library(shiny)
library(shinydashboard)
source("../R/function.R")
source("../R/colorPicker.R")
source("../R/columnSelector.R")
source("../R/transformation.R")
source("../R/global_cor_heatmap.R")
source("../R/limit.R")
source("../R/global.R")
source("../R/clarion.R")
# test data
data <- data.table::as.data.table(mtcars, keep.rowname = "id")
# create metadata
metadata <- data.table::data.table(names(data), level = c("feature", rep("sample", 7), rep("condition", 4)))
names(metadata)[1] <- "key"
clarion <- Clarion$new(data = data, metadata = metadata)
#####
ui <- dashboardPage(
header = dashboardHeader(),
sidebar = dashboardSidebar(
numericInput(inputId = "width", label = "width in cm", value = 0, min = 0),
numericInput(inputId = "height", label = "height in cm", value = 0, min = 0),
sliderInput(inputId = "scale", label = "scale plot", value = 1, min = 1, max = 10)
),
dashboardBody(
fluidPage(
global_cor_heatmapUI("id")
)
)
)
server <- function(input, output) {
table <- shiny::callModule(global_cor_heatmap, "id", clarion = clarion, plot.method = "static", width = reactive(input$width), height = reactive(input$height), scale = reactive(input$scale))
shiny::observe({
print(table())
})
}
shinyApp(ui = ui, server = server)
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