Nothing
#' 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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