#Текст программы на языке программирования R.
#Файлы с выборкой не вошли в 10 предложенных мб по правилам заявки.
#Если необходимо предоставить выборку, просьба написать по почте maska0218@gmail.com
library(shiny)
library(plotly)

if(Sys.getenv('SHINY_PORT') == "") options(shiny.maxRequestSize=10000*1024^2)

ui <- fluidPage(
  
  sidebarLayout(
    
    sidebarPanel(
      
      
      fileInput("nn", "Choose CSV file",
                multiple = TRUE,
                accept = c("text/csv",
                           "text/comma-separated-values,text/plain",
                           ".csv")),
      
      sliderInput("slaedr1", "spar",
                  min = 0, max = 1,
                  value = c(0.3)),
      
      uiOutput("ui"),
      uiOutput("uui")
    ),
    
    
    mainPanel(
      
      tabsetPanel(type = "tabs",
                  tabPanel("Один параметр для выбранного пациента", plotlyOutput("Plot1")),
                  tabPanel("R5 для одного человека", plotlyOutput("Plot1a")),
                  tabPanel("Выбранный параметр для одного пациента", plotlyOutput("Plot11")),
                  tabPanel("Изменение сопротивления R5", plotlyOutput("Plot111")),
                  tabPanel("R5 и изменение сопротивления R5", plotlyOutput("Plot111a"))
      )
    )
  )
)

server <- function(input, output) {
  n <- reactive({
    read.csv(input$nn$datapath, dec = ',',header = TRUE, sep = ';', stringsAsFactors = FALSE)
  })
  
  output$ui <- renderUI({
    if(!is.null(input$nn))
    {
      selectInput("patients", "Patients",
                  choices = unique(n()$'Name'),
                  multiple = TRUE,
                  selected = c('А***ин С***ан'))
    }
  })
  
  output$uui <- renderUI({
    if(!is.null(input$nn))
    {
      selectInput("parameters", "Parameters",
                  choices = names(n()),
                  multiple = TRUE,
                  selected = c('R5_L.L.', 'R5_R.L.')
      )
    }
  })
  
  output$'Plot1' <- renderPlotly({
    if(!is.null(input$nn))
    {
      n1 = n()
      p <- plot_ly()
      for (param in input$parameters)
      {
        y1 = n1[n1[,'Name'] == input$patients, param]
        p <- add_trace(p, x = seq(1, nrow(n1[n1$'Name' == input$patients,]), 1)*2, y = (y1-y1[1])/y1[1]*100, type = "scatter", mode = "markers", name = param)
      }
      
      for (param in input$parameters)
      {
        X = seq(1, nrow(n1[n1$'Name' == input$patients,]), 1)
        Y = n1[n1[,'Name'] == input$patients, param]
        ad <- smooth.spline(Y, spar = input$slaedr1)
        nad = predict(ad, X)$y
        p <- add_trace(p, x = X*2, y = (nad-nad[1])/nad[1]*100, type = "scatter", mode = "lines", name = param)
      }
      p <- layout(p, title = list(title = "Один параметр для выбранного пациента"), xaxis = list(title = "Time (sec)"), yaxis = list(title = "Resistance (mOm)"))
      p
    }
    else
      plot_ly()
  })
  
  output$'Plot1a' <- renderPlotly({
    if(!is.null(input$nn))
    {
      n1 = n()
      p <- plot_ly()
      for (nnn in input$patients)
      {
        y1 = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        y2 = n1[n1[,'Name'] == nnn, 'R5_R.L.']
        p <- add_trace(p, x = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)*2, y = (y1-y1[1])/y1[1]*1000, type = "scatter", mode = "markers", name = "")
        p <- add_trace(p, x = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)*2, y = (y2-y2[1])/y2[1]*1000, type = "scatter", mode = "markers", name = "")
        X = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)
        Y1 = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        Y2 = n1[n1[,'Name'] == nnn, 'R5_R.L.']
        ad1 <- smooth.spline(Y1, spar = input$slaedr1)
        ad2 <- smooth.spline(Y2, spar = input$slaedr1)
        nad1 = predict(ad1, X)$y
        nad2 = predict(ad2, X)$y
        p <- add_trace(p, x = X*2, y = (nad1-nad1[1])/nad1[1]*1000, type = "scatter", mode = "lines", name = "")
        p <- add_trace(p, x = X*2, y = (nad2-nad2[1])/nad2[1]*1000, type = "scatter", mode = "lines", name = "")
      }
      p <- layout(p, title = list(title = "R5 для одного человека"), xaxis = list(title = "Time (sec)"), yaxis = list(title = "Resistance (mOm)"))
      p
    } 
    else
      plot_ly()
  })
  
  output$'Plot111' <- renderPlotly({
    if(!is.null(input$nn))
    {
      n1 = n()
      p <- plot_ly()
      for (nnn in input$patients)
      {
        deltn = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        delta = deltn[1]
        X = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)
        Y1 = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        Y2 = n1[n1[,'Name'] == nnn, 'R5_R.L.']
        ad1 <- smooth.spline(Y1, spar = input$slaedr1)
        ad2 <- smooth.spline(Y2, spar = input$slaedr1)
        nad1 = predict(ad1, X)$y
        nad2 = predict(ad2, X)$y
        sd1 = (nad2-nad2[1])/nad2[1]-(nad1-nad1[1])/nad1[1]
        yy = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        yy1 = n1[n1[,'Name'] == nnn, 'R5_R.L.']
        y1 = (yy1-yy1[1])/yy1[1]-(yy-yy[1])/yy[1]
        p <- add_trace(p, x = X*2, y = y1*1000, type = "scatter", mode = "markers", name = "")
        p <- add_trace(p, x = X*2, y = sd1*1000, type = "scatter", mode = "lines", name = "")
      }
      p <- layout(p, title = list(title = ""), xaxis = list(title = "Time (sec)"), yaxis = list(title = "Resistance (mOm)"))
      p
    }
    else
      plot_ly()
  })
  
  output$'Plot111a' <- renderPlotly({
    if(!is.null(input$nn))
    {
      n1 = n()
      p <- plot_ly()
      for (nnn in input$patients)
      {
        deltn = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        delta = deltn[1]
        X = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)
        Y1 = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        Y2 = n1[n1[,'Name'] == nnn, 'R5_R.L.']
        ad1 <- smooth.spline(Y1, spar = input$slaedr1)
        ad2 <- smooth.spline(Y2, spar = input$slaedr1)
        nad1 = predict(ad1, X)$y
        nad2 = predict(ad2, X)$y
        sd1 = (nad2-nad2[1])/nad2[1]-(nad1-nad1[1])/nad1[1]
        yy = n1[n1[,'Name'] == nnn, 'R5_L.L.']
        yy1 = n1[n1[,'Name'] == nnn, 'R5_R.L.']
        y1 = (yy1-yy1[1])/yy1[1]-(yy-yy[1])/yy[1]
        p <- add_trace(p, x = X*2, y = y1*1000, type = "scatter", mode = "markers", name = "")
        p <- add_trace(p, x = X*2, y = sd1*1000, type = "scatter", mode = "lines", name = "")
      }
      y1 = n1[n1[,'Name'] == input$patients, 'R5_L.L.']
      y2 = n1[n1[,'Name'] == input$patients, 'R5_R.L.']
      p <- add_trace(p, x = seq(1, nrow(n1[n1$'Name' == input$patients,]), 1)*2, y = (y1-y1[1])/y1[1]*1000, type = "scatter", mode = "markers", name = "R5 L.L.")
      p <- add_trace(p, x = seq(1, nrow(n1[n1$'Name' == input$patients,]), 1)*2, y = (y2-y2[1])/y2[1]*1000, type = "scatter", mode = "markers", name = "R5 R.L.")
      X = seq(1, nrow(n1[n1$'Name' == input$patients,]), 1)
      Y1 = n1[n1[,'Name'] == input$patients, 'R5_L.L.']
      Y2 = n1[n1[,'Name'] == input$patients, 'R5_R.L.']
      ad1 <- smooth.spline(Y1, spar = input$slaedr1)
      ad2 <- smooth.spline(Y2, spar = input$slaedr1)
      nad1 = predict(ad1, X)$y
      nad2 = predict(ad2, X)$y
      p <- add_trace(p, x = X*2, y = (nad1-nad1[1])/nad1[1]*1000, type = "scatter", mode = "lines", name = "R5 L.L.")
      p <- add_trace(p, x = X*2, y = (nad2-nad2[1])/nad2[1]*1000, type = "scatter", mode = "lines", name = "R5 R.L.")
      p <- layout(p, title = list(title = ""), xaxis = list(title = "Time (sec)"), yaxis = list(title = "Resistance (mOm)"))
      p
    }
    else
      plot_ly()
  })
  
  output$'Plot11' <- renderPlotly({
    if(!is.null(input$nn))
    {
      n1 = n()
      p <- plot_ly()
      for (nnn in input$patients)
      {
        X = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)
        Y = n1[n1$'Name' == nnn, input$parameters]
        ad <- smooth.spline(Y, spar = input$slaedr1)
        nad = predict(ad, X)$y
        y1 = n1[n1$'Name' == nnn, input$parameters]
        p <- add_trace(p, x = seq(1, nrow(n1[n1$'Name' == nnn,]), 1)*2, y = (y1-y1[1])/y1[1]*1000, type = "scatter", mode = "markers", name = "")
        p <- add_trace(p, x = X*2, y = (nad-nad[1])/nad[1]*1000, type = "scatter", mode = "lines", name = "")
      }
      p <- layout(p, title = list(title = "Выбранный параметр для одного пациента"), xaxis = list(title = "Time (sec)"), yaxis = list(title = "Resistance (mOm)"))
      p
    }
    else
      plot_ly()
  })
}
shinyApp(ui,server)