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library(shiny)
library(shinydashboard)
library(shinyWidgets)
library(shinyExample)
toNum <- function(x, min=-Inf, max=+Inf) {
x <- suppressWarnings(as.numeric(x))
if (length(x)!=1) return(NA)
if(is.na(x)) return(NA)
if (x<min) return(NA)
if (x>max) return(NA)
x
}
library("dbscan")
library("rio")
x <- scale(import("BANK2.sav"))
ui <- dashboardPage(
dashboardHeader(title="", titleWidth=, disable=),
dashboardSidebar(collapsed=, width=, disable=,
uiOutput("outputId"="UIeps"),
uiOutput("outputId"="UIpts"),
shiny::tags$div(align="center",
shiny::tags$hr(),
shiny::tags$a(href = 'https://github.com/sigbertklinke/shinyExample', 'Created with shinyExample'),
shiny::tags$br(),
shiny::tags$a(target="_blank", href="https://www.wihoforschung.de/de/flipps-1327.php", 'Supported by BMBF')
)
),
dashboardBody(
shiny::plotOutput("outputId"="plot",
"width"="100%",
"height"="400px",
"inline"=FALSE)
)
)
server <- function(input, output, session) {
seed <- list(inBookmark=FALSE)
onBookmark(function(state) {
state$seed <- seed
})
onRestore(function(state) {
seed <- state$seed
seed$inBookmark <- TRUE
})
onRestored(function(state) {
seed$inBookmark <- FALSE
})
onStop(function() {
# if (isLocal()) {
# count <- getMMstat('lang', 'stats', 'count')
# cat(sprintf('gettext("%s"); // %.0f\n', names(count), count))
# }
})
value <- function(val) {
param <- substitute(val)
if(param=="input$eps") { v<-toNum(val, min=0, max=1); if(is.na(v)) return(0.5) else return(v) }
if(param=="input$pts") { v<-toNum(val, min=2, max=10); if(is.na(v)) return(5) else return(v) }
return(val)
}
observe({
sel <- value(isolate(input$eps))
shiny::updateSliderInput("session"=session,
"inputId"="eps",
"label"=("Core distance"),
"value"=sel,
"min"=0,
"max"=1,
"step"=0.01)
})
observe({
sel <- value(isolate(input$pts))
shiny::updateSliderInput("session"=session,
"inputId"="pts",
"label"=("Minimal neighbour "),
"value"=sel,
"min"=2,
"max"=10,
"step"=1)
})
output$plot <- shiny::renderPlot({
#/home/sigbert/syncthing/projekte/R/shinyApp/inst/app/dbscan/dbscan2.R
# shinyApp/inst/app/dbscan/dbscan2.R
db <- dbscan(x[,c(4,6)], value(input$eps), value(input$pts))
col <- c('grey', rainbow(max(db$cluster)))
plot(x[,c(4,6)], col=col[1+db$cluster], pch=19, asp=TRUE)
})
output$UIeps<- renderUI({
shiny::sliderInput("inputId"="eps",
"label"=("Core distance"),
"min"=0,
"max"=1,
"value"=0.5,
"step"=0.01,
"round"=FALSE,
"ticks"=TRUE,
"animate"=FALSE,
"width"=NULL,
"sep"=",",
"pre"=NULL,
"post"=NULL,
"timeFormat"=NULL,
"timezone"=NULL,
"dragRange"=TRUE)
})
output$UIpts<- renderUI({
shiny::sliderInput("inputId"="pts",
"label"=("Minimal neighbour "),
"min"=2,
"max"=10,
"value"=5,
"step"=1,
"round"=FALSE,
"ticks"=TRUE,
"animate"=FALSE,
"width"=NULL,
"sep"=",",
"pre"=NULL,
"post"=NULL,
"timeFormat"=NULL,
"timezone"=NULL,
"dragRange"=TRUE)
})
}
shinyApp(ui, server)
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