speed up start of app

[uwesterr]

move libraries to optimizingChain.R find reason why plots are always created twice

[uwesterr]

reason for double plots was that

The input updater functions send a message to the client, telling it to change the settings of an input object. The messages are collected and sent after all the observers (including outputs) have finished running. could be solved by adding sliderUpdate to rkiAndPredictData <- reactive({ and adding

###### set values according to optimized values ############ 
RkiDataWithR0N0 <- r0_no_erfasstDf() %>% unnest(data)
OptResultDf <- RkiDataWithR0N0[[1,"optimizedInput"]]
isolate(inputForOptimization <- input) # to make setting reduzierung_rtx easy and fast

for (inputVarName in OptResultDf[[1]] %>% names) {
  print("for (inputVarName in OptResultDf[[1]] %>% names) {")

  if (inputVarName %in% (isolate(inputForOptimization %>% names))) {
    if (inputVarName %in% (str_subset(isolate(inputForOptimization %>% names), "reduzierung"))) {
      (updateSliderInput(session, inputVarName, value = OptResultDf[[1]][[inputVarName]]))
    } else {
      (updateNumericInput(session, inputVarName, value = round(OptResultDf[[1]][[inputVarName]],1)))
    }
  }
}
### set input values since update function send data only after plots are generated
#browser()
OptResultDf <- RkiDataWithR0N0[[1,"optimizedInput"]]
inputForOptimization <-  isolate(reactiveValuesToList(input)) # to make setting reduzierung_rtx easy and fast
for (inputVarName in OptResultDf[[1]] %>% names) {
  if (inputVarName %in% (inputForOptimization %>% names)) {
    inputForOptimization[[inputVarName]]<- OptResultDf[[1]][[inputVarName]] 
  }
}

fixed in commit https://github.com/uwesterr/CoronaPredict/commit/0c50af234a6a27baa30ef1bdbe36ee3b0310d7fe

[uwesterr]

tools to help profvis({runApp()}) which shows that most time is spend in ggplotly

um das doppelte aufrufen zu eliminieren hilft das tool reactlog https://rstudio.github.io/reactlog/?_ga=2.128972495.2110847215.1589012676-10469058.1589012676