rm(list = ls(all.names = TRUE))
library(shiny)
library(shinyjs)
library(shinyMatrix)
library(tidyverse)
library(eolpop)
# source("./inst/ShinyApp/f_output.R")
source("./inst/ShinyApp/param_fixes.R")
species_data <- read.csv("./inst/ShinyApp/species_list.csv", sep = ",")
species_list <- unique(as.character(species_data$NomEspece))
data_sf <- read.csv("./inst/ShinyApp/survivals_fecundities_species.csv", sep = ";", encoding = "UTF-8")
# 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)
# 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)
# 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 éoliennes"),
# Creation of the first page (select species, analysis type choice)
wellPanel(
selectInput(inputId = "species_list",
h4(strong("Sélection d'une espèce ou groupe d'espèces")),
choices = species_list),
radioButtons(inputId = "analysis_choice",
h4(strong("Sélectionner un type d'analyse")),
choices = c("Impacts non cumulés" = "scenario", "Impacts cumulés" = "cumulated"))
), # End wellPanel
##--------------------------------------------
## General information --
##--------------------------------------------
wellPanel(
fluidRow(
column(width = 4,
textOutput(outputId = "specie_name"),
h4("Mortalités"),
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("Capacité 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("Paramètres démographiques"),
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 = "Mortalités"),
radioButtons(inputId = "fatal_constant",
label = h4("Modélisation"),
choices = c("Taux de mortalités (h) constant" = "h",
"Nombre de mortalités (M) constant" = "M")),
### Part for non-cumulated impacts
# Input type
radioButtons(inputId = "fatalities_input_type",
label = h4("Source des données"),
choices = c("Valeurs", "Elicitation d'expert")),
# Values
numericInput(inputId = "fatalities_mean",
label = "Moyenne des mortalités annuelles",
value = 5,
min = 0, max = Inf, step = 0.5),
numericInput(inputId = "fatalities_se",
label = "Ecart-type des mortalités annuelles",
value = 0.05,
min = 0, max = Inf, step = 0.1),
# 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),
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 éoliens",
value = 3, min = 2, max = Inf, step = 1),
matrixInput(inputId = "fatalities_mat_cumulated",
value = matrix(data_fatalities, 3, 3,
dimnames = list(c(paste0("Parc n°", c(1:3))),
c("Moyennes des mortalités annuelles",
"Ecart-type des mortalités annuelles",
"Année 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("Unité"),
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 = data_eli, 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 = "Capacité de charge"),
radioButtons(inputId = "carrying_cap_input_type",
label = h4("Type d'unité"),
choices = c("Valeurs", "Elicitation d'expert")),
numericInput(inputId = "carrying_capacity",
label = "Capacité de charge",
value = 1000,
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),
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 régionale")),
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 = data_eli_trend, 4, 6, dimnames = list(c("#1", "#2", "#3", "#4"), c("Nom", "Poids", "Min", "Meilleure Estimation", "Max", "IC (coverage)" )), 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", "Déclin")),
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 = "Paramètres démographiques"),
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", "Fécondité"))),
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", "Fécondité"))),
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 scénario", align = "center"),
plotOutput("graph_impact", width = "100%", height = "550px"),
hr(),
h4("Graphique : Trajectoire démographique", align = "center"),
plotOutput("graph_traj", width = "100%", height = "550px")),
tabPanel(title = "Distribution paramètres",
br(),
hr(),
h4("#Graphe élicitation d'expert pour les mortalités", align = "center"),
plotOutput(outputId = "fatalities_expert_plot"),
hr(),
h4("#Graphe élicitation d'expert pour la taille de la population", align = "center"),
plotOutput(outputId = "pop_size_expert_plot"),
hr(),
h4("#Graphe élicitation d'expert pour la capacité de charge", align = "center"),
plotOutput(outputId = "carrying_cap_expert_plot"),
hr(),
h4("#Graphe élicitation 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'espèce"),
choices = c("Sédentaire", "Non-sédentaire nicheur", "Non-sédentaire hivernant", "Migrateur de passage")),
numericInput(inputId = "wind_turbines",
h4("Nombre d'éoliennes"),
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'éoliennes"),
value = 1, min = 0, max = Inf, step = 1)
) # End tabPanel
) # End tabSetPanel
) # End mainPanel
) # sidebarLayout
) # FluidPage
# End UI
shinyApp(ui = ui, server = server)