Nothing
### Generate ERT table
ERTPlot.Aggr.ERTs_obj <- reactive({
input$ERTPlot.Aggr.Refresh
dsList <- isolate(ERTPlot.Aggr.data())
if (is.null(dsList)) return(NULL)
aggr_on <- 'funcId'
targets <- isolate(ERTPlot.Aggr.Targets_obj)
dt <- generate_data.Aggr(dsList, aggr_on = aggr_on, targets = targets)
dt
})
### Plot the data
render_ERTPlot_aggr_plot <- reactive({
withProgress({
y_attr <- if (input$ERTPlot.Aggr.Ranking) 'rank' else 'value'
y_title <- if (input$ERTPlot.Aggr.Ranking) 'Rank' else 'ERT'
reverse_scale <- input$ERTPlot.Aggr.Mode == 'radar'
dt <- ERTPlot.Aggr.ERTs_obj()
if (is.null(dt))
return(NULL)
dt <- dt[funcId %in% isolate(input$ERTPlot.Aggr.Funcs), ]
plot_general_data(dt, type = input$ERTPlot.Aggr.Mode, x_attr = 'funcId',
y_attr = y_attr, x_title = "FuncId", y_title = y_title, show.legend = T,
scale.ylog = input$ERTPlot.Aggr.Logy, scale.reverse = reverse_scale,
inf.action = 'jitter')
},
message = "Creating plot")
})
### Gather relevant datasetlist
ERTPlot.Aggr.data <- function() {
data <- subset(DATA_RAW(), ID %in% isolate(input$ERTPlot.Aggr.Algs))
if (length(data) == 0) return(NULL)
data <- subset(data, DIM == input$Overall.Dim)
if (length(unique(get_funcId(data))) == 1) {
shinyjs::alert("This plot is only available when the dataset contains
multiple functions for the selected dimension.")
return(NULL)
}
if (length(unique(get_id(data))) == 1) {
shinyjs::alert("This plot is only available when the dataset contains
multiple IDs for the selected dimension.")
return(NULL)
}
data
}
### format table for display
ert_multi_function <- function() {
dt <- ERTPlot.Aggr.ERTs_obj()
dt <- dcast(dt, funcId~ID, value.var = 'value')
format(dt, digits = 4)
}
### Table with default targets
default_targets_table <- reactive({
data <- ERTPlot.Aggr.data()
if (is.null(data)) return(NULL)
targets <- get_target_dt(data, which = 'by_FV')
targets <- targets[, c('funcId','target')]
# %>% melt(id.vars = 'funcId') %>% dcast(variable ~ funcId)
# targets <- targets[, 'variable' = NULL]
# rownames(targets) <- 'funcId'
# targets
})
### Target table object
ERTPlot.Aggr.Targets_obj <- NULL
### Target table proxy
proxy_ERTPlot.Aggr.Targets <- dataTableProxy('ERTPlot.Aggr.Targets')
### Target table print
output$ERTPlot.Aggr.Targets <- DT::renderDataTable({
req(length(DATA_RAW()) > 0)
ERTPlot.Aggr.Targets_obj <<- default_targets_table()
ERTPlot.Aggr.Targets_obj
}, editable = TRUE, rownames = FALSE,
options = list(pageLength = 5, lengthMenu = c(5, 10, 25, -1), scrollX = T, server = T))
### Target table edit
observeEvent(input$ERTPlot.Aggr.Targets_cell_edit, {
info <- input$ERTPlot.Aggr.Targets_cell_edit
i <- info$row
req(i > 0)
j <- info$col + 1
v <- info$value
ERTPlot.Aggr.Targets_obj[i, j] <<-
DT::coerceValue(v, ERTPlot.Aggr.Targets_obj[['target']][[i]])
replaceData(proxy, ERTPlot.Aggr.Targets_obj, resetPaging = FALSE, rownames = FALSE)
})
### Table output
output$ERTPlot.Aggr.ERTTable <- DT::renderDataTable({
input$ERTPlot.Aggr.Refresh
req(length(DATA_RAW()) > 0)
withProgress({
dt <- ert_multi_function()
},
message = "Creating table")
dt
}, editable = FALSE, rownames = TRUE,
options = list(pageLength = 5, lengthMenu = c(5, 10, 25, -1), scrollX = T, server = T))
### plot output
output$ERTPlot.Aggr.Plot <- renderPlotly(
render_ERTPlot_aggr_plot()
)
### Download table
output$ERTPlot.Aggr.DownloadTable <- downloadHandler(
filename = function() {
eval(ERT_multi_func_name)
},
content = function(file) {
df <- ert_multi_function()
save_table(df, file)
}
)
### Download plot
output$ERTPlot.Aggr.Download <- downloadHandler(
filename = function() {
eval(FIG_NAME_ERT_AGGR)
},
content = function(file) {
save_plotly(render_ERTPlot_aggr_plot(), file)
},
contentType = paste0('image/', input$ERTPlot.Aggr.Format)
)
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