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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Initial stuff
{
## 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))
## 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
theta = 1 # DD parameter theta
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# 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
# 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)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
titlePanel("eolpop : Impact demographique des oliennes"),
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###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
# Head Panel 1 : type of analysis and species
{wellPanel(
{fluidRow(
# Select type of analysis : cumulated impacted or not
{column(width = 4,
radioButtons(inputId = "analysis_choice",
h4(strong("Slectionner un type d'analyse")),
choices = c("Impacts non cumuls" = "scenario", "Impacts cumuls" = "cumulated")),
selectInput(inputId = "species_choice",
selected = 1, width = '80%',
label = h4(strong("Slectionner une espce")),
choices = species_list),
)}, # close column
# Show vital rate values
{column(width = 4,
fluidRow(
h4(strong("Paramtres dmographiques")),
tableOutput(outputId = "vital_rates_info"),
),
)}, # close column
## Modify vital rates (if needed)
{column(width = 4,
tags$style(HTML('#button_vital_rates{background-color:#C2C8D3}')),
actionButton(inputId = "button_vital_rates",
label = tags$span("Modifier les paramtres dmographiques",
style = "font-weight: bold; font-size: 18px;")
),
br(),
matrixInput(inputId = "mat_fill_vr",
label = "",
value = matrix(data = NA, 3, 2,
dimnames = list(c("Juv 1", "Juv 2", "Adulte"), c("Survie", "Fcondit"))),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)
)
)}, # close column
)}, # End fluidRow
)}, # End wellPanel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
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# Head Panel 2 : Model parameters
{wellPanel(
#h2("Saisie des paramtres"),
p("Saisie des paramtres", style="font-size:28px"),
{fluidRow(
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 1. Fatalities
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_fatalities{background-color:#C2C8D3}')),
actionButton(inputId = "button_fatalities",
label = tags$span("Mortalits annuelles", style = "font-weight: bold; font-size: 18px;")
),
br(""),
### Part for non-cumulated impacts
# Input type
radioButtons(inputId = "fatalities_input_type",
label = "Type de saisie",
choices = c("Valeurs" = "val", "Elicitation d'expert" = "eli_exp")),
# Values
numericInput(inputId = "fatalities_mean",
label = "Moyenne des mortalits annuelles",
value = 5,
min = 0, max = Inf, step = 0.5),
numericInput(inputId = "fatalities_se",
label = "Erreur-type des mortalits annuelles",
value = 0.05,
min = 0, max = Inf, step = 0.1),
# Matrix for expert elicitation
matrixInput(inputId = "fatalities_mat_expert",
value = matrix(data = eli_fatalities, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "fatalities_run_expert", label = "Utiliser valeurs experts"),
### Part for cumulated impacts
numericInput(inputId = "farm_number_cumulated",
label = "Nombre de parcs oliens",
value = 3, min = 2, max = Inf, step = 1),
matrixInput(inputId = "fatalities_mat_cumulated",
value = matrix(init_cumul, 3, 3,
dimnames = list(c(paste0("Parc n", c(1:3))),
c("Moyenne",
"Erreur-type",
"Anne de mise en service du parc"))),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
)}, # end column "mortalit"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
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##~~~~~~~~~~~~~~~~~~~~~~~~~
## 2. Population Size
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_pop_size{background-color:#C2C8D3}')),
actionButton(inputId = "button_pop_size",
label = tags$span("Taille de la population", style = "font-weight: bold; font-size: 18px;")
),
br(""),
conditionalPanel("output.hide_pop_size",
wellPanel(style = "background:#FFF8DC",
radioButtons(inputId = "pop_size_unit", inline = TRUE,
label = "Unit",
choices = c("Nombre de couple" = "Npair", "Effectif total" = "Ntotal"),
selected = "Ntotal"),
),
),
radioButtons(inputId = "pop_size_input_type",
label = "Type de saisie",
choices = c("Valeurs" = "val", "Elicitation d'expert" = "eli_exp")),
numericInput(inputId = "pop_size_mean",
label = "Moyenne de la taille de la population",
value = 200,
min = 0, max = Inf, step = 50),
numericInput(inputId = "pop_size_se",
label = "Erreur-type de la taille de la population",
value = 25,
min = 0, max = Inf, step = 1),
matrixInput(inputId = "pop_size_mat_expert",
value = matrix(data = eli_pop_size, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "pop_size_run_expert", label = "Utiliser valeurs experts"),
)}, # end column "mortalit"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
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##~~~~~~~~~~~~~~~~~~~~~~~~~
## 3. Population Growth
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_pop_trend{background-color:#C2C8D3}')),
actionButton(inputId = "button_pop_trend",
label = tags$span("Tendance de la population", style = "font-weight: bold; font-size: 18px;")
),
br(""),
radioButtons(inputId = "pop_growth_input_type",
label = "Type de saisie",
choices = c("Taux de croissance" = "val",
"Elicitation d'expert" = "eli_exp",
"Tendance locale ou rgionale" = "trend")),
numericInput(inputId = "pop_growth_mean",
label = "Moyenne de la croissance de la population",
value = 1.1,
min = 0, max = Inf, step = 0.01),
numericInput(inputId = "pop_growth_se",
label = "Erreur-type de la croissance de la population",
value = 0.01,
min = 0, max = Inf, step = 0.01),
matrixInput(inputId = "pop_growth_mat_expert",
value = matrix(data = eli_pop_growth, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "pop_growth_run_expert", label = "Utiliser valeurs experts"),
radioButtons(inputId = "pop_trend",
label = NULL,
choices = c("Croissance", "Stable", "Dclin")),
radioButtons(inputId = "pop_trend_strength",
label = NULL,
choices = c("Faible", "Moyen", "Fort")),
)}, # end column "mortalit"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 4. Carrying capacity
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_carrying_cap{background-color:#C2C8D3}')),
actionButton(inputId = "button_carrying_cap",
label = tags$span("Capacit de charge", style = "font-weight: bold; font-size: 18px;")
),
br(""),
radioButtons(inputId = "carrying_cap_input_type",
label = "Type de saisie",
choices = c("Valeurs" = "val", "Elicitation d'expert" = "eli_exp")),
numericInput(inputId = "carrying_capacity",
label = "Capacit de charge",
value = 500,
min = 0, max = Inf, step = 100),
matrixInput(inputId = "carrying_cap_mat_expert",
value = matrix(data = eli_carrying_cap, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "carrying_cap_run_expert", label = "Utiliser valeurs experts"),
)}, # end column "mortalit"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
)}, # # End wellPanel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
## Side Panel : Parameter information
{sidebarLayout(
{sidebarPanel(
# Mortalits annuelles
{wellPanel(style = "background:#DCDCDC",
p("Mortalits annuelles", style="font-size:20px; font-weight: bold"),
span(textOutput(outputId = "fatalities_mean_info"), style="font-size:16px"),
span(textOutput(outputId = "fatalities_se_info"), style="font-size:16px"),
)},
# Taille de population
{wellPanel(style = "background:#DCDCDC",
p("Taille de la population", style="font-size:20px; font-weight: bold"),
shiny::tags$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"),
)},
# Capacit 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"),
)},
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tabPanel(title = "Distribution paramtres",
br(),
hr(),
h3("Mortalits annuelles", align = "center"),
plotOutput(outputId = "fatalities_distri_plot"),
br(""),
hr(),
h3("Taille de la population", align = "center"),
plotOutput(outputId = "pop_size_distri_plot"),
br(""),
hr(),
h3("Taux de croissance de la population", align = "center"),
plotOutput(outputId = "pop_growth_distri_plot"),
br(""),
hr(),
h3("Capacit de charge: Elicitation d'expert", align = "center"),
plotOutput(outputId = "carrying_cap_distri_plot"),
), # End tabPanel
numericInput(inputId = "nsim", label = "Nombre de simulations",
value = 50, min = 0, max = Inf, step = 10),
###### A DEPLACER #############
radioButtons(inputId = "fatal_constant",
label = h4("Modlisation"),
choices = c("Taux de mortalits (h) constant" = "h",
"Nombre de mortalits (M) constant" = "M")),
###############################
br(),
strong(span(textOutput("message"), style="color:blue; font-size:24px", align = "center")),
actionButton(inputId = "run", label = "Lancer l'analyse"),
hr(),
h4("Graphique : Impact relatif de chaque scnario", align = "center"),
plotOutput("graph_impact", width = "100%", height = "550px"),
hr(),
h4("Graphique : Trajectoire dmographique", align = "center"),
plotOutput("graph_traj", width = "100%", height = "550px")
), # End tabPanel
tabPanel(title = "Rapport",
br(),
radioButtons(inputId = "lifestyle",
h4("Mode de vie de l'espce"),
choices = c("Sdentaire", "Non-sdentaire nicheur", "Non-sdentaire hivernant", "Migrateur de passage")),
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",
)} # End mainPanel
)} # sidebarLayout
)} # FluidPage
# End UI #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###