## Server.R
## MAIN FUNCTION
function(input, output, session) {
# input data (with default)
values <- reactiveValues(data_primary = if ("startData" %in% names(.GlobalEnv)) startData else ExampleData.DeValues$CA1,
data_secondary = setNames(as.data.frame(matrix(NA_real_, nrow = 5, ncol = 2)), c("x", "y")),
data = NULL,
args = NULL)
session$onSessionEnded(function() {
stopApp()
})
# check and read in file (DATA SET 1)
observeEvent(input$file1, {
inFile<- input$file1
if(is.null(inFile))
return(NULL) # if no file was uploaded return NULL
values$data_primary <- fread(file = inFile$datapath, data.table = FALSE) # inFile[1] contains filepath
})
# check and read in file (DATA SET 2)
observeEvent(input$file2, {
inFile<- input$file2
if(is.null(inFile))
return(NULL) # if no file was uploaded return NULL
values$data_secondary <- fread(file = inFile$datapath, data.table = FALSE) # inFile[1] contains filepath
})
### GET DATA SETS
observe({
### GET DATA
data <- list(values$data_primary, values$data_secondary)
data <- lapply(data, function(x) {
x_tmp <- x[complete.cases(x), ]
if (nrow(x_tmp) == 0) return(NULL)
else return(x_tmp)
})
data <- data[!sapply(data, is.null)]
data <- lapply(data, function(x) setNames(x, c("Dose", "Error")))
values$data <- data
})
output$table_in_primary <- renderRHandsontable({
rhandsontable(values$data_primary,
height = 300,
colHeaders = c("Dose", "Error"),
rowHeaders = NULL)
})
observeEvent(input$table_in_primary, {
# Workaround for rhandsontable issue #138
# https://github.com/jrowen/rhandsontable/issues/138
df_tmp <- input$table_in_primary
row_names <- as.list(as.character(seq_len(length(df_tmp$data))))
df_tmp$params$rRowHeaders <- row_names
df_tmp$params$rowHeaders <- row_names
df_tmp$params$rDataDim <- as.list(c(length(row_names),
length(df_tmp$params$columns)))
if (df_tmp$changes$event == "afterRemoveRow")
df_tmp$changes$event <- "afterChange"
if (!is.null(hot_to_r(df_tmp)))
values$data_primary <- hot_to_r(df_tmp)
})
output$table_in_secondary <- renderRHandsontable({
rhandsontable(values$data_secondary,
height = 300,
colHeaders = c("Dose", "Error"),
rowHeaders = NULL)
})
observeEvent(input$table_in_secondary, {
# Workaround for rhandsontable issue #138
# https://github.com/jrowen/rhandsontable/issues/138
df_tmp <- input$table_in_secondary
row_names <- as.list(as.character(seq_len(length(df_tmp$data))))
df_tmp$params$rRowHeaders <- row_names
df_tmp$params$rowHeaders <- row_names
df_tmp$params$rDataDim <- as.list(c(length(row_names),
length(df_tmp$params$columns)))
if (df_tmp$changes$event == "afterRemoveRow")
df_tmp$changes$event <- "afterChange"
if (!is.null(hot_to_r(df_tmp)))
values$data_secondary <- hot_to_r(df_tmp)
})
# dynamically inject sliderInput for central value
output$centValue<- renderUI({
centValue.data <- do.call(rbind, values$data)
sliderInput(inputId = "centValue",
label = "Central Value",
min = min(centValue.data[,1])*0.9,
max = max(centValue.data[,1])*1.1,
value = mean(centValue.data[,1]))
})## EndOf::renderUI()
# dynamically inject sliderInput for z-axis range
output$xlim<- renderUI({
xlim.data<- do.call(rbind, values$data)
if(input$logz == TRUE) {
sd<- xlim.data[,2] / xlim.data[,1]
} else {
sd<- xlim.data[,2]
}
prec<- 1/sd
sliderInput(inputId = "xlim",
label = "Range x-axis",
min = 0,
max = max(prec)*2,
value = c(0, max(prec)*1.05), round=FALSE, step=0.0001)
})## EndOf::renderUI()
# dynamically inject sliderInput for z-axis range
output$zlim<- renderUI({
zlim.data<- do.call(rbind, values$data)
sliderInput(inputId = "zlim",
label = "Range z-axis",
min = min(zlim.data[,1])*0.25,
max = max(zlim.data[,1])*1.75,
value = c(min(zlim.data[,1])*0.8, max(zlim.data[,1])*1.2))
})## EndOf::renderUI()
observe({
# refresh plot on button press
input$refresh
# make sure that input panels are registered on non-active tabs.
# by default tabs are suspended and input variables are hence
# not available
outputOptions(x = output, name = "zlim", suspendWhenHidden = FALSE)
outputOptions(x = output, name = "centValue", suspendWhenHidden = FALSE)
outputOptions(x = output, name = "xlim", suspendWhenHidden = FALSE)
# if custom datapoint color get RGB code from separate input panel
color <- ifelse(input$color == "custom", input$rgb, input$color)
if(!all(is.na(unlist(values$data_secondary)))) {
# if custom datapoint color get RGB code from separate input panel
if(input$color2 == "custom") {
color2<- input$rgb2
} else {
color2<- input$color2
}
} else {
color2<- adjustcolor("white", alpha.f = 0)
}
# if custom datapoint style get char from separate input panel
pch<- ifelse(input$pch == "custom", input$custompch, as.integer(input$pch)-1)
# if custom datapoint style get char from separate input panel
pch2<- ifelse(input$pch2 == "custom", input$custompch2, as.integer(input$pch2)-1)
# workaround to initialize plotting after app startup
centValue <- ifelse(is.null(input$centValue), 3000, input$centValue)
# create numeric vector of lines
line <- sapply(1:8, function(x) input[[paste0("line", x)]])
# create char vector of line colors
line.col <- sapply(1:8, function(x) input[[paste0("colline", x)]])
# create char vector of line labels
line.label <- sapply(1:8, function(x) input[[paste0("labline", x)]])
# if custom bar color get RGB from separate input panel or "none"
bar.col <- ifelse(input$bar == "custom",
adjustcolor(col = input$rgbBar,
alpha.f = input$alpha.bar/100),
ifelse(input$bar == "none",
input$bar,
adjustcolor(col = input$bar,
alpha.f = input$alpha.bar/100)))
# if custom bar color get RGB from separate input panel or "none"
# SECONDARY DATA SET
bar.col2 <- ifelse(input$bar2 == "custom",
adjustcolor(col = input$rgbBar2,
alpha.f = input$alpha.bar/100),
ifelse(input$bar2 == "none",
input$bar,
adjustcolor(col = input$bar2,
alpha.f = input$alpha.bar/100)))
# if custom grid color get RGB from separate input panel or "none"
grid.col <- ifelse(input$grid == "custom",
adjustcolor(col = input$rgbGrid,
alpha.f = input$alpha.grid/100),
ifelse(input$grid == "none",
input$grid,
adjustcolor(col = input$grid,
alpha.f = input$alpha.grid/100)))
# workaround: if no legend wanted set label to NA and hide
# symbol on coordinates -999, -999
if(input$showlegend == FALSE) {
legend<- c(NA,NA)
legend.pos<- c(-999,-999)
} else {
if(!all(is.na(unlist(values$data_secondary))))
{
legend<- c(input$legendname, input$legendname2)
legend.pos<- input$legend.pos
} else {
legend<- c(input$legendname, "")
legend.pos<- input$legend.pos
}
}
# plot radial Plot
values$args <- list(
data = values$data,
xlim = input$xlim,
zlim = input$zlim,
xlab = c(input$xlab1, input$xlab2),
ylab = input$ylab,
zlab = input$zlab,
y.ticks = input$yticks,
grid.col = grid.col,
bar.col = c(bar.col, bar.col2),
pch = c(pch,pch2),
col = c(color,color2),
line = line,
line.col = line.col,
line.label = line.label,
main = input$main,
cex = input$cex,
mtext = input$mtext,
log.z = input$logz,
stats = input$statlabels,
plot.ratio = input$curvature,
summary = if (input$summary) input$stats else NA,
summary.pos = input$sumpos,
legend = legend,
legend.pos = legend.pos,
na.rm = TRUE,
central.value = input$centValue,
centrality = input$centrality,
lwd = c(input$lwd, input$lwd2),
lty = c(as.integer(input$lty), as.integer(input$lty2)))
})
# render Radial Plot
output$main_plot <- renderPlot({
# validate(need()) makes sure that all data are available to
# renderUI({}) before plotting and will wait until there
validate(
need(expr = input$centValue, message = 'Waiting for data... Please wait!'),
need(expr = input$zlim, message = 'Waiting for data... Please wait!')
)
do.call(plot_RadialPlot, args = values$args)
})##EndOf::renderPlot({})
observe({
# nested renderText({}) for code output on "R plot code" tab
code.output <- callModule(RLumShiny:::printCode, "printCode", n_input = 2,
fun = "plot_RadialPlot(data,", args = values$args)
output$plotCode<- renderText({
code.output
})##EndOf::renderText({})
callModule(RLumShiny:::exportCodeHandler, "export", code = code.output)
callModule(RLumShiny:::exportPlotHandler, "export", fun = "plot_RadialPlot", args = values$args)
})
# renderTable() that prints the data to the second tab
output$dataset<- renderDataTable(
options = list(pageLength = 10, autoWidth = FALSE),
callback = "function(table) {
table.on('click.dt', 'tr', function() {
$(this).toggleClass('selected');
Shiny.onInputChange('rows',
table.rows('.selected').values$data.toArray());
});
}",
{
data<- values$data[[1]]
colnames(data)<- c("De","De error")
data
})##EndOf::renterTable()
# renderTable() that prints the secondary data to the second tab
output$dataset2<- renderDataTable(
options = list(pageLength = 10, autoWidth = FALSE),
callback = "function(table) {
table.on('click.dt', 'tr', function() {
$(this).toggleClass('selected');
Shiny.onInputChange('rows',
table.rows('.selected').values$data.toArray());
});
}",
{
if(!all(is.na(unlist(values$data_secondary)))) {
data<- values$data[[2]]
colnames(data)<- c("De","De error")
data
} else {
}
})##EndOf::renterTable()
# renderTable() to print the results of the
# central age model (CAM)
output$CAM<- renderDataTable(
options = list(pageLength = 10, autoWidth = FALSE),
{
data <- values$data
t<- as.data.frame(matrix(nrow = length(data), ncol = 7))
colnames(t)<- c("Data set","n", "log data", "Central dose", "SE abs.", "OD (%)", "OD error (%)")
res<- lapply(data, function(x) { calc_CentralDose(x, verbose = FALSE, plot = FALSE) })
for(i in 1:length(res)) {
t[i,1]<- ifelse(i==1,"pimary","secondary")
t[i,2]<- length(res[[i]]@data$data[,1])
t[i,3]<- res[[i]]@data$args$log
t[i,4:7]<- round(res[[i]]@data$summary[1:4],2)
}
t
})##EndOf::renterTable()
}##EndOf::shinyServer(function(input, output)
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