R/utils_updating.R

In epiforecasts/crowdforecastr: Eliciting crowd forecasts in R shiny

# 
# update_values <- function(id_prefix = "prediction_", forecast, 
#                           num_horizons, session) {
#   
#   # turn latent values into values that are actually stored
#   forecast$median <- forecast$median_latent
#   forecast$width <- forecast$width_latent
#   
#   lapply(1:num_horizons,
#          FUN = function(i) {
#            # update numeric inputs. this could be necessary if we update the baseline
#            updateNumericInput(inputId = paste0(id_prefix, i, "-median"),
#                               session = session,
#                               value = forecast$median[i])
#            
#            updateNumericInput(inputId = paste0(id_prefix, i, "-width"),
#                               session = session,
#                               value = forecast$width[i])
#          })
# }
# 
# # for (i in steps) {
# #   
# #   # rv[[paste0("forecasts_week_", i)]] <<- qlnorm(quantile_grid, 
# #   #                                               meanlog = log(rv$median[i]), 
# #   #                                               sdlog = as.numeric(rv$width[i]))
# #   
# #   if (input$distribution == "log-normal") {
# #     rv[[paste0("forecasts_week_", i)]] <<- exp(qnorm(quantile_grid, 
# #                                                      mean = log(rv$median[i]),
# #                                                      sd = as.numeric(rv$width[i])))
# #   } else if (input$distribution == "normal") {
# #     rv[[paste0("forecasts_week_", i)]] <<- (qnorm(quantile_grid, 
# #                                                   mean = (rv$median[i]),
# #                                                   sd = as.numeric(rv$width[i])))
# #     
# #   } else if (input$distribution == "cubic-normal") {
# #     rv[[paste0("forecasts_week_", i)]] <<- (qnorm(quantile_grid, 
# #                                                   mean = (rv$median[i]) ^ (1 / 3),
# #                                                   sd = as.numeric(rv$width[i]))) ^ 3
# #   } else if (input$distribution == "fifth-power-normal") {
# #     rv[[paste0("forecasts_week_", i)]] <<- (qnorm(quantile_grid, 
# #                                                   mean = (rv$median[i]) ^ (1 / 5),
# #                                                   sd = as.numeric(rv$width[i]))) ^ 5
# #   } else if (input$distribution == "seventh-power-normal") {
# #     rv[[paste0("forecasts_week_", i)]] <<- (qnorm(quantile_grid, 
# #                                                   mean = (rv$median[i]) ^ (1 / 7),
# #                                                   sd = as.numeric(rv$width[i]))) ^ 7
# #   }