Animate Process Maps

library(bupaverse)
library(processanimateR)

Here, we use the patients event log provided by the eventdataR package.

A basic animation with static color and token size:

animate_process(patients)

Default token color, size, or image can be changed as follows:

animate_process(patients, mapping = token_aes(size = token_scale(12), shape = "rect"))
animate_process(patients, mapping = token_aes(color = token_scale("red")))

The example animation on the top of this site:

animate_process(patients, mode = "relative", jitter = 10, legend = "color",
  mapping = token_aes(color = token_scale("employee", 
    scale = "ordinal", 
    range = RColorBrewer::brewer.pal(7, "Paired"))))

Tokens can also be assigned images, for example:

animate_process(patients,
   mapping = token_aes(shape = "image",
    size = token_scale(10),
    image = token_scale("https://upload.wikimedia.org/wikipedia/en/5/5f/Pacman.gif")))

Use external data

It is possible to use a secondary data frame to determine the aesthetics of tokens regardless of the timestamps at which activities occurred. This could be useful if some measurements were taken throughout a process, but the measurement event itself should not be included in the process map.

For example, the lacticacid measurements of the sepsis data set could be used in that way:

library(processanimateR)
library(dplyr)
library(bupaR)
# Extract only the lacticacid measurements
lactic <- sepsis %>%
    mutate(lacticacid = as.numeric(lacticacid)) %>%
    filter_activity(c("LacticAcid")) %>%
    as.data.frame() %>%
    select("case" = case_id, 
            "time" =  timestamp, 
            value = lacticacid) # format needs to be 'case,time,value'

# Remove the measurement events from the sepsis log
sepsisBase <- sepsis %>%
    filter_activity(c("LacticAcid", "CRP", "Leucocytes", "Return ER",
                      "IV Liquid", "IV Antibiotics"), reverse = T) %>%
    filter_trace_frequency(percentage = 0.95)

# Animate with the secondary data frame `lactic`
animate_process(sepsisBase, 
                mode = "relative", 
                duration = 300,
                legend = "color", 
                mapping = token_aes(color = token_scale(lactic, 
                                                        scale = "linear", 
                                                        range = c("#fff5eb","#7f2704"))))

processanimateR animation can be also used interactively as part of a (Shiny) web-application. Here, an example application that expects attributes are of an appropriate data type and automatically chooses appropriate color scales is given. We first define a function ianimate_process() that defines our Shiny application as follows:

Shiny

library(processanimateR)
library(shiny)
library(shinycssloaders)
ianimate_process <- function(eventlog, min.time = 30, max.time = 600, default.time = 60) {

  ui <- function(request) {
    fluidPage(
      tags$head(tags$style("#process{height:90vh !important;}")),
      titlePanel("Hello processanimateR!"),

      sidebarLayout(

        sidebarPanel(
          width = 2,
          sliderInput("duration", "Animation duration", min.time, max.time, default.time),
          selectInput("type", "Animation type", c("relative", "absolute"), "relative"),
          selectInput("sizeAttribute", "Size attribute", c("none", colnames(eventlog)), "none"),
          selectInput("colorAttribute", "Color attribute", c("none", colnames(eventlog)), "none"),
          selectInput("orientation", "Orientation", c("horizontal"="LR", "vertical"="TB"), "horizontal"),
          h4("Selected cases"),
          textOutput("token_selection"),
          h4("Selected activities"),
          textOutput("activity_selection")
        ),

        mainPanel(
          width = 10,
          shinycssloaders::withSpinner(processanimaterOutput("process"))
        )
      )
    )
  }

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

    data <- reactive({

      if (input$colorAttribute != "none") {
        attr <- rlang::sym(input$colorAttribute)
        val <- eventlog %>% pull(!!attr)
        if (!(is.character(val) || is.factor(val))) {
          warning("Trying to use a numeric attribute for the token color!")
        }
      }

      if (input$sizeAttribute != "none") {
        # This only works for numeric attributes
        attr <- rlang::sym(input$sizeAttribute)
        val <- eventlog %>% pull(!!attr)
        if (!is.numeric(val)) {
          warning("Trying to use a non-numeric attribute for the token size!")
        }
      }

      eventlog

    })

    output$token_selection <- renderText({

      paste0(input$process_tokens, ",")

    })

    output$activity_selection <- renderText({

      paste0(input$process_activities, ",")

    })

    output$process <- renderProcessanimater(expr = {
      graph <- processmapR::process_map(data(), render = F)
      model <- DiagrammeR::add_global_graph_attrs(graph, attr = "rankdir", value = input$orientation, attr_type = "graph")
      if (input$sizeAttribute != "none" && input$colorAttribute != "none") {
        animate_process(data(), model,
                        mode = input$type,
                        legend = "color",
                        mapping = token_aes(color = token_scale(input$colorAttribute, scale = "ordinal", 
                                                                range = RColorBrewer::brewer.pal(5, "YlOrBr")),
                                            size = token_scale(input$sizeAttribute, scale = "linear", range = c(6,10))),
                        duration = input$duration)
      } else if (input$sizeAttribute != "none") {
        animate_process(data(), model,
                        mode = input$type,
                        legend = "size",
                        mapping = token_aes(size = token_scale(input$sizeAttribute, scale = "linear", range = c(6,10))),
                        duration = input$duration)

      } else if (input$colorAttribute != "none") {
        animate_process(data(), model,
                        mode = input$type,
                        legend = "color",
                        mapping = token_aes(color = token_scale(input$colorAttribute, scale = "ordinal", range = RColorBrewer::brewer.pal(5, "YlOrBr"))),
                        duration = input$duration)
      } else {
        animate_process(data(), model,
                        mode = input$type,
                        duration = input$duration)
      }

    })

  }

  shinyApp(ui, server, options = list(height = 500))

}

Then, the application can be, for example, launched by calling:

library(eventdataR)
library(edeaR)
library(dplyr)
ianimate_process(sepsis %>%
  filter_trace_frequency(percentage = 0.2) %>%
  filter_activity(c("Return ER"), reverse = T) %>%
  # we fix the datatype of some of the attributes to allow proper rendering of the token color
  # the token size option currently only support numeric attributes
  mutate_at(c("lacticacid", "leucocytes", "crp", "age"), as.numeric) %>%
  mutate_at(c("disfuncorg", "sirscriteria2ormore", "infectionsuspected"), as.logical))

Selections

Selections made in the processanimateR animation can be used as input by Shiny applications. Here a simple example in which a Shiny module is created that renders the case identifiers of selected tokens and the identifiers and names of selected activities:

library(shiny)
library(processanimateR)
library(eventdataR)
library(jsonlite)

shinyAnimation <- function(eventlog, min.time = 30, max.time = 600, default.time = 60) {

  # Define Shiny Module
  animationUI <- function(id, title) {
    ns <- NS(id)
    tagList(
      h2(title),
      processanimaterOutput(ns("process")),
      h4("Selected cases"),
      textOutput(ns("token_selection")),
      h4("Selected activities"),
      textOutput(ns("activity_selection")),
      h4("Current time"),
      textOutput(ns("activity_time"))
    )
  }

  animation <- function(input, output, session, ...) {

    output$token_selection <- renderText({
      if (is.null(input$process_tokens)) {
        "None"
      } else {
        paste0(input$process_tokens, collapse = ",")
      }
    })

    output$activity_selection <- renderText({
      if (is.null(input$process_activities)) {
        "None"
      } else {
        activities <- jsonlite::fromJSON(input$process_activities)
        paste0("(", activities$id, ",", activities$activity, ")", collapse = ",")
      }
    })
    
    output$activity_time <- renderText({
      if (is.null(input$process_time)) {
        "0"
      } else {
        input$process_time
      }
    })    

    output$process <- renderProcessanimater(expr = {
      animate_process(eventlog, ...)
    })

  }

  ui <- fluidPage(
    animationUI("module1", "Relative"),
    animationUI("module2", "Absolute")
  )

  # Two animations
  server <- function(input, output, session) {
    callModule(animation, "module1", mode = "relative")
    callModule(animation, "module2")
  }

  shinyApp(ui, server, options = list(height = 500))

}

shinyAnimation(patients)

User defined bins

Contributed by Dominic Rowney.

It is possible to change the aesthetics of tokens based on the timestamp of the animation.

For example, the number of days a ‘patient’ has been in the system.

# Libraries ---------------------------------------------------------------
library(dplyr)            ##pipes
library(tidyr)            ##tidy data, partcularly the crossing() function
## 
## Attaching package: 'tidyr'
## The following object is masked from 'package:processcheckR':
## 
##     contains
library(lubridate)        ##date time manipulation
## 
## Attaching package: 'lubridate'
## The following objects are masked from 'package:base':
## 
##     date, intersect, setdiff, union
library(bupaR)            ##buisness process analytics
library(processanimateR)  ##animates process


# Create performance time flags ------------------------------------------------
my_flags <- data.frame(value = c(0,2,4,8,16)) %>% 
            mutate(day = days(value)) #convert numeric value into days

This will change the colour of the token at 0, 2, 4, 8, and 16 days.

crossing() joins the cases from patients to my_flags and creates all possible combinations.

# Create timestamps of flags ----------------------------------------------

my_timeflags <- patients %>% 
                cases %>%
                crossing(my_flags) %>% ##similar to a SQL outer join
                mutate(time = start_timestamp + day) %>% 
                filter(time <= complete_timestamp) %>% 
                select("case" = patient,time,value) ##must be case, time, value

The data for the token_scale() must have the column headings ‘case, time, value’.

Without setting domain = my_flags$value the flags follow alphabetic order (e.g. 0, 16, 2, 4, 8) rather than the numeric order we want. See d3-legend for further information.

# Animate process ---------------------------------------------------------

patients %>%
  animate_process(mode ="absolute",
                  jitter=10,
                  legend = "color", 
                  mapping = token_aes(
                    color = token_scale(my_timeflags
                                        , scale = "ordinal"
                                        , domain = my_flags$value
                                        , range = rev(RColorBrewer::brewer.pal(5,"Spectral"))
                    )))