R/city_count.R

In zappingseb/stravachaser: Visualize STRAVA city data

#' UI function to generate a segment overview per city
#' 
#' @param id ID
#' @export
#' 
cityCountUI <- function(id) {
  # Create a namespace function using the provided id
  ns <- NS(id)
  
  mytag <- 
    div(class="city count",
        barChartOutput(
          id = ns("count_compare"),
          label = "# of segments per city"
        )# barChartOutput
  )#div
  
  fluidRow(
    tags$h2("Selected Segments"),
    column(12,attachstravavisDep(tag = mytag)),
    column(12,div(style="height:2em")),
    column(12,
           
        tags$label("length of segment (Average)"),
        div(class="city count withhover",
                  
        # Send out a value jsValue to show hide the histograms inside the wrapper          
        onClick=paste0("Shiny.onInputChange('",ns('jsValue'),"',Math.random());"),
        barChartOutput(
          ns("count_length")
        )# plotOutput
       
    )),#div #column
    column(12,HTML("Click the bar for a detailed distribution")),
    column(12,div(style="height:5em")),
    div(id=ns("city_hist_wrapper"),class="count wrapper",style="display:none",
        column(6,cityhistUI(ns("city_hist1"))),
        column(6,cityhistUI(ns("city_hist2")))
    )#div
  )
}

#' Server function of city_count module
#' 
#' This module shows how many segments can be seen for each city
#' It contains a plot for the average length of a segment.
#' Additionally it contains the \link{city_hist} module twice
#' to show the histogram of the segment length for each city.
#' 
#' @param input shiny input object
#' @param output shiny output object
#' @param session shiny session 
#' 
#' @param city_data \code{reactive} representing strava crawled data from at
#'  least two different cities
#'  
#' @importFrom dplyr group_by summarise
#' @importFrom jsonlite toJSON
#' @importFrom rlang .data
#'  
city_count <- function(input, output, session, city_data=NULL) {
  
  
  # Left right plot of the # of segments
  output$count_compare <-renderBarChart({
      city_data_sets <- city_data()
      data <- city_data_sets %>% dplyr::group_by(.data$city) %>% dplyr::summarise(n = dplyr::n())
      return(jsonlite::toJSON(
          list(left  = round(data$n[1],3),
               right = round(data$n[2],3),
               unit  = '',
               round = 1
          )
        ))
  })
  
  # left right plot of the average length of a segment
  output$count_length <- renderBarChart(
    {
      city_data_sets <- city_data()
      data <- city_data_sets %>% dplyr::group_by(.data$city) %>% dplyr::summarise(n = mean(as.numeric(.data$distance)/1000,na.rm=T))
      return(jsonlite::toJSON(
        list(left  = round(data$n[1],3),
             right = round(data$n[2],3),
             unit  = 'km',
             round = 100
        )
      ))
      
    }
    
  )
  
  # Upon JS Value show or hide the histograms of the segment length
  observeEvent(input$jsValue, {
    
    toggle("city_hist_wrapper")  # toggle is a shinyjs function
    Sys.sleep(0.05)
   
    callModule(city_hist,"city_hist1",which_id = 1, city_data = city_data)
    callModule(city_hist,"city_hist2",which_id = 2, city_data = city_data)
    Sys.sleep(0.1)
    shinyjs::runjs('
                   $(window).scrollTop($(".count.wrapper").offset().top+$(".count.wrapper").children().height()+$(".count.wrapper").height())
                   ')
  })
}