Merge branch 'master' of https://gitlab.gwdg.de/gross47/optimlanduse_shiny

app.R

-library(shiny)
-
-ui <- source("./ui.R")
-server <- source("./server.R")
-
-shinyApp(ui = ui, server = server)
\ No newline at end of file

calcDistanceToPerformanceScenario.R

-##--#####################################################--##
-#### Attach portfolio performance and distance to target ####
-##--#####################################################--##
-# Wed Jan 29 16:19:22 2020 ------------------------------
-# Kai Husmann
-
-#' Attach portfolio performance and distance to target
-#'
-#' The function calculates and attaches the portfolio performance and distance to target. See Gosling et al. Equations 10 and 11.
-#' @param x An optimized optimLanduse object.
-
-#'@export
-calcDistanceToPerformanceScenario <- function(x) {
-
-  if(!all(names(x$scenarioTable[, startsWith(names(x$scenarioTable), "adj")]) ==
-          paste0("adjSem", names(x$landUse)))) {
-    cat("Error: Unexpected variables in the scenario table.")
-  }
-
-  if(!x$status == "optimized") {cat("Error: No optimim found. Did you call solveScenario?")}
-  #---------------------------------#
-  #### Add portfolio performance ####
-  #---------------------------------#
-
-  # See e.g. Gosling et al. Eq. 10
-
-  #rep(averageNomimalIndicatorValue[1 ,], each = dim(scenarioTable)[1])
-
-  x$scenarioTable$portfolioPerformance <- apply(do.call(rbind, replicate(dim(x$scenarioTable)[1],
-                                                                         x$landUse[1 ,], simplify = FALSE)) *
-                                                  x$scenarioTable[, startsWith(names(x$scenarioTable), "adj")], 1, sum)
-
-  #------------------------------------------#
-  #### Add distance to target performance ####
-  #------------------------------------------#
-
-  # See. e.g. Gosling et al. Eq. 11
-  x$scenarioTable <- x$scenarioTable %>% mutate(distanceToTargetPerformance = 1 - ifelse(direction == "more is better",
-                                                                                           ((portfolioPerformance - minAdjSem) / diffAdjSem),
-                                                                                           ((maxAdjSem - portfolioPerformance) / diffAdjSem)))
-
-  x$status <- "optimized - information updated"
-
-  return(x)
-
-}

rsconnect/shinyapps.io/vongross/applicationOfThePackage.dcf

-name: applicationOfThePackage
-title: applicationOfThePackage
-username:
-account: vongross
-server: shinyapps.io
-hostUrl: https://api.shinyapps.io/v1
-appId: 2497473
-bundleId: 3310870
-url: https://vongross.shinyapps.io/applicationOfThePackage/
-when: 1593001607.9347
-asMultiple: FALSE
-asStatic: FALSE
-ignoredFiles: A|B|tt-frim-home.RData|3 performanceTest/applyPackage.R|1 simulateDataSource|2 applyOptimizations

rsconnect/shinyapps.io/vongross/app_1.dcf → rsconnect/shinyapps.io/vongross/optimlanduse_shiny.dcf

-name: app_1
+name: optimlanduse_shiny
 title:
 username:
 account: vongross
 server: shinyapps.io
 hostUrl: https://api.shinyapps.io/v1
-appId: 2497524
-bundleId: 3311994
-url: https://vongross.shinyapps.io/app_1/
-when: 1593017851.0568
-asMultiple: FALSE
-asStatic: FALSE
+appId: 3090351
+bundleId: 3780081
+url: https://vongross.shinyapps.io/optimlanduse_shiny/
+when: 1603629504.65333

server.R

-# 
-# dat <- read_excel("database.xlsx", sheet = "data", col_names = FALSE)
-# 
-# dataSource <- datainput(dat, uncertainty = "sd")
-# 
-# dataSource <- dataSource %>% filter(branch == "Ecology" | branch == "Economics")
+
 
 server <- function(input, output, session) {
   

ui.R

+
 #---#################################################################---#
 #### Try to apply the stepwise linear approach on the Indonesia Data ####
 #---#################################################################---#
@@ -20,34 +21,20 @@
 #### Load data and functions ####
 #-------------------------------#
 source("initScenario.R")
-source("calcDistanceToPerformanceScenario.R")
-source("helper.R")
 source("solveScenario.R")
+source("helper.R")
 source("functions.R")
 
 library(lpSolveAPI)
-library(tidyverse)
-library(readxl)
-library(writexl)
 library(shiny)
 library(rsconnect)
-library(shinyWidgets)
-library(stringr)
-library(png)
 library(shinyjs)
-library(DT)
-library(visNetwork)
-library(rintrojs)
 
 
 #-----------------#
 #### Load data ####
 #-----------------#
-# dat <- read_excel("database.xlsx", sheet = "data", col_names = FALSE)
-# 
-# dataSource <- datainput(dat, uncertainty = "sd")
-# 
-# dataSource <- dataSource %>% filter(branch == "Ecology" | branch == "Economics")
+
 
 ui <- navbarPage(title = img(src="Logo_TUM_GOE.jpg", height = "40px", width = "250px"), id = "navBar",
                  theme = "test.css",