In rpkgs/rgee2: Extra functions for R Google Earth Engine

knitr::opts_chunk$set(echo = TRUE)

This R Markdown document is made interactive using Shiny. Unlike the more traditional workflow of creating static reports, you can now create documents that allow your readers to change the assumptions underlying your analysis and see the results immediately.

To learn more, see Interactive Documents.

Inputs and Outputs

You can embed Shiny inputs and outputs in your document. Outputs are automatically updated whenever inputs change. This demonstrates how a standard R plot can be made interactive by wrapping it in the Shiny renderPlot function. The selectInput and sliderInput functions create the input widgets used to drive the plot.

library(shiny)
library(leaflet)
library(RColorBrewer)

ui <- bootstrapPage(
  tags$style(type = "text/css", "html, body {width:100%;height:100%}"),
  leafletOutput("map", width = "100%", height = "100%"),
  absolutePanel(top = 10, right = 10,
    sliderInput("range", "Magnitudes", min(quakes$mag), max(quakes$mag),
      value = range(quakes$mag), step = 0.1
    ),
    selectInput("colors", "Color Scheme",
      rownames(subset(brewer.pal.info, category %in% c("seq", "div")))
    ),
    checkboxInput("legend", "Show legend", TRUE)
  )
)

server <- function(input, output, session) {

  # Reactive expression for the data subsetted to what the user selected
  filteredData <- reactive({
    quakes[quakes$mag >= input$range[1] & quakes$mag <= input$range[2],]
  })

  # This reactive expression represents the palette function,
  # which changes as the user makes selections in UI.
  colorpal <- reactive({
    colorNumeric(input$colors, quakes$mag)
  })

  output$map <- renderLeaflet({
    # Use leaflet() here, and only include aspects of the map that
    # won't need to change dynamically (at least, not unless the
    # entire map is being torn down and recreated).
    leaflet(quakes) %>% addTiles() %>%
      fitBounds(~min(long), ~min(lat), ~max(long), ~max(lat))
  })

  # Incremental changes to the map (in this case, replacing the
  # circles when a new color is chosen) should be performed in
  # an observer. Each independent set of things that can change
  # should be managed in its own observer.
  observe({
    pal <- colorpal()

    leafletProxy("map", data = filteredData()) %>%
      clearShapes() %>%
      addCircles(radius = ~10^mag/10, weight = 1, color = "#777777",
        fillColor = ~pal(mag), fillOpacity = 0.7, popup = ~paste(mag)
      )
  })

  # Use a separate observer to recreate the legend as needed.
  observe({
    proxy <- leafletProxy("map", data = quakes)

    # Remove any existing legend, and only if the legend is
    # enabled, create a new one.
    proxy %>% clearControls()
    if (input$legend) {
      pal <- colorpal()
      proxy %>% addLegend(position = "bottomright",
        pal = pal, values = ~mag
      )
    }
  })
}

shinyApp(ui, server)