R/hit_lit_ratio.R

In Toniiiio/biketrainr:

dont_run <- function(shiny, ggplot2, hit_sec, as.numeric, as.Date, ride_duration_sec, total_duration_sec, week_load_total, week_load_hit, week_load_lit, hit_ratio, unique, variable, letters, value) {
  library(shiny)
  library(ggplot2)

  source("R/hit_lit_ratio.R")

  names(hit_sec) %>% as.numeric %>% as.Date()
  hit_sec

  week_nr <- format(as.Date("2021-01-01"), "%U") %>% as.numeric

  date <- names(hit_sec) %>% as.numeric %>% as.Date
  week <- data.frame(
    date,
    hit_sec,
    ride_duration_sec,
    total_duration_sec
  )
  week
  week$week_nr <- format(as.Date(week$date), "%U") %>% as.numeric
  week %<>% group_by(week_nr) %>% mutate(week_load_total = sum(ride_duration_sec)/3600)
  week %<>% group_by(week_nr) %>% mutate(week_load_hit = sum(hit_sec)/3600)
  week %<>% group_by(week_nr) %>% mutate(week_load_lit = week_load_total - week_load_hit)
  week

  week %<>% mutate(hit_ratio = week_load_hit/week_load_total*100)
  week

  week_aggr <- week %>% select(week_nr, week_load_hit, week_load_lit, hit_ratio) %>% unique
  week_aggr_long <- melt(week_aggr, id.vars = c("week_nr", "hit_ratio"))

  # display text only for hit
  week_aggr_long %<>%
    mutate(hit_ratio = ifelse(variable == "week_load_hit", paste0(round(hit_ratio, 0), "% HIT"), paste0(100 - round(hit_ratio, 0), "% LIT")))


  ui <- fluidPage(
    fluidRow(
      column(6,
             plotOutput("plot1", click = "plot1_click")
      ),
      column(5,
             uiOutput("text")
      )
    )
  )

  server <- function(input, output) {
    global <- reactiveValues(toHighlight = rep(FALSE, length(letters$word)),
                             selectedBar = NULL)

    observeEvent(eventExpr = input$plot1_click, {
      week <- round(input$plot1_click$x)
      print(week_nr)
      print(input$plot1_click$y)

      y <- input$plot1_click$y
      week_sel <- week_aggr %>% filter(week_nr == week)
      week_sel
      is_lit <- y > 0 & y <= week_sel$week_load_lit
      is_hit <- y > week_sel$week_load_lit & y <= week_sel$week_load_hit + week_sel$week_load_lit
      print(is_hit)
      print(is_lit)
    })

    output$plot1 <- renderPlot({
      ggplot(week_aggr_long, aes(fill = variable, y = value, x = week_nr), label = hit_ratio) +
        geom_bar(position = "stack", stat = "identity") +
        geom_text(aes(label = hit_ratio), size = 3, position = position_stack(vjust = 0.5))
    })

    output$text <- renderUI({
      req(global$selectedBar)
      textInput(inputId = "label", label = "selected text:", value = global$selectedBar)
    })
  }
  shinyApp(ui, server)


  # volume, HIT, HIT Ratio, Consistency
  # LIT really LIT?
  # low TSS before HIT?
  # https://v1.nitrocdn.com/IAEZpQbHvRqkjIDrVgmeAoKybhOCdsVs/assets/static/optimized/rev-5423573/wp-content/uploads/2018/03/seiler-hierarchy-of-endurance-training-needs.jpg

  # 25 < Volume > 7
}