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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
# Initial stuff
{
## Load libraries
library(shiny)
library(shinyjs)
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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)
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 )
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
titlePanel("eolpop : Impact demographique des oliennes"),
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
# Head Panel 1 : type of analysis and species
{wellPanel(
{fluidRow(
# Select type of analysis : cumulated impacted or not
{column(width = 4,
# radioButton : Choix du type d'analyse
{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 cumuls</b> : pour analyser l\\'impact d\\'<b>un seul parc olien</b>. <br><br> <b>Impact cumuls</b> : pour analyser l\\'impact de <b>plusieurs parcs oliens</b> (attention : il faudra fournir des valeurs de mortalits propres chaque parc)."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
),
choices = c("Impacts non cumuls" = "scenario", "Impacts cumuls" = "cumulated")
)},
# Choix de l'espce (selectInput)
{selectInput(inputId = "species_choice",
label = h4(strong("Slectionner une espce"),
bsButton("Q_species_choice", label = "", icon = icon("question"), size = "extra-small"),
bsPopover(id = "Q_species_choice",
title = "Choix de l\\'espce",
content = HTML(
"Ncessaire pour fixer les valeurs de <b>paramtres dmographiques</b> (survie, fcondit). <br> La liste fournie correspond une liste d\\'espces prioritaires. Au besoin, une option \\'espce gnrique\\' est disponible la fin de la liste."
),
placement = "right",
trigger = "click",
options = list(container='body')
)
),
choices = species_list)},
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)}, # 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$span("Modifier les paramtres dmographiques",
style = "font-weight: bold; font-size: 18px;")
),
br(),
matrixInput(inputId = "mat_fill_vr",
label = "",
value = matrix(data = NA, 3, 2,
dimnames = list(c("Juv 1", "Juv 2", "Adulte"), c("Survie", "Fcondit"))),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)
)
)}, # close column
)}, # End fluidRow
)}, # End wellPanel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
# Head Panel 2 : Model parameters
{wellPanel(
p("Saisie des paramtres", style="font-size:28px"),
{fluidRow(
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 1. Fatalities
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_fatalities{background-color:#C2C8D3}')),
actionButton(inputId = "button_fatalities", width = '100%',
label = tags$span("Mortalits annuelles", style = "font-weight: bold; font-size: 18px;")
),
### Part for non-cumulated impacts
# Input type
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{conditionalPanel("output.hide_fatalities",
br(),
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "fatalities_input_type",
label = "Type de saisie",
choices = c("Valeurs" = "val", "Elicitation d'expert" = "eli_exp")),
# Values
numericInput(inputId = "fatalities_mean",
label = "Moyenne des mortalits annuelles",
value = 5,
min = 0, max = Inf, step = 0.5),
numericInput(inputId = "fatalities_se",
label = "Erreur-type des mortalits annuelles",
value = 0.05,
min = 0, max = Inf, step = 0.1),
# Matrix for expert elicitation
matrixInput(inputId = "fatalities_mat_expert",
value = matrix(data = eli_fatalities, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "fatalities_run_expert", label = "Utiliser valeurs experts"),
### Part for cumulated impacts
numericInput(inputId = "farm_number_cumulated",
label = "Nombre de parcs oliens",
value = 3, min = 2, max = Inf, step = 1),
matrixInput(inputId = "fatalities_mat_cumulated",
value = matrix(init_cumul, 3, 3,
dimnames = list(c(paste0("Parc num.", c(1:3))),
c("Moyenne",
"Erreur-type",
"Anne de mise en service du parc"))),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
)}, # close wellPanel
)}, # close conditional panel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 2. Population Size
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_pop_size{background-color:#C2C8D3}')),
actionButton(inputId = "button_pop_size", width = '100%',
label = tags$span("Taille de la population", style = "font-weight: bold; font-size: 18px;")
),
{conditionalPanel("output.hide_pop_size",
br(),
{wellPanel(style = "background:#FFF8DC",
radioButtons(inputId = "pop_size_unit", inline = TRUE,
label = "Unit",
choices = c("Nombre de couple" = "Npair", "Effectif total" = "Ntotal"),
selected = "Ntotal"),
)}, # close wellPanel 1
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "pop_size_input_type",
label = "Type de saisie",
choices = c("Valeurs" = "val", "Elicitation d'expert" = "eli_exp")),
numericInput(inputId = "pop_size_mean",
label = "Moyenne de la taille de la population",
value = 200,
min = 0, max = Inf, step = 50),
numericInput(inputId = "pop_size_se",
label = "Erreur-type de la taille de la population",
value = 25,
min = 0, max = Inf, step = 1),
matrixInput(inputId = "pop_size_mat_expert",
value = matrix(data = eli_pop_size, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "pop_size_run_expert", label = "Utiliser valeurs experts"),
)}, # close wellPanel 2
)}, # close conditional panel
)}, # end column "mortalite"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 3. Population Growth
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$style(HTML('#button_pop_growth{background-color:#C2C8D3}')),
actionButton(inputId = "button_pop_growth", width = '100%',
label = tags$span("Tendance de la population", style = "font-weight: bold; font-size: 18px;")
),
{conditionalPanel("output.hide_pop_growth",
br(),
{wellPanel(style = "background:#F0F8FF",
radioButtons(inputId = "pop_growth_input_type",
label = "Type de saisie",
choices = c("Taux de croissance" = "val",
"Elicitation d'expert" = "eli_exp",
"Tendance locale ou rgionale" = "trend")),
numericInput(inputId = "pop_growth_mean",
label = "Moyenne de la croissance de la population",
value = 1.1,
min = 0, max = Inf, step = 0.01),
numericInput(inputId = "pop_growth_se",
label = "Erreur-type de la croissance de la population",
value = 0.01,
min = 0, max = Inf, step = 0.01),
matrixInput(inputId = "pop_growth_mat_expert",
value = matrix(data = eli_pop_growth, nrow = 4, ncol = 5,
dimnames = list(c("#1", "#2", "#3", "#4"),
c("Poids", "Min", "Best", "Max", "% IC" )),
byrow = TRUE),
class = "numeric",
rows = list(names = TRUE),
cols = list(names = TRUE)),
actionButton(inputId = "pop_growth_run_expert", label = "Utiliser valeurs experts"),
## Input trend: radio buttons
{fluidRow(
# Trend
column(6,
radioButtons(inputId = "pop_trend",
label = "Tendance",
choices = c("Croissance" = "growth",
"Stable" = "stable",
"Dclin" = "decline")),
),
# Strength of trend
column(6,
radioButtons(inputId = "pop_trend_strength",
label = "Force",
choices = c("Faible" = "weak",
"Moyen" = "average",
"Fort" = "strong")),
)}, # close wellPanel
)}, # close conditional panel
)}, # end column "mortalite"
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
##~~~~~~~~~~~~~~~~~~~~~~~~~
## 4. Carrying capacity
##~~~~~~~~~~~~~~~~~~~~~~~~~
{column(width = 3,
tags$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;")
),
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{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 wellPanel
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
###~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###
## Side Panel : Parameter information
{sidebarLayout(
{sidebarPanel(
thierrychambert
committed
p("Valeurs utilises", style="font-size:28px"),
# Mortalites 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"),
)},
# 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"),
)},
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
tabPanel(title = "Distribution paramtres",
br(),
hr(),
#h3("Mortalites annuelles", align = "center"),
span(textOutput(outputId = "title_distri_plot"), style="font-size:24px; font-weight:bold"),
plotOutput(outputId = "distri_plot"),
br(),
numericInput(inputId = "nsim",
label = "Nombre de simulations",
thierrychambert
committed
value = 10, min = 0, max = Inf, step = 10),
choices = c("Taux de mortalits (h) constant" = "h",
"Nombre de mortalits (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")),
tags$h4(textOutput("title_impact_plot"), align = "center"),
plotOutput("impact_plot", width = "100%", height = "550px"),
tags$h4(textOutput("title_traj_plot"), align = "center"),
plotOutput("traj_plot", width = "100%", height = "550px")
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")),
h4("Nombre de parcs"),
value = 1, min = 0, max = Inf, step = 1),
)} # End mainPanel
)} # sidebarLayout
)} # FluidPage
# End UI #~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~###