library(shiny)
library(plotly)
library(ggplot2)
library(ggQC)
# https://www.brodrigues.co/blog/2018-02-16-importing_30gb_of_data/
# scara0 <- read_delim("IoT_Predictive_Maintenance_Demo/scara0","\t", escape_double = FALSE, trim_ws = TRUE)
## why class(scara0) "tbl_df"     "tbl"        "data.frame"?

# https://github.com/IndrajeetPatil/ggstatsplot
# subplots ----------------------------------------------------------------

rand <- function() {
  # set.seed(0)
  rnorm(1, mean = 5,sd=3 )
}

ui <- fluidPage(
  # includeCSS("styles.css"),

  headerPanel(h1("Scara Streams", align = "center")),
  br(),
  div(actionButton("button", "Traces"), align = "center"), #Traces
  br(),
  div(plotlyOutput("plot"), id='graph')
)

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

  p <- plot_ly(
    y = c(rand(),rand(),rand()),
    type = 'scatter',
    mode = 'lines',
    line = list(
      color = '#25FEFD',
      width = 3
    )
  ) %>%
    layout(
      yaxis = list(range = c(0,30))
    )

  pp <- plot_ly(
    y = c(rand(),rand(),rand()),
    type = 'scatter',
    mode = 'lines',
    line = list(
      color = '#636EFA',
      width = 3
    )
  ) %>%
    layout(
      yaxis = list(range = c(0,30))
    )

  ppp <- plot_ly(
    y = c(rand(),rand(),rand()),
    type = 'scatter',
    mode = 'lines',
    line = list(
      color = 'brown',
      width = 3
    )
  ) %>%
    layout(
      yaxis = list(range = c(0,30))
    )
  
  # pppp <- plot_ly(
  #   y = c(rand(),rand(),rand()),
  #   type = 'scatter',
  #   mode = 'lines',
  #   line = list(
  #     color = 'RED',
  #     width = 3
  #   )
  # ) %>%
  # 
  
  pppp <- 
    ggplot(c(rand(),rand(),rand()), aes(x = Run_Number, y = Value)) + #init ggplot
    geom_point() + geom_line() + #add the points and lines
    stat_QC(method = "XmR", #specify QC charting method
            auto.label = T, # Use Autolabels
            label.digits = 2, #Use two digit in the label
            show.1n2.sigma = T  #Show 1 and two sigma lines
    ) +  
    stat_QC(method="mR") +
    scale_x_continuous(expand =  expand_scale(mult = .15)) %>%
    layout(
      yaxis = list(range = c(0,30))
    )

  

  # pppp<-ggplot(rand, aes(x = Cycle, y = rand, group = 1, color=mold_cell)) +
  #   stat_summary(fun.y = mean, geom = "point") +
  #   stat_summary(fun.y = mean, geom = "line") +
  #   stat_QC() + stat_QC_labels() +
  #   # Show Individuals
  #   geom_point(alpha= 1/2) +
  #   stat_QC(n=1, color.qc_limits = "orange") +
  #   stat_QC_labels(n=1, color.qc_limits = "orange")


  
  
  s <- subplot(p,pp,ppp,pppp, nrows = 4)

  output$plot <- renderPlotly(s)

  observeEvent(input$button, {
    while(TRUE){
      Sys.sleep(1)
      plotlyProxy("plot", session) %>%
        plotlyProxyInvoke("extendTraces", list(y=list(list(rand()), list(rand()),list(rand()),list(rand()))),list(0,1,2,3))
    }
  })

}


shinyApp(ui, server)