inst/myappp/server.R

#'   a <- m_q_c_vector_from_M_Q_C(2,3,4)
#'
#'   a$m
#'   a$q
#'   a$c
#' #'
#' DF<-data.frame(
#'   m =m_q_c_vector_from_M_Q_C(M,Q,C)$m,
#'   q=m_q_c_vector_from_M_Q_C(M,Q,C)$q,
#'   c=m_q_c_vector_from_M_Q_C(M,Q,C)$c
#'   # h=ddd$h,
#'   # f=ddd$f
#' )
#
# C<-ddd$C
# M<-ddd$M
# Q<-ddd$Q



server <- shiny::shinyServer(function(input, output) {



  # This is use such as fit() instesad of fit
  fit <-shiny::reactive({

    # fit <- BayesianFROC::fit_Bayesian_FROC(
    #   ite  = input$Number_of_MCMC_samples,
    #   cha =  input$Number_of_MCMC_chains,
    #   summary = T,
    #   Null.Hypothesis = F,
    #   dataList = values[["dataList"]],# input$selected_data ,
    #
    #   DrawCurve = F,
    #   dig = 5)
    #
    # return(fit)

  })




  values <- shiny::reactiveValues()

  ## Handsontable
  shiny::observe({
    if (!is.null(input$hot)) {
      DF = rhandsontable::hot_to_r(input$hot)
    } else {
      if (is.null(values[["DF"]]))
        DF <- DF
      else
        DF <- values[["DF"]]
    }
    values[["DF"]] <- DF
    values[["dataList"]] <- list(NL=input$Number_of_lesions,
                                 NI=input$Number_of_images,
                                 h=DF$h,
                                 f=DF$f,
                                 m=DF$m,
                                 q=DF$q,
                                 c=DF$c,
                                 C=input$C,
                                 M=input$M,
                                 Q=input$Q


    )

  })

  output$hot <- rhandsontable::renderRHandsontable({
    DF <- values[["DF"]]
    if (!is.null(DF))
      rhandsontable::rhandsontable(DF,
                                   # useTypes = as.logical(input$useType),
                                   stretchH = "all")

  })

  ## Save
  # shiny::observeEvent(input$save, {
  #   finalDF <- isolate(values[["DF"]])
  #   # saveRDS(finalDF, file=file.path(outdir, sprintf("%s.rds", outfilename)))
  #
  #
  #
  #
  #
  # })


  output$print_fit <- shiny::renderPrint({

      fitt <-methods::as(fit(), "stanfit")
      print( fitt, digits = 4)

                    })# shiny::renderPrint






})

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BayesianFROC documentation built on Jan. 23, 2022, 9:06 a.m.