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server.R
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server.R
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library(DT)
library(shiny)
library(waiter)
library(shinyjs)
library(tinytex)
library(rmarkdown)
library(shinyWidgets)
library(summarytools)
library(shinyscreenshot)
library(tRophicPosition)
library(knitr)
function(input, output, session) {
## Global Waiter -------------------------------------------------------------
hostess <- Hostess$new("loader")
for (i in 1:10) {
Sys.sleep(runif(1) / 3)
hostess$set(i * 10)
}
waiter_hide()
observeEvent(input$refresh, {
refresh()
})
## Functions -----------------------------------------------------------------
emty_data <- function() {
fluidRow(
column(width = 3),
column(width = 6,
fluidRow(id = 'espera',
img(src="img/waitingData.gif", align = "center",width='200px'),
)),
column(width = 3),
)
}
plot_screenfoodweb <- function() {
df <- df_upload()
tRophicPosition::screenFoodWeb(
df = df,
grouping = c("Spp", "FG"),
printSummary = TRUE,
#title = "Food Webs",
#order = TRUE
)
}
observeEvent(input$logout, {
radioGroupButtons(
inputId = "somevalue1",
label = "Choose a value: ",
choices = c("A", "B", "C")
)
})
## Upload file ---------------------------------------------------------------
df_upload <- reactive({
if (input$select_a_file == "Upload") {
inFile <- input$file
if (is.null(inFile)) {
return(NULL)
} else{
df <- read.csv(
inFile$datapath,
header = as.logical(input$header),
sep = input$sep,
quote = input$quote
)
return(df)
}
} else if (input$select_a_file == "Bilagay-MEC") {
df <- read.csv(
'data/Bilagay-MEC.csv',
header = as.logical(input$header),
sep = input$sep,
quote = input$quote
)
return(df)
} else if (input$select_a_file == "Bilagay_for_tRophicPosition") {
df <- read.csv(
'data/Bilagay_for_tRophicPosition.csv',
header = as.logical(input$header),
sep = input$sep,
quote = input$quote
)
return(df)
} else{
return(NULL)
}
})
df_generate <- function() {
df <- tRophicPosition::generateTPData(
dCb1 = input$dCb1,
dNb1 = input$dNb1,
dCc = input$dCc,
dNc = input$dNc,
dCb2 = input$dCb2,
dNb2 = input$dNb2,
consumer = input$consumer_name
)
return(df)
}
output$sample_table <- DT::renderDataTable({
if (as.logical(input$up_file) == TRUE) {
df <- df_upload()
DT::datatable(df,
class = 'cell-border stripe',
options = list(pageLength = 10, dom = 'tip'))
} else if (as.logical(input$up_create_dataset) == TRUE) {
df <- df_generate()
print(df)
plot(df)
# result <- array(c(df[1:6]), dim = c(6, 25))
# DT::datatable(result,
# class = 'cell-border stripe',
# options = list(pageLength = 10, dom = 'tip'),
# colnames = c('dNb1',
# 'dCb1',
# 'dNb2',
# 'dCb2',
# 'dNc',
# 'dCc'))
}
})
output$screenfoodweb <- renderPlot({
return(plot_screenfoodweb())
})
observeEvent(input$download_dfSummary, {
screenshot(
"#dfSummary",
filename = paste("dfSummary_", Sys.Date(), "", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$download_screenfoodweb, {
screenshot(
"#screenfoodweb",
filename = paste("screenfoodweb_", Sys.Date(), "", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$download_df_generate_data, {
screenshot(
"#df_generate_data",
filename = paste("plot_consumer_", Sys.Date(), "", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$up_file, {
shinyjs::disable('file')
# updateButton(session, 'up_file', style='default')
shinyjs::show("process1")
Sys.sleep(2)
shinyjs::hide("process1")
shinyjs::disable('up_file')
shinyjs::disable('up_create_dataset')
shinyjs::disable('type_dataset')
shinyjs::disable('select_a_file')
shinyjs::disable('<h4>LOAD</h4>')
shinyjs::disable('<h4>GENERATE</h4>')
})
observeEvent(input$up_create_dataset, {
#shinyjs::disable('file')
# updateButton(session, 'up_file', style='default')
shinyjs::show("process1")
Sys.sleep(2)
shinyjs::hide("process1")
shinyjs::disable('up_file')
shinyjs::disable('up_create_dataset')
shinyjs::disable('type_dataset')
shinyjs::disable('<h4>LOAD</h4>')
shinyjs::disable('<h4>GENERATE</h4>')
shinyjs::disable('select_a_file')
})
observeEvent(input$type_dataset, {
output$dataset_config <- renderUI({
if (input$type_dataset == '<h4>LOAD</h4>') {
fluidRow(column(
width = 12,
pickerInput(
'select_a_file',
tags$h3('Select a File'),
choices = list(
Available = c('Bilagay-MEC',
'Bilagay_for_tRophicPosition'),
Upload = c('Upload')
),
selected = NULL,
),
conditionalPanel(
condition = "input.select_a_file == 'Upload' ",
radioButtons(
"sep",
tags$h3("Separator"),
choices = c(
'Comma' = ",",
'Semicolon' = ";",
'Tab' = "\t"
),
selected = ",",
inline = TRUE
),
radioButtons(
"quote",
tags$h3("Comma"),
choices = c(
'None' = "",
'Double Quote' = '"',
"Single Quote" = "'"
),
selected = '"',
inline = TRUE
),
radioButtons(
inputId = 'header',
label = tags$h3('Header'),
choices = c('Yes' = TRUE,
'No' = FALSE),
selected = TRUE,
inline = TRUE,
),
fileInput(
'file',
tags$h3('Load your File'),
accept = c('text/csv',
'text/comma-separated-values',
'.csv'),
buttonLabel = tags$b(icon("fas fa-folder")),
placeholder = "Example.csv",
multiple = FALSE,
),
),
actionBttn(
inputId = "up_file",
tags$h4("LOAD DATASET"),
style = "fill",
color = "success",
size = "sm",
block = TRUE,
),
))
} else if (input$type_dataset == '<h4>GENERATE</h4>') {
fluidRow(
column(
width = 12,
numericInput(
'dNb1',
h4('dNb1'),
value = 14.2,
min = -100,
max = 100,
step = 0.01
),
numericInput(
'dCb1',
h4('dCb1'),
value = -17.3,
min = -100,
max = 100,
step = 0.01
),
numericInput(
'dNb2',
h4('dNb2'),
value = 15.4,
min = -100,
max = 100,
step = 0.01
),
numericInput(
'dCb2',
h4('dCb2'),
value = -12.7,
min = -100,
max = 100,
step = 0.01
),
numericInput(
'dNc',
h4('dNc'),
value = 21,
min = -100,
max = 100,
step = 0.01
),
numericInput(
'dCc',
h4('dCc'),
value = -15,
min = -100,
max = 100,
step = 0.01
),
textInput('consumer_name',
h4('Consumer Name'),
'Consumer'),
actionBttn(
inputId = "up_create_dataset",
tags$h4("GENERATE DATASET"),
style = "fill",
color = "success",
size = "sm",
block = TRUE,
),
)
)
}
})
})
output$df_generate_data <- renderPrint({
df <- df_generate()
return(df)
})
output$content_data <- renderUI({
if (!is.null(input$up_file) && input$up_file > 0) {
df <- df_upload()
fluidRow(column(width = 12,
fluidPage(
id = 'resultados',
tabsetPanel(
type = "pills",
tabPanel(
title = tags$b("DATA TABLE", icon("database")),
br(),
DT::dataTableOutput("sample_table")
),
tabPanel(
title = tags$b("DATA SUMMARY", icon("table")),
br(),
st_options(dfSummary.custom.2 =
expression(
paste(
"Q1 & Q4 :",
quantile(
column_data,
probs = .25,
type = 2,
names = FALSE,
na.rm = TRUE
),
digits = 1
,
" & ",
quantile(
column_data,
probs = 1,
type = 2,
names = FALSE,
na.rm = TRUE
),
digits = 1
)
)),
div(
id = "dfSummary",
print(
dfSummary(
df,
varnumbers = TRUE,
valid.col = FALSE,
style = "multiline",
graph.magnif = 1.5
),
method = 'render',
headings = FALSE,
bootstrap.css = FALSE,
style = "grid",
tmp.img.dir = "/tmp"
),
),
actionBttn(
"download_dfSummary",
label = "DOWNLOAD SUMMARY",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
),
tabPanel(
title = tags$b("DATA SPECIES",
icon("area-chart")),
br(),
div(id = "screenfoodweb",
plotOutput("screenfoodweb"),),
br(),
actionBttn(
"download_screenfoodweb",
label = "DOWNLOAD PLOT",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
),
),
)),)
} else if (!is.null(input$up_create_dataset) &&
input$up_create_dataset > 0) {
df <- df_generate()
fluidRow(column(
width = 12,
fluidPage(
id = 'resultados',
tags$h2("Generated Dataset"),
div(id = "df_generate_data",
verbatimTextOutput('df_generate_data')),
br(),
actionBttn(
"download_df_generate_data",
label = "DOWNLOAD GENERATE DATA",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
)
),)
} else {
emty_data()
}
})
## IsotopeData Object --------------------------------------------------------
TDF_values <- eventReactive(input$TDF_set, {
return(
tRophicPosition::TDF(
author = input$TDF_author,
element = input$element,
type = input$type
)
)
})
isotopeData <- reactive({
df <- df_upload()
TDF <- TDF_values()
if (input$element == 'N') {
consumer <-
tRophicPosition::loadIsotopeData(
df,
consumer = input$consumer,
consumersColumn = input$consumersColumn,
b1 = input$b1,
b2 = input$b2,
baselineColumn = input$baselineColumn,
group = input$group,
groupsColumn = input$groupsColumn,
deltaN = TDF$deltaN,
deltaC = NULL
)
} else if (input$element == 'C') {
consumer <-
tRophicPosition::loadIsotopeData(
df,
consumer = input$consumer,
consumersColumn = input$consumersColumn,
b1 = input$b1,
b2 = input$b2,
baselineColumn = input$baselineColumn,
group = input$group,
groupsColumn = input$groupsColumn,
deltaC = TDF$deltaC,
deltaN = NULL
)
} else{
consumer <-
tRophicPosition::loadIsotopeData(
df,
consumer = input$consumer,
consumersColumn = input$consumersColumn,
b1 = input$b1,
b2 = input$b2,
baselineColumn = input$baselineColumn,
group = input$group,
groupsColumn = input$groupsColumn,
deltaN = TDF$deltaN,
deltaC = TDF$deltaC
)
}
return(consumer)
})
output$plot_consumer <- renderPlot({
consumer <- isotopeData()
plot(consumer, b1 = input$b1, b2 = input$b2)
})
output$tdf_summary <- renderPrint({
TDF <- TDF_values()
return(TDF)
})
output$content_TP <- renderUI({
if (is.null(input$file)) {
emty_data()
} else
(return(fluidRow(
column(width = 12),
column(width = 3),
column(width = 7,
fluidRow(
id = 'espera',
tags$h2("Define your TDF",
icon("thumbs-up")),
)),
column(width = 2),
)))
})
observeEvent(input$TDF_set, {
df <- df_upload()
output$load_isotope <- renderUI({
fluidRow(
column(
width = 12,
tags$h2('Load Isotope Data', icon("fas fa-filter")),
tags$hr(),
selectInput(
'consumer',
tags$h4('consumer'),
choices = c(as.list(df$Spp)),
selected = TRUE,
),
selectInput(
'group',
tags$h4('group'),
choices = c(as.list(df$Location)),
selected = TRUE,
),
selectInput(
'b1',
tags$h4('b1'),
choices = c(as.list(df$FG)),
selected = TRUE,
),
selectInput(
'b2',
tags$h4('b2'),
choices = c(as.list(df$FG)),
selected = TRUE,
),
selectInput(
'consumersColumn',
tags$h4('consumersColumn'),
choices = c(colnames(df)),
selected = 'FG'
),
selectInput(
'baselineColumn',
tags$h4('baselineColumn'),
choices = c(colnames(df)),
selected = 'FG'
),
selectInput(
'groupsColumn',
tags$h4('groupsColumn'),
choices = c(colnames(df)),
selected = 'Location'
),
actionBttn(
inputId = "create_isotop",
tags$h4("CREATE ISOTOPEDATA OBJECT"),
style = "fill",
color = "success",
size = "sm",
block = TRUE
),
)
)
})
})
observeEvent(input$TDF_set, {
output$content_TP <- renderUI({
if (is.null(input$file)) {
emty_data()
} else
(return(fluidRow(
column(width = 12),
column(width = 3),
column(width = 7,
fluidRow(
id = 'espera',
tags$h2(
"Now lets define your Isotope Data Object",
icon("thumbs-up")
),
)),
column(width = 2),
)))
})
})
observeEvent(input$download_tdf_summary, {
screenshot(
"#tdf_summary",
filename = paste("tdf_summary", Sys.Date(), ".png", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$download_plot_consumer, {
screenshot(
"#plot_consumer",
filename = paste("plot_consumer_", Sys.Date(), ".png", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$create_isotop, {
output$content_TP <- renderUI({
if (input$create_isotop < 1) {
emty_data()
} else
fluidRow(column(width = 12,
fluidPage(
id = 'resultados',
tabsetPanel(
type = "pills",
tabPanel(
title = tags$b("TROPHIC DISCRIMINATOR FACTOR",
icon("bug")),
br(),
div(id = "tdf_summary",
verbatimTextOutput('tdf_summary')),
br(),
actionBttn(
"download_tdf_summary",
label = "DOWNLOAD SUMMARY",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
),
tabPanel(
title = tags$b("PLOT ISOTOPE OBJECT",
icon("line-chart")),
br(),
div(id = "plot_consumer",
plotOutput('plot_consumer')),
br(),
actionBttn(
"download_plot_consumer",
label = "DOWNLOAD PLOT",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
)
)
)))
})
})
## Posterior Sample ----------------------------------------------------------
output$post_summary <- renderPrint({
posterior_samples <- posterior()
summary(posterior_samples)
})
posterior <- reactive({
consumer <- isotopeData()
model.string <-
tRophicPosition::jagsBayesianModel(model = "oneBaseline",
TP = "dnorm(4, 0.1)")
model <-
tRophicPosition::TPmodel(
data = consumer,
model.string = model.string,
n.adapt = input$n.adapt,
n.chains = input$n.chains,
quiet = TRUE
)
posterior.samples <-
tRophicPosition::posteriorTP(
model = model,
n.iter = input$n.iter,
variable.names = c("TP", "muDeltaN"),
quiet = TRUE
)
return(posterior.samples)
})
output$plot_TP <- renderPlot({
consumer <- isotopeData()
posterior_samples <- posterior()
combined <-
as.data.frame(coda::mcmc(do.call(rbind, posterior_samples)))
plotTP(combined, xlab = "Monitored variables")
})
output$plot_post <- renderPlot({
posterior_samples <- posterior()
posterior.combined <-
coda::mcmc(do.call(rbind, posterior_samples))
getPosteriorMode(posterior.combined)
plot(posterior_samples)
})
output$content_model <- renderUI({
if (is.null(input$file)) {
emty_data()
} else
(return(fluidRow(
column(width = 12),
column(width = 3),
column(width = 7,
fluidRow(
id = 'espera',
tags$h2("Let's create the model now",
icon("thumbs-up")),
)),
column(width = 2),
)))
})
observeEvent(input$create_model, {
output$content_model <- renderUI({
if (is.null(input$file)) {
emty_data()
} else
(return(fluidRow(
column(width = 12),
column(width = 3),
column(width = 7,
fluidRow(
id = 'espera',
tags$h2("Let's make the posterior samples",
icon("thumbs-up")),
)),
column(width = 2),
)))
})
})
observeEvent(input$download_post_summary, {
screenshot(
"#post_summary",
filename = paste("post_summary_", Sys.Date(), ".png", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$download_plot_post, {
screenshot(
"#plot_post",
filename = paste("plot_post_", Sys.Date(), ".png", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$download_plot_TP, {
screenshot(
"#plot_TP",
filename = paste("plot_TP_", Sys.Date(), ".png", sep = ""),
timer = 1,
scale = 3
)
})
observeEvent(input$make_post, {
output$content_model <- renderUI({
if (input$make_post < 1) {
emty_data()
} else
fluidRow(column(width = 12,
fluidPage(
id = 'resultados',
tabsetPanel(
type = "pills",
tabPanel(
title = tags$b("POSTERIOR SUMMARY", icon("bug")),
br(),
div(id = "post_summary",
verbatimTextOutput('post_summary')),
br(),
actionBttn(
"download_post_summary",
label = "DOWNLOAD SUMMARY",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
)
),
tabPanel(
title = tags$b("CODA PLOT", icon("area-chart")),
br(),
div(id = "plot_post",
plotOutput('plot_post'),),
br(),
actionBttn(
"download_plot_post",
label = "DOWNLOAD PLOT",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
),
tabPanel(
title = tags$b("PLOT", icon("pie-chart")),
br(),
div(id = "plot_TP",
plotOutput('plot_TP'),),
br(),
actionBttn(
"download_plot_TP",
label = "DOWNLOAD PLOT",
icon("camera"),
style = "jelly",
color = "warning",
size = "xs"
),
)
)
)))
})
})
## Report Setup --------------------------------------------------------------
output$downloadReport <- downloadHandler(
filename = function() {
paste('my-report', sep = '.', switch(
input$format,
PDF = 'pdf',
HTML = 'html',
Word = 'docx'
))
},
content = function(file) {
src <- normalizePath('Report.Rmd')
# # temporarily switch to the temp dir, in case you do not have write
# # permission to the current working directory
owd <- setwd(tempdir())
on.exit(setwd(owd))
file.copy(src, 'Report.Rmd', overwrite = TRUE)
data <- df_upload()
include <- input$Try
out <- rmarkdown::render('Report.Rmd',
params = list(data = data, include = include),
switch(
input$format,
PDF = pdf_document(),
HTML = html_document(),
Word = word_document()
))
file.rename(out, file)
}
)
output$report_setup <- renderUI({
fluidRow(column(
width = 12,
radioButtons(
'format',
tags$h3('Document format:'),
c('PDF', 'HTML', 'Word'),
inline = TRUE
),
conditionalPanel(
condition = "input.up_file",
checkboxGroupInput(
"Try",
tags$h3("Include Outputs:"),
choiceNames = list(
"Include DATA TABLE",
"Include DATA SUMMARY",
"Include DATA SPECIES"
),
choiceValues = list("DATA TABLE",
"DATA SUMMARY",
"DATA SPECIES")
),
),
actionBttn(
inputId = "render_pdf",
tags$h4("CREATE REPORT"),