rm(list = ls(all.names = TRUE))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Initial stuff
{
## Load libraries
library(shiny)
library(shinyjs)
library(shinyBS)
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))
## 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 = 0.03
time_horzion = 30
theta = 1 # DD parameter theta
CP = 0.99 # Coverage probability for lower - upper values
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Pre-fill data
{
## Data elicitation pre-fill data
# fatalities
eli_fatalities <- c(1.0, 2, 5, 8, 0.80,
0.2, 0, 3, 6, 0.90,
0.2, 2, 4, 10, 0.90,
0.1, 1, 3, 7, 0.70)
# population size
eli_pop_size <- c(1.0, 150, 200, 250, 0.80,
0.5, 120, 180, 240, 0.90,
0.8, 170, 250, 310, 0.90,
0.3, 180, 200, 230, 0.70)
# carrying capacity
eli_carrying_cap <- c(1.0, 500, 700, 1000, 0.80,
0.5, 1000, 1500, 2000, 0.90,
0.8, 800, 1200, 1600, 0.90,
0.3, 100, 1200, 1500, 0.70)
# population growth rate
eli_pop_growth <- c(1 , 0.95, 0.98, 1.00, 0.95,
0.2, 0.97, 1.00, 1.01, 0.90,
0.5, 0.92, 0.96, 0.99, 0.90,
0.3, 0.90, 0.95, 0.98, 0.70)
## Other pre-fill data
# fatality table for cumulated impacts (several wind farms)
set.seed(seed = 200)
init_cumul <-
matrix(
round(c(
runif(n = 20, 1, 10),
runif(n = 20, 0.01, 0.20),
sort(sample(x = 2000:2050, size = 20, replace = TRUE))
), 2),
nrow = 20, ncol = 3, byrow = FALSE)
# Undo last 'set.seed'
set.seed( ((((Sys.time() %>% as.numeric) %% 1e10) * 1e9) %% 1e5) %>% round )
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
## User Interface
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
# fluidPage
{ui <- fluidPage(
useShinyjs(),
titlePanel("eolpop : Impact demographique des collisions aviaires avec les �oliennes"),
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
# Head Panel 1 : type of analysis and species
{wellPanel(
{fluidRow(
# Select type of analysis : cumulated impacted or not
{column(width = 4,
# Choose analysis type (radioButton)
{radioButtons(inputId = "analysis_choice",
label = h4(strong("Type d'analyse"),
bsButton("Q_analysis_choice", label = "", icon = icon("question"), size = "extra-small"),
bsPopover(id = "Q_analysis_choice",
title = "Choix du type d\\'analyse",
content = HTML(
"<b>Impacts non cumul�s</b> : pour analyser l\\'impact d\\'<b>un seul parc �olien</b>. <br><br> <b>Impact cumul�s</b> : pour analyser l\\'impact de <b>plusieurs parcs �oliens</b> (attention : il faudra fournir des valeurs de mortalit�s propres � chaque parc)."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
),
choices = c("Impacts non cumul�s" = "scenario", "Impacts cumul�s" = "cumulated")
)},
# Choose species (selectInput)
{selectInput(inputId = "species_choice",
selected = "Faucon cr�cerellette", width = '80%',
label = h4(strong("S�lectionner une esp�ce"),
bsButton("Q_species_choice", label = "", icon = icon("question"), size = "extra-small"),
bsPopover(id = "Q_species_choice",
title = "Choix de l\\'esp�ce",
content = HTML(
"N�cessaire pour fixer les valeurs de <b>param�tres d�mographiques</b> (survie, f�condit�). <br> La liste fournie correspond � une liste d\\'esp�ces prioritaires. Au besoin, une option \\'esp�ce g�n�rique\\' est disponible � la fin de la liste."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
),
choices = species_list)},
)}, # close column
# Show vital rate values (tableOutput)
{column(width = 4,
fluidRow(
h4(strong("Param�tres d�mographiques"),
bsButton("Q_vital_rates_info", label = "", icon = icon("question"), size = "extra-small"),
bsPopover(id = "Q_vital_rates_info",
title = "Param�tres d�mographiques",
content = HTML(
"Valeurs de <b>survie et f�condit�s par classe d\\'�ge</b>, pour l\\'esp�ce s�lectionn�e. <br><br><b>Juv 0</b> correspond � un individu n� dans l\\'ann�e, n\\'ayant <u>pas encore</u> 1 an r�volu.<br><b>Juv 1</b> correspond � un individu ayant 1 an r�volu, donc dans sa 2<sup>e</sup> ann�e de vie.<br>Etc."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
),
tableOutput(outputId = "vital_rates_info"),
),
)}, # close column
## Modify vital rates, if needed (actionButton and matrixInput)
{column(width = 4,
tags$style(HTML('#button_vital_rates{background-color:#C2C8D3}')),
actionButton(inputId = "button_vital_rates",
label = tags$span("Modifier les param�tres d�mographiques",
style = "font-weight: bold; font-size: 18px;")
),
br(),
matrixInput(inputId = "mat_fill_vr",
label = "",
value = matrix(data = NA, 3, 2,
dimnames = list(c("Juv 1", "Juv 2", "Adulte"), c("Survie", "F�condit�"))),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)
)
)}, # close column
)}, # End fluidRow
)}, # End wellPanel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
# Head Panel 2 : Model parameters
{wellPanel(
## Enter parameter values (TITLE)
{p("Saisie des param�tres", style="font-size:28px",
bsButton("Q_param_enter", label = "", icon = icon("question"), size = "extra-small"),
bsPopover(id = "Q_param_enter",
title = "Saisie des param�tres pour l\\'analyse",
content = HTML(
"Cliquer sur les boutons ci-dessous pour saisir les valeurs des quatre param�tres requis pour l\\'analyse : <br>(1) Mortalit�s annuelles, <br>(2) Taille de la population, <br>(3) Tendance de la population, <br>(4) Capacit� de charge."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
)},
{fluidRow(
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 1. Fatalities
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_fatalities{background-color:#C2C8D3}')),
actionButton(inputId = "button_fatalities", width = '100%',
label = tags$span("Mortalit�s annuelles", style = "font-weight: bold; font-size: 18px;")
),
bsPopover(id = "button_fatalities",
title = "Mortalit�s annuelles",
content = HTML(
"Nombre de mortalit�s totales <b><u>annuelles</u> (cad. sur 12 mois) </b> attendues, pour l\\'esp�ce s�lectionn�e, sur chaque parc �olien concern� (somme des mortalit�s attendues sur toutes les �oliennes d\\'un parc)."
),
placement = "top",
trigger = "hover",
options = list(container='body')
),
### Part for non-cumulated impacts
# Input type
{conditionalPanel("output.hide_fatalities",
br(),
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "fatalities_input_type",
label = "Type de saisie",
choices = c("Intervalle" = "itvl",
"Valeurs" = "val",
"Elicitation d'expert" = "eli_exp")),
# Interval
numericInput(inputId = "fatalities_lower",
label = "Borne inf�rieure (mortalit�s annuelles)",
value = 0.5,
min = 0, max = Inf, step = 0.5),
numericInput(inputId = "fatalities_upper",
label = "Borne sup�rieure (mortalit�s annuelles)",
value = 2.5,
min = 0, max = Inf, step = 0.5),
# Values
numericInput(inputId = "fatalities_mean",
label = "Moyenne (mortalit�s annuelles)",
value = 2.2,
min = 0, max = Inf, step = 0.5),
numericInput(inputId = "fatalities_se",
label = "Erreur-type (mortalit�s annuelles)",
value = 0.5,
min = 0, max = Inf, step = 0.1),
# Matrix for expert elicitation
matrixInput(inputId = "fatalities_mat_expert",
value = matrix(data = eli_fatalities, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "fatalities_run_expert", label = "Utiliser valeurs experts"),
### 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",
label = span("Mortalit�s dans chaque parc",
bsButton("Q_fatalities_mat_cumulated", label = "", icon = icon("question"), size = "extra-small"),
bsPopover(id = "Q_fatalities_mat_cumulated",
title = "Mortalit�s cumul�es",
content = HTML(
"1 ligne = 1 parc <br><br>Les parcs doivent �tre fournis dans l\\'<b>ordre chronologique</b> de leur mise en service (\\'Ann�e d�but\\'). <br><br>Pour chaque parc, veuillez indiquer la <u>moyenne</u> et l\\'<u>erreur-type</u> du nombre de mortalit�s estim�es, ainsi que son <u>ann�e de mise en service</u>."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
),
value = matrix(init_cumul, 3, 3,
dimnames = list(c(paste0("Parc num.", c(1:3))),
c("Moyenne",
"Erreur-type",
"Ann�e de mise en service du parc"))),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
)}, # close wellPanel
)}, # close conditional panel
)}, # end column "mortalit�"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 2. Population Size
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_pop_size{background-color:#C2C8D3}')),
actionButton(inputId = "button_pop_size", width = '100%',
label = tags$span("Taille de la population", style = "font-weight: bold; font-size: 18px;")
),
bsPopover(id = "button_pop_size",
title = "Taille de la population",
content = HTML(
"Effectif de la population cible pour l\\'analyse d\\'impact. <br> Il peut s\\'agir soit du <b>nombre de couples</b>, soit de l\\'<b>effectif total</b> de la population (cad. toutes classes d\\'�ge incluses)."
),
placement = "top",
trigger = "hover",
options = list(container='body')
),
{conditionalPanel("output.hide_pop_size",
br(),
{wellPanel(style = "background:#FFF8DC",
radioButtons(inputId = "pop_size_unit", inline = TRUE,
label = "Unit�",
choices = c("Nombre de couples" = "Npair", "Effectif total" = "Ntotal"),
selected = "Npair"),
)}, # close wellPanel 1
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "pop_size_input_type",
label = "Type de saisie",
choices = c("Intervalle" = "itvl",
"Valeurs" = "val",
"Elicitation d'expert" = "eli_exp")),
# Interval
numericInput(inputId = "pop_size_lower",
label = "Borne inf�rieure (taille population)",
value = 130,
min = 0, max = Inf, step = 10),
numericInput(inputId = "pop_size_upper",
label = "Borne sup�rieure (taille population)",
value = 140,
min = 0, max = Inf, step = 10),
# Values
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 = "Erreur-type de la taille de la population",
value = 25,
min = 0, max = Inf, step = 1),
# Matrix for expert elicitation
matrixInput(inputId = "pop_size_mat_expert",
value = matrix(data = eli_pop_size, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "pop_size_run_expert", label = "Utiliser valeurs experts"),
)}, # close wellPanel 2
)}, # close conditional panel
)}, # end column "mortalite"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 3. Population Growth
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_pop_growth{background-color:#C2C8D3}')),
actionButton(inputId = "button_pop_growth", width = '100%',
label = tags$span("Tendance de la population", style = "font-weight: bold; font-size: 18px;")
),
bsPopover(id = "button_pop_growth",
title = "Tendance de la population",
content = HTML(
"<b>Taux de croissance annuel (λ) </b> de la population (avec λ = 1 pour une population stable). <br>A d�faut, on pourra juste cocher la <b>tendance globale</b> (d�clin, stabilit� ou croissance) et l\\'intensit� de cette tendance (faible, moyenne, forte)."
),
placement = "top",
trigger = "hover",
options = list(container='body')
),
{conditionalPanel("output.hide_pop_growth",
br(),
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "pop_growth_input_type",
label = "Type de saisie",
choices = c("Taux de croissance" = "val",
"Elicitation d'expert" = "eli_exp",
"Tendance locale ou r�gionale" = "trend")),
## Input values: mean and se
numericInput(inputId = "pop_growth_mean",
label = "Moyenne de la croissance de la population",
value = 0.99,
min = 0, max = Inf, step = 0.01),
numericInput(inputId = "pop_growth_se",
label = "Erreur-type de la croissance de la population",
value = 0,
min = 0, max = Inf, step = 0.01),
## Input expert elicitation: table
matrixInput(inputId = "pop_growth_mat_expert",
value = matrix(data = eli_pop_growth, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "pop_growth_run_expert", label = "Utiliser valeurs experts"),
## Input trend: radio buttons
{fluidRow(
# Trend
column(6,
radioButtons(inputId = "pop_trend",
label = "Tendance",
choices = c("Croissance" = "growth",
"Stable" = "stable",
"D�clin" = "decline")),
),
# Strength of trend
column(6,
radioButtons(inputId = "pop_trend_strength",
label = "Force",
choices = c("Faible" = "weak",
"Moyen" = "average",
"Fort" = "strong")),
),
)}, # close fluidRow
)}, # close wellPanel
)}, # close conditional panel
)}, # end column "mortalite"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 4. Carrying capacity
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_carrying_cap{background-color:#C2C8D3}')),
actionButton(inputId = "button_carrying_cap", width = '100%',
label = tags$span("Capacit� de charge", style = "font-weight: bold; font-size: 18px;")
),
bsPopover(id = "button_carrying_cap",
title = "Capacit� de charge",
content = HTML(
"La capacit� de charge correspond � la <b>taille maximale que peut atteindre la population</b> dans son environnement et les limites spatiales consid�r�es. <br><br><u>Note:</u> Ce chiffre sera exprim� dans la <b>m�me unit�</b> que la taille de population (cad. nombre de couples ou effectif total). <br>Il n\\'a pas besoin d\\'�tre tr�s pr�cis ; il doit simplement fournir un ordre de grandeur de la taille limite au-del� de laquelle la population ne peut plus cro�tre (environnement local �satur�)."
),
placement = "top",
trigger = "hover",
options = list(container='body')
),
{conditionalPanel("output.hide_carrying_cap",
br(),
{wellPanel(style = "background:#FFF8DC",
span(textOutput(outputId = "carrying_cap_unit_info"), style="font-size:16px"),
)}, # close wellPanel 1
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "carrying_cap_input_type",
label = "Type de saisie",
choices = c("Valeurs" = "val", "Elicitation d'expert" = "eli_exp")),
numericInput(inputId = "carrying_capacity",
label = "Capacit� de charge",
value = 500,
min = 0, max = Inf, step = 100),
matrixInput(inputId = "carrying_cap_mat_expert",
value = matrix(data = eli_carrying_cap, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "carrying_cap_run_expert", label = "Utiliser valeurs experts"),
)}, # close wellPanel 2
)}, # close conditional panel
)}, # end column "fatalities"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
)}, # # End fluidRow
)}, # # End wellPanel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
## Side Panel : Parameter information
{sidebarLayout(
{sidebarPanel(
p("Valeurs s�lectionn�es", style="font-size:28px",
bsButton("Q_selected_values", label = "", icon = icon("question"), size = "extra-small"),
bsTooltip(id = "Q_selected_values",
title = "Rappel des valeurs de param�tres actuellement s�lectionn�es.",
placement = "right",
trigger = "click",
options = list(container='body')
)
),
# Mortalites annuelles
{wellPanel(style = "background:#DCDCDC",
p("Mortalit�s annuelles", style="font-size:20px; font-weight: bold"),
span(textOutput(outputId = "fatalities_mean_info"), style="font-size:16px"),
span(textOutput(outputId = "fatalities_se_info"), style="font-size:16px"),
)},
# Taille de population
{wellPanel(style = "background:#DCDCDC",
p("Taille de la population", style="font-size:20px; font-weight: bold"),
shiny::tags$u(textOutput(outputId = "pop_size_unit_info"), style="font-size:16px"),
p(""),
span(textOutput(outputId = "pop_size_mean_info"), style="font-size:16px"),
span(textOutput(outputId = "pop_size_se_info"), style="font-size:16px"),
)},
# Tendance de la population
{wellPanel(style = "background:#DCDCDC",
p("Tendance de la population", style="font-size:20px; font-weight: bold"),
span(textOutput(outputId = "pop_growth_mean_info"), style="font-size:16px"),
span(textOutput(outputId = "pop_growth_se_info"), style="font-size:16px"),
)},
# Capacite de charge
{wellPanel(style = "background:#DCDCDC",
p("Capacit� de charge", style="font-size:20px; font-weight: bold"),
span(textOutput(outputId = "carrying_capacity_info"), style="font-size:16px"),
)},
)}, # End sidebarPanel
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Creation of outputs parts
{mainPanel(
tabsetPanel(
tabPanel(title = "Distribution param�tres",
br(),
hr(),
#h3("Mortalites annuelles", align = "center"),
span(textOutput(outputId = "title_distri_plot"), style="font-size:24px; font-weight:bold"),
plotOutput(outputId = "distri_plot"),
), # End tabPanel
tabPanel(title = "Impact population",
br(),
numericInput(inputId = "nsim",
label = "Nombre de simulations",
value = 10, min = 0, max = Inf, step = 10),
radioButtons(inputId = "fatal_constant",
label = "Mod�lisation",
choices = c("Taux de mortalit�s (h) constant" = "h",
"Nombre de mortalit�s (M) constant" = "M")),
br(),
actionButton(inputId = "run", label = "Lancer l'analyse"),
hr(),
span(textOutput("title_impact_result"), align = "left", style = "font-weight: bold; font-size: 18px;"),
br(),
strong(span(textOutput("impact_text"), style="color:blue; font-size:18px", align = "left")),
strong(span(tableOutput("impact_table"), style="color:blue; font-size:18px", align = "left")),
br(),
hr(),
tags$h4(textOutput("title_impact_plot"), align = "center"),
plotOutput("impact_plot", width = "100%", height = "550px"),
hr(),
tags$h4(textOutput("title_traj_plot"), align = "center"),
plotOutput("traj_plot", width = "100%", height = "550px")
), # End tabPanel
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_farm_nb",
h4("Nombre de parcs"),
value = 1, min = 0, max = Inf, step = 1),
numericInput(inputId = "wind_turbine_nb",
h4("Nombre d'�oliennes"),
value = 1, min = 0, max = Inf, step = 1)
) # End tabPanel
) # End tabSetPanel
)} # End mainPanel
)} # sidebarLayout
)} # FluidPage
# End UI #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###