Fixed some issue

Added observe(param) in server to make sure param used in simulations keep up to date !

inst/ShinyApp/runApp.R

+library(eolpop)
 source("./inst/ShinyApp/ui.R")
 source("./inst/ShinyApp/server.R")
 

inst/ShinyApp/server.R

@@ -157,6 +157,7 @@ server <- function(input, output, session){
                           carrying_cap_eli_result = NULL)
   ###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
 
+  observe(param)
 
   ##--------------------------------------------
   ##  Display parameter distribution          --
@@ -192,7 +193,6 @@ server <- function(input, output, session){
   ##  Run expert elicitation                  --
   ##--------------------------------------------
   plot_expert <- function(out, show_se = TRUE, ...){
-    #plot_elicitation(out, ylab = "Densit de probabilit", xlab = "Valeur du paramtre", cex.lab = 1.2)
     plot_elicitation(out, ylab = "", xlab = "Valeur du paramtre", cex.lab = 1.2, yaxt = "n")
     mtext(text = "Densit de probabilit", side = 2, line = 2, cex = 1.2)
 
@@ -353,6 +353,17 @@ server <- function(input, output, session){
   })
 
 
+  ###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~##
+  ## Survivals, fecundities and rMAX_species ###~~~~~~~~~~~~~~~~~~~~~~~~~~###
+  observeEvent({input$run}, {
+    param$survivals <- input$mat_fill_vr[,1]
+    param$fecundities <- input$mat_fill_vr[,2]
+    param$rMAX_species <- rMAX_spp(surv = tail(param$survivals,1), afr = min(which(param$fecundities != 0)))
+  }) # end observeEvent
+
+
+
+
   ###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~##
   ## Population growth ###~~~~~~~~~~~~~~~~~~~~~~~~~~###
   observeEvent({
@@ -399,14 +410,6 @@ server <- function(input, output, session){
     }
   })
 
-  # Survivals and fecundities
-  observeEvent({input$run}, {
-      param$survivals <- input$mat_fill_vr[,1]
-      param$fecundities <- input$mat_fill_vr[,2]
-      param$rMAX_species <- rMAX_spp(surv = tail(param$survivals,1), afr = min(which(param$fecundities != 0)))
-  }) # end observeEvent
-
-
   # Survival and fecundity calibration
   observeEvent({
     input$run
@@ -466,7 +469,7 @@ server <- function(input, output, session){
                                   fecundities = param$f_calibrated,
 
                                   carrying_capacity = param$carrying_capacity,
-                                  theta = param$theta,
+                                  theta = theta,
                                   rMAX_species = param$rMAX_species,
 
                                   model_demo = NULL,

inst/ShinyApp/ui.R

@@ -219,7 +219,8 @@ ui <- fluidPage(
 
       radioButtons(inputId = "pop_size_type",
                    label = h4("Unit"),
-                   choices = c("Nombre de couple" = "Npair", "Effectif total" = "Ntotal")),
+                   choices = c("Nombre de couple" = "Npair", "Effectif total" = "Ntotal"),
+                   selected = "Ntotal"),
 
       radioButtons(inputId = "pop_size_input_type",
                    label = h4("Type de saisie"),
@@ -265,7 +266,7 @@ ui <- fluidPage(
 
       numericInput(inputId = "pop_growth_mean",
                    label = "Moyenne de la croissance de la population",
-                   value = 1,
+                   value = 1.1,
                    min = 0, max = Inf, step = 0.01),
 
       numericInput(inputId = "pop_growth_se",
@@ -311,7 +312,7 @@ ui <- fluidPage(
 
       numericInput(inputId = "carrying_capacity",
                    label = "Capacit de charge",
-                   value = 1000,
+                   value = 500,
                    min = 0, max = Inf, step = 100),
 
       matrixInput(inputId = "carrying_cap_mat_expert",

run_analysis.R

@@ -69,6 +69,7 @@ lambda( build_Leslie(s = s_calibrated, f = f_calibrated) )
 #fatal_constant = "M"
 #cumulated_impacts = FALSE
 
+pop_growth_mean = 1.1
 pop_size_type = "Ntotal"
 carrying_capacity = 500