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helpers.r
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helpers.r
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# modifying behaviour of qtnorm to deal with its errors when the specified parameters fall outside allowed values (e.g. when mu>upper and sd==0), returning 0
qtnorm_possibly <- possibly(qtnorm, otherwise = 0)
fread_possibly <- possibly(fread, otherwise = NULL)
# Function to create icons and labels with info about parameters
label.help <- function(label, id){
HTML(paste0(label, actionLink(id,label=NULL,icon=icon('info-circle'))))
}
NormNumericInput <- function(paramID, specID, varName, infoId="foo", infoText ="",
E_value=50, E_min=1, E_max=100, E_step=1,
SD_value=50, SD_min=1, SD_max=100, SD_step=1,
via_InsertUI = FALSE){
if(via_InsertUI==FALSE){
toolTip <- bsTooltip(
#id = paste0("lbl_", paramID),
id = infoId,
title = infoText,
options = list(container = "body"),
placement = "right", trigger = "hover")
}else{
toolTip <- NULL
}
# wellPanel(width=5,
# style = "padding: 5px;",
div(
splitLayout(
cellWidths = "50%",
numericInput(inputId = paste0("numInput_", paramID, "_E_", specID),
label = label.help(varName, infoId), #varName,
min = E_min, max = E_max, step = E_step,
value = E_value, width = '90%'),
numericInput(inputId = paste0("numInput_", paramID, "_SD_", specID),
label = paste0("SD of ", varName),
#label = "Std. Dev.",
min = SD_min, max = SD_max, step = SD_step,
value = SD_value, width = '90%')
),
toolTip
)
}
selectSpecies_UITabBuilder <- function(specName, tabName, specLabel, session, specStartVals){
plotWidth <- 330
plotHeight <- 200
tabItem(
tabName = tabName,
fluidRow(
box(
title = paste0(specName, " Parameters"),
width = 12,
status = "primary",
solidHeader = TRUE,
#side = "right",
fluidRow(
column(width = 4,
box(width=12,
radioGroupButtons(inputId = paste0("slctInput_biomPars_flType_tp_", specLabel),
label = label.help("Flight Type", paste0("lbl_flType_", specLabel)),
choices = c("Flapping", "Gliding"),
selected = ifelse(is.null(specStartVals$flType), "Flapping", specStartVals$flType),
individual = TRUE, justified = FALSE,
checkIcon = list(yes = icon("ok", lib = "glyphicon"),
no = icon("remove", lib = "glyphicon"))
)
)
)
),
fluidRow(
column(width = 4,
box(width = 12,
NormNumericInput(paramID = "biomPars_bodyLt", specID = specLabel,
varName = "Body Length (m)",
infoId = paste0("lbl_bodyLt_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$bodyLt_E), 1, specStartVals$bodyLt_E),
E_min=0, E_max=5, E_step = 0.01,
SD_value = ifelse(is.null(specStartVals$bodyLt_SD), 0, specStartVals$bodyLt_SD),
SD_min = 0, SD_step = 0.001),
h5(paste0("PDF of ", specName, "'s body length")),
plotOutput(paste0("plot_biomPars_bodyLt_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_bodyLt_", specLabel))
)
)
),
column(width = 4,
box(width = 12,
NormNumericInput(paramID = "biomPars_wngSpan", specID = specLabel,
varName = "Wing Span (m)",
infoId = paste0("lbl_wngSpan_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$wngSpan_E), 1, specStartVals$wngSpan_E),
E_min=0, E_step = 0.01,
SD_value = ifelse(is.null(specStartVals$wngSpan_SD), 0, specStartVals$wngSpan_SD),
SD_min = 0, SD_step = 0.001),
h5(paste0("PDF of ", specName, "'s wing span")),
plotOutput(paste0("plot_biomPars_wngSpan_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_wngSpan_", specLabel))
)
)
),
column(width = 4,
box(width = 12,
NormNumericInput( paramID = "biomPars_flSpeed", specID = specLabel,
varName = "Flight Speed (m/s)",
infoId = paste0("lbl_flSpeed_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$flSpeed_E), 1, specStartVals$flSpeed_E),
E_min=0, E_step = 0.01,
SD_value = ifelse(is.null(specStartVals$flSpeed_SD), 0, specStartVals$flSpeed_SD),
SD_min = 0, SD_step = 0.01),
h5(paste0("PDF of ", specName, "'s flight speed")),
plotOutput(paste0("plot_biomPars_flSpeed_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_flSpeed_", specLabel))
)
)
)
),
br(),
br(),
fluidRow(
column(width = 4,
box(width = 12,
NormNumericInput(paramID = "biomPars_noctAct", specID = specLabel,
varName = "Nocturnal Activity",
infoId = paste0("lbl_noctAct_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$noctAct_E), 1, specStartVals$noctAct_E),
E_min=0, E_step = 0.001,
SD_value = ifelse(is.null(specStartVals$noctAct_SD), 0, specStartVals$noctAct_SD),
SD_min = 0, SD_step = 0.001),
h5(paste0("PDF of ", specName, "'s Nocturnal Activity")),
plotOutput(paste0("plot_biomPars_noctAct_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_noctAct_", specLabel))
)
)
),
column(width = 4,
box(width = 12,
NormNumericInput(paramID = "biomPars_basicAvoid", specID = specLabel,
varName = "Basic Avoidance",
infoId = paste0("lbl_basicAvoid_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$basicAvoid_E), 1, specStartVals$basicAvoid_E),
E_min=0, E_step = 0.001,
SD_value = ifelse(is.null(specStartVals$basicAvoid_SD), 0, specStartVals$basicAvoid_SD),
SD_min = 0, SD_step = 0.001),
h5(paste0("PDF of ", specName, "'s basic avoidance")),
plotOutput(paste0("plot_biomPars_basicAvoid_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_basicAvoid_", specLabel))
)
)
),
column(width = 4,
box(width = 12,
NormNumericInput(paramID = "biomPars_extAvoid", specID = specLabel,
varName = "Extended Avoidance",
infoId = paste0("lbl_extAvoid_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$extAvoid_E), 1, specStartVals$extAvoid_E),
E_min=0, E_step = 0.001,
SD_value = ifelse(is.null(specStartVals$extAvoid_SD), 0, specStartVals$extAvoid_SD),
SD_min = 0, SD_step = 0.001),
h5(paste0("PDF of ", specName, "'s extended avoidance")),
plotOutput(paste0("plot_biomPars_extAvoid_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_extAvoid_", specLabel))
)
)
)
),
br(),
br(),
fluidRow(
column(width = 4,
box(width = 12,
NormNumericInput(paramID = "biomPars_CRHeight", specID = specLabel,
varName = "Proportion at CRH",
infoId = paste0("lbl_CRHeight_", specLabel),
via_InsertUI = TRUE,
E_value = ifelse(is.null(specStartVals$CRHeight_E), 1, specStartVals$CRHeight_E),
E_min=0, E_step = 0.01,
SD_value = ifelse(is.null(specStartVals$CRHeight_SD), 0, specStartVals$CRHeight_SD),
SD_min = 0, SD_step = 0.001),
h5(paste0("PDF of ", specName, "'s Collision Risk Height")),
plotOutput(paste0("plot_biomPars_CRHeight_", specLabel), width = plotWidth, height = plotHeight),
column(11,
verbatimTextOutput(paste0("qtls_biomPars_CRHeight_", specLabel))
)
)
),
column(width = 8,
box(width=12,
tags$b(HTML(paste0("Flight Height Distribution",
actionLink(paste0("lbl_FHD_", specLabel), label=NULL,
icon=icon('info-circle'))))),
br(),
br(),
fluidRow(
column(5,
radioGroupButtons(inputId = paste0("slctInput_userOpts_FHD_dtSrc_", specLabel),
individual = TRUE,
justified = TRUE,
label = "Choose data source:",
choices = c("Johnson et al (2014)" = "default",
"Other" = "other"),
selected = ifelse(is.null(specStartVals$FHD_dtSrc), "default", specStartVals$FHD_dtSrc),
checkIcon = list(yes = tags$i(class = "fa fa-circle",
style = "color: steelblue"),
no = tags$i(class = "fa fa-circle-o",
style = "color: steelblue")))
)
),
# Panels for default FHD data
conditionalPanel(
condition = paste0("input.slctInput_userOpts_FHD_dtSrc_", specLabel, " == 'default'"),
br(),
column(12, p(paste0("Proportion of ", specName," flying at 1m height intervals
(medians and 95% intervals of bootstrap data) - Default Data"))),
br(),
plotOutput(paste0("plot_defaultFHD_QtsBoot_", specLabel), width = "100%", height = 400),
br(),
column(3, offset = 9,
helpText(tags$i(tags$a(href ="http://onlinelibrary.wiley.com/doi/10.1111/1365-2664.12191/full",
target = "_blank", "Source: Johnson et al (2014)")))),
# # --- Default FHD data
# awesomeRadio(inputId = paste0("aweRadio_userOpts_defaultFHDPlotType_", specLabel),
# label = "Data visualisation",
# choices = c("Bootstrap quantiles" = "Qtls",
# "Bootstrap samples" = "bootSamp"),
# inline = TRUE,
# selected = "Qtls",
# status = "warning"),
#
# # nested conditions for panels with plots of bootstrap data
# conditionalPanel(condition = paste0("input.aweRadio_userOpts_defaultFHDPlotType_", specLabel, " == 'Qtls'"),
# column(12, p(paste0("Proportion of ", specName," flying at 1m height intervals
# (medians and 95% intervals of bootstrap data) - Default Data"))),
# br(),
# plotOutput(paste0("plot_defaultFHD_QtsBoot_", specLabel), width = "100%", height = 400),
# br(),
# column(3, offset = 9,
# helpText(tags$i(tags$a(href ="http://onlinelibrary.wiley.com/doi/10.1111/1365-2664.12191/full",
# target = "_blank", "Source: Johnson et al (2014)"))))
# ),
# conditionalPanel(condition = paste0("input.aweRadio_userOpts_defaultFHDPlotType_", specLabel, " == 'bootSamp'"),
# column(12, p(paste0("100 Bootstrap samples of proportion of ", specName, " flying at 1m height
# bands (first 50m plotted; full data up to 300m) - Default Data"))),
# br(),
# d3heatmapOutput(paste0("plot_defaultFHD_allBoots_", specLabel), width = "105%", height = 430),
# column(3, offset = 9,
# helpText(tags$i(tags$a(href ="http://onlinelibrary.wiley.com/doi/10.1111/1365-2664.12191/full",
# target = "_blank",
# "Source: Johnson et al (2014)"))))
# )
),
conditionalPanel(
condition = paste0("input.slctInput_userOpts_FHD_dtSrc_", specLabel, " == 'other'"),
br(),
uiOutput(paste0("renderUI_uploadUserFHD_", specLabel), inline = TRUE),
column(12,
column(12, p(paste0("Proportion of ", specName," flying at 1m height intervals
(medians and 95% intervals of bootstrap data) - Uploaded Data"))),
br(),
plotOutput(paste0("plot_UserFHD_QtsBoot_", specLabel), width = "100%", height = 430)
# # --- User FHD data
# awesomeRadio(inputId = paste0("aweRadio_userOpts_UserFHDPlotType_", specLabel),
# label = "Data visualisation",
# choices = c("Bootstrap quantiles" = "Qtls",
# "Bootstrap samples" = "bootSamp"),
# inline = TRUE,
# selected = "Qtls",
# status = "warning"),
#
# # nested conditions for panels with plots of bootstrap data
# conditionalPanel(condition = paste0("input.aweRadio_userOpts_UserFHDPlotType_", specLabel, " == 'Qtls'"),
# column(12, p(paste0("Proportion of ", specName," flying at 1m height intervals
# (medians and 95% intervals of bootstrap data) - Uploaded Data"))),
# br(),
# plotOutput(paste0("plot_UserFHD_QtsBoot_", specLabel), width = "100%", height = 430)
# ),
# conditionalPanel(condition = paste0("input.aweRadio_userOpts_UserFHDPlotType_", specLabel, " == 'bootSamp'"),
# column(12, p(paste0("100 Bootstrap samples of proportion of ", specName, " flying at 1m height
# bands (only first 50m plotted) - Uploaded Data"))),
# br(),
# d3heatmapOutput(paste0("plot_UserFHD_allBoots_", specLabel), width = "105%", height = 430)
# )
)
)
)
)
),
br(),
fluidRow(
box(width = 12,
tags$b(HTML(paste0("Monthly Densities", actionLink(paste0("lbl_monthOPs_", specLabel), label=NULL, icon=icon('info-circle'))))),
br(),
br(),
radioGroupButtons(inputId = paste0("slctInput_userOpts_monthDens_sampler_", specLabel),
individual = TRUE,
justified = FALSE,
label = "Choose how to specify the distribution of monthly bird densities",
choices = c("Truncated Normal" = "truncNorm",
"Distribution reference points" = "pcntiles",
"Distribution samples" = "reSamp"),
selected = ifelse(is.null(specStartVals$monthDens_sampler), "truncNorm", specStartVals$monthDens_sampler),
checkIcon = list(yes = tags$i(class = "fa fa-circle",
style = "color: steelblue"),
no = tags$i(class = "fa fa-circle-o",
style = "color: steelblue"))),
br(),
conditionalPanel(condition = paste0("input.slctInput_userOpts_monthDens_sampler_", specLabel, " == 'truncNorm'"),
helpText("Provide the means and standard deviations of monthly densities, assuming Truncated Normals bounded at 0"),
br(),
rHandsontableOutput(paste0("hotInput_birdDensPars_tnorm_", specLabel), width = "100%"),
tags$style(type="text/css", paste0("#hotInput_birdDensPars_tnorm_", specLabel, " th {font-weight:bold;}")),
br(),
br(),
br(),
fluidRow(
column(width=8, offset = 2,
plotOutput(paste0("plot_birdDensPars_", specLabel), width = 800, height = 350)
)
)
),
conditionalPanel(condition = paste0("input.slctInput_userOpts_monthDens_sampler_", specLabel, " == 'pcntiles'"),
uiOutput(paste0("renderUI_userUpload_monthDens_summaries_", specLabel), inline = TRUE),
br(),
br(),
fluidRow(
column(12,
plotOutput(paste0("plot_inputMonthDens_summaries_", specLabel), width = "100%", height = 300)
)
),
br(),
br(),
fluidRow(
column(12, offset = 3,
plotOutput(paste0("plot_inputMonthDens_QtlsBars_summaries_", specLabel), width = 800, height = 350)
)
)
),
conditionalPanel(condition = paste0("input.slctInput_userOpts_monthDens_sampler_", specLabel, " == 'reSamp'"),
uiOutput(paste0("renderUI_userUpload_monthDens_samples_", specLabel), inline = TRUE),
br(),
br(),
fluidRow(
column(12,
plotOutput(paste0("plot_inputMonthDens_samples_", specLabel), width = "100%", height = 400)
)
),
br(),
br(),
fluidRow(
column(12, offset = 3, plotOutput(paste0("plot_inputMonthDens_QtlsBars_samples_", specLabel), width = 800, height = 350))
)
),
br(),
br()
)
),
# Include bsTooltips with info on parameters
uiOutput(paste0("BiomBStoolTips_", specLabel))
)
)
)
}
results_tabPanelsBuilder <- function(specName, specLabel){
#plotWidth <- 400
#plotHeight <- 200
tabPanel(title = tags$b(specName),
fluidRow(
box(width = 12,
h4(paste0("Annual number of collisions - ", specName)),
br(),
column(6,
plotOutput(paste0(specLabel, "_plot_overallCollisions"), width = "100%")
),
column(6,
align="center",
div(dataTableOutput(paste0(specLabel, "_summTable_overallCollisions")),
style = "font-size: 90%; width: 100%")
)
)
),
fluidRow(
box(width = 12,
h4(paste0("Monthly number of collisions by model option - ", specName)),
br(),
fluidRow(
column(6,
br(),br(),br(),br(),
plotOutput(paste0(specLabel, "_plot_monthCollisions_Option1"), width = "100%")
),
column(6,
align="center",
div(dataTableOutput(paste0(specLabel, "_summTable_monthCollisions_Option1")),
style = "font-size: 90%; width: 100%")
)
),
br(),
br(),
hr(),
fluidRow(
column(6,
br(),br(),br(),br(),
plotOutput(paste0(specLabel, "_plot_monthCollisions_Option2"), width = "100%")
),
column(6,
align="center",
div(dataTableOutput(paste0(specLabel, "_summTable_monthCollisions_Option2")),
style = "font-size: 90%; width: 100%")
)
),
br(),
br(),
hr(),
fluidRow(
column(6,
br(),br(),br(),br(),
plotOutput(paste0(specLabel, "_plot_monthCollisions_Option3"), width = "100%")
),
column(6,
align="center",
div(dataTableOutput(paste0(specLabel, "_summTable_monthCollisions_Option3")),
style = "font-size: 90%; width: 100%")
)
)
)
)
)
}
divUI_monthDens_PctlsAndSample_DownButtons <- function(introText, fileInputId, fileInputPopUpText, downButtOutputId){
fluidRow(
column(12, helpText(introText)),
br(),
column(3,
tipify(
fileInput(inputId = fileInputId,
label = "Upload file",
multiple = FALSE,
accept = c("text/csv",
"text/comma-separated-values,text/plain",
".csv")),
title = fileInputPopUpText,
placement = "left", trigger = "hover", options = list(container = "body")
)
),
column(1,
style = "margin-top: 25px; margin-left: -10px",
downloadButton(outputId = downButtOutputId, label = NULL, class = "butt"),
tags$head(tags$style(".butt{background-color:#4570a5;
color: #efecec}
.butt:hover{
background-color:#4570a5;
color: #efecec}"
))
),
bsTooltip(id = downButtOutputId,
title = "Template dataset. Fill in, save locally and upload on the adjacent field",
options = list(container = "body"),
placement = "right", trigger = "hover")
)
}
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
## ----- Functions for Plotting --------
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
# DEPRECATED function for Normal density plot of model input parameters
normDensPlotPars <- function(mu, stdev, fill="olivedrab", xlab){
req(mu, stdev)
data.frame(qtls = qnorm(c(0.001, 0.999), mean = mu, sd=stdev)) %>%
ggplot(aes(qtls)) +
stat_function(fun=dnorm, args = list(mean = mu, sd = stdev), col = "black", size =1) +
stat_function(fun=dnorm, args = list(mean = mu, sd = stdev), geom="area", fill = fill, alpha = 0.3) +
labs(y="Density", x = xlab)
}
# function for Normal density plot of model input parameters
normDens_ParsPlots <- function(mu, stdev, fill="olivedrab", xlab, refValue_E = mu, refValue_SD = stdev){
req(mu, stdev)
data.frame(qtls = qnorm(c(0.0001, 0.9999), mean = mu, sd=stdev)) %>%
ggplot(aes(qtls)) +
stat_function(fun=dnorm, args = list(mean = mu, sd = stdev), col = "black", size =1) +
stat_function(fun=dnorm, args = list(mean = mu, sd = stdev), geom="area", fill = fill, col = "black", alpha = 0.3) +
labs(y="Density", x = xlab) +
#geom_vline(aes(xintercept = 0)) +
coord_cartesian(xlim = qnorm(c(0.000001, 0.999999), mean = refValue_E, sd = refValue_SD))
}
# function for Normal density quantiles of model input parameters
normDens_ParsQtls <- function(mu, stdev, varTag, decPlaces = 3){
req(mu, stdev)
data.frame(pctile = paste0(varTag, "|"), t(round(qnorm(p = c(0.025, 0.25, 0.5, 0.75, 0.975), mean = mu, sd = stdev), decPlaces))) %>%
rename(`%tile|` = pctile, `2.5th` = X1, `25th` = X2, `50th` = X3, `75th` = X4, `97.5th` = X5) %>%
mutate_at(.vars = vars(`2.5th`:`97.5th`), list(~sprintf(fmt = paste0("%.", decPlaces, "f"), .)))%>%
mutate(dummy = "") %>%
column_to_rownames("dummy")
}
# function for Truncated Normal density plot of model input parameters
truncNormPars_densPlots <- function(mu, stdev, lower = -Inf, upper = Inf, fill="olivedrab", xlab){
req(mu, stdev)
yaxixUpLimBands <- data.frame(start = c(0.0, 0.25, 0.5, 1, 2, 4, 6), end = c(0.25, 0.5, 1, 2, 4, 6, 10))
if(stdev == 0){
if(mu <= lower){
NULL
}else{
data.frame(x = seq(mu-500, mu+500, by = 1), y = 0) %>% #%>% mutate(y = if_else(x == mu, 0.5, 0)) %>%
ggplot(aes(x=x, y=y)) +
geom_path() +
geom_segment(aes(x = mu, xend = mu, y = 0, yend = Inf), size = 1) +
coord_cartesian(xlim = c(0, mu*1.65), ylim = c(0, 0.5)) +
labs(y="Density", x = xlab)
}
}else{
if(stdev>0){
distTails <- qtnorm(c(0.00001, 0.999999), mean = mu, sd = stdev, lower = lower, upper = upper)
xaxisUpLim <- distTails[2]*1.1
xaxisLowLim <- ifelse(distTails[1]*0.5 > mu/2.5, distTails[1]*0.7, 0)
yaxisMax <- max(dtnorm(seq(mu-500, mu+500, by = 1), mean = mu, sd = stdev, lower = lower, upper = upper))
yaxisUpLim <- yaxixUpLimBands %>%
mutate(yaxisMax = yaxisMax) %>%
filter(between(yaxisMax, start, end)) %>%
select(end)
if(nrow(yaxisUpLim) == 0){
yaxisUpLim <- data.frame(end = yaxisMax)
}
data.frame(qtls = qtnorm(c(0.0001, 0.9999), mean = mu, sd=stdev, lower = lower, upper = upper)) %>%
ggplot(aes(qtls)) +
stat_function(fun=dtnorm, args = list(mean = mu, sd = stdev, lower = lower, upper = upper), col = "black", size = 1) +
stat_function(fun=dtnorm, args = list(mean = mu, sd = stdev, lower = lower, upper = upper), geom="area",
fill = fill, col = "black", alpha = 0.3)+
labs(y="Density", x = xlab) +
coord_cartesian(xlim = c(xaxisLowLim, max(0, xaxisUpLim, na.rm=TRUE)), ylim = c(0, yaxisUpLim$end))
}else{
NULL
}
}
}
# function for Beta density plot of model input parameters
betaInputPars_densPlots <- function(p, stdev, fill="olivedrab", xlab){
req(p, stdev)
yaxixUpLimBands <- data.frame(start = c(0.0, 0.5, 1, 2, 4, 6, 10), end = c(0.5, 1, 2, 4, 6, 10, 20))
betaMeanVarCond <- stdev^2 < p*(1-p)
if(p >= 0 & p <= 1){
if(stdev == 0){
data.frame(x = seq(0, 1, length.out = 100), y = 0) %>%
ggplot(aes(x=x, y=y)) +
geom_path() +
geom_segment(aes(x = p, xend = p, y = 0, yend = Inf), size = 1) +
coord_cartesian(xlim = c(0,1), ylim = c(0, 0.5)) +
labs(y="Density", x = xlab)
}else{
if(stdev > 0){
if(betaMeanVarCond){
eta <- p*(1-p)/stdev^2 - 1
alpha <- eta*p
beta <- eta*(1-p)
distTails <- qbeta(c(0.00001, 0.999999), shape1 = alpha, shape2 = beta)
xaxisUpLim <- ifelse(distTails[2] > 0.6, 1, ifelse(distTails[2] > 0.3, 0.6, 0.3))
xaxisLowLim <- ifelse(distTails[1] < 0.6, 0, ifelse(distTails[1] < 0.85, 0.5, 0.86))
yaxisMax <- max(dbeta(seq(0, 1, by = 0.001), shape1 = alpha, shape2 = beta))
yaxisUpLim <- yaxixUpLimBands %>%
mutate(yaxisMax = yaxisMax) %>%
filter(between(yaxisMax, start, end)) %>%
select(end)
if(nrow(yaxisUpLim) == 0){
yaxisUpLim <- data.frame(end = yaxisMax)
}
p1 <- data.frame(qtls = qbeta(c(0.0001, 0.9999), shape1 = alpha, shape2 = beta)) %>%
ggplot(aes(qtls)) +
stat_function(fun=dbeta, args = list(shape1 = alpha, shape2 = beta), col = "black", size = 1) +
stat_function(fun=dbeta, args = list(shape1 = alpha, shape2 = beta), geom="area",
fill = fill, col = "black", alpha = 0.3) +
labs(y="Density", x = xlab)
if(is.infinite(yaxisUpLim$end)){
p1
}else{
p1 + coord_cartesian(xlim = c(xaxisLowLim, xaxisUpLim), ylim = c(0, yaxisUpLim$end))
}
}else{
NULL
}
}else{
NULL
}
}
}else{
NULL
}
}
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
## ----- Functions for outputing quantiles --------
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
# function for Truncated Normal density quantiles of model input parameters
truncNormPars_qtlTbl <- function(mu, stdev, lower = -Inf, upper = Inf, varTag, decPlaces = 3){
req(mu, stdev)
if(stdev == 0 & mu <= lower){
#NULL
invisible()
}else{
if(stdev >= 0){
data.frame(pctile = paste0(varTag, "|"), t(round(qtnorm(p = c(0.025, 0.25, 0.5, 0.75, 0.975), mean = mu, sd = stdev, lower = lower,
upper = upper), decPlaces))) %>%
rename(`%tile|` = pctile, `2.5th` = X1, `25th` = X2, `50th` = X3, `75th` = X4, `97.5th` = X5) %>%
mutate_at(.vars = vars(`2.5th`:`97.5th`), list(~sprintf(fmt = paste0("%.", decPlaces, "f"), .))) %>%
mutate(dummy = "") %>%
column_to_rownames("dummy")
}else{
invisible()
}
}
}
# function for beta quantiles of model input parameters
betaInputPars_qtlTbl <- function(p, stdev, varTag, decPlaces = 3){
req(p, stdev)
eta <- p*(1-p)/stdev^2 - 1
alpha <- eta*p
beta <- eta*(1-p)
betaMeanVarCond <- stdev^2 < p*(1-p)
if(p >= 0 & p <= 1){
if(stdev == 0){ # if sd == 0, fixe sampled values to chosen p/mu (default qbeta generates fixed 0.5, as alpha = beta = Inf => p = 0.5)
data.frame(pctile = paste0(varTag, "|"), X1 = p, X2 = p, X3 = p, X4 = p, X5 = p) %>%
rename(`%tile|` = pctile, `2.5th` = X1, `25th` = X2, `50th` = X3, `75th` = X4, `97.5th` = X5) %>%
mutate_at(.vars = vars(`2.5th`:`97.5th`), list(~sprintf(fmt = paste0("%.", decPlaces, "f"), .))) %>%
mutate(dummy = "") %>%
column_to_rownames("dummy")
}else{
if(stdev > 0){
if(betaMeanVarCond){
data.frame(pctile = paste0(varTag, "|"), t(round(qbeta(p = c(0.025, 0.25, 0.5, 0.75, 0.975), shape1 = alpha, shape2 = beta), decPlaces))) %>%
rename(`%tile|` = pctile, `2.5th` = X1, `25th` = X2, `50th` = X3, `75th` = X4, `97.5th` = X5) %>%
mutate_at(.vars = vars(`2.5th`:`97.5th`), list(~sprintf(fmt = paste0("%.", decPlaces, "f"), .))) %>%
mutate(dummy = "") %>%
column_to_rownames("dummy")
}else{
invisible()
}
}else{
invisible()
}
}
}else{
invisible()
}
}
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
## ----- Functions for Alerts on Parameter Validation --------
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
# General function for alerts for parameters with truncated normal
tnormParamsAlert <- function(expVal, stdv, varName, varTag, session){
c_alertId_E <- paste0("alertInput_", varTag, "_E")
c_alertId_SD <- paste0("alertInput_", varTag, "_SD")
if(!is.na(expVal) & !is.na(stdv)){
if(stdv == 0 & expVal <= 0){
createAlert(session, anchorId = "alert", alertId = c_alertId_E, title = "Oops...",
content = paste0("<b>", varName, ":</b> needs Mean > 0<br/> when SD = 0"), append = TRUE, style = "danger")
}else{
closeAlert(session, alertId = c_alertId_E)
}
}
if(!is.na(stdv)){
if(stdv < 0){
createAlert(session, anchorId = "alert", alertId = c_alertId_SD, title = "Oops...",
content = paste0("<b>", varName, ":</b> needs SD >= 0"), append = TRUE, style = "danger")
}else{
closeAlert(session, alertId = c_alertId_SD)
}
}
}
# General function for alerts for validation of Beta distributed parameters
betaParamsAlert <- function(p, stdv, varName, varTag, session){
c_alertId_E <- paste0("alertInput_", varTag, "_E")
c_alertId_SD <- paste0("alertInput_", varTag, "_SD")
#if(p == 0.2 & stdv == 0.2){ browser() }
betaMeanVarCond <- stdv^2 < p*(1-p)
# input validation for p
if(!is.na(p)){
if(p < 0 | p > 1){
createAlert(session, anchorId = "alert", alertId = c_alertId_E, title = "Oops...",
content = paste0("<b>", varName, ":</b> needs Mean <br/> between 0 and 1"), append = TRUE, style = "danger")
}else{
closeAlert(session, alertId = c_alertId_E)
}
}
# input validation for SD
if(!is.na(stdv) & !is.na(p)){
if(p >= 0 & p <= 1){
if(stdv > 0){
if(p == 0 | p == 1){
createAlert(session, anchorId = "alert", alertId = c_alertId_SD, title = "Oops...",
content = paste0("<b>", varName, ":</b> <br/> needs SD = 0 when Mean is 0 or 1"), append = TRUE, style = "danger")
}else{
closeAlert(session, alertId = c_alertId_SD)
}
if(!betaMeanVarCond){
condLimit <- round(sqrt(p*(1-p)), digits = 3)
createAlert(session, anchorId = "alert", alertId = c_alertId_SD, title = "Oops...",
content = paste0("<b>", varName, ":</b> <br/> needs SD < ", condLimit, " for the <br/> Mean p = ", round(p, digits = 3)), append = TRUE, style = "danger")
}else{
closeAlert(session, alertId = c_alertId_SD)
}
}else{
if(stdv < 0){
createAlert(session, anchorId = "alert", alertId = c_alertId_SD, title = "Oops...",
content = paste0("<b>", varName, ":</b> needs SD >= 0"), append = TRUE, style = "danger")
}else{
closeAlert(session, alertId = c_alertId_SD)
}
}
}
}
}
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
## ----- Functions for customized output from distribution functions --------
## ------------------------------------------------------------------------------------- ##
## ------------------------------------------------------------------------------------- ##
# generate random samples from a beta distribution, parameterized as mean and sd, and returning NAs if conditions are not met
rbeta_dmp <- function(n, p, sd){
eta <- p*(1-p)/sd^2 - 1
alpha <- eta*p
beta <- eta*(1-p)
betaMeanVarCond <- sd^2 < p*(1-p)
if(is.na(p) | is.na(sd)){
out <- rep(NA, n)
warning("NA values for p and/or stdev - NAs produced")
}else{
if(p >= 0 & p <= 1){
if(sd < 0){
out <- rep(NA, n)
warning("stdev < 0 - NAs produced")
}
if(sd == 0){
out <- rep(p, n)
}
if(sd > 0){
if(betaMeanVarCond){
out <- rbeta(n, shape1 = alpha, shape2 = beta)
}else{
out <- rep(NA, n)
warning("condition var < p*(1 - p) not met - NAs produced")
}
}
}else{
out <- rep(NA, n)
warning("p < 0 | p > 1 - NAs produced")
}
}
return(out)
}
# generate random samples from a truncated normal, returning NAs if conditions are not met
rtnorm_dmp <- function(n, mean=0, sd=1, lower=-Inf, upper=Inf){
if(is.na(mean)|is.na(sd)){
out <- rep(NA, n)
warning("NA values for mu and/or stdev - NAs produced")
}else{
if(sd >= 0){
if(sd == 0 & mean == lower){
out <- rep(lower, n)
}
if(sd == 0 & mean < lower){
out <- rep(NA, n)
warning("mu < lower & SD = 0 - NAs produced")
}
if(sd == 0 & mean > lower){
#out <- qtnorm(p, mean = mean, sd = sd, lower = lower, upper = upper)
out <- rep(mean, n)
}
if(sd > 0){
out <- rtnorm(n, mean = mean, sd = sd, lower = lower, upper = upper)
}
}else{
warning("SD < 0 - NAs produced")
out <- rep(NA, n)
}
}
return(out)
}
qtnorm_dmp <- function(p, mean=0, sd=1, lower=-Inf, upper=Inf){
if(is.na(mean)|is.na(sd)){
out <- rep(NA, length(p))
warning("NA values for mu and/or stdev - NAs produced")
}else{
if(sd >= 0){
if(sd == 0 & mean == lower){
out <- rep(lower, length(p))
}
if(sd == 0 & mean < lower){
out <- rep(NA, length(p))
warning("mu < lower & SD = 0 - NAs produced")
}
if(sd == 0 & mean > lower){
out <- rep(mean, length(p))
}
if(sd > 0){
out <- qtnorm(p, mean = mean, sd = sd, lower = lower, upper = upper)
}
}else{
warning("SD < 0 - NAs produced")
out <- rep(NA, length(p))
}
}
return(out)
}
## -------------------------------------------------------------------- ##
## -------------------------------------------------------------------- ##
## ----- Miscelaneous functions --------
## -------------------------------------------------------------------- ##
## -------------------------------------------------------------------- ##
# generate a temporary folder name for the current session to write out the simulation output files
getTempFolderName <- function(){
paste0("sessionOutputs_", paste(sample(c(letters, LETTERS, 0:9), size = 12, replace = TRUE), collapse = ""))
}
# little safety function required to surpass the "Error:" value returned when ref points or resampled user bird density data is missing -
# used when checking/preparing data for modelling
safe_names <- possibly(names, "MissingData")