From 45d27977f6ca77d9951ebe18bb46da766734deb3 Mon Sep 17 00:00:00 2001
From: thierrychambert <thierry.chambert@gmail.com>
Date: Wed, 11 Aug 2021 17:00:57 +0200
Subject: [PATCH] Thies version of Shiny works (thierry branch) !
---
inst/ShinyApp/server.R | 11 +-
inst/ShinyApp/server_old.R | 605 -------------------------------------
inst/ShinyApp/ui_old.R | 389 ------------------------
3 files changed, 5 insertions(+), 1000 deletions(-)
delete mode 100644 inst/ShinyApp/server_old.R
delete mode 100644 inst/ShinyApp/ui_old.R
diff --git a/inst/ShinyApp/server.R b/inst/ShinyApp/server.R
index fbb0a94..0a01155 100644
--- a/inst/ShinyApp/server.R
+++ b/inst/ShinyApp/server.R
@@ -553,15 +553,14 @@ server <- function(input, output, session){
nrow <- input$farm_number_cumulated
number_parks <- rows_names(nrow)
- # data_fatalities_cumulated <- c(c(input$fatalities_mat_cumulated[,1]),
- # c(input$fatalities_mat_cumulated[,2]),
- # c(input$fatalities_mat_cumulated[,3]))
+
+ init_cumul_new <- rep(init_cumul_add, nrow)
updateMatrixInput(session, inputId = "fatalities_mat_cumulated",
- value = matrix("", nrow = nrow, 3,
+ value = matrix(init_cumul_new, nrow = nrow, 3, byrow = TRUE,
dimnames = list(number_parks,
- c("Moyennes des mortalités annuelles",
- "Ecart-type des mortalités annuelles",
+ c("Moyenne",
+ "Ecart-type",
"Année de mise en service du parc"))))
})
diff --git a/inst/ShinyApp/server_old.R b/inst/ShinyApp/server_old.R
deleted file mode 100644
index f914e7a..0000000
--- a/inst/ShinyApp/server_old.R
+++ /dev/null
@@ -1,605 +0,0 @@
-server <- function(input, output, session){
-
- # Hide all inputs excepted actionButtons
-
- observe({
- shinyjs::hide("fatal_constant")
- shinyjs::hide("fatalities_input_type")
- shinyjs::hide("fatalities_mean")
- shinyjs::hide("fatalities_se")
- shinyjs::hide("fatalities_mat_expert")
- shinyjs::hide("fatalities_run_expert")
- shinyjs::hide("farm_number_cumulated")
- shinyjs::hide("fatalities_mat_cumulated")
- shinyjs::hide("pop_size_type")
- shinyjs::hide("pop_size_input_type")
- shinyjs::hide("pop_size_mean")
- shinyjs::hide("pop_size_se")
- shinyjs::hide("pop_size_mat_expert")
- shinyjs::hide("pop_size_run_expert")
- shinyjs::hide("carrying_cap_input_type")
- shinyjs::hide("carrying_capacity")
- shinyjs::hide("carrying_cap_mat_expert")
- shinyjs::hide("carrying_cap_run_expert")
- shinyjs::hide("lambda_input_type")
- shinyjs::hide("pop_growth_mean")
- shinyjs::hide("pop_growth_se")
- shinyjs::hide("pop_growth_mat_expert")
- shinyjs::hide("pop_growth_run_expert")
- shinyjs::hide("pop_trend")
- shinyjs::hide("pop_trend_strength")
- shinyjs::hide("fill_type_vr")
- shinyjs::hide("mat_display_vr")
- shinyjs::hide("mat_fill_vr")
-
- # Show fatalities part
-
- if(input$button_fatalities%%2 == 1){
- shinyjs::show("fatal_constant")
-
- # Show inputs for none cumulated impacts scenario
-
- if(input$analysis_choice == "scenario"){
- shinyjs::show("fatalities_input_type")
- if(input$fatalities_input_type == "Valeurs"){
- shinyjs::show("fatalities_mean")
- shinyjs::show("fatalities_se")
- }
- if(input$fatalities_input_type == "Elicitation d'expert"){
- shinyjs::show("fatalities_mat_expert")
- shinyjs::show("fatalities_run_expert")
- }
- }
-
- # Show inputs for cumulated scenario
-
- if(input$analysis_choice == "cumulated"){
- shinyjs::show("farm_number_cumulated")
- shinyjs::show("fatalities_mat_cumulated")
- }
-
- }
-
- # Show inputs for population size part
-
- if(input$button_pop_size%%2 == 1){
- shinyjs::show("pop_size_type")
- shinyjs::show("pop_size_input_type")
- if(input$pop_size_input_type == "Valeurs"){
- shinyjs::show("pop_size_mean")
- shinyjs::show("pop_size_se")
- }
- if(input$pop_size_input_type == "Elicitation d'expert"){
- shinyjs::show("pop_size_mat_expert")
- shinyjs::show("pop_size_run_expert")
- }
- }
-
- # Show inputs for carrying capacity part
-
- if(input$button_carrying_cap%%2 == 1){
- shinyjs::show("carrying_cap_input_type")
- if(input$carrying_cap_input_type == "Valeurs"){
- shinyjs::show("carrying_capacity")
- }
- if(input$carrying_cap_input_type == "Elicitation d'expert"){
- shinyjs::show("carrying_cap_mat_expert")
- shinyjs::show("carrying_cap_run_expert")
- }
- }
-
- # Show inputs for population trend part
-
- if(input$button_pop_trend%%2 == 1){
- shinyjs::show("lambda_input_type")
- if(input$lambda_input_type == "Taux de croissance"){
- shinyjs::show("pop_growth_mean")
- shinyjs::show("pop_growth_se")
- }
- if(input$lambda_input_type == "Elicitation d'expert"){
- shinyjs::show("pop_growth_mat_expert")
- shinyjs::show("pop_growth_run_expert")
- }
- if(input$lambda_input_type == "Tendance locale ou régionale"){
- shinyjs::show("pop_trend")
- shinyjs::show("pop_trend_strength")
- }
- }
-
- # Show inputs vital rates part
-
- if(input$button_vital_rates%%2 == 1){
- shinyjs::show("fill_type_vr")
- if(input$fill_type_vr == "Automatique"){
- shinyjs::show("mat_display_vr")
- }
- if(input$fill_type_vr == "Manuelle"){
- shinyjs::show("mat_fill_vr")
- }
- }
- })
-
- # Elicitation experts part
-
- func_eli <- function(mat_expert){
- t_mat_expert <- t(mat_expert)
- vals = t_mat_expert[3:5,]
- Cp = t_mat_expert[6,]
- weights = t_mat_expert[2,]
-
- out <- elicitation(vals, Cp, weights)
- return(list(out = out, mean = out$mean_smooth, SE = sqrt(out$var_smooth)))
- }
-
- func_eli_plot <- function(out){
- plot_elicitation(out)
- }
-
- ## Output
-
- param <- reactiveValues(N1 = NULL,
- fatalities_mean = NULL,
- fecundities = NULL,
- survivals = NULL,
- s_calibrated = NULL,
- f_calibrated = NULL,
- vr_calibrated = NULL,
- cumulated_impacts = NULL,
- onset_time = NULL,
- onset_year = NULL,
- carrying_capacity = NULL,
- rMAX_species = rMAX_species,
- theta = theta,
- fatalities_eli_result = NULL,
- pop_size_eli_result = NULL,
- pop_size_mean = NULL,
- pop_size_se = NULL,
- pop_size_type = NULL,
- pop_growth_eli_result = NULL,
- pop_growth_mean = NULL,
- pop_growth_se = NULL,
- carrying_cap_eli_result = NULL)
-
- # Elicitation
-
- ## Fatalities
-
- observeEvent({input$fatalities_run_expert}, {
- if(all(is.na(input$fatalities_mat_expert))) {} else {
- param$fatalities_eli_result <- func_eli(input$fatalities_mat_expert)
-
- ### Plot fatalities
- output$fatalities_expert_plot <- renderPlot({func_eli_plot(param$fatalities_eli_result$out)})}
- })
-
- ## Population size
-
- observeEvent({input$pop_size_run_expert}, {
- if(all(is.na(input$pop_size_mat_expert))) {} else {
- param$pop_size_eli_result <- func_eli(input$pop_size_mat_expert)
-
- ### Plot pop size
- output$pop_size_expert_plot <- renderPlot({func_eli_plot(param$pop_size_eli_result$out)})}
- })
-
- ## Population growth
-
- observeEvent({input$pop_growth_run_expert},{
- if(all(is.na(input$pop_growth_mat_expert))) {} else {
- param$pop_growth_eli_result <- func_eli(input$pop_growth_mat_expert)
-
- ### plot pop growth
- output$pop_growth_expert_plot <- renderPlot({func_eli_plot(param$pop_growth_eli_result$out)})
- }
- })
-
- ## Carrying capacity
-
- observeEvent({input$carrying_cap_run_expert},{
- if(all(is.na(input$carrying_cap_mat_expert))) {} else {
- param$carrying_cap_eli_result <- func_eli(input$carrying_cap_mat_expert)
-
- ### Plot carrying capacity
- output$carrying_cap_expert_plot <- renderPlot({func_eli_plot(param$carrying_cap_eli_result$out)})
- }
- })
-
- # Reactive values (cumulated impacts, fatalities mean, fatalities se, onset_time, survivals mean, fecundities mean)
-
- observeEvent({input$run}, {
- if(input$analysis_choice == "scenario"){
- param$cumulated_impacts = FALSE
- } else {
- param$cumulated_impacts = TRUE
- }
- })
-
- # Fatalities
- ## onset time, mean and se
-
- observeEvent({input$run}, {
- if(input$analysis_choice == "scenario"){
- if(input$fatalities_input_type == "Elicitation d'expert"){
- if(!(is.null(param$fatalities_eli_result))) {
- param$fatalities_mean <- c(0, round(param$fatalities_eli_result$mean))
- param$onset_time = NULL
- param$fatalities_se <- c(0, round(param$fatalities_eli_result$SE))
- } else {
- print("#Intégrer un message d'erreur")
- }
- } else {
- param$fatalities_mean <- c(0, input$fatalities_mean)
- param$onset_time = NULL
- param$fatalities_se <- c(0, input$fatalities_se)
- }
- } else {
- param$fatalities_mean <- c(0, input$fatalities_mat_cumulated[,1])
- param$onset_year <- c(min(input$fatalities_mat_cumulated[,3]), input$fatalities_mat_cumulated[,3])
- param$onset_time <- param$onset_year - min(param$onset_year) + 1
- param$fatalities_se <- c(0, input$fatalities_mat_cumulated[,2])
- }
- })
-
- # Population size
- ## Mean, se and type
-
- observeEvent({input$run},{
- if(input$pop_size_input_type == "Elicitation d'expert"){
- if(!(is.null(param$pop_size_eli_result))){
- param$pop_size_mean <- round(param$pop_size_eli_result$mean)
- param$pop_size_se <- round(param$pop_size_eli_result$SE)
- } else {
- print("#intégrer un message d'erreur")
- }
- } else {
- param$pop_size_mean <- input$pop_size_mean
- param$pop_size_se <- input$pop_size_se
- }
- param$pop_size_type <- input$pop_size_type
- })
-
- # Observe pop growth value
- ## Avoid unrealistic scenarios
-
- observeEvent({input$run}, {
- if(input$lambda_input_type == "Elicitation d'expert"){
- if(!(is.null(param$pop_growth_eli_result))){
- param$pop_growth_mean <- round(min(1 + param$rMAX_species, round(param$pop_growth_eli_result$mean, 2)), 2)
- param$pop_growth_se <- round(param$pop_growth_eli_result$SE, 2)
- } else {
- print("#intégrer un message d'erreur")
- }
- } else if(input$lambda_input_type == "Tendance locale ou régionale"){
- if(input$pop_trend == "Croissance") {
- if(input$pop_trend_strength == "Faible") {
- param$pop_growth_mean <- 1.01
- } else if(input$pop_trend_strength == "Moyen"){
- param$pop_growth_mean <- 1.03
- } else {
- param$pop_growth_mean <- 1.06
- }
- } else if(input$pop_trend == "Déclin"){
- if(input$pop_trend_strength == "Faible") {
- param$pop_growth_mean <- 0.99
- } else if(input$pop_trend_strength == "Moyen"){
- param$pop_growth_mean <- 0.97
- } else {
- param$pop_growth_mean <- 0.94
- }
- } else {
- param$pop_growth_mean <- 1
- }
- param$pop_growth_se <- 0.03
- }
- else {
- param$pop_growth_mean <- round(min(1 + param$rMAX_species, input$pop_growth_mean), 2)
- param$pop_growth_se <- input$pop_growth_se
- }
- })
-
- # Survivals and fecundities
-
- observeEvent({input$run}, {
- if(input$fill_type_vr == "Manuelle"){
- param$survivals <- input$mat_fill_vr[,1]
- param$fecundities <- input$mat_fill_vr[,2]
- } else {
- param$survivals <- survivals
- param$fecundities <- fecundities
- }
- })
-
- # Survival and fecundity calibration
-
- observeEvent({
- input$run
- # input$species_choice
- # input$pop_growth_mean
- },{
-
- ## Avoid unrealistic scenarios
- #param$pop_growth_mean <- min(1 + param$rMAX_species, input$pop_growth_mean)
-
- param$vr_calibrated <- calibrate_params(
- inits = init_calib(s = param$survivals, f = param$fecundities, lam0 = param$pop_growth_mean),
- f = param$fecundities, s = param$survivals, lam0 = param$pop_growth_mean
- )
- param$s_calibrated <- head(param$vr_calibrated, length(param$survivals))
- param$f_calibrated <- tail(param$vr_calibrated, length(param$fecundities))
- })
-
-
- # Observe carrying capacity
- observeEvent({input$run}, {
- if(input$carrying_cap_input_type == "Elicitation d'expert"){
- if(!(is.null(param$carrying_cap_eli_result))){
- param$carrying_capacity <- round(param$carrying_cap_eli_result$mean)
- } else {
- print("#intégrer un message d'erreur")
- }
- } else {
- param$carrying_capacity <- input$carrying_capacity
- }
- })
-
- observeEvent({input$run}, {
- print(param$pop_growth_mean)
- print(param$pop_growth_se)
- })
-
- # End of reactive
-
- # Simulations
-
- observeEvent({
- input$run
- }, {
-
- withProgress(message = 'Simulation progress', value = 0, {
-
- param$N1 <- run_simul_shiny(nsim = input$nsim,
- cumuated_impacts = param$cumulated_impacts,
-
- fatalities_mean = param$fatalities_mean,
- fatalities_se = param$fatalities_se,
- onset_time = param$onset_time,
-
- pop_size_mean = param$pop_size_mean,
- pop_size_se = param$pop_size_se,
- pop_size_type = param$pop_size_type,
-
- pop_growth_mean = param$pop_growth_mean,
- pop_growth_se = param$pop_growth_se,
-
- survivals = param$s_calibrated,
- fecundities = param$f_calibrated,
-
- carrying_capacity = param$carrying_capacity,
- theta = param$theta,
- rMAX_species = param$rMAX_species,
-
- model_demo = NULL,
- time_horzion = time_horzion,
- coeff_var_environ = coeff_var_environ,
- fatal_constant = input$fatal_constant)
- }) # Close withProgress
- }) # Close observEvent
-
-
- # Plot Impacts
-
- plot_out_impact <- function(){
- if(is.null(param$N1)) {} else {plot_impact(N = param$N1$N, xlab = "year", ylab = "pop size")}
- }
-
- output$graph_impact <- renderPlot({
- plot_out_impact()
- })
-
- # Plot trajectories
-
- plot_out_traj <- function(){
- if(is.null(param$N1)) {} else {plot_traj(N = param$N1$N, xlab = "year", ylab = "pop size")}
- }
-
- output$graph_traj <- renderPlot({
- plot_out_traj()
- })
- # End simulations
-
- # General informations output
-
- ## Fatalities
-
- output$fatalities_mean_info <- renderText({
- if(input$fatalities_input_type == "Elicitation d'expert"){
- if(!(is.null(param$fatalities_eli_result))){
- info <- round(param$fatalities_eli_result$mean)
- } else {info <- NA}
- }
- else {
- info <- input$fatalities_mean
- }
- paste0("Moyenne des mortalités : ", info)
- })
-
- output$fatalities_se_info <- renderText({
- if(input$fatalities_input_type == "Elicitation d'expert"){
- if(!(is.null(param$fatalities_eli_result))){
- info <- round(param$fatalities_eli_result$SE)
- } else {info <- NA}
- }
- else {
- info <- input$fatalities_se
- }
- paste0("Ecart-type des mortalités : ", info)
- })
-
- ## Poplutation size
-
- output$pop_size_type_info <- renderText({
- if(input$pop_size_type == "Npair"){
- paste0("Type de taille de pop : ", "Nombre de couple")
- } else {
- paste0("Type de taille de pop : ", "Effectif total")
- }
- })
-
- output$pop_size_mean_info <- renderText({
- if(input$pop_size_input_type == "Elicitation d'expert"){
- if(!(is.null(param$pop_size_eli_result))){
- info <- round(param$pop_size_eli_result$mean)
- } else {info <- NA}
- }
- else {
- info <- input$pop_size_mean
- }
- paste0("Moyenne de la taille de la population : ", info)
- })
-
- output$pop_size_se_info <- renderText({
- if(input$pop_size_input_type == "Elicitation d'expert"){
- if(!(is.null(param$pop_size_eli_result))){
- info <- round(param$pop_size_eli_result$SE)
- } else {info <- NA}
- }
- else {
- info <- input$pop_size_se
- }
- paste0("Ecart-type de la taille de la population : ", info)
- })
-
- ## Carrying capacity
-
- output$carrying_capacity_info <- renderText({
- if(input$carrying_cap_input_type == "Elicitation d'expert"){
- if(!(is.null(param$carrying_cap_eli_result))){
- info <- round(param$carrying_cap_eli_result$mean)
- } else {info <- NA}
- }
- else {
- info <- input$carrying_capacity
- }
- paste0("Capacité de charge du milieu : ", info)
- })
-
- ## Population growth
-
- output$pop_trend_type_info <- renderText({paste0("Type de Tendance de pop : ", input$lambda_input_type)})
-
- output$pop_growth_mean_info <- renderText({
- if(input$lambda_input_type == "Elicitation d'expert"){
- if(!(is.null(param$pop_growth_eli_result))){
- info <- round(param$pop_growth_eli_result$mean, 2)
- } else {info <- NA}
- } else if(input$lambda_input_type == "Tendance locale ou régionale"){
- if(input$pop_trend == "Croissance") {
- if(input$pop_trend_strength == "Faible") {
- info <- 1.01
- } else if(input$pop_trend_strength == "Moyen"){
- info <- 1.03
- } else {
- info <- 1.06
- }
- } else if(input$pop_trend == "Déclin"){
- if(input$pop_trend_strength == "Faible") {
- info <- 0.99
- } else if(input$pop_trend_strength == "Moyen"){
- info <- 0.97
- } else {
- info <- 0.94
- }
- } else {
- info <- 1.00
- }
- } else {
- info <- input$pop_growth_mean
- }
- paste0("Moyenne de la croissance de la population : ", info)
- })
-
- output$pop_growth_se_info <- renderText({
- if(input$lambda_input_type == "Elicitation d'expert"){
- if(!(is.null(param$pop_growth_eli_result))){
- info <- round(param$pop_growth_eli_result$SE, 2)
- } else {info <- NA}
- } else if (input$lambda_input_type == "Tendance locale ou régionale") {
- info <- 0.03
- }
- else {
- info <- input$pop_growth_se
- }
- paste0("Ecart-type de la croissance de la population : ", info)
- })
-
- ## Vital rates
-
- output$vital_rates_info <- renderTable({
- if(input$fill_type_vr == "Automatique"){
- input$mat_display_vr
- } else {
- input$mat_fill_vr
- }
- })
- # End genral informations output
-
- ## Update matrix cumulated impact
-
- observeEvent({
- input$farm_number_cumulated
- }, {
-
- park_names <- function(n){
- v <- c(paste0("Parc n°", c(1:n)))
- return(v)
- }
-
- n_row <- input$farm_number_cumulated
-
- updateMatrixInput(session, inputId = "fatalities_mat_cumulated",
- value = matrix(init_cumul, nrow = n_row, 3, byrow = TRUE,
- dimnames = list(park_names(n_row),
- c("Moyenne",
- "Ecart-type",
- "Année de mise en service du parc"))))
- }) # end observEvent
-
- # Survivals and Fecundities
-
- create.matrice <- function(species){
- tab_test <- data_sf %>%
- filter(species == data_sf$Nom_espece) %>%
- select(classes_age, survie, fecondite)
- return(tab_test)
- }
-
- observeEvent({input$species_list}, {
- if(input$species_list == "Espèce") {} else {
- tab_species <- create.matrice(input$species_list)
-
- if(all(is.na(tab_species))) {
- updateMatrixInput(session, inputId = "mat_fill_vr",
- value = matrix(data = "",
- nrow = 4,
- ncol = 2,
- dimnames = list(c("Juv 1", "Juv 2", "Juv 3", "Adulte"), c("Survie", "Fécondité"))))
-
- } else {
- number_age_class <- nrow(tab_species)
- ages <- tab_species$classes_age
- survivals <- tab_species$survie
- fecundities <- tab_species$fecondite
-
- updateMatrixInput(session, inputId = "mat_fill_vr",
- value = matrix(data = c(survivals, fecundities),
- nrow = number_age_class,
- ncol = 2,
- dimnames = list(ages, c("Survie", "Fécondité"))))
- }
- }
- })
-}
-# End server
-
-
-
diff --git a/inst/ShinyApp/ui_old.R b/inst/ShinyApp/ui_old.R
deleted file mode 100644
index 47624bc..0000000
--- a/inst/ShinyApp/ui_old.R
+++ /dev/null
@@ -1,389 +0,0 @@
-rm(list = ls(all.names = TRUE))
-
-## Load libraries
-library(shiny)
-library(shinyjs)
-library(shinyMatrix)
-library(tidyverse)
-library(eolpop)
-
-
-# source("./inst/ShinyApp/f_output.R")
-# source("./inst/ShinyApp/param_fixes.R")
-
-## Load species list
-species_data <- read.csv("./inst/ShinyApp/species_list.csv", sep = ",")
-species_list <- unique(as.character(species_data$NomEspece))
-# species_list <- species_data$NomEspece
-
-## Load survival and fecundities data
-data_sf <- read.csv("./inst/ShinyApp/survivals_fecundities_species.csv", sep = ",")#, encoding = "UTF-8")
-(data_sf)
-
-# Fixed parameters (for now)
-nsim = 10
-coeff_var_environ = 0.10
-time_horzion = 30
-survivals <- c(0.5, 0.7, 0.8, 0.95)
-fecundities <- c(0, 0, 0.05, 0.55)
-
-## Data elicitation pre-fill data
-# fatalities
-eli_fatalities <- c("A", 1.0, 2, 5, 8, 0.80,
- "B", 0.2, 0, 3, 6, 0.90,
- "C", 0.2, 2, 4, 10, 0.90,
- "D", 0.1, 1, 3, 7, 0.70)
-
-# population size
-eli_pop_size <- c("A", 1.0, 150, 200, 250, 0.80,
- "B", 0.5, 120, 180, 240, 0.90,
- "C", 0.8, 170, 250, 310, 0.90,
- "D", 0.3, 180, 200, 230, 0.70)
-
-# carrying capacity
-eli_carrying_cap <- c("A", 1.0, 500, 700, 1000, 0.80,
- "B", 0.5, 1000, 1500, 2000, 0.90,
- "C", 0.8, 800, 1200, 1600, 0.90,
- "D", 0.3, 100, 1200, 1500, 0.70)
-
-# population growth rate
-eli_pop_growth <- c("A", 1 , 0.95, 0.98, 1.00, 0.95,
- "B", 0.2, 0.97, 1.00, 1.01, 0.90,
- "C", 0.5, 0.92, 0.96, 0.99, 0.90,
- "D", 0.3, 0.90, 0.95, 0.98, 0.70)
-
-## Other pre-fill data
-# fatalities for several wind farms (cumulated impacts)
-init_cumul <- c(10, 5, 8,
- 0.05, 0.05, 0.05,
- 2010, 2015, 2018)
-init_cumul_add <- c(3, 0.05, 2020)
-
-
-
-# vital rates
-init_vr = c(survivals, fecundities)
-
-# DD parameters
-theta = 1
-
-# Define theoretical rMAX for the species
-rMAX_species <- rMAX_spp(surv = tail(survivals, 1), afr = min(which(fecundities != 0)))
-rMAX_species
-
-
-##--------------------------------------------
-## User Interface --
-##--------------------------------------------
-ui <- fluidPage(
- useShinyjs(),
- titlePanel("eolpop : Impact demographique des éoliennes"),
-
- # Creation of the first page (select species, analysis type choice)
-
- wellPanel(
- selectInput(inputId = "species_list",
- h4(strong("Sélection d'une espèce")),
- choices = species_list),
- radioButtons(inputId = "analysis_choice",
- h4(strong("Sélectionner un type d'analyse")),
- choices = c("Impacts non cumulés" = "scenario", "Impacts cumulés" = "cumulated"))
- ), # End wellPanel
-
-
- ##--------------------------------------------
- ## General information --
- ##--------------------------------------------
-
- wellPanel(
- fluidRow(
- column(width = 4,
- textOutput(outputId = "specie_name"),
- h4("Mortalités"),
- textOutput(outputId = "fatalities_mean_info"),
- textOutput(outputId = "fatalities_se_info"),
- h4("Taille de la population"),
- textOutput(outputId = "pop_size_type_info"),
- textOutput(outputId = "pop_size_mean_info"),
- textOutput(outputId = "pop_size_se_info")),
- fluidRow(
- column(width = 4,
- h4("Capacité de charge"),
- textOutput(outputId = "carrying_capacity_info"),
- h4("Tendance de la population"),
- textOutput(outputId = "pop_trend_type_info"),
- textOutput(outputId = "pop_growth_mean_info"),
- textOutput(outputId = "pop_growth_se_info")),
- fluidRow(
- column(width = 4,
- h4("Paramètres démographiques"),
- tableOutput(outputId = "vital_rates_info"))
- )
- )
- )
- ), # End wellPanel
-
-
- # Paramter Inputs (fatalities, pop size, carrying capacity, pop trend and vital rates).
-
- sidebarLayout(
- sidebarPanel(
-
- ##--------------------------------------------
- ## 1. Fatalities --
- ##--------------------------------------------
-
- actionButton(inputId = "button_fatalities",
- label = "Mortalités"),
- radioButtons(inputId = "fatal_constant",
- label = h4("Modélisation"),
- choices = c("Taux de mortalités (h) constant" = "h",
- "Nombre de mortalités (M) constant" = "M")),
-
- ### Part for non-cumulated impacts
- # Input type
- radioButtons(inputId = "fatalities_input_type",
- label = h4("Source des données"),
- choices = c("Valeurs", "Elicitation d'expert")),
-
- # Values
- numericInput(inputId = "fatalities_mean",
- label = "Moyenne des mortalités annuelles",
- value = 5,
- min = 0, max = Inf, step = 0.5),
- numericInput(inputId = "fatalities_se",
- label = "Ecart-type des mortalités annuelles",
- value = 0.05,
- min = 0, max = Inf, step = 0.1),
-
- # Matrix for expert elicitation
- matrixInput(inputId = "fatalities_mat_expert",
- value = matrix(data = eli_fatalities, 4, 6,
- dimnames = list(c("#1", "#2", "#3", "#4"),
- c("Nom", "Poids", "Min", "Best", "Max", "% IC" )),
- byrow = TRUE),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE)),
-
- actionButton(inputId = "fatalities_run_expert", label = "Analyse"),
-
- ### Part for cumulated impacts
-
- numericInput(inputId = "farm_number_cumulated",
- label = "Nombre de parcs éoliens",
- value = 3, min = 2, max = Inf, step = 1),
-
- matrixInput(inputId = "fatalities_mat_cumulated",
- value = matrix(init_cumul, 3, 3,
- dimnames = list(c(paste0("Parc n°", c(1:3))),
- c("Moyenne",
- "Ecart-type",
- "Année de mise en service du parc"))),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE)),
-
-
- ##--------------------------------------------
- ## 2. Population Size --
- ##--------------------------------------------
-
- br(" "),
- actionButton(inputId = "button_pop_size",
- label = "Taille de la population"),
-
- radioButtons(inputId = "pop_size_type",
- label = h4("Unité"),
- choices = c("Nombre de couple" = "Npair", "Effectif total" = "Ntotal")),
-
- radioButtons(inputId = "pop_size_input_type",
- label = h4("Type de saisie"),
- choices = c("Valeurs", "Elicitation d'expert")),
-
- numericInput(inputId = "pop_size_mean",
- label = "Moyenne de la taille de la population",
- value = 200,
- min = 0, max = Inf, step = 50),
-
- numericInput(inputId = "pop_size_se",
- label = "Ecart-type de la taille de la population",
- value = 25,
- min = 0, max = Inf, step = 1),
-
- matrixInput(inputId = "pop_size_mat_expert",
- value = matrix(data = eli_pop_size, 4, 6,
- dimnames = list(c("#1", "#2", "#3", "#4"),
- c("Nom", "Poids", "Min", "Best", "Max", "% IC" )),
- byrow = TRUE),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE)),
-
- actionButton(inputId = "pop_size_run_expert", label = "Analyse"),
-
-
- ##--------------------------------------------
- ## 3. Carrying capacity --
- ##--------------------------------------------
-
- br(" "),
- actionButton(inputId = "button_carrying_cap",
- label = "Capacité de charge"),
-
- radioButtons(inputId = "carrying_cap_input_type",
- label = h4("Type d'unité"),
- choices = c("Valeurs", "Elicitation d'expert")),
-
- numericInput(inputId = "carrying_capacity",
- label = "Capacité de charge",
- value = 1000,
- min = 0, max = Inf, step = 100),
-
- matrixInput(inputId = "carrying_cap_mat_expert",
- value = matrix(data = eli_carrying_cap, 4, 6,
- dimnames = list(c("#1", "#2", "#3", "#4"),
- c("Nom", "Poids", "Min", "Best", "Max", "% IC" )),
- byrow = TRUE),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE)),
-
- actionButton(inputId = "carrying_cap_run_expert", label = "Analyse"),
-
- ##--------------------------------------------
- ## 4. Population Trend --
- ##--------------------------------------------
-
- br(" "),
- actionButton(inputId = "button_pop_trend",
- label = "Tendance de la population"),
-
- radioButtons(inputId = "lambda_input_type",
- label = h4("Type de tendance"),
- choices = c("Taux de croissance", "Elicitation d'expert", "Tendance locale ou régionale")),
-
- numericInput(inputId = "pop_growth_mean",
- label = "Moyenne de la croissance de la population",
- value = 1,
- min = 0, max = Inf, step = 0.01),
-
- numericInput(inputId = "pop_growth_se",
- label = "Ecart-type de la croissance de la population",
- value = 0,
- min = 0, max = Inf, step = 0.01),
-
- matrixInput(inputId = "pop_growth_mat_expert",
- value = matrix(data = eli_pop_growth, 4, 6,
- dimnames = list(c("#1", "#2", "#3", "#4"),
- c("Nom", "Poids", "Min", "Best", "Max", "% IC" )),
- byrow = TRUE),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE)),
-
- actionButton(inputId = "pop_growth_run_expert", label = "Analyse"),
-
- h4("Tendance de la population"),
-
- radioButtons(inputId = "pop_trend",
- label = NULL,
- choices = c("Croissance", "Stable", "Déclin")),
-
- radioButtons(inputId = "pop_trend_strength",
- label = NULL,
- choices = c("Faible", "Moyen", "Fort")),
-
- # tags$style("#pop_trend_strength {position:fixed; top: 600px; right: 100px;}"),
-
-
- ##--------------------------------------------
- ## 5. Vital rates --
- ##--------------------------------------------
-
- br(" "),
- actionButton(inputId = "button_vital_rates",
- label = "Paramètres démographiques"),
-
- radioButtons(inputId = "fill_type_vr",
- label = "Type de saisie",
- choices = c("Automatique", "Manuelle")),
-
- # tableOutput(outputId = "mat_display_vr"),
-
- matrixInput(inputId = "mat_display_vr",
- value = matrix("", 4, 2, dimnames = list(c("Juv 1", "Juv 2", "Juv 3", "Adulte"), c("Survie", "Fécondité"))),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE)),
-
- matrixInput(inputId = "mat_fill_vr",
- value = matrix(data = init_vr, 4, 2, dimnames = list(c("Juv 1", "Juv 2", "Juv 3", "Adulte"), c("Survie", "Fécondité"))),
- class = "numeric",
- rows = list(names = TRUE),
- cols = list(names = TRUE))
-
- ), # End sidebarPanel
-
-
- #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-
-
- # Creation of outputs parts
-
- mainPanel(
- tabsetPanel(
- tabPanel(title = "Impact population",
- strong(span(textOutput("message"), style="color:blue; font-size:24px", align = "center")),
- br(),
- numericInput(inputId = "nsim", label = "Nombre de simulations",
- value = 50, min = 0, max = Inf, step = 10),
- br(),
- actionButton(inputId = "run", label = "Lancer l'analyse"),
- hr(),
- h4("Graphique : Impact relatif de chaque scénario", align = "center"),
- plotOutput("graph_impact", width = "100%", height = "550px"),
- hr(),
- h4("Graphique : Trajectoire démographique", align = "center"),
- plotOutput("graph_traj", width = "100%", height = "550px")),
-
- tabPanel(title = "Distribution paramètres",
- br(),
- hr(),
- h4("#Graphe élicitation d'expert pour les mortalités", align = "center"),
- plotOutput(outputId = "fatalities_expert_plot"),
- hr(),
- h4("#Graphe élicitation d'expert pour la taille de la population", align = "center"),
- plotOutput(outputId = "pop_size_expert_plot"),
- hr(),
- h4("#Graphe élicitation d'expert pour la capacité de charge", align = "center"),
- plotOutput(outputId = "carrying_cap_expert_plot"),
- hr(),
- h4("#Graphe élicitation d'expert pour la tendance de la population", align = "center"),
- plotOutput(outputId = "pop_growth_expert_plot"),
- ),
-
- tabPanel(title = "Rapport",
- br(),
- radioButtons(inputId = "lifestyle",
- h4("Mode de vie de l'espèce"),
- choices = c("Sédentaire", "Non-sédentaire nicheur", "Non-sédentaire hivernant", "Migrateur de passage")),
- numericInput(inputId = "wind_turbines",
- h4("Nombre d'éoliennes"),
- value = 5, min = 0, max = Inf, step = 1),
- numericInput(inputId = "farm_number",
- h4("Nombre de parcs"),
- value = 1, min = 0, max = Inf, step = 1),
- numericInput(inputId = "wind_turbines_2",
- h4("Nombre d'éoliennes"),
- value = 1, min = 0, max = Inf, step = 1)
-
- ) # End tabPanel
- ) # End tabSetPanel
- ) # End mainPanel
- ) # sidebarLayout
-) # FluidPage
-
-# End UI
-
--
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