rm(list = ls(all.names = TRUE))
## Load libraries
library(shiny)
library(shinyjs)
library(shinyMatrix)
library(tidyverse)
library(eolpop)
## 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)
#####################
### Pre-fill data ###
#####################
## 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
data_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 �oliennes"),
# Creation of the first page (select species, analysis type choice)
wellPanel(
selectInput(inputId = "species_list",
h4(strong("S�lection d'une esp�ce ou groupe d'esp�ces")),
choices = species_list),
radioButtons(inputId = "analysis_choice",
h4(strong("S�lectionner un type d'analyse")),
choices = c("Impacts non cumul�s" = "scenario", "Impacts cumul�s" = "cumulated"))
), # End wellPanel
##--------------------------------------------
## General information --
##--------------------------------------------
wellPanel(
fluidRow(
column(width = 4,
textOutput(outputId = "specie_name"),
h4("Mortalit�s"),
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("Capacit� 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("Param�tres d�mographiques"),
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 = "Mortalit�s"),
radioButtons(inputId = "fatal_constant",
label = h4("Mod�lisation"),
choices = c("Taux de mortalit�s (h) constant" = "h",
"Nombre de mortalit�s (M) constant" = "M")),
### Part for non-cumulated impacts
# Input type
radioButtons(inputId = "fatalities_input_type",
label = h4("Source des donn�es"),
choices = c("Valeurs", "Elicitation d'expert")),
# Values
numericInput(inputId = "fatalities_mean",
label = "Moyenne des mortalit�s annuelles",
value = 5,
min = 0, max = Inf, step = 0.5),
numericInput(inputId = "fatalities_se",
label = "Ecart-type des mortalit�s 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 �oliens",
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",
"Ann�e 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("Unit�"),
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 = "Capacit� de charge"),
radioButtons(inputId = "carrying_cap_input_type",
label = h4("Type d'unit�"),
choices = c("Valeurs", "Elicitation d'expert")),
numericInput(inputId = "carrying_capacity",
label = "Capacit� 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 r�gionale")),
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", "D�clin")),
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 = "Param�tres d�mographiques"),
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", "F�condit�"))),
class = "numeric",
rows = list(names = TRUE),
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", "F�condit�"))),
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 sc�nario", align = "center"),
plotOutput("graph_impact", width = "100%", height = "550px"),
hr(),
h4("Graphique : Trajectoire d�mographique", align = "center"),
plotOutput("graph_traj", width = "100%", height = "550px")),
tabPanel(title = "Distribution param�tres",
br(),
hr(),
h4("#Graphe �licitation d'expert pour les mortalit�s", align = "center"),
plotOutput(outputId = "fatalities_expert_plot"),
hr(),
h4("#Graphe �licitation d'expert pour la taille de la population", align = "center"),
plotOutput(outputId = "pop_size_expert_plot"),
hr(),
h4("#Graphe �licitation d'expert pour la capacit� de charge", align = "center"),
plotOutput(outputId = "carrying_cap_expert_plot"),
hr(),
h4("#Graphe �licitation 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'esp�ce"),
choices = c("S�dentaire", "Non-s�dentaire nicheur", "Non-s�dentaire hivernant", "Migrateur de passage")),
numericInput(inputId = "wind_turbines",
h4("Nombre d'�oliennes"),
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'�oliennes"),
value = 1, min = 0, max = Inf, step = 1)
) # End tabPanel
) # End tabSetPanel
) # End mainPanel
) # sidebarLayout
) # FluidPage
# End UI