inst/shiny-server/server/ERT_summary.R

# Data summary for Fixed-Target Runtime (ERT)  --------------
runtime_summary_condensed <- reactive({
  data <- DATA()
  req(length(data) > 0)
  # fall <- get_funvals(data)
  data <- subset(data, ID %in% input$RTSummary.Overview.ID)
  df <- get_FV_overview(data)
  df$budget %<>% as.numeric
  df$runs %<>% as.integer
  df$funcId %<>% as.integer
  df$DIM %<>% as.integer
  df$succ %<>% as.integer
  df$"worst recorded" <- format_FV(df$"worst recorded")
  df$"worst reached" <- format_FV(df$"worst reached")
  df$"mean reached" <- format_FV(df$"mean reached")
  df$"median reached" <- format_FV(df$"median reached")
  df$"best reached" <- format_FV(df$"best reached")
  df
})

output$table_RT_overview <- DT::renderDataTable({
  req(input$RTSummary.Overview.ID)
  runtime_summary_condensed()
}, filter = list(position = 'top', clear = FALSE),
options = list(dom = 'lrtip', pageLength = 15, scrollX = T, server = T))

output$RTSummary.Overview.Download <- downloadHandler(
  filename = function() {
    eval(RT_overview_name)
  },
  content = function(file) {
    df <- runtime_summary_condensed()
    df <- df[input[["table_RT_overview_rows_all"]]]
    save_table(df, file)
  }
)

# Data summary for Fixed-Target Runtime (ERT)  --------------
runtime_summary <- reactive({
  req(input$RTSummary.Statistics.Min,
      input$RTSummary.Statistics.Max,
      input$RTSummary.Statistics.Step)

  fstart <- format_FV(input$RTSummary.Statistics.Min)
  fstop <- format_FV(input$RTSummary.Statistics.Max)
  fstep <- format_FV(input$RTSummary.Statistics.Step)
  data <- DATA()
  data <- subset(data, ID %in% input$RTSummary.Statistics.ID)
  if (!input$RTSummary.Statistics.Single) {
    req(fstart <= fstop, fstep <= fstop - fstart, length(data) > 0)
    fall <- get_funvals(data)
    fseq <- seq_FV(fall, fstart, fstop, fstep)
    req(fseq)
  } else { 
    fseq <- fstart
  }

  df <- get_RT_summary(data, fseq)
  df <- df[, c('DIM', 'funcId') := NULL]
  df$target <- format_FV(df$target) %>% as.numeric

  # format the integers
  probs <- getOption("IOHanalyzer.quantiles")
  for (p in paste0(probs * 100, '%')) {
    df[[p]] %<>% as.integer
  }

  df$mean <- round(df$mean, digits = 2)
  df$sd <- round(df$sd, digits = 2)
  df$ERT <- round(df$ERT, digits = 2)
  df$ps <- round(df$ps, digits = 2)

  df$target <- format_FV(df$target)
  df
})

output$table_RT_summary <- DT::renderDataTable({
  runtime_summary()
}, filter = list(position = 'top', clear = FALSE),
options = list(dom = 'lrtip', pageLength = 10, scrollX = T, server = T))

output$RTSummary.Statistics.Download <- downloadHandler(
  filename = function() {
    eval(RT_csv_name)
  },
  content = function(file) {
    df <- runtime_summary()
    df <- df[input[["table_RT_summary_rows_all"]]]
    save_table(df, file)
  }
)

get_RT <- reactive({
  req(input$RTSummary.Sample.Min,
      input$RTSummary.Sample.Max,
      input$RTSummary.Sample.Step)

  fstart <- format_FV(input$RTSummary.Sample.Min)
  fstop <- format_FV(input$RTSummary.Sample.Max)
  fstep <- format_FV(input$RTSummary.Sample.Step)
  data <- DATA()
  data <- subset(data, ID %in% input$RTSummary.Sample.ID)
  if (!input$RTSummary.Sample.Single) {
    req(fstart <= fstop, fstep <= fstop - fstart, length(data) > 0)
    fall <- get_funvals(data)
    fseq <- seq_FV(fall, fstart, fstop, fstep)
    req(fseq)
  }
  else{
    fseq <- fstart
  }

  df <- get_RT_sample(data, ftarget = fseq,
                output = input$RTSummary.Sample.DownloadFormat)
  df$target <- format_FV(df$target)
  df[is.na(df)] <- 'NA'
  df
})

output$RTSummary.Sample.Download <- downloadHandler(
  filename = function() {
    eval(RTSample_csv_name)
  },
  content = function(file) {
    df <- get_RT()
    df <- df[input[["table_RT_sample_rows_all"]]]
    save_table(df, file)
    }
)

output$table_RT_sample <- DT::renderDataTable({
  df <- get_RT()
  df[is.na(df)] <- 'NA'
  df
}, filter = list(position = 'top', clear = FALSE),
options = list(dom = 'lrtip', pageLength = 10, scrollX = T, server = T))

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IOHanalyzer documentation built on Oct. 21, 2021, 5:06 p.m.