diff --git a/inst/ShinyApp/runApp.R b/inst/ShinyApp/runApp.R
index cafa2b5e825a8220c8670225e8679b74e76d94a2..266fa210a05ae741e5c5cbfe42d73897b7722936 100644
--- a/inst/ShinyApp/runApp.R
+++ b/inst/ShinyApp/runApp.R
@@ -1,3 +1,4 @@
source("./inst/ShinyApp/ui.R")
source("./inst/ShinyApp/server.R")
+
shinyApp(ui = ui, server = server)
diff --git a/inst/ShinyApp/server.R b/inst/ShinyApp/server.R
index 929fe89b994701ebf065fba6683b26835819086c..f914e7ac356b973b6e415b3d3b92f0eb2d79ceda 100644
--- a/inst/ShinyApp/server.R
+++ b/inst/ShinyApp/server.R
@@ -545,25 +545,24 @@ server <- function(input, output, session){
## Update matrix cumulated impact
- observeEvent({input$farm_number_cumulated}, {
- rows_names <- function(n){
+ observeEvent({
+ input$farm_number_cumulated
+ }, {
+
+ park_names <- function(n){
v <- c(paste0("Parc n°", c(1:n)))
return(v)
- }
+ }
- 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]))
+ n_row <- input$farm_number_cumulated
updateMatrixInput(session, inputId = "fatalities_mat_cumulated",
- value = matrix("", nrow = nrow, 3,
- dimnames = list(number_parks,
- c("Moyennes des mortalités annuelles",
- "Ecart-type des mortalités annuelles",
+ 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
@@ -602,6 +601,5 @@ server <- function(input, output, session){
}
# End server
-shinyApp(ui, server)
diff --git a/inst/ShinyApp/survivals_fecundities_species.csv b/inst/ShinyApp/survivals_fecundities_species.csv
index b2bce0a2b10a784ed2371f9fb4b884f51b01bd0c..df0645a4126cce8130c562fa86fade53e01e8838 100644
--- a/inst/ShinyApp/survivals_fecundities_species.csv
+++ b/inst/ShinyApp/survivals_fecundities_species.csv
@@ -1,10 +1,12 @@
Nom_espece,classes_age,survie,fecondite
-Aigle botté,Juv 1,0.5,0
-Aigle botté,Juv 2,0.7,0
-Aigle botté,Juv 3,0.8,0.05
-Aigle botté,Adulte,0.95,0.55
-Aigle de Bonelli,Juv 1,0.4,0
-Aigle de Bonelli,Juv 2,0.55,0
-Aigle de Bonelli,Juv 3,0.6,0.05
-Aigle de Bonelli,Juv 4,0.65,0.3
-Aigle de Bonelli,Adulte,0.8,0.4
\ No newline at end of file
+Aigle de Bonelli,Juv 1,0.65,0
+Aigle de Bonelli,Juv 2,0.75,0
+Aigle de Bonelli,Juv 3,0.85,0.05
+Aigle de Bonelli,Adulte,0.94,0.4
+Aigle royal,Juv 1,0.5,0
+Aigle royal,Juv 2,0.6,0
+Aigle royal,Juv 3,0.75,0.05
+Aigle royal,Juv 4,0.8,0.35
+Aigle royal,Adulte,0.95,0.55
+Alouette des champs,Juv 1,0.5,0
+Alouette des champs,Adulte,0.5,2.5
\ No newline at end of file
diff --git a/inst/ShinyApp/ui.R b/inst/ShinyApp/ui.R
index dfdac543157696a08d4db12906dd2b9b8a6b38b0..47624bc0d175dd0224a9f0ddc27a86b499bbfddb 100644
--- a/inst/ShinyApp/ui.R
+++ b/inst/ShinyApp/ui.R
@@ -1,25 +1,24 @@
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 = ",")
-head(species_data)
-
-# species_list <- unique(as.character(species_data$NomEspece))
-species_list <- species_data$NomEspece
+species_list <- unique(as.character(species_data$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")
-head(data_sf)
-
+(data_sf)
# Fixed parameters (for now)
nsim = 10
@@ -28,17 +27,48 @@ time_horzion = 30
survivals <- c(0.5, 0.7, 0.8, 0.95)
fecundities <- c(0, 0, 0.05, 0.55)
-# Data elicitation, fatalities for cumulated impacts, vital rates and DD_params
-data_eli = c("",1, 50, 70, 100, 0.80, "", 0.2, 200, 240, 280, 0.90, "", 0.2, 100, 180, 300, 0.90,"", 0.1, 120, 160, 220, 0.70)
-data_eli_trend = c("", 1, 0.60, 0.66, 0.78, 0.80, "", 0.2, 0.75, 0.83, 0.89, 0.90, "", 0.2, 0.56, 0.67, 0.77, 0.90, "", 0.1, 0.76, 0.89, 0.94, 0.70)
-data_fatalities = c(10, 5, 8, 0.05, 0.05, 0.05, 2010, 2015, 2018)
-data_vr = c(0.5, 0.7, 0.8, 0.95, 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 <- rMAX_spp(surv = tail(survivals, 1), afr = min(which(fecundities != 0)))
rMAX_species
@@ -53,7 +83,7 @@ ui <- fluidPage(
wellPanel(
selectInput(inputId = "species_list",
- h4(strong("Sélection d'une espèce ou groupe d'espèces")),
+ h4(strong("Sélection d'une espèce")),
choices = species_list),
radioButtons(inputId = "analysis_choice",
h4(strong("Sélectionner un type d'analyse")),
@@ -128,7 +158,10 @@ ui <- fluidPage(
# Matrix for expert elicitation
matrixInput(inputId = "fatalities_mat_expert",
- value = matrix(data = data_eli, 4, 6, dimnames = list(c("#1", "#2", "#3", "#4"), c("Nom", "Poids", "Min", "Meilleure Estimation", "Max", "IC (coverage)" )), byrow = TRUE),
+ 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)),
@@ -142,10 +175,10 @@ ui <- fluidPage(
value = 3, min = 2, max = Inf, step = 1),
matrixInput(inputId = "fatalities_mat_cumulated",
- value = matrix(data_fatalities, 3, 3,
+ value = matrix(init_cumul, 3, 3,
dimnames = list(c(paste0("Parc n°", c(1:3))),
- c("Moyennes des mortalités annuelles",
- "Ecart-type des mortalités annuelles",
+ c("Moyenne",
+ "Ecart-type",
"Année de mise en service du parc"))),
class = "numeric",
rows = list(names = TRUE),
@@ -179,9 +212,9 @@ ui <- fluidPage(
min = 0, max = Inf, step = 1),
matrixInput(inputId = "pop_size_mat_expert",
- value = matrix(data = data_eli, 4, 6,
+ value = matrix(data = eli_pop_size, 4, 6,
dimnames = list(c("#1", "#2", "#3", "#4"),
- c("Nom", "Poids", "Min", "Best", "Max", "IC" )),
+ c("Nom", "Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
@@ -208,7 +241,10 @@ ui <- fluidPage(
min = 0, max = Inf, step = 100),
matrixInput(inputId = "carrying_cap_mat_expert",
- value = matrix(data = data_eli, 4, 6, dimnames = list(c("#1", "#2", "#3", "#4"), c("Nom", "Poids", "Min", "Meilleure Estimation", "Max", "IC (coverage)" )), byrow = TRUE),
+ 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)),
@@ -238,7 +274,10 @@ ui <- fluidPage(
min = 0, max = Inf, step = 0.01),
matrixInput(inputId = "pop_growth_mat_expert",
- value = matrix(data = data_eli_trend, 4, 6, dimnames = list(c("#1", "#2", "#3", "#4"), c("Nom", "Poids", "Min", "Meilleure Estimation", "Max", "IC (coverage)" )), byrow = TRUE),
+ 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)),
@@ -279,7 +318,7 @@ ui <- fluidPage(
cols = list(names = TRUE)),
matrixInput(inputId = "mat_fill_vr",
- value = matrix(data = data_vr, 4, 2, dimnames = list(c("Juv 1", "Juv 2", "Juv 3", "Adulte"), c("Survie", "Fécondité"))),
+ 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))
@@ -347,3 +386,4 @@ ui <- fluidPage(
) # FluidPage
# End UI
+