DT Reload within RShiny - r

Within shiny how would I go about updating values within a DT table without it repainting the entire table and thus flickering on each update.
The following example compares both the standard tableOutput with DT::dataTableOutput.
Note the flickering on each update of dataTableOutput.
Is there away to avoid this and have a smoother user interaction? ui.R and server.R example below.
require(shiny);require(DT)
shinyUI(fluidPage(
titlePanel("Sliders"),
sidebarLayout(
sidebarPanel(
sliderInput(
"integer", "Integer:",
min = 0, max = 1000, value = 500
),
sliderInput(
"decimal", "Decimal:",
min = 0, max = 1, value = 0.5, step = 0.1
),
sliderInput(
"range", "Range:",
min = 1, max = 1000, value = c(200,500)
),
sliderInput(
"format", "Custom Format:",
min = 0, max = 10000, value = 0, step = 2500,
pre = "$", sep = ",", animate = TRUE
),
sliderInput(
"animation", "Looping Animation:", 1, 2000, 1,
step = 10, animate =
animationOptions(
interval = 300, loop = TRUE,
playButton = "PLAY", pauseButton = "PAUSE"
)
)
),
mainPanel(tableOutput("values"),
DT::dataTableOutput('DTtable'))
)
))
shinyServer(function(input, output) {
sliderValues <- reactive({
data.frame(
Name = c("Integer",
"Decimal",
"Range",
"Custom Format",
"Animation"),
Value = as.character(
c(
input$integer,
input$decimal,
paste(input$range, collapse = ' '),
input$format,
input$animation
)
),
stringsAsFactors = FALSE
)
})
output$values <- renderTable({
sliderValues()
})
output$DTtable = DT::renderDataTable(rownames = FALSE,
{
sliderValues()
},
options = list(processing = FALSE))
})
It looks like the ideal solution would be to implement the reload functionality:
https://datatables.net/reference/api/ajax.reload()
Any advice on how to do this?

Related

Strange behaviour in noUiSliderInput() when formating decimal to integer e.g. 5.00 to 5

In noUiSliderInput() the numbers are shown as decimal by default like: 5.00
To change to integer like: 5
we can use the argument format: format = list(wNumbFormat(decimals = 0, thousand = ",", prefix = "$"))
This only works partially like here:
library( shiny )
library( shinyWidgets )
ui <- fluidPage(
div(style = 'position: absolute;left: 150px; top:270px; width:950px;margin:auto',
noUiSliderInput(
inputId = "noui2", label = "Slider vertical:",
min = 0, max = 45, step = 1,
value = c(15, 20), margin = 10,
orientation = "vertical",
width = "100px", height = "300px",
format = list(wNumbFormat(decimals = 0, thousand = ",", prefix = "$"))
),
verbatimTextOutput(outputId = "res2")
)
)
server <- function(input, output, session) {
output$res2 <- renderPrint(input$noui2)
}
shinyApp(ui, server)
What is the reason for this behavior?
I'm not sure why you are wrapping wNumbFormat in a list, but notice that while you set the prefix to "$", it does not show up in your graphic/video, suggesting that your options are not being used.
Remove the list and it works:
ui <- fluidPage(
div(style = 'position: absolute;left: 150px; top:270px; width:950px;margin:auto',
noUiSliderInput(
inputId = "noui2", label = "Slider vertical:",
min = 0, max = 45, step = 1,
value = c(15, 20), margin = 10,
orientation = "vertical",
width = "100px", height = "300px",
format = wNumbFormat(decimals = 0, thousand = ",", prefix = "$")
),
verbatimTextOutput(outputId = "res2")
)
)

Calculating sum in Shiny

I'm trying to create a shiny app as a practice planner where users can select which drills they are going to do and how long they will do each drill and the app then shows them the total meters covered for the whole practice. Now I'm trying to calculate the total values of meters covered during a session based on the drills selected and the number of minutes selected for each drill. However my total is always equal to 0 even though it works for calculating each drill separately. Could someone help me figure out what I'm doing wrong please. Below is my code with sample data.
library(shiny)
library(dplyr)
# MyData <- read.csv("/Users/sonamoravcikova/Desktop/ShinyTest/ForShiny1.csv")
MyData <- structure(list(Drill = c("GP Warm Up", "5v2 Rondo", "11v11", "10v6 Drop
Behind Ball"), PlayerLoadPerMinute = c(7.72949670665213, 6.49382926701571,
9.67483408668731, 5.86770863636364), MetersPerMinute = c(69.9524820610687,
45.823744973822, 95.9405092879257, 58.185375), class = "data.frame", row.names
= c(NA, -4L)))
# Define UI ----
ui <- fluidPage(
titlePanel("Practice Planner"),
sidebarLayout(
sidebarPanel(
#Select number of drills
numericInput("num", h3("Number of Drills"), value = 1),
textOutput("MpM_Total")
),
mainPanel(
#Show boxes for the number of drill selected and select drill type
selectInput("DrillName1",
label = "Choose a Drill:",
choices = unique(MyData$Drill),
selected = NULL,
multiple = FALSE),
sliderInput("slider1",
label = h3("Slider"),
min = 0,
max = 60,
value = 0),
textOutput("MpM1"),
br(),
conditionalPanel(
condition = "input.num > '1'",
selectInput("DrillName2",
label = "Choose a Drill:",
choices = unique(MyData$Drill),
selected = NULL,
multiple = FALSE),
sliderInput("slider2",
label = h3("Slider"),
min = 0,
max = 60,
value = 0),
textOutput("MpM2")),
br(),
conditionalPanel(
condition = "input.num > '2'",
selectInput("DrillName3",
label = "Choose a Drill:",
choices = unique(MyData$Drill),
selected = NULL,
multiple = FALSE),
sliderInput("slider3",
label = h3("Slider"),
min = 0,
max = 60,
value = 0),
textOutput("MpM3"))
)
)
)
# Define server logic ----
server <- function(input, output, session) {
#Calculate number of meters covered
lapply(1:10, function(x) {
MetersPerMin <- reactive({
chosendrill <- input[[paste0("DrillName",x)]]
MpM <- MyData %>%
distinct(MetersPerMinute, .keep_all = T)
MpM_text <- (MpM$MetersPerMinute[MpM$Drill == chosendrill]) * (input[[paste0("slider",x)]])
})
output[[paste0("MpM", x)]] <- renderText({
paste0("Meters covered: ", MetersPerMin())
})
MpM_Sum <- reactive({
sum(MetersPerMin())
})
output$MpM_Total <- renderText({
paste("Total Meters Covered", MpM_Sum())
})
})
}
# Create Shiny app ----
shinyApp(ui = ui, server = server)
library(shiny)
library(dplyr)
MyData <- data.frame(Drill = c('GP Warm Up', '5v2 Rondo', '11v11', '10v6 Drop Behind Ball'),
PlayerLoadPerMinute = c(7.72949670665213, 6.49382926701571, 9.67483408668731, 5.86770863636364),
MetersPerMinute = c(69.9524820610687, 45.823744973822, 95.9405092879257, 58.185375))
MpM <- MyData %>%
distinct(MetersPerMinute, .keep_all = T)
# Define UI ----
ui <- fluidPage(
titlePanel('Practice Planner'),
sidebarLayout(
sidebarPanel(
#Select number of drills
numericInput('num', h3('Number of Drills'), value = 1),
textOutput('MpM_Total')
),
mainPanel(
#Show boxes for the number of drill selected and select drill type
selectInput('DrillName1',
label = 'Choose a Drill:',
choices = unique(MyData$Drill),
selected = NULL,
multiple = FALSE),
sliderInput('slider1',
label = h3('Slider'),
min = 0,
max = 60,
value = 0),
textOutput('MpM1'),
br(),
conditionalPanel(
condition = 'input.num > "1"',
selectInput('DrillName2',
label = 'Choose a Drill:',
choices = unique(MyData$Drill),
selected = NULL,
multiple = FALSE),
sliderInput('slider2',
label = h3('Slider'),
min = 0,
max = 60,
value = 0),
textOutput('MpM2')
),
br(),
conditionalPanel(
condition = 'input.num > "2"',
selectInput('DrillName3',
label = 'Choose a Drill:',
choices = unique(MyData$Drill),
selected = NULL,
multiple = FALSE),
sliderInput('slider3',
label = h3('Slider'),
min = 0,
max = 60,
value = 0),
textOutput('MpM3')
)
)
)
)
# Define server logic ----
server <- function(input, output, session) {
MetersPerMin <- reactive({
idx <- input$num
if (idx < 1) {
idx <- 1
} else if (idx > 3) {
idx <- 3
}
mpms <- sapply(1:idx, function(x) {
chosendrill <- input[[ paste0('DrillName', x) ]]
mpm <- (MpM$MetersPerMinute[ MpM$Drill == chosendrill ]) * (input[[ paste0('slider', x) ]])
output[[ paste0('MpM', x) ]] <- renderText(paste0('Meters covered: ', mpm))
mpm
})
mpms
})
output$MpM_Total <- renderText({
paste('Total Meters Covered', sum(MetersPerMin()))
})
}
# Create Shiny app ----
shinyApp(ui = ui, server = server)

R Shiny Application moving graph location

I'm currently building an application in R-Shiny and having troubles with the location of the graph since I've added tabs to the application. I want to move the graph from the first tab from below the inputs to the right of them. I'm currently getting the following message from R.
bootstrapPage(position =) is deprecated as of shiny 0.10.2.2. The 'position' argument is no longer used with the latest version of Bootstrap. Error in tabsetPanel(position = "right", tabPanel("Drawdown Plot", plotOutput("line"), : argument is missing, with no default
Any help would be greatly appreciated! Code is below
ui <- fluidPage(
titlePanel("Drawdown Calculator"),
theme = bs_theme(version = 4, bootswatch = "minty"),
sidebarPanel(
numericInput(inputId = "pot",
label = "Pension Pot",
value = 500000, min = 0, max = 2000000, step = 10000),
numericInput(inputId = "with",
label = "Withdrawal Amount",
value = 40000, min = 0, max = 200000, step = 1000),
numericInput(inputId = "age",
label = "Age", value = 65, max = 90, min = 40),
sliderInput(inputId = "int",
label = "Interest",
value = 4, max = 15, min = 0, step = 0.1)),
mainPanel(
tabsetPanel(position = "right",
tabPanel("Drawdown Plot", plotOutput("line"),
p("This drawdown calculator calculates a potential drawdown outcome")),
tabPanel ("Breakdown of Drawdown Withdrawals",
tableOutput("View")),
))
)
Try this code -
library(shiny)
library(bslib)
ui <- fluidPage(
titlePanel("Drawdown Calculator"),
theme = bs_theme(version = 4, bootswatch = "minty"),
sidebarPanel(
numericInput(inputId = "pot",
label = "Pension Pot",
value = 500000, min = 0, max = 2000000, step = 10000),
numericInput(inputId = "with",
label = "Withdrawal Amount",
value = 40000, min = 0, max = 200000, step = 1000),
numericInput(inputId = "age",
label = "Age", value = 65, max = 90, min = 40),
sliderInput(inputId = "int",
label = "Interest",
value = 4, max = 15, min = 0, step = 0.1)),
mainPanel(
tabsetPanel(
tabPanel("Drawdown Plot",
p("This drawdown calculator calculates a potential drawdown outcome"),
tableOutput("View")),
tabPanel("Breakdown of Drawdown Withdrawals",
plotOutput("line"))
))
)
server <- function(input, output) {}
shinyApp(ui, server)

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.

How Can I Have Two Numeric Inputs in R Shiny

Below I have an R code that takes an input value from the numericInput object and stores it in an Excel spreadsheet. I am now trying to have two numericInput's, but I'm not sure how to do that. Below in the code, I tried to just duplicate the object as a last resort effort, but it gave me an error. (I'm not surprised) Any advice?
library(shiny)
library(xlsxjars)
library(rJava)
library(xlsx)
ui <- fluidPage(
numericInput(inputId = "num",
label = "Choose a number",
min = 0, max = 1000000, value = 1),
actionButton(inputId = "submit",
label = "Submit"),
numericInput(inputId = "num2",
label = "Choose a number2", min = 0, max = 1000000, value = 1),
)
server <- function(input, output) {
options(java.parameters = "- Xmx1024m")
wb <- loadWorkbook(file = "F:\\RProject-Rough\\DirectEffect.xlsx")
sheet<-getSheets(wb)
observeEvent(input$submit, {
addDataFrame(c(input$num,input$num2), sheet$'Direct Effects',
col.names = FALSE, row.names = FALSE, startRow = 3,startColumn = 5)
saveWorkbook(wb,"F:\\RProject-Rough\\DirectEffect.xlsx")
})
}
shinyApp(ui = ui, server = server)
First of all, after your second numericInput, there is a comma that does not belong there.
Secondly, addDataFrame takes a data.frame as an argument and not a vector.
The following works for me:
library(shiny)
library(xlsxjars)
library(rJava)
library(xlsx)
ui <- fluidPage(
numericInput(inputId = "num",
label = "Choose a number",
min = 0, max = 1000000, value = 1),
actionButton(inputId = "submit",
label = "Submit"),
numericInput(inputId = "num2",
label = "Choose a number2", min = 0, max = 1000000, value = 1)
)
server <- function(input, output) {
options(java.parameters = "- Xmx1024m")
wb <- loadWorkbook(file = "/PATH/TO/test.xlsx")
sheet <- getSheets(wb)
observeEvent(input$submit, {
addDataFrame(data.frame(c(input$num,input$num2)), sheet$`Direct Effects`,
col.names = FALSE, row.names = FALSE, startRow = 3, startColumn = 5)
saveWorkbook(wb, "/PATH/TO/test.xlsx")
})
}
shinyApp(ui = ui, server = server)

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