conditional panel where condition is length of input - r

I'm having trouble understanding why my condition input.wave1.length > 1 does not work.
What I would like happen is for the checkbox "Overall Curve" to not appear unless input$loess AND if there are more than 1 items checked in the either Wave 1 or Wave 2 accordions.
I don't see what I'm doing wrong. Is there a condition in javascript that will make this work or can this be done with R script?
my app:
library(shiny)
library(shinydashboard)
library(bsplus) #accordion
#########define waves##########
wave1 <- c(
"Cayuga", "Columbia", "Erie", "Greene",
"Lewis", "Putnam", "Suffolk", "Ulster"
)
wave2 <- c(
"Broome", "Chautauqua", "Cortland", "Genesee",
"Monroe", "Orange", "Sullivan", "Yates"
)
ui <- dashboardPage(
dashboardHeader(title = "Example"),
dashboardSidebar(
tags$h4("waves:", style = "margin: 5px;"),
bs_accordion(id = "waves") %>%
#use the entire heading panel as a link instead of just title
bs_set_opts(use_heading_link = TRUE) %>%
bs_append(
title = "Wave 1",
content = checkboxGroupInput(inputId = "wave1", label = NULL,
choices = c(wave1, "All Wave 1"),
selected = "Cayuga")
) %>%
bs_append(
title = "Wave 2",
content = checkboxGroupInput(inputId = "wave2", label = NULL,
choices = c(wave2, "All Wave 2"))
),
br(),
#LOESS CURVE ####
checkboxInput(inputId = "loess", label = "Display Loess Curve",
value = FALSE),
uiOutput("loess_a"),
# uiOutput("loess_overall"),
conditionalPanel(condition = "input.loess == TRUE & input.wave1.length > 1", # should include selected > 1
checkboxInput(inputId = "loessGrouped", label = "Overall Curve",
value = TRUE)
)
),
dashboardBody(
tags$style(HTML('.checkbox label{color: red;}'))
)
)
server <- function(input, output, session) {
# conditional loess smoother #######
output$loess_a <- renderUI({
req(input$loess)
conditionalPanel(condition = "input.loess == TRUE",
sliderInput(inputId = "smoothing", label = NULL,
min = 0, max = 1, value = 1, step = 0.1))
})
}
shinyApp(ui = ui, server = server)

To work with either Wave 1 or Wave 2 accordions having more than 1 item checked, you can use the following:
conditionalPanel(condition = "input.loess == 1 & (input.wave1.length > 1 || input.wave2.length > 1)", # should include selected > 1
checkboxInput(inputId = "loessGrouped", label = "Overall Curve",
value = TRUE)
)
In addition, you still need to make input.loess == 1 on the server side

Related

How do I add the option to connect observations by ID in Shiny?

I'm working on my Shiny app that visualizes/summarizes PK data. Anyways, I have a small question. I want to add in the option for the user to connect observations by ID in Shiny, so I want them to choose. This could be a single tickbox which would be: "Connect observations by ID', or just a statement like: 'Connect observations by ID:" with boxes as 'Yes' or 'No'. I hope you get what I mean. How do I do this? I have a pretty large code for my app, as I've come a long way already.
Small note, I can't generate a report yet, as the code is not right, but you can just ignore this. Tab 2 is not finished yet, but the base is there.
UI
ui <- fluidPage(
tabsetPanel(tabPanel("Tab 1",
titlePanel("Shiny App: Concentration vs Time Graphs"),
sidebarLayout(
mainPanel("Concentration vs Time graphs", plotOutput(outputId = "plot")),
sidebarPanel(style = "height:90vh; overflow-y: auto",
p("This app is developed to visualize pharmacokinetic data of different antibodies. Please select the data you want to visualize before running the graph. The graph can be reset with the reset button."),
strong("1. Filter your data for these following variables:"),
checkboxInput('checkbox1', 'Filter by study', FALSE),
conditionalPanel(condition = "input.checkbox1 == 1",
selectInput(inputId = "study", label = "Include study:",
choices = c("GLP Toxicity" = "GLPTOX", "Dose Range Finding" = "DRF", "Single Dose" = "SD", "Repeat Dose" = "RD"),
selected = c("GLPTOX", "DRF", "SD", "RD"),
multiple = T)
),
checkboxInput('checkbox2', 'Filter by platform', FALSE),
conditionalPanel(condition = "input.checkbox2 == 1",
selectInput(inputId = "platform", label = "Include platform:",
choices = c("Hexabody", 'Duobody' = "Doubody", "Bispecific"), selected = c("Hexabody", "Doubody", "Bispecific"),
multiple = T)
),
checkboxInput('checkbox3', 'Filter by species', F),
conditionalPanel(condition = "input.checkbox3 == 1",
selectInput(inputId = "species", label = "Include species:",
choices = c("Monkey", 'Mouse'), selected = c('Monkey', 'Mouse'), multiple = T)
),
checkboxInput('checkbox4', 'Filter by administration route', F),
conditionalPanel(condition = "input.checkbox4 == 1",
selectInput(inputId = "route", label = "Include administration route:",
choices = c('Route 1' = "ROUTE1", 'Route 2' = "ROUTE2"), selected = c("ROUTE1", "ROUTE2"),
multiple = T)
),
selectInput(inputId = "x", label = "2. X-axis:", choices = c("Time" = "TIME", "TLD"), selected = "Time"
),
selectInput(inputId = 'column', label = "3. Columns for:",
choices = c("Dose mg/kg" = "DOSEMGKG", "Species" = "SPECIES", "Antibody" = "ABXID", "Subspecies" = "SUBSPECIES", "Age" = "AGE", "Animal ID" = "ANIMALID"),
selected = "DOSEMGKG"
),
conditionalPanel(condition = "input.column == 'DOSEMGKG'",
selectInput(inputId = 'dose', label = "Choose dose(s):",
choices = c("0.05", '0.5', "20", '5'), selected = c('0.05', '0.5', '20', '5'), multiple = T
)
),
selectInput(inputId = 'row', label = "4. Rows for:",
choices = c("Dose mg/kg" = "DOSEMGKG", "Species" = "SPECIES", "Antibody" = "ABXID", "Subspecies" = "SUBSPECIES", "Age" = "AGE", "Animal ID" = "ANIMALID",
"Platform" = "PLATFORM", "Mutation" = "MUTATION"),
selected = "ABXID"
),
conditionalPanel(condition = "input.row == 'MUTATION'",
selectInput(inputId = 'mutation', label = "Choose mutation(s):", choices = c('M1', "M2", "M3"), selected = c('M1', "M2", "M3"), multiple = T
)
),
conditionalPanel(
condition = "input.row == 'ABXID'",
selectInput(
inputId = 'antibody',
label = "Choose antibody(s):",
choices = c('Duobody-XXXXX', "Duobody-CD3x5T4"), selected = c('Duobody-XXXXX', 'Duobody-CD3x5T4'), multiple = T
)
),
selectInput(
inputId = "group",
label = "5. Group by:",
choices = c("Dose mg/kg" = "DOSEMGKG", "Species" = "SPECIES", "Antibody" = "ABXID", "Subspecies" = "SUBSPECIES", "Age" = "AGE", "Animal ID" = "ANIMALID",
'Administration route' = 'ROUTE'),
selected = "ANIMALID"
),
sliderInput(
inputId = 'trange',
label = "6. Time range:",
min = 0,
max = 1704,
value = c(0, 1704 )
),
actionButton(
inputId = 'runbutton',
label = 'Run graph'
),
actionButton(
inputId = 'resetbutton',
label = 'Reset graph'
),
downloadButton(outputId = 'report', label = "Generate report"),
br(),
br(),
br(),
p("----------")
))
)),
tabsetPanel(tabPanel("Tab 2",
titlePanel("Tab 2"),
sidebarLayout(
mainPanel("Plot #2", plotOutput(outputId = "plot2")),
sidebarPanel(helpText("Whatever text..."),
selectInput(
inputId = 't',
label = "Example",
choices = c("#1", "#2", "#3"),
selected = "#1"
)
)
)))
)
Server
server <- function(input, output, session){
observeEvent(input$runbutton, {output$plot <- renderPlot({
ggplot(data = df %>% filter(STUDYID %in% input$study & ABXID %in% input$antibody & MUTATION %in% input$mutation & PLATFORM %in% input$platform
& SPECIES %in% input$species & DOSEMGKG %in% input$dose & ROUTE %in% input$route),
aes_string(x = input$x, y = "DV", col = input$group)) + xlab("Time") + ylab("Concentration (ug/mL)") +
geom_point() + facet_grid(get(input$row) ~ get(input$column)) + scale_x_continuous(limits = input$trange) +
scale_color_viridis(discrete = T, option = 'F', begin = 0, end = 0.8) + theme_bw() + scale_y_log10()})})
observeEvent(input$resetbutton, {output$plot <- renderPlot({ NULL })})
output$report <- downloadHandler(filename = "report.pdf", content = function(file){
tempReport <- file.path(tempdir(), "report.Rmd")
file.copy("report.Rmd", tempReport, overwrite = T)
params <- list(n = input$x)
rmarkdown::render(tempReport, output_file = file, params = params, envir = new.env(parent = globalenv()))
})
}
shinyApp(ui = ui, server = server)
I know that it's something with geom_line(aes(group = "ANIMALID")), but I do not yet know how to make this an option to include/exclude.
Here is a simple app, that has a ggplot2 with some data, and whether the points are to be drawn connected by lines (within relevant groups) is toggleable.
I hope it helps you; your posted code is not reproducible as it uses private data, (and it is not minimal, its a lot of content to look at).
perhaps you can use this example as a base to ask further questions from as you complicate it, or account for relevant differences. but notice how my example is at least reproducible (you can run it; it is based on public, not private data).
library(shiny)
library(tidyverse)
some_data <- distinct(
iris,
Species, Petal.Width, Petal.Length
) |>
group_by(Species, Petal.Width) |>
summarise(avg_Petal.Length = mean(Petal.Length)) |>
ungroup()
ui <- fluidPage(
plotOutput("myplot", width = 400, height = 400),
checkboxInput("mytog", "line?")
)
server <- function(input, output, session) {
output$myplot <- renderPlot({
plot_to_show <-
ggplot(data = some_data) +
aes(
x = Petal.Width,
y = avg_Petal.Length,
colour = Species
) +
geom_point()
if (isTruthy(input$mytog)) {
plot_to_show <- plot_to_show + geom_line()
}
plot_to_show
})
}
shinyApp(ui, server)

Warning: Error in tagAssert: Expected an object with class 'shiny.tag'

new to shiny, I am developing a dynamic application for several users.
(Pages should be displayed according to user credentials)
I thought about doing it with the conditionpanel.
but i have this error: agAssert: Expected an object with class 'shiny.tag'
my questions are: can we put sidebar or dashbarbody in conditionpanel? if this is possible how?
and do you have other proposals or approaches? Thank you
below is my code:
# Shiny dashboard project
# TIDE 2021-2022
# global option for sipnners
options(spinner.color="#0275D8", spinner.color.background="#ffffff", spinner.size=2)
# Define dashboardHeader()
header <- dashboardHeader(title = "GOUZOU",
dropdownMenu(
type = "notifications",
headerText = strong("HELP"),
icon = icon("question"),
badgeStatus = NULL,
notificationItem(
text = "Faire une demande de Geste Commercial",
icon = icon("spinner")
)
),
tags$li(class="dropdown",
tags$a(href="http://icx.gan.fr/icx/ActionXMLAppel.do",
icon("github"),
"A propos d'ICX",
target="_blank")
)
) #close header
ui_first <- fluidPage(
useShinyjs(), #set up shinyjs
sidebarLayout(
shinyjs::hidden(
div(id = "Siderbar", sidebarPanel(
conditionalPanel(
condition = "input.tabselected > 1",
# Define dashboardSidebar()
dashboardSidebar(
sidebarMenu(
menuItem("Demande", tabName = "do_demande",
menuItem("Mouvements", tabName = "mouvement", icon = icon("spinner")),
menuItem("Mutualisation", tabName = "do_mutualisation", icon= icon("spinner")),
menuItem("Avance", tabName = "do_avance", icon= icon("spinner")),
menuItem("PEDA", tabName = "do_peda", icon= icon("spinner"))
),
badgeLabel =icon("info-circle"), badgeColor = "light-blue",
menuItem("Validation", icon = icon("th"), tabName = "do_validation",
badgeLabel =icon("database"),
badgeColor = "light-blue"),
menuItem("Chargement", icon = icon("trophy"), tabName = "do_chargement",
badgeLabel =icon("sort-amount-up"),
badgeColor = "light-blue"),
menuItem("Autres", icon = icon("eye"), tabName = "autres",
badgeLabel =icon("chart-bar"),
badgeColor = "light-blue") )
) #close sidebar
) #conditionpanel
) #close siderbarpanel
) #close div
), #close hidden
# Main-Panel ------
mainPanel(
tabsetPanel(
# > Login -------
tabPanel("Login",
value = 1,
br(),
textInput("username", "Nom utilisateur"),
passwordInput("password", label = "GJ utilisateur"),
# If you want to add custom javascript messages
# tags$head(tags$script(src = "message-handler.js")),
actionButton("login", "Login"),
textOutput("pwd")
), # closes tabPanel
id = "tabselected", type = "pills"
) # closes tabsetPanel
) # closes mainPanel
) #close sidebarLayout
) #close fluidePage ui first
# Define dashboardBody()
body <- dashboardBody(
# Found at https://stackoverflow.com/questions/40985684/r-shiny-present-a-shinybs-modal-popup-on-page-visit-no-user-action
# bsModal("window", "Window",
# title="Project Details", size="large",
# h4("English", align = "justify"),
# h5(description_eng, align = "justify"),
# #h4("", align = "justify"),
# h4("French", align = "justify"),
# h5(description_fr, align = "justify"),
# #footer = h4(actionLink('create_account',),align='center'),
# tags$head(tags$style("#window .modal-footer{display:bloc}
# .modal-header .close{display:none}"),
# tags$script("$(document).ready(function(){
# $('#window').modal();
# });")
# )
# ),
tabItems(
tabItem("mouvement",
# Row srtucture
fluidRow(
column(4,
# Define User inputs
selectInput("ag_file1",
label = "choisir une agence",
choices = code_ag,
selected = NULL
),
selectInput("motifs_mouv",
label = "Choisir un motif",
choices = motifs_mouv,
selected = NULL
),
selectInput("enveloppe_mouv",
label = "Choisir une enveloppe",
choices = ""
),
textOutput("founds"),
selectInput("transaction", label = "Debit ou Credit", choices = c("Debit", "Credit")
),
numericInput("montant", label = "saisir le montant(€)" ,
value = "" ,min = 5, max=50000 )
,
actionBttn("soumettre_mouv",
"Soumettre", icon=NULL, style = "unite", color = "success",
size="md", block = FALSE, no_outline = TRUE)
),
column(8,
uiOutput("infos_mouv"))
)
)
,
tabItem("do_mutualisation",
# Row srtucture
fluidPage( tabsetPanel(
tabPanel("Mutualisation entre enveloppes",
selectInput("agence_mut",
label = "veuillez selectionner une agence",
choices = "",
selected = NULL),
selectInput("env_mutu_deb",
label = "sectionner l'enveloppe à debiter",
choices = c("N500", "N600"), selected = NULL),
selectInput("env_mutu_deb",
label = "selectionner l'enveloppe à crediter",
choices = c("N500", "N600") ,
selected = NULL
),
numericInput("montant_mutu",
label = "Saisir le montant",
value = "",
min = 0,
max= Inf),
bsButton("valider_mutu",
label = "Soumettre",
icon = icon("spinner"),
style = "success")
),
tabPanel("mutualisation entre agences",
column(4,
selectInput(
"Code_agence",
label = "Selctionner le code d' l'agence à debiter",
choices = "",
selected = NULL
),
checkboxGroupInput("env_mut_ag_deb",
label = "cocher l'enveloppe à debiter",
choices = c("N500", "N600"),
width = 5)
),
column(10,
selectInput("code_agence",
label = "selectionner le code de l'agence à crediter",
choices = ""),
checkboxGroupInput("env_mut_ag_deb",
label = "cocher l'enveloppe à crediter",
choices = c("N500", "N600"),
width = 5)
,
bsButton("valider_mutu_ag",
label = "Soumettre",
icon = icon("spinner"),
style = "success"),
column(6,
numericInput("mont_mutu_ag",
label = "saisir le montant",
value = "",
min= 5, max = 50000
),
)
),
)
)
)
)
,
tabItem("do_avance",
fluidRow(
column(4,
selectInput("ag_file2",
label = "choisir une agence",
choices = "",
selected = NULL),
selectInput('motifs_avance',
'Selctionnez le motif',
choices = motifs_avance,
selected = "AVANCE SUR CONTRAT"),
selectInput("enveloppe_avance",
"Selectionner une enveloppe",
choices = "",
selected = NULL),
numericInput("montant_avance",
"Saisir le montant de l'avance demandée ou à recuperer",
value = "",
min = 0, max = Inf
),
actionBttn("soumettre_avance",
"Soumettre", icon=NULL, style = "unite", color = "success",
size="md", block = FALSE, no_outline = TRUE)
)
)
),
tabItem("do_validation"
#fluidPage(
# fluidRow(
# column(4,
# selectInput("tab_fil1",
# label = "Filter Select",
# choices = c("Country","Language", "Genre")
# )
#),#
# column(4,
# selectInput("tab_fil2",
# label = "",
# choices = "")
# ),
# column(4,
# numericInput("tab_fil3",
# label = "Number of observations",
# min = 0,
# max = Inf,
# value = 50
# )
# )
# ),
# textOutput("founds2"),
# dataTableOutput("data_view") %>% withSpinner(type = 6)
# )
),
tabItem("do_chargement"
#fluidPage(
# fluidRow(
# column(6,
# selectInput("HOF_fil1",
# label = "Select filter below",
# choices = c("Decade", "Genre", "Year")
#)
#),
#column(6,
# selectInput("HOF_fil2",
# label = "",
# choices = "")
#)
#),
#fluidRow(
# uiOutput("podium_table")
#)
#)
),
tabItem("autres"
#fluidPage(
#fluidRow(
# column(6,
#
# pickerInput(
# inputId = "dec_fil1",
# label = "Select decade below",
# choices = dec_val,
# multiple = FALSE,
# choicesOpt = list(
# disabled = dec_val %in% dec_val[1:2]
# )
# )
# ),
# column(6,
# verbatimTextOutput("cont")
# )
# ),
# fluidRow(
# plotOutput("countTitleGraph",width = "70%") %>% withSpinner(type = 6)
# )
)
)
) #close body
footer <- dashboardFooter(
left = "Gan",
right = "contact:"
)
# ui out to server
ui<-dashboardPagePlus(header, ui_first, body, footer=footer)
#server :
server <- function(input, output, session) {
user_vec <- c("niang" = "GJ7471",
"gouzou" = "PL4350")
# I usually do run the code below on a real app on a server
# user <- reactiveValues(his = readRDS(file = "logs/user_his.rds"),
# log = readRDS(file = "logs/user_log.rds"),
# vec = readRDS(file = "logs/user_vec.rds"))
#
# where user_his is defined as follows
# user_his <- vector(mode = "integer", length = length(user_vec))
# names(user_his) <- names(user_vec)
observeEvent(input$login, {
if (str_to_lower(input$username) %in% names(user_vec)) { # is username in user_vec?
# Alternatively if you want to limit login attempts to "3" using the user_his file
# if (str_to_lower(input$username) %in% names(user$vec[user$his < 3])) {
if (input$password == unname(user_vec[input$username])) {
# nulls the user_his login attempts and saves this on server
# user$his[str_to_lower(input$username)] <- 0
# saveRDS(user$his, file = "logs/user_his.rds")
# Saves a temp log file
# user_log_temp <- data.frame(username = str_to_lower(input$username),
# timestamp = Sys.time())
# saves temp log in reactive value
# user$log <- rbind(user$log, user_log_temp)
# saves reactive value on server
# saveRDS(user$log, file = "logs/user_log.rds")
# > Add MainPanel and Sidebar----------
shinyjs::show(id ="Siderbar")
appendTab(inputId = "tabselected",
tabPanel("Tab 1",
value = 2
) # closes tabPanel,
)
appendTab(inputId = "tabselected",
tabPanel("Tab 2",
value = 3
) # closes tabPanel,
)
appendTab(inputId = "tabselected",
tabPanel("Tab 3",
value = 4
) # closes tabPanel
)
removeTab(inputId = "tabselected",
target = "1")
} else { # username correct, password wrong
# adds a login attempt to user_his
# user$his[str_to_lower(input$username)] <- user$his[str_to_lower(input$username)] + 1
# saves user_his on server
# saveRDS(user$his, file = "logs/user_his.rds")
# Messge which shows how many log-in tries are left
#
# session$sendCustomMessage(type = 'testmessage',
# message = paste0('Password not correct. ',
# 'Remaining log-in tries: ',
# 3 - user$his[str_to_lower(input$username)]
# )
# )
} # closes if-clause
} else { # username name wrong or more than 3 log-in failures
# Send error messages with javascript message handler
#
# session$sendCustomMessage(type = 'testmessage',
# message = paste0('Wrong user name or user blocked.')
# )
} # closes second if-clause
}) # closes observeEvent
#demande
######### Server Mouvement
observeEvent(
input$motifs_mouv,
updateSelectInput(session,
inputId = "enveloppe_mouv",
label = "Choisir une enveloppe",
choices = enveloppeChoices()
)
)
enveloppeChoices <- reactive({
MOUVEMENT$ENVELOPPES[MOUVEMENT$MOTIFS == input$motifs_mouv] %>% sort()
})
output$founds <- reactive({
paste(MOUVEMENT$ENVELOPPES[MOUVEMENT$MOTIFS == input$motifs_mouv] %>% length(), "enveloppe(s) trouvrées")
})
# filtering data and rendering to htmlTable
output$infos_mouv <- renderUI({
table(
code_agence = input$ag_file1,
titulaires = TABLEICX$TITULAIR[TABLEICX$CODEICX == input$ag_file1],
reseau = TABLEICX$RESEAU[TABLEICX$CODEICX == input$ag_file1],
region = TABLEICX$REGION[TABLEICX$CODEICX== input$ag_file1],
telephone= TABLEICX$TEL[TABLEICX$CODEICX== input$ag_file1],
ICRA= TABLEICX$NOMICRA[TABLEICX$CODEICX == input$ag_file1],
DCR= TABLEICX$NOMDR[TABLEICX$CODEICX == input$ag_file1],
email= TABLEICX$EMAIL[TABLEICX$CODEICX == input$ag_file1]
)
})
observeEvent(input$soumettre_mouv, {
log <- data.frame(
Demandeur = TABLEICX$TITULAIR[TABLEICX$CODEICX == input$ag_file1],
Code = input$ag_file1,
Motif = input$motifs_mouv,
enveloppe = input$enveloppe_mouv,
Date = Sys.time(),
transaction = input$transaction,
montant = input$montant
)
write.table(log,
file = "logs.table",
sep = ";",
append = TRUE,
row.names = FALSE,
col.names = FALSE)
sendSweetAlert(
session = session,
title = "Recapitulatif de votre demande",
text = fluidRow(
column(12,
uiOutput("demande_details"),
style= "font-size: 9pt"
),
column(
width = 12,
DT::DTOutput("logs_table"),
style = "font-size: 8pt"
#tableOutput("logs_table")
),
column(
width=12,
actionBttn("valider_mouv", "Valider", icon=NULL, style = "unite", color = "success",
size="md", block = FALSE, no_outline = TRUE
)
)
),
# style = "margin-top: 50px"
html = TRUE
)
})
logs <- eventReactive(input$soumettre_mouv, {
if (file.exists("logs.table")) {
Sys.sleep(2)
read.table(
"logs.table",
sep = ";",
colClasses = "character",
col.names = c("Demandeur", "Code", "Motif", "enveloppe","Date","transaction", "montant")
)
}
} %>%
arrange(desc(Date), .by_group= FALSE) %>% head(1)
, ignoreNULL = FALSE)
output$demande_details <- renderUI({
req(logs())
tagList(
h4(logs()$Code),
p(paste("Vous allez faire une demander de ", input$transaction," ", "pour le motif " ," ", logs()$Motif, " ", "sur votre enveloppe ", logs()$enveloppe )
)
)
})
output$logs_table <- DT::renderDT({
req(logs())
logs() %>%
select(Demandeur, enveloppe, montant, Date) %>%
DT::datatable(
options = list(pageLength = 10, responsive = TRUE, dom = "tp"),
selection = "single",
class = "display compact",
rownames = FALSE
)
})
observeEvent(input$valider_mouv,
{
#req(logs())
histo_mouv <- data.frame(
Demandeur = logs()$Demandeur,
Code = logs()$Code,
Motif = logs()$Motif,
Enveloppe = logs()$enveloppe,
Date = logs()$Date,
Transaction = logs()$transaction,
Montant = logs()$montant,
ICRA= TABLEICX$NOMICRA[TABLEICX$CODEICX == input$ag_file1],
DCR= TABLEICX$NOMDR[TABLEICX$CODEICX == input$ag_file1]
)
write.table(histo_mouv,
file = "mouv_histo.table",
sep = ";",
append = TRUE,
row.names = FALSE,
col.names = FALSE)
column(
width = 12,
DT::DTOutput("histo_mouv_table"),
style = "font-size: 8pt"
#tableOutput("logs_table")
)
sendSweetAlert(
session = session,
title = "Validé !",
text = "Votre demande a bien été soumise",
type = "success"
)
}
)
mouv_histo <- eventReactive(input$valider_mouv, {
if (file.exists("mouv_histo.table")) {
Sys.sleep(2)
read.table(
"mouv_histo.table",
sep = ";",
colClasses = "character",
col.names = c("Demandeur", "Code", "Motif", "Enveloppe","Date","Transaction", "Montant","ICRA", "DCR")
)
}
} %>%
arrange(desc(Date), .by_group= FALSE)
, ignoreNULL = FALSE)
output$histo_mouv_table <- DT::renderDT({
req(logs())
mouv_histo() %>%
DT::datatable(
options = list(pageLength = 5, responsive = TRUE, dom = "tp"),
selection = "single",
class = "display compact",
rownames = FALSE
)
})
#Avance server
observeEvent(
input$motifs_avance,
updateSelectInput(session,
inputId = "enveloppe_avance",
label = "Choisir une enveloppe",
choices = enveloppeAvance()
)
)
enveloppeAvance <- reactive({
AVANCE$ENVELOPPES[AVANCE$MOTIFS == input$motifs_avance]
})
# filtering data and rendering to htmlTable
#output$infos_mouv <- renderUI({
# })
# output of the findings length afer user input filter
}
#####################################################################

Map either numerical values or a character string

I'm trying to create a ShinyApp and hoping I could get some pointers.
I'm trying to get a summary table ("Summary score") to represent either i) the minimum value associated with user input for radio buttons (e.g., Id037_crit1 & Id038_crit1) or the text string "NA" if a checkbox is selected (Id039_crit1).
I'm not sure how to change the code such that the summary table shows either the minimum value for the radio buttons or the character string if the checkbox is selected. I'm assuming there's some kind of if-else statement but I can't get it to work.
library(shinydashboard)
library(shinythemes)
library(shiny)
library(shinyWidgets)
library(DT)
library(tidyverse)
ui <- fluidPage(
theme = shinytheme("united"),
# Application title
titlePanel("TITLE"),
sidebarLayout(
sidebarPanel(
selectInput("select",
label = helpText("Select a critera"),
choices = list("Criteria_1", "Criteria_2"),
selected = c("NULL")
)
),
mainPanel(tabsetPanel(
tabPanel(
"Criteria", conditionalPanel(h3("Question 1", align = "left"),
condition = "input.select == 'Criteria_1'",
prettyRadioButtons(
inputId = "Id037_crit1",
label = "Predictions:",
choices = c(
"Option 1" = 1,
"Option 2" = 2,
"Option 3" = 3
),
inline = TRUE,
status = "danger",
fill = TRUE
),
),
conditionalPanel(h3("Question 2", align = "left"),
condition = "input.select == 'Criteria_1'",
prettyRadioButtons(
inputId = "Id038_crit1",
label = "Hypotheses:",
choices = c(
"Option 1" = 1,
"Option 2" = 2,
"Option 3" = 3
),
inline = TRUE,
status = "danger",
fill = TRUE)
),
conditionalPanel(h3("Or", align = "left"),
condition = "input.select == 'Criteria_1'",
awesomeCheckbox(
inputId = "Id039_crit1",
label = "NA",
status = "danger")
),
# User side-pannel selection - criteria 2
conditionalPanel(h3("Question 1", align = "left"),
condition = "input.select == 'Criteria_2'",
prettyRadioButtons(
inputId = "Id040_crit2",
label = "Methods:",
choices = c(
"Option 1" = 1,
"Option 2" = 2
),
inline = TRUE,
status = "danger",
fill = TRUE)),
# Second Tab --------------------------------------------------------------
tabPanel(
"Summary score",
DTOutput("summary")
),
))
)
)
# SERVER ------------------------------------------------------------------
server <- function(input, output) {
calc_min_val <- function(contains) {
radios_inputid <- str_subset(names(input), contains)
map_dbl(radios_inputid, ~ as.numeric(input[[.x]])) %>%
min()
}
summ <- reactive({
min_values <- c("crit1$", "crit2$") %>%
map(calc_min_val)
tibble(
Lowest_Criteria = c("Specific hypotheses and prediction are provided?", "Predictions regarding the electromagnetic area of
interest are sufficient?"),
value = map(min_values, ~.)
)
})
output$summary <- DT::renderDT({
datatable(summ())
})
# Downloadable csv of selected dataset ----
output$downloadData <- downloadHandler(
filename = function() {
paste("DATA", ".csv", sep = "")
},
content = function(file) {
write.csv(datasettable(summ()), file, row.names = FALSE)
}
)
}
shinyApp(ui, server)
Perhaps you are looking for this
summ <- reactive({
min_values <- c("crit1$", "crit2$") %>%
map(calc_min_val)
if (input$Id039_crit1 & input$select == 'Criteria_1') value = "NA" else value = map(min_values, ~.)
tibble(
Lowest_Criteria = c("Specific hypotheses and prediction are provided?", "Predictions regarding the electromagnetic area of
interest are sufficient?"),
value = value
)
})

Filtering data in shinydashboard

I'm having issues with a filter option in my R shinydashboard app. I'm able to filter a dataframe column (padj < 1) but when I incorporate this same filter into the app the data is missing padj rows that are very tiny like 1.41103072458963E-14. I get all rows up to 4 decimal places (0.00011014) but not rows with padj smaller than that. This cuts off dozens of wanted rows.
I may be coding something wrong and have tried searching for similar issues but haven't found any.
The select input I chose is:
pickerInput("FDR", "False Discovery Rate", choices = c(1, 0.1, 0.05, 0.01))
when I try to filter using above input:
genes1 <- reactive({
genes <- DEG2 %>% dplyr::filter(padj <= input$FDR) %>% dplyr::filter(log2FoldChange >= input$FC | log2FoldChange <= -input$FC)
})
Any help/advice is greatly appreciated.
data to be loaded here:
datafile.
See below for the app code.
library(shinydashboard)
library(dashboardthemes)
library(shiny)
library(shinythemes)
library(shinyWidgets)
library(shinycssloaders)
library(shinyjs)
library(htmlTable)
library(DT)
library(dplyr)
library(ggpubr)
library(ggplot2)
library(htmlwidgets)
library(plotly)
library(table1)
# load dataset
DEG2 <- read.csv("DEG2.csv")
# to add color to the spinner
options(spinner.color="#287894")
#############################################
### HEADER #################################
#############################################
header <- dashboardHeader(title = tagList(
tags$span(class = "logo-mini", "Cell"),
tags$span( class = "logo-lg", "My 1st App" )),
titleWidth = 300)
#############################################
### SIDEBAR #################################
#############################################
sidebar <- dashboardSidebar(width = 300, sidebarMenu(id = "sidebar", # id important for updateTabItems
menuItem("Pipeline", tabName = "pipe", icon = icon("bezier-curve")),
menuItem("Something", tabName = "plot", icon = icon("braille")),
menuItem("Something else", tabName = "pathways", icon = icon("connectdevelop")),
menuItem("Contact", tabName = "contact", icon = icon("address-card"))
)
)
#############################################
### BODY #################################
#############################################
body <- dashboardBody(
useShinyjs(), # Set up shinyjs
# changing theme
shinyDashboardThemes(theme = "blue_gradient"),
tabItems(
######### Tab 1 #########################################
tabItem("pipe",
fluidPage(
h2("Pipeline"),
#### STEP 1 ####
box(width = 12, title = "Step1: Filter for DEGs", collapsible = TRUE, collapsed = FALSE, status = "primary", solidHeader = TRUE,
fluidRow(
column(4, offset = 0,
sliderTextInput("FC", "Fold-Change (absolute value)", choices = seq(from= 0, to= 5, by=0.5), grid = TRUE),
pickerInput("FDR", "False Discovery Rate", choices = c(1, 0.1, 0.05, 0.01)),
setSliderColor(color = '#EE9B00', sliderId = 1),),
column(6, offset= 1,
valueBoxOutput("genes_filtered", width = 4))),
br(),
fluidRow(
column(10, offset =0,
DT::dataTableOutput("genetable") %>% withSpinner(type = 8, size=1))),
br(),
actionBttn("step1", "Select to advance:step 2", color = "warning", style = "fill", icon = icon("angle-double-down" ))
)),
#### STEP 2 ####
conditionalPanel(
condition = "input.step1 == 1",
fluidPage(
box(width = 12, title = "Step2: Filter for gene regulation", collapsible = TRUE, collapsed = FALSE, status = "primary", solidHeader = TRUE,
"Choose to subset the genes that are up or down regulated",
br(),
br(),
fluidRow(
column(6, offset = 0,
prettyRadioButtons("reg", "Choose:", choices = c("Up-regulated", "Down-regulated", "All"), status = "success", fill=TRUE, inline = TRUE))
),
br(),
fluidRow(
column(6, offset = 0,
valueBoxOutput("value", width = 6)))
) # box
)
) # conditional panel
)# end tab3
) # end tabItems
)#dashboardBody
ui <- dashboardPage(header = header,
sidebar = sidebar,
body = body
)
server <- function(input, output, session) {
############################################
###### TAB1 ##################
############################################
# step 1
genes1 <- reactive({
genes <- DEG2 %>% dplyr::filter(padj <= input$FDR) %>% dplyr::filter(log2FoldChange >= input$FC | log2FoldChange <= -input$FC)
})
output$genes_filtered <- renderValueBox({
valueBox(value=length(genes1()$symbol), subtitle = "Filtered genes", color = "purple", icon=icon("filter"))
})
output$genetable <- DT::renderDataTable({
genes1() }, server = FALSE, extensions =c("Responsive", "Buttons"), rownames = FALSE, options = list(dom = 'Blfrtip', buttons = list('copy', list(extend = "collection",
buttons = c("csv", "excel", "pdf"),
text = "Download")))
)
# step 2
genes2 <- reactive({
g2 <- if (input$reg == "Up-regulated"){
genes1() %>% filter(log2FoldChange > 0)
} else if (input$reg == "Down-regulated"){
genes1() %>% filter(log2FoldChange < 0)
} else {
genes1()
}
})
output$value <- renderValueBox({
if (input$reg == "Up-regulated"){
valueBox(value = length(genes2()$symbol), subtitle = "Up-regulated genes", color = "red", icon = icon("hand-point-up"))
} else if (input$reg == "Down-regulated"){
valueBox(value = length(genes2()$symbol), subtitle = "Down-regulated genes", color = "blue", icon = icon("hand-point-down"))
} else {
valueBox(value = length(genes2()$symbol), subtitle = "All genes", color = "orange", icon = icon("record-vinyl"))
}
})
} #server
shinyApp(ui, server)
Try as.numeric(input$FDR) in your filter as shown below.
genes <- DEG2 %>% dplyr::filter(padj <= as.numeric(input$FDR))

Issue with heatmaply when using navbar in shiny

EDIT: I have simplified the application and make it all the code reproducible.
EDIT 2: I just discovered that when I use the navBarPage I must click on Additional Parameters -> Colour. Then is coloured as expected.
I'm developing a shiny app which filters my genes and then plots a heatmap of the remaining genes. Recently, I have found shinyHeatmaply package. I have download their global, UI and Server, and when I try it on my own computer they work as expected. Unfortunately, when I try to combine my filter app and their heatmap using navbarPage, the last one is not rending properly.
I have created a minimalist example adding the shinyheatmap to the second tabPanel of navbarPage in the https://shiny.rstudio.com/gallery/shiny-theme-selector.html app, but I get the same grey render anyway.
Same mistake in a simpler application
The UI:
Navbar 1 belongs to the shinytheme application, whilst the content of Navbar 2 belongs to the shinyheatmaply
tagList(
shinythemes::themeSelector(),
navbarPage(
# theme = "cerulean", # <--- To use a theme, uncomment this
"shinythemes",
tabPanel("Navbar 1",
sidebarPanel(
fileInput("file", "File input:"),
textInput("txt", "Text input:", "general"),
sliderInput("slider", "Slider input:", 1, 100, 30),
tags$h5("Deafult actionButton:"),
actionButton("action", "Search"),
tags$h5("actionButton with CSS class:"),
actionButton("action2", "Action button", class = "btn-primary")
),
mainPanel(
tabsetPanel(
tabPanel("Tab 1",
h4("Table"),
tableOutput("table"),
h4("Verbatim text output"),
verbatimTextOutput("txtout"),
h1("Header 1"),
h2("Header 2"),
h3("Header 3"),
h4("Header 4"),
h5("Header 5")
),
tabPanel("Tab 2", "This panel is intentionally left blank"),
tabPanel("Tab 3", "This panel is intentionally left blank")
)
)
),
tabPanel("Navbar 2",
fluidPage(
sidebarLayout(
sidebarPanel(width=4,
h4('Data Selection'),
fileInput(inputId="mydata", label = "Import Data",multiple = T),
uiOutput('data'),
checkboxInput('showSample','Subset Data'),
conditionalPanel('input.showSample',uiOutput('sample')),
hr(),h4('Data Preprocessing'),
column(width=4,selectizeInput('transpose','Transpose',choices = c('No'=FALSE,'Yes'=TRUE),selected = FALSE)),
column(width=4,selectizeInput("transform_fun", "Transform", c(Identity=".",Sqrt='sqrt',log='log',Scale='scale',Normalize='normalize',Percentize='percentize',"Missing values"='is.na10', Correlation='cor'),selected = '.')),
uiOutput('annoVars'),
br(),hr(),h4('Row dendrogram'),
column(width=6,selectizeInput("distFun_row", "Distance method", c(Euclidean="euclidean",Maximum='maximum',Manhattan='manhattan',Canberra='canberra',Binary='binary',Minkowski='minkowski'),selected = 'euclidean')),
column(width=6,selectizeInput("hclustFun_row", "Clustering linkage", c(Complete= "complete",Single= "single",Average= "average",Mcquitty= "mcquitty",Median= "median",Centroid= "centroid",Ward.D= "ward.D",Ward.D2= "ward.D2"),selected = 'complete')),
column(width=12,sliderInput("r", "Number of Clusters", min = 1, max = 15, value = 2)),
#column(width=4,numericInput("r", "Number of Clusters", min = 1, max = 20, value = 2, step = 1)),
br(),hr(),h4('Column dendrogram'),
column(width=6,selectizeInput("distFun_col", "Distance method", c(Euclidean="euclidean",Maximum='maximum',Manhattan='manhattan',Canberra='canberra',Binary='binary',Minkowski='minkowski'),selected = 'euclidean')),
column(width=6,selectizeInput("hclustFun_col", "Clustering linkage", c(Complete= "complete",Single= "single",Average= "average",Mcquitty= "mcquitty",Median= "median",Centroid= "centroid",Ward.D= "ward.D",Ward.D2= "ward.D2"),selected = 'complete')),
column(width=12,sliderInput("c", "Number of Clusters", min = 1, max = 15, value = 2)),
#column(width=4,numericInput("c", "Number of Clusters", min = 1, max = 20, value = 2, step = 1)),
br(),hr(), h4('Additional Parameters'),
column(3,checkboxInput('showColor','Color')),
column(3,checkboxInput('showMargin','Layout')),
column(3,checkboxInput('showDendo','Dendrogram')),
hr(),
conditionalPanel('input.showColor==1',
hr(),
h4('Color Manipulation'),
uiOutput('colUI'),
sliderInput("ncol", "Set Number of Colors", min = 1, max = 256, value = 256),
checkboxInput('colRngAuto','Auto Color Range',value = T),
conditionalPanel('!input.colRngAuto',uiOutput('colRng'))
),
conditionalPanel('input.showDendo==1',
hr(),
h4('Dendrogram Manipulation'),
selectInput('dendrogram','Dendrogram Type',choices = c("both", "row", "column", "none"),selected = 'both'),
selectizeInput("seriation", "Seriation", c(OLO="OLO",GW="GW",Mean="mean",None="none"),selected = 'OLO'),
sliderInput('branches_lwd','Dendrogram Branch Width',value = 0.6,min=0,max=5,step = 0.1)
),
conditionalPanel('input.showMargin==1',
hr(),
h4('Widget Layout'),
column(4,textInput('main','Title','')),
column(4,textInput('xlab','X Title','')),
column(4,textInput('ylab','Y Title','')),
sliderInput('row_text_angle','Row Text Angle',value = 0,min=0,max=180),
sliderInput('column_text_angle','Column Text Angle',value = 45,min=0,max=180),
sliderInput("l", "Set Margin Width", min = 0, max = 200, value = 130),
sliderInput("b", "Set Margin Height", min = 0, max = 200, value = 40)
)
),
mainPanel(
tabsetPanel(
tabPanel("Heatmaply",
tags$a(id = 'downloadData', class = paste("btn btn-default shiny-download-link",'mybutton'), href = "", target = "_blank", download = NA, icon("clone"), 'Download Heatmap as HTML'),
tags$head(tags$style(".mybutton{color:white;background-color:blue;} .skin-black .sidebar .mybutton{color: green;}") ),
plotlyOutput("heatout",height='600px')
),
tabPanel("Data",
DT::dataTableOutput('tables')
)
)
)
)
)
),
tabPanel("Navbar 3", "This panel is intentionally left blank")
)
)
The server:
Regarding to the server, first two output correspond to the shinytheme and the others belong to shinyheatmaply
d=data(package='datasets')$results[,'Item']
d=d[!grepl('[\\()]',d)]
d=d[!d%in%c('UScitiesD','eurodist','sleep','warpbreaks')]
d=d[unlist(lapply(d,function(d.in) eval(parse(text=paste0('ncol(as.data.frame(datasets::',d.in,'))')))))>1]
d=d[-which(d=='mtcars')]
d=c('mtcars',d)
server <- shinyServer(function(input, output,session) {
####This to output belongs to the shinytheme application####
output$txtout <- renderText({
paste(input$txt, input$slider, format(input$date), sep = ", ")
})
output$table <- renderTable({
head(cars, 4)
})
#######################################################
#Up to here the code belongs to shinyheatmaply
output$txtout <- renderText({
paste(input$txt, input$slider, format(input$date), sep = ", ")
})
output$table <- renderTable({
head(cars, 4)
})
TEMPLIST<-new.env()
TEMPLIST$d<-d
#Annotation Variable UI ----
observeEvent(data.sel(),{
output$annoVars<-renderUI({
data.in=data.sel()
NM=NULL
if(any(sapply(data.in,class)=='factor')){
NM=names(data.in)[which(sapply(data.in,class)=='factor')]
}
column(width=4,
selectizeInput('annoVar','Annotation',choices = names(data.in),selected=NM,multiple=T,options = list(placeholder = 'select columns',plugins = list("remove_button")))
)
})
#Sampling UI ----
output$sample<-renderUI({
list(
column(4,textInput(inputId = 'setSeed',label = 'Seed',value = sample(1:10000,1))),
column(4,numericInput(inputId = 'selRows',label = 'Number of Rows',min=1,max=pmin(500,nrow(data.sel())),value = pmin(500,nrow(data.sel())))),
column(4,selectizeInput('selCols','Columns Subset',choices = names(data.sel()),multiple=T))
)
})
})
#Data Selection UI ----
output$data=renderUI({
if(!is.null(input$mydata)) TEMPLIST$d=c(input$mydata$name,TEMPLIST$d)
selData=head(TEMPLIST$d,1)
selectInput("data","Select Data",TEMPLIST$d,selected = selData)
})
#Color Pallete UI ----
output$colUI<-renderUI({
colSel='Vidiris'
if(input$transform_fun=='cor') colSel='RdBu'
if(input$transform_fun=='is.na10') colSel='grey.colors'
selectizeInput(inputId ="pal", label ="Select Color Palette",
choices = c('Vidiris (Sequential)'="viridis",
'Magma (Sequential)'="magma",
'Plasma (Sequential)'="plasma",
'Inferno (Sequential)'="inferno",
'Magma (Sequential)'="magma",
'Magma (Sequential)'="magma",
'RdBu (Diverging)'="RdBu",
'RdYlBu (Diverging)'="RdYlBu",
'RdYlGn (Diverging)'="RdYlGn",
'BrBG (Diverging)'="BrBG",
'Spectral (Diverging)'="Spectral",
'BuGn (Sequential)'='BuGn',
'PuBuGn (Sequential)'='PuBuGn',
'YlOrRd (Sequential)'='YlOrRd',
'Heat (Sequential)'='heat.colors',
'Grey (Sequential)'='grey.colors'),
selected=colSel)
})
#Manual Color Range UI ----
output$colRng=renderUI({
if(!is.null(data.sel())) {
rng=range(data.sel(),na.rm = TRUE)
}else{
rng=range(mtcars) # TODO: this should probably be changed
}
# sliderInput("colorRng", "Set Color Range", min = round(rng[1],1), max = round(rng[2],1), step = .1, value = rng)
n_data = nrow(data.sel())
min_min_range = ifelse(input$transform_fun=='cor',-1,-Inf)
min_max_range = ifelse(input$transform_fun=='cor',1,rng[1])
min_value = ifelse(input$transform_fun=='cor',-1,rng[1])
max_min_range = ifelse(input$transform_fun=='cor',-1,rng[2])
max_max_range = ifelse(input$transform_fun=='cor',1,Inf)
max_value = ifelse(input$transform_fun=='cor',1,rng[2])
a_good_step = 0.1 # (max_range-min_range) / n_data
list(
numericInput("colorRng_min", "Set Color Range (min)", value = min_value, min = min_min_range, max = min_max_range, step = a_good_step),
numericInput("colorRng_max", "Set Color Range (max)", value = max_value, min = max_min_range, max = max_max_range, step = a_good_step)
)
})
#Import/Select Data ----
data.sel=eventReactive(input$data,{
if(input$data%in%d){
eval(parse(text=paste0('data.in=as.data.frame(datasets::',input$data,')')))
}else{
data.in=importSwitch(input$mydata[input$mydata$name%in%input$data,])
}
data.in=as.data.frame(data.in)
# data.in=data.in[,sapply(data.in,function(x) class(x))%in%c('numeric','integer')] # no need for this
return(data.in)
})
#Building heatmaply ----
interactiveHeatmap<- reactive({
data.in=data.sel()
if(input$showSample){
if(!is.null(input$selRows)){
set.seed(input$setSeed)
if((input$selRows >= 2) & (input$selRows < nrow(data.in))){
# if input$selRows == nrow(data.in) then we should not do anything (this save refreshing when clicking the subset button)
if(length(input$selCols)<=1) data.in=data.in[sample(1:nrow(data.in),pmin(500,input$selRows)),]
if(length(input$selCols)>1) data.in=data.in[sample(1:nrow(data.in),pmin(500,input$selRows)),input$selCols]
}
}
}
# ss_num = sapply(data.in,function(x) class(x)) %in% c('numeric','integer') # in order to only transform the numeric values
if(length(input$annoVar)>0){
if(all(input$annoVar%in%names(data.in)))
data.in <- data.in%>%mutate_at(funs(factor),.vars=vars(input$annoVar))
}
ss_num = sapply(data.in, is.numeric) # in order to only transform the numeric values
if(input$transpose) data.in=t(data.in)
if(input$transform_fun!='.'){
if(input$transform_fun=='is.na10'){
updateCheckboxInput(session = session,inputId = 'showColor',value = T)
data.in[, ss_num]=is.na10(data.in[, ss_num])
}
if(input$transform_fun=='cor'){
updateCheckboxInput(session = session,inputId = 'showColor',value = T)
updateCheckboxInput(session = session,inputId = 'colRngAuto',value = F)
data.in=cor(data.in[, ss_num],use = "pairwise.complete.obs")
}
if(input$transform_fun=='log') data.in[, ss_num]= apply(data.in[, ss_num],2,log)
if(input$transform_fun=='sqrt') data.in[, ss_num]= apply(data.in[, ss_num],2,sqrt)
if(input$transform_fun=='normalize') data.in=heatmaply::normalize(data.in)
if(input$transform_fun=='scale') data.in[, ss_num] = scale(data.in[, ss_num])
if(input$transform_fun=='percentize') data.in=heatmaply::percentize(data.in)
}
if(!is.null(input$tables_true_search_columns))
data.in=data.in[activeRows(input$tables_true_search_columns,data.in),]
if(input$colRngAuto){
ColLimits=NULL
}else{
ColLimits=c(input$colorRng_min, input$colorRng_max)
}
distfun_row = function(x) dist(x, method = input$distFun_row)
distfun_col = function(x) dist(x, method = input$distFun_col)
hclustfun_row = function(x) hclust(x, method = input$hclustFun_row)
hclustfun_col = function(x) hclust(x, method = input$hclustFun_col)
p <- heatmaply(data.in,
main = input$main,xlab = input$xlab,ylab = input$ylab,
row_text_angle = input$row_text_angle,
column_text_angle = input$column_text_angle,
dendrogram = input$dendrogram,
branches_lwd = input$branches_lwd,
seriate = input$seriation,
colors=eval(parse(text=paste0(input$pal,'(',input$ncol,')'))),
distfun_row = distfun_row,
hclustfun_row = hclustfun_row,
distfun_col = distfun_col,
hclustfun_col = hclustfun_col,
k_col = input$c,
k_row = input$r,
limits = ColLimits) %>%
layout(margin = list(l = input$l, b = input$b, r='0px'))
p$elementId <- NULL
p
})
#Render Plot ----
observeEvent(input$data,{
output$heatout <- renderPlotly({
if(!is.null(input$data))
interactiveHeatmap()
})
})
#Render Data Table ----
output$tables=DT::renderDataTable(data.sel(),server = T,filter='top',
extensions = c('Scroller','FixedHeader','FixedColumns','Buttons','ColReorder'),
options = list(
dom = 't',
buttons = c('copy', 'csv', 'excel', 'pdf', 'print','colvis'),
colReorder = TRUE,
scrollX = TRUE,
fixedColumns = TRUE,
fixedHeader = TRUE,
deferRender = TRUE,
scrollY = 500,
scroller = TRUE
))
#Clone Heatmap ----
observeEvent({interactiveHeatmap()},{
h<-interactiveHeatmap()
l<-list(main = input$main,xlab = input$xlab,ylab = input$ylab,
row_text_angle = input$row_text_angle,
column_text_angle = input$column_text_angle,
dendrogram = input$dendrogram,
branches_lwd = input$branches_lwd,
seriate = input$seriation,
colors=paste0(input$pal,'(',input$ncol,')'),
distfun_row = input$distFun_row,
hclustfun_row = input$hclustFun_row,
distfun_col = input$distFun_col,
hclustfun_col = input$hclustFun_col,
k_col = input$c,
k_row = input$r,
limits = paste(c(input$colorRng_min, input$colorRng_max),collapse=',')
)
#l=l[!l=='']
l=data.frame(Parameter=names(l),Value=do.call('rbind',l),row.names = NULL,stringsAsFactors = F)
l[which(l$Value==''),2]='NULL'
paramTbl=print(xtable::xtable(l),type = 'html',include.rownames=FALSE,print.results = F,html.table.attributes = c('border=0'))
h$width='100%'
h$height='800px'
s<-tags$div(style="position: relative; bottom: 5px;",
HTML(paramTbl),
tags$em('This heatmap visualization was created using',
tags$a(href="https://github.com/yonicd/shinyHeatmaply/",target="_blank",'shinyHeatmaply'),
Sys.time()
)
)
output$downloadData <- downloadHandler(
filename = function() {
paste("heatmaply-", gsub(' ','_',Sys.time()), ".html", sep="")
},
content = function(file) {
libdir <- paste(tools::file_path_sans_ext(basename(file)),"_files", sep = "")
htmltools::save_html(htmltools::browsable(htmltools::tagList(h,s)),file=file,libdir = libdir)
if (!htmlwidgets:::pandoc_available()) {
stop("Saving a widget with selfcontained = TRUE requires pandoc. For details see:\n",
"https://github.com/rstudio/rmarkdown/blob/master/PANDOC.md")
}
htmlwidgets:::pandoc_self_contained_html(file, file)
unlink(libdir, recursive = TRUE)
}
)
})
#End of Code ----
})
Thanks in advance to the hero who solves this problem.
Best rewards, Daniel.
The problem was a conflict between a conditional panel (which uses js) and the navbar page, for any reason default parameters were not read, thus autocoloring which should be enabled wasn't. I just removed this conditional panel and set always its options.

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