUI)) {   install.packages("miniUI");    require(miniUI)}
if(!require(haven)) {   install.packages("haven");    require(haven)}
if(!require(foreign)) { install.packages("foreign");  require(foreign)}
if(!require(DT)) {      install.packages("DT");       require(DT)}
if(!require(ggplot2)) { install.packages("ggplot2");  require(ggplot2)}
if(!require(rmarkdown)) { install.packages("rmarkdown");  require(rmarkdown)}
if(!require(evaluate)) { install.packages("evaluate");  require(evaluate)}
if(!require(pander)) { install.packages("pander");  require(pander)}

library(Rcpp)
library(devtools)
library(roxygen2)
library(shiny)
library(miniUI)
library(haven)
library(foreign)
library(DT)
library(ggplot2)
library(rmarkdown)
library(evaluate)
library(pander)

shiny_pkv <- function(options = c("sas2csv","nm_dataviz", "none")){

  if (options=="none") {return(NULL)}

  else if(options=="sas2csv") {
library(haven)
library(foreign)
library(DT)
    server <- function(input, output) {
      #Input the uploaded file to a reactive function#
      con<-reactive({
        inFile <- input$file1
        if (is.null(inFile))
          return(NULL)
        substrRight <- function(inFile, n){
          substr(inFile, nchar(inFile)-n+1, nchar(inFile))
        }

        type= substrRight(input$file1, 4)
        if(type==".xpt")
        {read.xport(inFile$datapath)}
        else {read_sas(inFile$datapath, catalog_file = NULL, encoding = NULL)}
      })

      #Input the contents as a table to visualize#
      df <- reactive({data <-con()})

      output$contents <- DT::renderDataTable( con(),filter = 'top')

      #Download data#
      output$downloadData <- downloadHandler(
        filename = function() { paste("data", '.csv', sep='') },
        content = function(file) {
          write.csv(df(), file)
        })
    }

    #########################
    #          ui.R         #
    #########################

    ui <- fluidPage(
      titlePanel("Convert .sas/.xpt to .csv file"),
      sidebarLayout(
        sidebarPanel(
          fileInput('file1', 'Choose .sas or .xpt File',
                    accept=c( '.sas7bdat','.sas','.xpt')),

          tags$hr(),
          downloadButton('downloadData', 'Download.csv')

        ),mainPanel( DT::dataTableOutput("contents"))
      ))

   shinyApp(ui = ui, server = server,options = list(launch.browser=TRUE))
  }
  else if(options=="nm_dataviz"){
    ui <- fluidPage(
      titlePanel("NONMEM dataset visualization"),
      sidebarLayout(
        sidebarPanel(
          fileInput('file1', 'Choose CSV File',
                    accept=c('text/csv','text/comma-separated-values,text/plain', '.csv')),


          tags$hr(),
          checkboxInput('header', 'Header', TRUE),
          radioButtons('sep', 'Separator',c(Comma=',',Tab='\t'),','),
          selectInput( "TYPE", "Output Type", c("Individual","All Subjects")), uiOutput("DOSE"),uiOutput("PERIOD"),
          conditionalPanel(condition = "input.TYPE == 'Individual'",uiOutput("ID"))),
        #tags$hr(),
        mainPanel(
          conditionalPanel(condition= "input.TYPE == 'Individual'", plotOutput("plotind", height=300,click = "plot_click"),h4("Data points"),
                           tableOutput("plot_clickedpoints1")),
          conditionalPanel(condition= "input.TYPE == 'All Subjects'",plotOutput("plotcum", height=300,click = "plot_click"),h4("Data points"),
                           tableOutput("plot_clickedpoints2"))
        ))
    )
    server <-function(input, output, session) {
      library(ggplot2)
      con<-reactive({
        inFile <- input$file1
        if (is.null(inFile))
          return(NULL)
        data_<- read.csv(inFile$datapath)
        #data_<-read.csv(paste(inpath))

        head(data_)
        df<- data.frame(names(data_))
        df$names.data_.<-trimws(df$names.data_.)
        names(df)[names(df) == 'names.data_.'] <- 'varlist'

        #Renaming the input filenames to match standard names used in the code below#

        df$id<-row.names(df)

        head(df)

        for (i in 1:nrow(df)) {
          s <- subset(df , df$id==i)
          s1<-nrow(s)
          ifelse( s1==1,names(data_)[names(data_) == 'subj'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'SUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'subjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'usubjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'USUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'ID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'id'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          #ifelse( s1==1,names(data_)[names(data_) == 'time'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          #ifelse( s1==1,names(data_)[names(data_) == 'TIME'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'ELMSTN'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'elmstn'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'RTFD'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'rtfd'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'conc'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'CONC'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'DV'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'dv'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'dose'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
          ifelse( s1==1,names(data_)[names(data_) == 'DOSE'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
          ifelse( s1==1,names(data_)[names(data_) == 'period'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'PERIOD'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'PER'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'per'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'COHORT'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'cohort'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'REG'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'reg'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'REGIMEN'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'regimen'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'ROUTE'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'route'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        }

        data<-data_
      })

      output$ID <- renderUI({
        df <-con()
        if (is.null(df)) return(NULL)
        subj<-unique(df$subj)
        selectInput("subj", "subj:",subj)})

      #uiOutput("dose")#
      output$DOSE <- renderUI({
        df <-con()
        if (is.null(df)) return(NULL)
        dose<-unique(df$dose)
        selectInput("dose", "dose:",dose)})

      output$PERIOD <- renderUI({
        df <-con()
        if (is.null(df)) return(NULL)
        period<-unique(df$period)
        selectInput("period", "period:",period)})
      #Individual Plots#
      output$plotind <- renderPlot({
        inFile <- input$file1
        if (is.null(inFile)==TRUE) {print(NULL) }
        else if (is.null(inFile)==FALSE) {

          #data<-read.csv(inFile$datapath)
          data_<- read.csv(inFile$datapath)
          #data_<-read.csv(paste(inpath))
          #data_<-read.csv("C:/Users/pk153230/Desktop/Theo_data.csv")
          head(data_)
          df<- data.frame(names(data_))
          df$names.data_.<-trimws(df$names.data_.)
          names(df)[names(df) == 'names.data_.'] <- 'varlist'

          #Renaming the input filenames to match standard names used in the code below#

          df$id<-row.names(df)

          head(df)

          for (i in 1:nrow(df)) {
            s <- subset(df , df$id==i)
            s1<-nrow(s)
            ifelse( s1==1,names(data_)[names(data_) == 'subj'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'SUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'subjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'usubjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'USUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'ID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'id'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            #ifelse( s1==1,names(data_)[names(data_) == 'time'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            #ifelse( s1==1,names(data_)[names(data_) == 'TIME'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'ELMSTN'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'elmstn'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'RTFD'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'rtfd'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'conc'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'CONC'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'DV'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'dv'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'dose'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
            ifelse( s1==1,names(data_)[names(data_) == 'DOSE'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
            ifelse( s1==1,names(data_)[names(data_) == 'period'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'PERIOD'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'PER'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'per'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'COHORT'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'cohort'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'REG'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'reg'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'REGIMEN'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'regimen'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'ROUTE'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'route'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          }

          data<-data_
          #data$DV<-as.numeric(data$DV)& data$MDV !=1
          data1 <- subset(data ,data$subj == input$subj & data$dose==input$dose & data$period==input$period  )
          p1<-ggplot(data1, aes(x=data1$time,y=data1$conc,color=factor(data1$subj))) + geom_point()+
            ggtitle("Individual Concentration Vs Time (Lin-Lin) ") +
            labs(x="Time in hours (RTFD)",y="Concentartion in ng/L (DV)")
          p2 <- p1 + geom_point(color="blue") + geom_line() + theme_bw() +
            theme(axis.line = element_line(colour = "black"),
                  panel.grid.major = element_blank(),
                  panel.grid.minor = element_blank(),
                  panel.background = element_blank(),
                  legend.position = "none")
          p2
        }})
      output$plotcum <- renderPlot({
        inFile <- input$file1
        if (is.null(inFile)==TRUE) {print(NULL) }
        else if (is.null(inFile)==FALSE) {

          data_<- read.csv(inFile$datapath)
          #data_<-read.csv(paste(inpath))
          head(data_)
          df<- data.frame(names(data_))
          df$names.data_.<-trimws(df$names.data_.)
          names(df)[names(df) == 'names.data_.'] <- 'varlist'

          #Renaming the input filenames to match standard names used in the code below#

          df$id<-row.names(df)

          head(df)

          for (i in 1:nrow(df)) {
            s <- subset(df , df$id==i)
            s1<-nrow(s)
            ifelse( s1==1,names(data_)[names(data_) == 'subj'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'SUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'subjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'usubjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'USUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'ID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            ifelse( s1==1,names(data_)[names(data_) == 'id'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
            #ifelse( s1==1,names(data_)[names(data_) == 'time'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            #ifelse( s1==1,names(data_)[names(data_) == 'TIME'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'ELMSTN'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'elmstn'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'RTFD'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'rtfd'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
            ifelse( s1==1,names(data_)[names(data_) == 'conc'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'CONC'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'DV'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'dv'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
            ifelse( s1==1,names(data_)[names(data_) == 'dose'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
            ifelse( s1==1,names(data_)[names(data_) == 'DOSE'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
            ifelse( s1==1,names(data_)[names(data_) == 'period'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'PERIOD'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'PER'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'per'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'COHORT'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'cohort'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'REG'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'reg'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'REGIMEN'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'regimen'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'ROUTE'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
            ifelse( s1==1,names(data_)[names(data_) == 'route'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          }

          data<-data_
          #data<-read.csv("W:/ex/op117387/Output/poppk_204725_19dec2016.csv")& data$MDV !=1& data$MDV !=1
          data1 <- subset(data , data$dose==input$dose & data$period==input$period  )
          # data1 <- subset(data , data$DOSE==2.4 & data$PERIOD==1 & data$MDV !=1 )& data$MDV !=1
          data1$conc<-as.numeric(data1$conc)
          p1<-ggplot(data1, aes(x=data1$time,y=data1$conc,color=factor(data1$subj))) + geom_point()+
            ggtitle("All Subjects Concentration Vs Time (Lin-Lin) ") +
            labs(x="Time in hours (RTFD)",y="Concentartion in ng/L (DV)")
          p2 <- p1 + geom_point(color="blue")+ geom_line() + theme_bw() +
            theme(axis.line = element_line(colour = "black"),
                  panel.grid.major = element_blank(),
                  panel.grid.minor = element_blank(),
                  panel.background = element_blank(),
                  legend.position = "none")
          p2
        }})
      con1<-reactive({


        data<-con()
        data1 <- subset(data ,data$subj == input$subj & data$dose==input$dose & data$period==input$period )
        # data1$DV<-as.numeric(data1$DV)
        data1
      })
      con2<-reactive({

        data<-con()
        data1 <- subset(data ,  data$dose==input$dose & data$period==input$period )
        #data1$DV<-as.numeric(data1$DV)
        data1
      })
      output$plot_clickedpoints1 <- renderTable({
        inFile <- input$file1
        if (is.null(inFile)==TRUE) {print(NULL) }
        else if (is.null(inFile)==FALSE) {
         res <- nearPoints(con1(), input$plot_click, "time","conc", )
          if (nrow(res) == 0)
            return()
          res
        }})
      output$plot_clickedpoints2 <- renderTable({
        inFile <- input$file1
        if (is.null(inFile)==TRUE) {print(NULL) }
        else if (is.null(inFile)==FALSE) {
         res <- nearPoints(con2(), input$plot_click, "time","conc", )
          if (nrow(res) == 0)
            return()
          res
        }})
    }
   shinyApp(ui = ui, server = server,options = list(launch.browser=TRUE))
  }
   else if(options=="dose_cvst"){   
     library(ggplot2)
      transparent_theme <- theme(
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.text.x = element_blank(), 
        axis.text.y = element_blank(),
        axis.ticks = element_blank(),
        panel.grid = element_blank(),
        axis.line = element_blank(),
        panel.background = element_rect(fill = "transparent",colour = NA),
        plot.background = element_rect(fill = "transparent",colour = NA))
     ui <- fluidPage(
  titlePanel("Conc Vs Time by Dose"),
  sidebarLayout(
    sidebarPanel(
      fileInput('file1', 'Choose CSV File',
                accept=c('text/csv','text/comma-separated-values,text/plain', '.csv')),
      
      
      tags$hr(),
      
      uiOutput("CID")),
    mainPanel(
      plotOutput("plotind", height=300,click = "plot_click"),
      h4("Data points"),
      tableOutput("plot_clickedpoints1"),
      tabsetPanel(
        tabPanel("Reporting", downloadButton('report','Download plots .pdf')))
    ))
)

#Server interface#

server <-function(input, output, session) {
  con<-reactive({
    inFile <- input$file1
    if (is.null(inFile))
      return(NULL)
    read.csv(inFile$datapath)
    
  }) 
  
  output$CID <- renderUI({
    df <-con()
    if (is.null(df)) return(NULL)
    CID<-unique(df$CID)
    selectInput("CID", "CID:",CID)})
  
  #plot ind function#
  
  output$plotind <- renderPlot({
    inFile <- input$file1
    if (is.null(inFile)==TRUE) {print(NULL) }
    else if (is.null(inFile)==FALSE) {
      transparent_theme <- theme(
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.text.x = element_blank(), 
        axis.text.y = element_blank(),
        axis.ticks = element_blank(),
        panel.grid = element_blank(),
        axis.line = element_blank(),
        panel.background = element_rect(fill = "transparent",colour = NA),
        plot.background = element_rect(fill = "transparent",colour = NA))
      #Create the graphs :
      data2<-read.csv(inFile$datapath) 
      #data2<- read.csv("W:/GSK1265744/LA200056-LATTE2/Output/PopPK.csv")
      data2$RTFD<-as.numeric(data2$RTFD)
      data2$CONC<-as.numeric(data2$CONC)
      data_ <- subset(data2 , DOSE!=-99)
      data<-subset(data_ , EVID==1)
      
      dat1 <- subset(data, CID==input$CID)
      #dat1 <- subset(data, CID==1)
      
      newdata2 <- subset(data_ , EVID==0)
      dat2 <- subset(newdata2, CID==input$CID)
      #dat2 <- newdata2
      
      library(ggplot2)
      p0<-ggplot(dat2, aes(x=dat2$RTFD, y=dat2$CONC)) + geom_point(shape =4) +
        labs(x="Relative Time from First Dose (Hrs)",y="Concentration (ng/L)") 
      p1 <- p0 + theme_bw() +
        theme(axis.line = element_line(colour = "black"),
              panel.grid.major = element_blank(),
              panel.grid.minor = element_blank(),
              panel.background = element_blank(),
              legend.position = "none")  
      p1 
      
      p2 <- ggplot(dat1, aes(x=dat1$RTFD, y=dat1$DOSE)) + geom_bar(stat = "identity", width=0.01,colour="green") +
        transparent_theme
      p2_grob = ggplotGrob(p2)
      
      p1 + annotation_custom(grob = p2_grob)
    }})

  con1<-reactive({
    data2<-con()
    data2$RTFD<-as.numeric(data2$RTFD)
    data2$CONC<-as.numeric(data2$CONC)
    data2$DOSE<-as.numeric(data2$DOSE)
    data_ <- subset(data2 , data2$DOSE!=-99)
    data<-subset(data_ , data_$EVID==1)
    
    dat1 <- subset(data, data$CID==input$CID)
    
    newdata2 <- subset(data_ , data_$EVID==0)
    dat2 <- subset(newdata2, newdata2$CID==input$CID)
    dat2
  })
  
  #Hovering #
  
  output$plot_clickedpoints1 <- renderTable({
    #inFile <- input$file1
    inFile<-con()
    
    if (is.null(inFile)==TRUE) {print(NULL) }
    else if (is.null(inFile)==FALSE) {
      res <- nearPoints(con1(), input$plot_click,"RTFD","CONC", )
      if (nrow(res) == 0)
        return()
      res
    }})
  
  #Download Visulizations in PDF
  output$report = downloadHandler(
    
    filename = 'myreport.pdf',
    content = function(file) {
      data <-con()
      #install.packages("rmarkdown")
      library(rmarkdown)
      library(evaluate)
      library(pander)
      out <- render('inppk.Rmd',pdf_document())
      file.rename(out, file) 
    },
    contentType = 'application/pdf'
  )
  
}

#Final run#
shinyApp(ui = ui, server = server,options = list(launch.browser=TRUE))
     }
}
  sas2csv <- function() {
  library(shiny)
    library(miniUI)
    library(haven)
  library(foreign)
  library(DT)
    server <- function(input, output) {
      #Input the uploaded file to a reactive function#
      con<-reactive({
        inFile <- input$file1
        if (is.null(inFile))
          return(NULL)
        substrRight <- function(inFile, n){
          substr(inFile, nchar(inFile)-n+1, nchar(inFile))
        }

        type= substrRight(input$file1, 4)
        if(type==".xpt")
        {read.xport(inFile$datapath)}
        else {read_sas(inFile$datapath, catalog_file = NULL, encoding = NULL)}
      })

      #Input the contents as a table to visualize#
      df <- reactive({data <-con()})

      output$contents <- DT::renderDataTable( con(),filter = 'top')

      #Download data#
      output$downloadData <- downloadHandler(
        filename = function() { paste("data", '.csv', sep='') },
        content = function(file) {
          write.csv(df(), file)
        })
    }

    #########################
    #          ui.R         #
    #########################

    ui <- fluidPage(
      titlePanel("Convert .sas/.xpt to .csv file"),
      sidebarLayout(
        sidebarPanel(
          fileInput('file1', 'Choose .sas or .xpt File',
                    accept=c( '.sas7bdat','.sas','.xpt')),

          tags$hr(),
          downloadButton('downloadData', 'Download.csv')

        ),mainPanel( DT::dataTableOutput("contents"))
      ))
    # We'll use a pane viwer, and set the minimum height at
    # 300px to ensure we get enough screen space to display the clock.
    viewer <- paneViewer(300)
    runGadget( ui, server, viewer = viewer)
}
nm_dataviz <- function() {
  library(shiny)
  library(miniUI)
  library(ggplot2)
  ui <- fluidPage(
    titlePanel("NONMEM dataset visualization"),
    sidebarLayout(
      sidebarPanel(
        fileInput('file1', 'Choose CSV File',
                  accept=c('text/csv','text/comma-separated-values,text/plain', '.csv')),
        
        
        tags$hr(),
        checkboxInput('header', 'Header', TRUE),
        radioButtons('sep', 'Separator',c(Comma=',',Tab='\t'),','),
        selectInput( "TYPE", "Output Type", c("Individual","All Subjects")), uiOutput("DOSE"),uiOutput("PERIOD"),
        conditionalPanel(condition = "input.TYPE == 'Individual'",uiOutput("ID"))),
      #tags$hr(),
      mainPanel(
        conditionalPanel(condition= "input.TYPE == 'Individual'", plotOutput("plotind", height=300,click = "plot_click"),h4("Data points"),
                         tableOutput("plot_clickedpoints1")),
        conditionalPanel(condition= "input.TYPE == 'All Subjects'",plotOutput("plotcum", height=300,click = "plot_click"),h4("Data points"),
                         tableOutput("plot_clickedpoints2"))
      ))
  )
  server <-function(input, output, session) {
    library(ggplot2)
    con<-reactive({
      inFile <- input$file1
      if (is.null(inFile))
        return(NULL)
      data_<- read.csv(inFile$datapath)
      #data_<-read.csv(paste(inpath))
      
      head(data_)
      df<- data.frame(names(data_))
      df$names.data_.<-trimws(df$names.data_.)
      names(df)[names(df) == 'names.data_.'] <- 'varlist'
      
      #Renaming the input filenames to match standard names used in the code below#
      
      df$id<-row.names(df)
      
      head(df)
      
      for (i in 1:nrow(df)) {
        s <- subset(df , df$id==i)
        s1<-nrow(s)
        ifelse( s1==1,names(data_)[names(data_) == 'subj'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        ifelse( s1==1,names(data_)[names(data_) == 'SUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        ifelse( s1==1,names(data_)[names(data_) == 'subjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        ifelse( s1==1,names(data_)[names(data_) == 'usubjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        ifelse( s1==1,names(data_)[names(data_) == 'USUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        ifelse( s1==1,names(data_)[names(data_) == 'ID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        ifelse( s1==1,names(data_)[names(data_) == 'id'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
        #ifelse( s1==1,names(data_)[names(data_) == 'time'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
        #ifelse( s1==1,names(data_)[names(data_) == 'TIME'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
        ifelse( s1==1,names(data_)[names(data_) == 'ELMSTN'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
        ifelse( s1==1,names(data_)[names(data_) == 'elmstn'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
        ifelse( s1==1,names(data_)[names(data_) == 'RTFD'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
        ifelse( s1==1,names(data_)[names(data_) == 'rtfd'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
        ifelse( s1==1,names(data_)[names(data_) == 'conc'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
        ifelse( s1==1,names(data_)[names(data_) == 'CONC'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
        ifelse( s1==1,names(data_)[names(data_) == 'DV'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
        ifelse( s1==1,names(data_)[names(data_) == 'dv'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
        ifelse( s1==1,names(data_)[names(data_) == 'dose'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
        ifelse( s1==1,names(data_)[names(data_) == 'DOSE'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
        ifelse( s1==1,names(data_)[names(data_) == 'period'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'PERIOD'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'PER'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'per'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'COHORT'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'cohort'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'REG'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'reg'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'REGIMEN'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'regimen'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'ROUTE'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        ifelse( s1==1,names(data_)[names(data_) == 'route'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
      }
      
      data<-data_
    })
    
    output$ID <- renderUI({
      df <-con()
      if (is.null(df)) return(NULL)
      subj<-unique(df$subj)
      selectInput("subj", "subj:",subj)})
    
    #uiOutput("dose")#
    output$DOSE <- renderUI({
      df <-con()
      if (is.null(df)) return(NULL)
      dose<-unique(df$dose)
      selectInput("dose", "dose:",dose)})
    
    output$PERIOD <- renderUI({
      df <-con()
      if (is.null(df)) return(NULL)
      period<-unique(df$period)
      selectInput("period", "period:",period)})
    #Individual Plots#
    output$plotind <- renderPlot({
      inFile <- input$file1
      if (is.null(inFile)==TRUE) {print(NULL) }
      else if (is.null(inFile)==FALSE) {
        
        #data<-read.csv(inFile$datapath)
        data_<- read.csv(inFile$datapath)
        #data_<-read.csv(paste(inpath))
        #data_<-read.csv("C:/Users/pk153230/Desktop/Theo_data.csv")
        head(data_)
        df<- data.frame(names(data_))
        df$names.data_.<-trimws(df$names.data_.)
        names(df)[names(df) == 'names.data_.'] <- 'varlist'
        
        #Renaming the input filenames to match standard names used in the code below#
        
        df$id<-row.names(df)
        
        head(df)
        
        for (i in 1:nrow(df)) {
          s <- subset(df , df$id==i)
          s1<-nrow(s)
          ifelse( s1==1,names(data_)[names(data_) == 'subj'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'SUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'subjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'usubjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'USUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'ID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'id'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          #ifelse( s1==1,names(data_)[names(data_) == 'time'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          #ifelse( s1==1,names(data_)[names(data_) == 'TIME'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'ELMSTN'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'elmstn'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'RTFD'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'rtfd'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'conc'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'CONC'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'DV'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'dv'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'dose'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
          ifelse( s1==1,names(data_)[names(data_) == 'DOSE'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
          ifelse( s1==1,names(data_)[names(data_) == 'period'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'PERIOD'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'PER'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'per'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'COHORT'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'cohort'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'REG'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'reg'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'REGIMEN'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'regimen'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'ROUTE'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'route'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        }
        
        data<-data_
        #data$DV<-as.numeric(data$DV)& data$MDV !=1
        data1 <- subset(data ,data$subj == input$subj & data$dose==input$dose & data$period==input$period  )
        p1<-ggplot(data1, aes(x=data1$time,y=data1$conc,color=factor(data1$subj))) + geom_point()+
          ggtitle("Individual Concentration Vs Time (Lin-Lin) ") +
          labs(x="Time in hours (RTFD)",y="Concentartion in ng/L (DV)")
        p2 <- p1 + geom_point(color="blue") + geom_line() + theme_bw() +
          theme(axis.line = element_line(colour = "black"),
                panel.grid.major = element_blank(),
                panel.grid.minor = element_blank(),
                panel.background = element_blank(),
                legend.position = "none")
        p2
      }})
    output$plotcum <- renderPlot({
      inFile <- input$file1
      if (is.null(inFile)==TRUE) {print(NULL) }
      else if (is.null(inFile)==FALSE) {
        
        data_<- read.csv(inFile$datapath)
        #data_<-read.csv(paste(inpath))
        head(data_)
        df<- data.frame(names(data_))
        df$names.data_.<-trimws(df$names.data_.)
        names(df)[names(df) == 'names.data_.'] <- 'varlist'
        
        #Renaming the input filenames to match standard names used in the code below#
        
        df$id<-row.names(df)
        
        head(df)
        
        for (i in 1:nrow(df)) {
          s <- subset(df , df$id==i)
          s1<-nrow(s)
          ifelse( s1==1,names(data_)[names(data_) == 'subj'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'SUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'subjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'usubjid'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'USUBJID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'ID'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          ifelse( s1==1,names(data_)[names(data_) == 'id'] <- 'subj',names(data_)[names(data_) == 'subj'] <- 'subj')
          #ifelse( s1==1,names(data_)[names(data_) == 'time'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          #ifelse( s1==1,names(data_)[names(data_) == 'TIME'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'ELMSTN'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'elmstn'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'RTFD'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'rtfd'] <- 'time',names(data_)[names(data_) == 'time'] <- 'time')
          ifelse( s1==1,names(data_)[names(data_) == 'conc'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'CONC'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'DV'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'dv'] <- 'conc',names(data_)[names(data_) == 'conc'] <- 'conc')
          ifelse( s1==1,names(data_)[names(data_) == 'dose'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
          ifelse( s1==1,names(data_)[names(data_) == 'DOSE'] <- 'dose',names(data_)[names(data_) == 'dose'] <- 'dose')
          ifelse( s1==1,names(data_)[names(data_) == 'period'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'PERIOD'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'PER'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'per'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'COHORT'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'cohort'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'REG'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'reg'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'REGIMEN'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'regimen'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'ROUTE'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
          ifelse( s1==1,names(data_)[names(data_) == 'route'] <- 'period',names(data_)[names(data_) == 'period'] <- 'period')
        }
        
        data<-data_
        #data<-read.csv("W:/GSK2798745/TR4117387/Output/poppk_204725_19dec2016.csv")& data$MDV !=1& data$MDV !=1
        data1 <- subset(data , data$dose==input$dose & data$period==input$period  )
        # data1 <- subset(data , data$DOSE==2.4 & data$PERIOD==1 & data$MDV !=1 )& data$MDV !=1
        data1$conc<-as.numeric(data1$conc)
        p1<-ggplot(data1, aes(x=data1$time,y=data1$conc,color=factor(data1$subj))) + geom_point()+
          ggtitle("All Subjects Concentration Vs Time (Lin-Lin) ") +
          labs(x="Time in hours (RTFD)",y="Concentartion in ng/L (DV)")
        p2 <- p1 + geom_point(color="blue")+ geom_line() + theme_bw() +
          theme(axis.line = element_line(colour = "black"),
                panel.grid.major = element_blank(),
                panel.grid.minor = element_blank(),
                panel.background = element_blank(),
                legend.position = "none")
        p2
      }})
    con1<-reactive({
      
      
      data<-con()
      data1 <- subset(data ,data$subj == input$subj & data$dose==input$dose & data$period==input$period )
      # data1$DV<-as.numeric(data1$DV)
      data1
    })
    con2<-reactive({
      
      data<-con()
      data1 <- subset(data ,  data$dose==input$dose & data$period==input$period )
      #data1$DV<-as.numeric(data1$DV)
      data1
    })
    output$plot_clickedpoints1 <- renderTable({
      inFile <- input$file1
      if (is.null(inFile)==TRUE) {print(NULL) }
      else if (is.null(inFile)==FALSE) {
        res <- nearPoints(con1(), input$plot_click, "time","conc", )
        if (nrow(res) == 0)
          return()
        res
      }})
    output$plot_clickedpoints2 <- renderTable({
      inFile <- input$file1
      if (is.null(inFile)==TRUE) {print(NULL) }
      else if (is.null(inFile)==FALSE) {
        res <- nearPoints(con2(), input$plot_click, "time","conc", )
        if (nrow(res) == 0)
          return()
        res
      }})
  }

  viewer <- paneViewer(300)
  runGadget( ui, server, viewer = viewer)
}
#nm_dataviz()
#devtools::install()
#library(shinypkv)
#options="sas2csv"
#shiny_pkv(options="sas2csv")
#shiny_pkv(options="none")
#shiny_pkv(options="nm_dataviz")

dose_cvst <- function() {
  library(shiny)
  library(miniUI)
  library(ggplot2)
  library(rmarkdown)
  library(evaluate)
  library(pander)
  transparent_theme <- theme(
  axis.title.x = element_blank(),
  axis.title.y = element_blank(),
  axis.text.x = element_blank(), 
  axis.text.y = element_blank(),
  axis.ticks = element_blank(),
  panel.grid = element_blank(),
  axis.line = element_blank(),
  panel.background = element_rect(fill = "transparent",colour = NA),
  plot.background = element_rect(fill = "transparent",colour = NA))
#User interface#
#setwd("C:/Users/pk153230/Desktop/R-Demo/Archive/")
ui <- fluidPage(
  titlePanel("Conc Vs Time by Dose"),
  sidebarLayout(
    sidebarPanel(
      fileInput('file1', 'Choose CSV File',
                accept=c('text/csv','text/comma-separated-values,text/plain', '.csv')),
      
      
      tags$hr(),
      
      uiOutput("CID")),
    mainPanel(
      plotOutput("plotind", height=300,click = "plot_click"),
      h4("Data points"),
      tableOutput("plot_clickedpoints1"),
      tabsetPanel(
        tabPanel("Reporting", downloadButton('report','Download plots .pdf')))
    ))
)

#Server interface#

server <-function(input, output, session) {
  library(ggplot2)
  con<-reactive({
    inFile <- input$file1
    if (is.null(inFile))
      return(NULL)
    read.csv(inFile$datapath)
    
  }) 
  
  output$CID <- renderUI({
    df <-con()
    if (is.null(df)) return(NULL)
    CID<-unique(df$CID)
    selectInput("CID", "CID:",CID)})
  
  #plot ind function#
  
  output$plotind <- renderPlot({
    inFile <- input$file1
    if (is.null(inFile)==TRUE) {print(NULL) }
    else if (is.null(inFile)==FALSE) {
      library(ggplot2)
      transparent_theme <- theme(
        axis.title.x = element_blank(),
        axis.title.y = element_blank(),
        axis.text.x = element_blank(), 
        axis.text.y = element_blank(),
        axis.ticks = element_blank(),
        panel.grid = element_blank(),
        axis.line = element_blank(),
        panel.background = element_rect(fill = "transparent",colour = NA),
        plot.background = element_rect(fill = "transparent",colour = NA))
      #Create the graphs :
      data2<-read.csv(inFile$datapath) 
      #data2<- read.csv("W:/GSK1265744/LA200056-LATTE2/Output/PopPK.csv")
      data2$RTFD<-as.numeric(data2$RTFD)
      data2$CONC<-as.numeric(data2$CONC)
      data_ <- subset(data2 , DOSE!=-99)
      data<-subset(data_ , EVID==1)
      
      dat1 <- subset(data, CID==input$CID)
      #dat1 <- subset(data, CID==1)
      
      newdata2 <- subset(data_ , EVID==0)
      dat2 <- subset(newdata2, CID==input$CID)
      #dat2 <- newdata2
      
      library(ggplot2)
      p0<-ggplot(dat2, aes(x=dat2$RTFD, y=dat2$CONC)) + geom_point(shape =4) +
        labs(x="Relative Time from First Dose (Hrs)",y="Concentration (ng/L)") 
      p1 <- p0 + theme_bw() +
        theme(axis.line = element_line(colour = "black"),
              panel.grid.major = element_blank(),
              panel.grid.minor = element_blank(),
              panel.background = element_blank(),
              legend.position = "none")  
      p1 
      
      p2 <- ggplot(dat1, aes(x=dat1$RTFD, y=dat1$DOSE)) + geom_bar(stat = "identity", width=0.01,colour="green") +
        transparent_theme
      p2_grob = ggplotGrob(p2)
      
      p1 + annotation_custom(grob = p2_grob)
    }})

  con1<-reactive({
    data2<-con()
    data2$RTFD<-as.numeric(data2$RTFD)
    data2$CONC<-as.numeric(data2$CONC)
    data2$DOSE<-as.numeric(data2$DOSE)
    data_ <- subset(data2 , data2$DOSE!=-99)
    data<-subset(data_ , data_$EVID==1)
    
    dat1 <- subset(data, data$CID==input$CID)
    
    newdata2 <- subset(data_ , data_$EVID==0)
    dat2 <- subset(newdata2, newdata2$CID==input$CID)
    dat2
  })
  
  #Hovering #
  
  output$plot_clickedpoints1 <- renderTable({
    #inFile <- input$file1
    inFile<-con()
    
    if (is.null(inFile)==TRUE) {print(NULL) }
    else if (is.null(inFile)==FALSE) {
      res <- nearPoints(con1(), input$plot_click,"RTFD","CONC", )
      if (nrow(res) == 0)
        return()
      res
    }})
  
  #Download Visulizations in PDF
  output$report = downloadHandler(
    
    filename = 'myreport.pdf',
    content = function(file) {
      data <-con()
      #install.packages("rmarkdown")
      library(rmarkdown)
      library(evaluate)
      library(pander)
      out <- render('inppk.Rmd',pdf_document())
      file.rename(out, file) 
    },
    contentType = 'application/pdf'
  )
  
}

#Final run#
#shinyApp(ui = ui, server = server)
viewer <- paneViewer(300)
runGadget( ui, server, viewer = viewer)
}