inst/shinyapp/ui/filter.R

In gongyh/RamanD2O: RamanD2O: an R/Shiny app designed for the analysis of cellular Ramanome data

# Filter tab
tabItem(
  tabName = "fl",
  h2("Filter"),
  br(),
  fluidRow(
    box(
      title = "Settings", status = "info",
      solidHeader = TRUE, collapsible = FALSE,
      column(
        12,
        fluidRow(
          column(4, uiOutput("hs_select_for_filter")),
          column(4,
                 withBusyIndicatorUI(actionButton("filter",
                                                  "Filter",
                                                  class = "btn-success")),
                 class = "top25"),
          column(4,
                 p("All selected filters will be performed sequentially."),
                 class = "top25")
        ),
        fluidRow(
          column(2, numericInput("filter_min", "Min",
                                 min = 0, max = 4000, step = 1,
                                 value = 0, width = "100%")),
          column(8, sliderInput("filter_range",
                                " Selecting Wavelength Ranges for Filtering:",
                                min = 0, max = 4000, value = c(0, 4000),
                                step = 1, dragRange = FALSE, width = "100%")
          ),
          column(2, numericInput("filter_max", "Max", min = 0, max = 4000,
                                 step = 1, value = 4000, width = "100%"))
        ),
        fluidRow(
          column(4, checkboxInput("filter_low", "By lowest intensity",
                                  value = TRUE), class = "top25"),
          column(4, numericInput("lowest", "Value", 0)),
          column(4, p("Filter spectra with too low signal."), class = "top25")
        ),
        fluidRow(
          column(4, checkboxInput("filter_high", "By highest intensity"),
                 class = "top25"),
          column(4, numericInput("highest", "Value", 100000)),
          column(4, p("Filter spectra with too high signal."), class = "top25")
        ),
        fluidRow(
          column(4, checkboxInput("filter_sd", "By standard deviations"),
                 class = "top25"),
          column(4, numericInput("n_sd", "n", 5, min = 1)),
          column(4, p("Filter outliers which are outside n*sd."),
                 class = "top25")
        )
      )
    ),
    box(
      title = "Notes", status = "info", solidHeader = TRUE, collapsible = FALSE,
      column(
        12,
        p("1. Select each checkbox to enable corresponding filter criteria."),
        p("2. Outlier filter: outside mean +- n*sd."),
        p("3. Choose the target spectra collection
          from the dropdown selector."),
        p("4. Row of the spectra table (bottom left) can be selected
          to visual the spectrum (bottom right).")
      )
    )
  ),
  fluidRow(
    box(
      title = "Spectra Table", status = "warning",
      solidHeader = TRUE, collapsible = TRUE,
      column(12, DTOutput("after_filter", height = "400px") %>% withSpinner())
    ),
    box(
      title = "Spectra Figure", status = "warning",
      solidHeader = TRUE, collapsible = TRUE,
      fluidRow(
        column(1,
               withBusyIndicatorUI(actionButton("prev_rm",
                                                label = icon("arrow-up"),
                                                class = "btn-success")),
               class = "top25", style = "text-align: center;"),
        column(1,
               withBusyIndicatorUI(actionButton("next_rm",
                                                label = icon("arrow-down"),
                                                class = "btn-success")),
               class = "top25", style = "text-align: center;"),
        column(2,
               withBusyIndicatorUI(actionButton("remove",
                                                "Remove",
                                                class = "btn-success")),
               class = "top25", style = "text-align: center;"),
        column(8,
               p("Caution: you use this button to manually remove the
                 selected spectrum, need double check!"),
               class = "top25")
      ),
      hr(),
      column(12, plotlyOutput("after_filter_plot") %>% withSpinner())
    )
  )
)