diff --git a/inst/ShinyApp/server.R b/inst/ShinyApp/server.R
index becdaafea8aa92d66f5524b2f5044496edf01bb6..afeb922ff720761439ce75c2a3020b14a1e0efda 100644
--- a/inst/ShinyApp/server.R
+++ b/inst/ShinyApp/server.R
@@ -280,23 +280,29 @@ server <- function(input, output, session){
## Fatalities ###~~~~~~~~~~~~~~~~~~~~~~~~~~###
observeEvent({
input$fatalities_input_type
+ input$button_fatalities
},{
- output$fatalities_distri_plot <- renderPlot({ plot_gamma(mu = input$fatalities_mean, se = input$fatalities_se) })
- })
+ output$title_distri_plot <- renderText({ "Mortalités annuelles" })
+ output$distri_plot <- renderPlot({ plot_gamma(mu = input$fatalities_mean, se = input$fatalities_se) })
+ }, ignoreInit = TRUE)
## Population size ###~~~~~~~~~~~~~~~~~~~~~~~~~~###
observeEvent({
input$pop_size_input_type
+ input$button_pop_size
},{
- output$pop_size_distri_plot <- renderPlot({ plot_gamma(mu = input$pop_size_mean, se = input$pop_size_se) })
- })
+ output$title_distri_plot <- renderText({ "Taille de population" })
+ output$distri_plot <- renderPlot({ plot_gamma(mu = input$pop_size_mean, se = input$pop_size_se) })
+ }, ignoreInit = TRUE)
## Population growth ###~~~~~~~~~~~~~~~~~~~~~~~~~~###
observeEvent({
input$pop_growth_input_type
+ input$button_pop_growth
},{
- output$pop_growth_distri_plot <- renderPlot({ plot_gamma(mu = input$pop_growth_mean, se = input$pop_growth_se) })
- })
+ output$title_distri_plot <- renderText({ "Taux de croissance de la population" })
+ output$distri_plot <- renderPlot({ plot_gamma(mu = input$pop_growth_mean, se = input$pop_growth_se) })
+ }, ignoreInit = TRUE)
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
@@ -327,7 +333,8 @@ server <- function(input, output, session){
param$fatalities_eli_result <- func_eli(input$fatalities_mat_expert)
## plot distribution
- output$fatalities_distri_plot <- renderPlot({ plot_expert(param$fatalities_eli_result$out) })
+ output$title_distri_plot <- renderText({ "Mortalités annuelles" })
+ output$distri_plot <- renderPlot({ plot_expert(param$fatalities_eli_result$out) })
} else {
print("missing value")
@@ -345,7 +352,8 @@ server <- function(input, output, session){
param$pop_size_eli_result <- func_eli(input$pop_size_mat_expert)
## plot distribution
- output$pop_size_distri_plot <- renderPlot({ plot_expert(param$pop_size_eli_result$out) })
+ output$title_distri_plot <- renderText({ "Taille de population" })
+ output$distri_plot <- renderPlot({ plot_expert(param$pop_size_eli_result$out) })
} else {
print("missing value")
@@ -363,7 +371,8 @@ server <- function(input, output, session){
param$pop_growth_eli_result <- func_eli(input$pop_growth_mat_expert)
## plot distribution
- output$pop_growth_distri_plot <- renderPlot({ plot_expert(param$pop_growth_eli_result$out) })
+ output$title_distri_plot <- renderText({ "Taux de croissance de la population" })
+ output$distri_plot <- renderPlot({ plot_expert(param$pop_growth_eli_result$out) })
} else {
print("missing value")
@@ -380,9 +389,8 @@ server <- function(input, output, session){
param$carrying_cap_eli_result <- func_eli(input$carrying_cap_mat_expert)
## run elicitation analysis
- output$carrying_cap_distri_plot <- renderPlot({
- plot_expert(param$carrying_cap_eli_result$out, show_se = FALSE)
- })
+ output$title_distri_plot <- renderText({ "Capacité de charge" })
+ output$distri_plot <- renderPlot({ plot_expert(param$carrying_cap_eli_result$out, show_se = FALSE) })
} else {
print("missing value")
diff --git a/inst/ShinyApp/ui.R b/inst/ShinyApp/ui.R
index b74dd8d924dd13eba9b2ead71e2095550df1c5a6..85219c7ce5905b5b5aa31ec2da563bba9454a1a2 100644
--- a/inst/ShinyApp/ui.R
+++ b/inst/ShinyApp/ui.R
@@ -278,6 +278,7 @@ rm(list = ls(all.names = TRUE))
"Elicitation d'expert" = "eli_exp",
"Tendance locale ou régionale" = "trend")),
+ ## Input values: mean and se
numericInput(inputId = "pop_growth_mean",
label = "Moyenne de la croissance de la population",
value = 1.1,
@@ -288,6 +289,7 @@ rm(list = ls(all.names = TRUE))
value = 0.01,
min = 0, max = Inf, step = 0.01),
+ ## Input expert elicitation: table
matrixInput(inputId = "pop_growth_mat_expert",
value = matrix(data = eli_pop_growth, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
@@ -299,13 +301,22 @@ rm(list = ls(all.names = TRUE))
actionButton(inputId = "pop_growth_run_expert", label = "Utiliser valeurs experts"),
- radioButtons(inputId = "pop_trend",
- label = NULL,
- choices = c("Croissance", "Stable", "Déclin")),
-
- radioButtons(inputId = "pop_trend_strength",
- label = NULL,
- choices = c("Faible", "Moyen", "Fort")),
+ ## Input trend: radio buttons
+ {fluidRow(
+ # Trend
+ column(6,
+ radioButtons(inputId = "pop_trend",
+ label = "Tendance",
+ choices = c("Croissance", "Stable", "Déclin")),
+ ),
+
+ # Strength of trend
+ column(6,
+ radioButtons(inputId = "pop_trend_strength",
+ label = "Force",
+ choices = c("Faible", "Moyen", "Fort")),
+ ),
+ )}, # close fluidRow
)}, # close wellPanel
@@ -423,23 +434,9 @@ rm(list = ls(all.names = TRUE))
br(),
hr(),
- h3("Mortalités annuelles", align = "center"),
- plotOutput(outputId = "fatalities_distri_plot"),
- br(""),
- hr(),
-
- h3("Taille de la population", align = "center"),
- plotOutput(outputId = "pop_size_distri_plot"),
- br(""),
- hr(),
-
- h3("Taux de croissance de la population", align = "center"),
- plotOutput(outputId = "pop_growth_distri_plot"),
- br(""),
- hr(),
-
- h3("Capacité de charge: Elicitation d'expert", align = "center"),
- plotOutput(outputId = "carrying_cap_distri_plot"),
+ #h3("Mortalités annuelles", align = "center"),
+ span(textOutput(outputId = "title_distri_plot"), style="font-size:24px; font-weight:bold"),
+ plotOutput(outputId = "distri_plot"),
), # End tabPanel