Problem getting current list of input values in Shiny - r

I'm having quite a few problems to get the updated values from several coonditionalPanels. I created a reactive variable parList which should contain the parN_sig input variables. These variables should come from conditional panels and they are all named parN_sig. I do not know why but I always end up getting values from the double_sig panel when another panel is shown at the UI.
Here's my code:
ui.r
jscode <- "
shinyjs.disableTab = function(name) {
var tab = $('.nav li a[data-value=' + name + ']');
tab.bind('click.tab', function(e) {
e.preventDefault();
return false;
});
tab.addClass('disabled');
}
shinyjs.enableTab = function(name) {
var tab = $('.nav li a[data-value=' + name + ']');
tab.unbind('click.tab');
tab.removeClass('disabled');
}
"
css <- "
.nav li a.disabled {
background-color: #aaa !important;
color: #333 !important;
cursor: not-allowed !important;
border-color: #aaa !important;
}"
# Create Shiny object
library(shiny)
library(shinythemes)
library(shinyjs)
library(ggplot2)
library(grid)
library(egg)
# source("input.r")
source("functions.r")
formula_tabs<-tabsetPanel(
tabPanel("double_sig",
withMathJax("$$y=d+\\frac{a}{1+exp^{-b*(t-c)}}+\\frac{e}{1+exp^{-f*(t-g)}}$$")
),
tabPanel("gompertz",
withMathJax("$$y=b*exp^{\\ln(\\frac{c}{b})*exp^{-a*t}}$$")
),
tabPanel("verhulst",
withMathJax("$$y=\\frac{b*c}{b+(b-c)*exp^{-a*t}}$$")
),
id = "formulas",
type = "tabs"
)
fluidPage(useShinyjs(),theme = shinytheme("lumen"),useShinyjs(),tags$style("#params { display:none; } #formulas { display:none; }"),
extendShinyjs(text = jscode),inlineCSS(css),
navbarPage("Protein turnover model",id="tabs",
tabsetPanel(tabPanel("Input data",
checkboxInput("multiple","Single file",value = FALSE),
uiOutput("mult_files"),
uiOutput("sing_file"),
actionButton("disp_distr","Show distributions"),
plotOutput("distr_plot"),
plotOutput("distr_stade")
),
tabPanel("Weight fitting",
fileInput("weight_data","Choose weight data to be fitted",accept = c("text/csv")),
div(style="display:inline-block",selectInput("method_we","Select fitting formula",choices = c("Logistic"="verhulst","Gompertz"="gompertz","Empiric"="empirique","Log polynomial"="log_poly","Double sigmoid"="double_sig"))),
div(style="display:inline-block",formula_tabs), ## "Contois"="contois",,"Noyau"="seed",
conditionalPanel("input.method_we=='verhulst'",textInput("par1_sig","Enter value of a",value =0.1),
textInput("par2_sig","Enter value of b",value = 100),
textInput("par3_sig","Enter value of c",value = 1)),
conditionalPanel("input.method_we=='gompertz'",textInput("par1_sig","Enter value of a",value =0.065),
textInput("par2_sig","Enter value of b",value = 114.39),
textInput("par3_sig","Enter value of c",value = 0.52)),
conditionalPanel("input.method_we=='empirique'",textInput("par1_sig","Enter value of a",value =5.38),
textInput("par2_sig","Enter value of b",value = 8),
textInput("par3_sig","Enter value of c",value = 7)),
conditionalPanel("input.method_we=='double_sig'",textInput("par1_sig","Enter value of a",value = 48),
textInput("par2_sig","Enter value of b",value = 0.144),
textInput("par3_sig","Enter value of c",value = 35),
textInput("par4_sig","Enter value of d",value = 0.4),
textInput("par5_sig","Enter value of e",value = 48),
textInput("par6_sig","Enter value of f",value = 0.042),
textInput("par7_sig","Enter value of g",value = 90)),
actionButton("fit_op","Fit"),
plotOutput("fitplot")
),
tabPanel("mRNA fitting and calculation",
textInput("ksmin","Value of ksmin",value =3*4*3*3.6*24),
selectInput("fit_mrna","Select fitting formula",choices=c("3rd degree polynomial"="3_deg","6th degree polynomial"="6_deg","3rd degree logarithmic polynomial"="3_deg_log")),
actionButton("run_loop","Run calculation"),
disabled(downloadButton("downFile","Save results"))
),
tabPanel("Results",id="tabRes",
uiOutput("select_res"),
plotOutput("fit_prot_plot")
)
))
)
server.r
library(shiny)
library(shinythemes)
library(shinyjs)
library(ggplot2)
library(grid)
library(egg)
# source("input.r")
source("functions.r")
function(input, output, session) {
js$disableTab("tabRes")
fit_op<-reactiveValues(data=NULL)
run_calc<-reactiveValues(data=NULL)
en_but<-reactiveValues(enable=FALSE)
theme<<-theme(panel.background = element_blank(),panel.border=element_rect(fill=NA),panel.grid.major = element_blank(),panel.grid.minor = element_blank(),strip.background=element_blank(),axis.text.x=element_text(colour="black"),axis.text.y=element_text(colour="black"),axis.ticks=element_line(colour="black"),plot.margin=unit(c(1,1,1,1),"line"))
output$mult_files<-renderUI({
if (!input$multiple){
tagList(fileInput("prot_file","Choose protein file"),
fileInput("mrna_file","Choose transcript file"))
}
})
output$sing_file<-renderUI({
if (input$multiple){
tagList(textInput("protein_tab","Name of protein tab",value = "Proteines"),
textInput("rna_tab","Name of mRNA tab",value = "Transcrits"),
fileInput("data_file","Choose xls/xlsx file",accept=c(".xls",".xlsx")))
}
})
observeEvent(input$method_we, {
# updateTabsetPanel(session, "params", selected = input$method_we)
updateTabsetPanel(session,"formulas",selected = input$method_we)
})
observe({
if(!is.null(input$data_file)){
inFile<-input$data_file
list_data<-loadData(inFile$datapath,input$rna_tab,input$protein_tab,poids=F)
mrna_data<-list_data$mrna
prot_data<-list_data$prot
test_list<-list_data$parse
test_list<<-sample(test_list,3)
clean_mrna_data<<-mrna_data[,-which(is.na(as.numeric(as.character(colnames(mrna_data)))))]
clean_prot_data<<-prot_data[,-which(is.na(as.numeric(as.character(colnames(prot_data)))))]
}
})
observe({
if((!is.null(input$prot_file)) & (!is.null(input$mrna_file))){
protFile<-input$prot_file
mrnaFile<-input$mrna_file
prot_data<-loadData(protFile$datapath,"","",poids=F)
mrna_data<-loadData(mrnaFile$datapath,"","",poids=F)
clean_mrna_data<<-mrna_data[,-which(is.na(as.numeric(as.character(colnames(mrna_data)))))]
clean_prot_data<<-prot_data[,-which(is.na(as.numeric(as.character(colnames(prot_data)))))]
total_data<-merge(mrna_data,prot_data)
lista<-vector("list",nrow(mrna_data))
for (i in seq(1,nrow(total_data))){
lista[[i]]<-list("Protein_ID"=total_data[i,"Protein"],"Transcrit_ID"=total_data[i,"Transcrit"],"Transcrit_val"=as.matrix(total_data[i,3:29]),"Protein_val"=as.matrix(total_data[i,30:ncol(total_data)]),"DPA"=t)
}
# test_list<<-lista
test_list<<-sample(lista,3)
}
})
observeEvent(input$disp_distr,{
print("Plotting...")
output$distr_plot<-renderPlot({print(combineGraphs(clean_mrna_data,clean_prot_data,"",moyenne = T))})
print("Finished")
})
# parList<-reactiveValues()
# observe({
# for (i in reactiveValuesToList(input)){
# print(i)
# if (grepl("par[1-9]+_sig",i,perl = T)){
# newlist[[input[[i]]]]<-input[[i]]
# }
# }
# # })
parList<-reactive({
x<-reactiveValuesToList(input)
x_ind<-grep("par[1-9]+",names(x),perl = T)
newlist<-vector("list",length(x_ind))
names(newlist)<-names(x[x_ind])
for (el in names(newlist)){
newlist[[el]]<-as.numeric(as.character(input[[el]]))
}
names(newlist)<-gsub("_sig","",names(newlist))
newlist<-newlist[order(names(newlist))]
newlist
})
observeEvent(input$fit_op,{
browser()
print(parList())
inFile<-input$weight_data
days_kiwi<-rep(c(0,13,26,39,55,76,118,179,222), each = 3)
poids_data<-loadData(inFile$datapath,"","",poids=T)
print("Fitting...")
tryCatch({
coefs_poids<<-fitPoids_v2(poids_data[,1],poids_data[,2],input$method_we,parList())
},
warning = function(warn){
showNotification(paste0(warn), type = 'warning')
},
error = function(err){
showNotification(paste0(err), type = 'err')
})
print(coefs_poids$coefs)
val_mu<-mu(c(poids_data$DPA),input$method_we,coefs_poids$coefs,coefs_poids$formula,dpa_analyse = NULL)
data_mu<-data.frame("DPA"=c(poids_data$DPA),"Mu"=val_mu)
g_mu<<-ggplot(data_mu,aes(x=DPA,y=Mu))+geom_line()+theme+xlab("DPA")+ylab("Growth rate (days^-1)")
fit_op$state<-TRUE
print("Finished!!")
output$fitplot<-renderPlot({
req((fit_op$state)==TRUE,exists("coefs_poids"))
ggarrange(coefs_poids$graph,g_mu,ncol=2)
})
})
observeEvent(input$run_loop,{
if (input$fit_mrna!=""){
ksmin=as.numeric(as.character(input$ksmin))
score=0
cont<-0
poids_coef<<-coefs_poids$coefs
formula_poids<<-coefs_poids$formula
mess<-showNotification(paste("Running..."),duration = NULL,type = "message")
for (el in test_list){
tryCatch({
run_calc$run<-TRUE
cont<-cont+1
print(cont)
norm_data<-normaMean(el$Protein_val,el$Transcrit_val,ksmin)
fittedmrna<<-fit_testRNA(el$DPA,norm_data$mrna,"3_deg")
par_k<-solgss_Borne(el$DPA,as.vector(norm_data$prot),as.numeric(norm_data$ks),score)
par_k[["plot_fit_prot"]]<-plotFitProt(el$DPA,as.vector(norm_data$prot),par_k$prot_fit)
X<-matrice_sens(el$DPA,par_k[["solK"]][,1])
diff<-(par_k[["error"]][["errg"]][1]*norm(as.vector(norm_data$prot),"2"))^2
par_k[["corr_matrix"]]<-matrice_corr(X,length(norm_data$prot),diff)
if (!is.null(par_k)){
test_list[[cont]]$SOL<-par_k
# write.csv(test_list[[cont]][["SOL"]][["solK"]],paste("solK/",paste(test_list[[cont]][["Transcrit_ID"]],"_Sol_ks_kd.csv"),sep = ""))
}
},error=function(e){showNotification(paste0("Protein fitting not achieved for ",el$Transcrit_ID,sep=" "),type = "error",duration = NULL)})
}
valid_res<<-Filter(function(x) {length(x) > 5}, test_list)
print(valid_res[[1]])
mess<-showNotification(paste("Finished!!"),duration = NULL,type = "message")
en_but$enable<-TRUE
}
})
output$downFile<-downloadHandler(
filename = function(){
paste("results_KsKd-",Sys.Date(),".zip",sep="")
},
content = function(file){
owd <- setwd(tempdir())
on.exit(setwd(owd))
files <- NULL;
for (res in valid_res){
fileName<-paste(res[["Transcrit_ID"]],"_Sol_ks_kd.csv",sep = "")
write.csv(res[["SOL"]][["solK"]],fileName)
files<-c(files,fileName)
}
zip(zipfile = file,files = files)
if(file.exists(paste0(file, ".zip"))) {file.rename(paste0(file, ".zip"), file)}
},contentType = "application/zip"
)
observe({
if (en_but$enable){
enable("downFile")
}
})
}
I recently started using Shiny, so any help would be extremely appreciated. Thanks in advance!

Welcome to SO.
You've identified the problem yourself: "...are all named parN_sig". That means you don't have several inputs, you only have one. So you always get the value of (say) input$par2_sig from the first conditional panel regardless of which panel you're trying to access.
You have two options:
Provide unique names for every textInput. That will be a pain. Or...
Use modules. They take a bit of getting used to, but are worth the effrt in the end.
If you set the module up correctly, you'll be able to use the same module for each conditional panel, even though they have different numbers of textinputs.
See this page for help on creating your first module.

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Drawing Customized Square Grids over highchart map in shiny

I have created a simple shiny app where I have country, name, and month as inputs according to which a certain map is plotted.
What I would like to do, is to draw cubic 50*50 km grids over each base map.
I have as data, the coordinates of the centroid of each grid, a certain value to plot per grid (filtered per year and month)
What I have till now, is the filter inputs and the base maps, still have no clue how to dram the grids over the map.
Any help is appreciated
Here is part of my code
dashboardHeader(title=""),
dashboardSidebar(sidebarMenu(
menuItem("",tabName="",icon =icon("dashboard"))
)),
dashboardBody(
tabItem(tabName="",
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box(title="Please choose a country,month and year", width=12,status="warning",solidHeader=TRUE,
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# Server input/output Function ---------------------------------------------------------
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data1<-reactive(
{
req(input$Country)
req(input$Month)
req(input$Year)
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}
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output$Map <- renderHighchart(
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if(input$Country=="Algeria"){
hcmap("https://code.highcharts.com/mapdata/countries/dz/dz-all.js")%>%hc_title(text = "Algeria")
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else if(input$Country=="Bahrain"){
hcmap("https://code.highcharts.com/mapdata/countries/bh/bh-all.js")%>%hc_title(text = "Bahrain")
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hcmap("https://code.highcharts.com/mapdata/countries/eg/eg-all.js")%>%hc_title(text = "Egypt")
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paste0(Sys.time(), ".csv", sep = "")
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How to correclty use MutationObserve in Shiny app

I'm trying to observe changes to css using javascript mutationObserver in Shiny. I'm using rhandsontable because we can change the width of a table element in the app, and I'm trying to pick up this change iwth the mutationObserver.
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MutationObserver code
jsCode <- "
const observer = new MutationObserver(
# this function runs when something is observed.
function(mutations){
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var i;
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tags$head(tags$script(HTML(jsCode))),
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observeEvent(input$colWidth, {
print(input$colWidth)
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}
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$(document).on('shiny:connected', function(){
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Shiny: How to change the shape and/or size of the clicked point?

I would like to change the shape and size of the clicked point in the below plot. How to achieve it? For this toy plot, I have reduced the number of points from original 100k to 2k. So, the expected solution should be highly scalable and do not deviate from the original plot i.e., all the colors before and after the update of the click point should be the same.
library(shiny)
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Val=sample(LETTERS,2000,replace=TRUE))
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ui <- fluidPage(
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sidebarLayout(
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ggplotly(p) %>% layout(height = 800, width = 800)
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d <- event_data("plotly_click")
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shinyApp(ui, server)
A related question has been asked here, but that approach of highlighting the point with a color does not work(when the number of levels of a variable is high, it is difficult to hard code a color which might be already present in the plot).
Plotly's restyle function won't help us here but we can still use the onclick event together with a little bit of JavaScript. The code has acceptable performance for 10,000 points.
We can get the point which was clicked on in JavaScript using:
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(scatterlayer is the layer where all the scatterplot elements are located,
scatter[n] is the n-th scatter plot and point[p] is the p-th point in it)
Now we just make this point a lot bigger (or whatever other shape/transformation you want):
point.setAttribute('d', 'M10,0A10,10 0 1,1 0,-10A10,10 0 0,1 10,0Z');
In order to get the possibility to revert everything, we store the unaltered info about the point together with the rest of the Plotly information:
var plotly_div = document.getElementsByClassName('plotly')[0];
plotly_div.backup = {curveNumber: data.points[0].curveNumber,
pointNumber: data.points[0].pointNumber,
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var old_point = document.getElementsByClassName('scatterlayer')[0].getElementsByClassName('scatter')[plotly_div.backup.curveNumber].getElementsByClassName('point')[plotly_div.backup.pointNumber]
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Now we can add all the code to the plotly widget.
javascript <- "
function(el, x){
el.on('plotly_click', function(data) {
var point = document.getElementsByClassName('scatterlayer')[0].getElementsByClassName('scatter')[data.points[0].curveNumber].getElementsByClassName('point')[data.points[0].pointNumber];
var plotly_div = document.getElementsByClassName('plotly')[0];
if (plotly_div.backup !== undefined) {
var old_point = document.getElementsByClassName('scatterlayer')[0].getElementsByClassName('scatter')[plotly_div.backup.curveNumber].getElementsByClassName('point')[plotly_div.backup.pointNumber]
if (old_point !== undefined) {
old_point.setAttribute('d', plotly_div.backup.d);
}
}
plotly_div.backup = {curveNumber: data.points[0].curveNumber,
pointNumber: data.points[0].pointNumber,
d: point.attributes['d'].value,
style: point.attributes['style'].value
}
point.setAttribute('d', 'M10,0A10,10 0 1,1 0,-10A10,10 0 0,1 10,0Z');
});
}"
[...]
ggplotly(p) %>% onRender(javascript)
Alternatively you could make a new SVG element based on the location of the clicked point but in the color and shape you would like.
You can try it here without R/Shiny.
//create some random data
var data = [];
for (var i = 0; i < 10; i += 1) {
data.push({x: [],
y: [],
mode: 'markers',
type: 'scatter'});
for (var p = 0; p < 200; p += 1) {
data[i].x.push(Math.random());
data[i].y.push(Math.random());
}
}
//create the plot
var myDiv = document.getElementById('myDiv');
Plotly.newPlot(myDiv, data, layout = { hovermode:'closest'});
//add the same click event as the snippet above
myDiv.on('plotly_click', function(data) {
//let's check if some traces are hidden
var traces = document.getElementsByClassName('legend')[0].getElementsByClassName('traces');
var realCurveNumber = data.points[0].curveNumber;
for (var i = 0; i < data.points[0].curveNumber; i += 1) {
if (traces[i].style['opacity'] < 1) {
realCurveNumber -= 1
}
}
data.points[0].curveNumber = realCurveNumber;
var point = document.getElementsByClassName('scatterlayer')[0].getElementsByClassName('scatter')[data.points[0].curveNumber].getElementsByClassName('point')[data.points[0].pointNumber];
var plotly_div = document.getElementsByClassName('plotly')[0];
if (plotly_div.backup !== undefined) {
var old_point = document.getElementsByClassName('scatterlayer')[0].getElementsByClassName('scatter')[plotly_div.backup.curveNumber].getElementsByClassName('point')[plotly_div.backup.pointNumber]
if (old_point !== undefined) {
old_point.setAttribute('d', plotly_div.backup.d);
}
}
plotly_div.backup = {curveNumber: data.points[0].curveNumber,
pointNumber: data.points[0].pointNumber,
d: point.attributes['d'].value,
style: point.attributes['style'].value
}
point.setAttribute('d', 'M10,0A10,10 0 1,1 0,-10A10,10 0 0,1 10,0Z');
});
<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
<div id="myDiv">

Problems with "observe" in Shiny

I am working in a ShinyApp which objective here is to create a selection based on attributes that are generated from an Excel database (the number of attributes may vary). Below is the most important part of my server.R code:
shinyServer(function(input, output, session){
seleciona_planilha <- observe({
dados = input$arquivo
if (is.null(dados))
{
return(NULL)
}
else
{
capturar = names(getSheets(loadWorkbook(dados$datapath)))
updateSelectInput(session,"planilha",choices = capturar)
}
})
carrega_dados <- reactive({
dados = input$arquivo
if (is.null(dados))
{
return(NULL)
}
else{return(read.xlsx(dados$datapath, sheetName = input$planilha))}
})
The first "observe" function above works well in order to select the correct sheet and proceed to analysis with the code below.
rotina <- reactive({
dados = carrega_dados()
tam_dados = length(dados)
pos_ini = 22
vet_comp = vector()
resultados = as.data.frame(matrix(nrow = length(seq(pos_ini,tam_dados,2)), ncol = 10))
nomes = names(dados)
cd = 4
k = 1
amostra = vector()
for(i in 1:length(dados[,1]))
{
if(dados[i,6] == 1)
{
amostra[1] = as.character(dados[i,7])
break
}
}
for(i in 1:length(dados[,1]))
{
if(dados[i,6] == 2)
{
amostra[2] = as.character(dados[i,7])
break
}
}
names(resultados) = c("Name",amostra[1], amostra[2],"NSD",
"Tau","Var(Tau)","D-Prime",
"Var(D-Prime)","IC(D-Prime)","p-value(D-Prime)")
for(i in seq(pos_ini,tam_dados,2))
{
cNSD = 0
c1 = 0
c2 = 0
for(j in 1:length(dados[,i]))
{
if(as.character(dados[j,i]) == " NSD" || as.character(dados[j,i]) == "NSD")
{
cNSD = cNSD + 1
}
if(as.character(dados[j,i]) == "1")
{
c1 = c1 + 1
}
if(as.character(dados[j,i]) == "2")
{
c2 = c2 + 1
}
}
vet_comp = c(c1,cNSD,c2)
resultados[k,1] = nomes[i]
resultados[k,2] = c1
resultados[k,3] = c2
resultados[k,4] = cNSD
resultados[k,5] = round(twoAC(vet_comp)$coefficients[1,1],cd)
resultados[k,6] = round((twoAC(vet_comp)$coefficients[1,2])^2,cd)
resultados[k,7] = round(twoAC(vet_comp)$coefficients[2,1],cd)
resultados[k,8] = round((twoAC(vet_comp)$coefficients[1,2])^2,cd)
if(vet_comp[1] != 0 && vet_comp[2] != 0 && vet_comp[3] != 0)
{
resultados[k,9] = paste("[",round(twoAC(vet_comp)$confint[,1],cd),";",
round(twoAC(vet_comp)$confint[,2],cd),"]")
}
else
{
resultados[k,9] = paste("No IC")
}
resultados[k,10] = round((twoAC(vet_comp)$p.value)/2,cd)
k = k + 1
}
return(resultados)
})
The reactive function "rotina" returns a data.frame. The first column in the data.frame are the attribute names that I would like to use in a selector.
But for some reason I don't know, when I call another "observe" function to get the attribute names and pass to the selector, it not works.
seleciona_atributo <- observe({
resultados = rotina()
atributos = resultados[,1]
updateSelectInput(session,"atributo",choices = atributos)
})
I tried to assign "resultados" as a global variable too, but with no success.
Finally, my ui.R code:
shinyUI(fluidPage(
titlePanel("2-AC Sensory Tool"),
sidebarLayout(
sidebarPanel(
fileInput('arquivo', 'Choose XLS/XLSX File',
accept=c('.xls','.xlsx')),
tags$hr(),
selectInput("planilha",label = h4("Select data sheet"),""),
tags$hr(),
selectInput("atributo",label = h4("Select attribute to generate d-prime graphic",""),
downloadButton('download', 'Download results')
),
mainPanel(
plotOutput("grafico_dp"),
plotOutput("grafico_dist"),
h4("Results Table"),
dataTableOutput("saida")
)
)
))
Thanks in advance!

Using global data in High Charts point click custom function in R Shiny

I am trying to show a different table or plot in a different div when a bar on a a bar plot is clicked. I have come this far.
server.R
library(shiny)
shinyServer(function(input,output,session) {
custom_data = # a data frame in R
barclick_func <- "#! function() {
var cats = ['100','200','3000','4000'];
var datum = [20,40,30,10];
}
$('#container_subcat').highcharts({
chart: {
type: 'column',
},
xAxis: { categories:cats },
series: [{data :datum}]
});
} !#"
output$my_plot <- renderChart2({
a <- hPlot(x="id",y="variable",data=custom_data,type="column")
a$tooltip( animation = 'true', formatter = "#! function() {return '<b>' + 'Frequency of tag_id ' + this.x + '</b>' + ' is ' + this.y;} !#")
a$plotOptions(series = list(color = '#388E8E'),column = list(dataLabels = list(enabled = T, rotation =-90, align = 'right', color = '#FFFFFF', x = 4, y = 10),
cursor = 'pointer', point = list(events = list(click = barclick_func))))
return(a)
})
})
ui.R
library(shiny)
require(rCharts)
shinyUI(fluidPage(
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "custom.css"),
tags$script(src="http://code.jquery.com/jquery-git2.min.js"),
),
titlePanel("Test"),
fluidRow(
showOutput("my_plot","highcharts")
),
div(id="container_subcat",style="min-width: 310-px; height: 400px; margin: 0 auto; margin-top:100px;")
)
))
In the above server.R script, in barclick_func() function, the data(variables cats and datum) is hardcoded. The above app works as expected when a bar is clicked, another plot pops up properly with the data.
But, if I want to use another data, that is if I have another data frame in R and want to use that data frame in barclick_func(), the console is throwing an error that the variable is not recognized and if I look at the type of that variable, it shows as 'undefined'. Can anyone suggest how to send data to the javascript function in this particular case. Ideally, my desired code is this.
server.R
library(shiny)
shinyServer(function(input,output,session) {
custom_data = # a data frame in R
custom_data2 = # another data frame in R for which I wanna shoe a plot when the bar is clicked.
barclick_func <- "#! function() {
var cats = #subsetting custom_data2 ;
var datum = #subsetting custom_data2 ;
}
$('#container_subcat').highcharts({
chart: {
type: 'column',
},
xAxis: { categories:cats },
series: [{data :datum}]
});
} !#"
output$my_plot <- renderChart2({
a <- hPlot(x="id",y="variable",data=custom_data,type="column")
a$tooltip( animation = 'true', formatter = "#! function() {return '<b>' + 'Frequency of tag_id ' + this.x + '</b>' + ' is ' + this.y;} !#")
a$plotOptions(series = list(color = '#388E8E'),column = list(dataLabels = list(enabled = T, rotation =-90, align = 'right', color = '#FFFFFF', x = 4, y = 10),
cursor = 'pointer', point = list(events = list(click = barclick_func))))
return(a)
})
})
You could try using paste to add the data to your barclick_func.
For example:
custom_data2 = data.frame(cats=c(100,200,3000,400),datum=c(20,40,30,10))
barclick_func <- paste("#! function() {
var cats = ",paste('[',paste(custom_data2$cats,collapse=','),']',sep=''),"
var datum = ",paste('[',paste(custom_data2$datum,collapse=','),']',sep=''),";
}
$('#container_subcat').highcharts({
chart: {
type: 'column',
},
xAxis: { categories:cats },
series: [{data :datum}]
});
} !#")
Should give the same barclick_func as in your hardcoded version.

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