changed minor stuff

R/run_simul.R

@@ -126,9 +126,8 @@ run_simul <- function(nsim, cumulated_impacts,
     ##--------------------------------------------
     for(sim in 1:nsim){
 
+      print("################################")
       print(paste("simul", sim))
-      Sys.sleep(0.01)
-      flush.console()
 
       ## PARAMETER UNCERTAINTY : draw values for each input
       # 1. Nomber of fatalities

inst/FR_EolPop_ANSI/runApp.R

 rm(list = ls(all.names = TRUE))
-setwd( paste0(getwd(),"/inst/FR_eolpop_ANSI/") )
-#setwd("../FR_eolpop_ANSI/")
+setwd( paste0(getwd(),"/inst/FR_EolPop_ANSI/") )
+#setwd("../EN_EolPop/")
+#setwd("../FR_EolPop_ANSI/")
+#setwd("../FR_EolPopUTF8/")
+
 getwd()
 
 source("ui.R")

inst/FR_EolPop_ANSI/server.R

@@ -1816,6 +1816,7 @@ server <- function(input, output, session){
         ## Loops now ##
         for(sim in 1:nsim){
 
+          print(paste("simul", sim))
           Sys.sleep(0.1)
 
           # Check for user interrupts

run_analysis.R

@@ -7,7 +7,7 @@ library(magrittr)
 library(eolpop)
 
 ## Inputs
-nsim = 200
+nsim = 500
 
 pop_size_mean = 126
 pop_size_se = 2
@@ -28,8 +28,8 @@ fecundities <- c(0, 1.18)
 lambda( build_Leslie(s = survivals, f = fecundities) )
 (lambda( build_Leslie(s = survivals, f = fecundities) ) - 1)*100
 
-pop_growth_mean = 1
-pop_growth_se = 0.05
+pop_growth_mean = 0.90
+pop_growth_se = 0
 
 
 model_demo = NULL # M2_noDD_WithDemoStoch #M1_noDD_noDemoStoch #M4_WithDD_WithDemoStoch #M3_WithDD_noDemoStoch #
@@ -38,6 +38,7 @@ coeff_var_environ = sqrt(0.08)
 fatal_constant = "M"
 cumulated_impacts = FALSE
 
+
 # Pop size total
 N000 <- pop_vector(pop_size = pop_size_mean, pop_size_type = pop_size_type, s = survivals, f = fecundities)
 N000
@@ -115,15 +116,32 @@ time
 
 out = list()
 out$run = run0
+
+unique(which(is.na(out$run$N), arr.ind = TRUE)[,4])
+#out$run$N <- run0$N[,,,-rem]
 dim(out$run$N)
+dim(run0$N)
+
 
 res = get_metrics(N = out$run$N, cumulated_impacts = cumulated_impacts)
 names(res)
 res$scenario$Pext
 res$scenario$impact[time_horizon,1,"sc1"]*100
 
-plot_impact(N = out$run$N, sel_sc = "1", show_CI = 0.999, Legend = paste("sc", (1:length(fatalities_mean))-1))
+res$scenario$impact
+
+plot_impact(N = out$run$N, sel_sc = "1", show_CI = 0.999,
+            Legend = paste("sc", (1:length(fatalities_mean))-1))
 
 x11()
 plot_traj(N = out$run$N, age_class_use = "NotJuv0", fecundities = fecundities,
           Legend = paste("sc", 1:length(fatalities_mean)), ylim = c(0, NA))
+
+
+x11()
+density_impact(N = out$run$N, show_CI = 0.95, center = "median", sel_sc = "all", xlims = NULL,
+                           percent = TRUE, xlab = "Relative impact (%)", ylab = "Probability density",
+                           Legend = NULL, legend_position = "right", text_size = "large")
+
+x11()
+ECDF_impact(N = out$run$N)