In wfeijen/Uitbreiden_ProcessMap: Construct Process Maps Using Event Data

knitr::opts_chunk$set(echo = TRUE)

#Initialisatie Let op de slashes / staan anders dan Windows ze zet \.
eventLogName <- "W:/Uitbreiden_ProcessMap/LogPatientMining.csv"
#eventLogName <- "W:/Uitbreiden_ProcessMap/Motivation.csv"

library(bupaR)
library(edeaR)
library(processmonitR)
library(plotluck)
library(DiagrammeR)
library(data.table)
#library(DiagrammeRsvg)

csvLog<-read.table(eventLogName,header = TRUE, sep = ";",na = c("n.v.t.","onbekend",""))
csvLog$status = "complete"
csvLog$activity_instance = 1:nrow(csvLog)
csvLog$timestamp<-as.POSIXct(strptime(csvLog$Timestamp, "%d-%m-%Y"))


kolomNamen<-colnames(csvLog)
csvLog$activity_instance = 1:nrow(csvLog)
csvLog$status<-"start"
csvLog$SentimentGem <- as.numeric(csvLog$Waardering)

#Gevonden kolomkoppen:
#colnames(csvLog)

#Omzetten naar een processmining Log 
if (!("Werknemer" %in% colnames(csvLog))){csvLog$Werknemer<-NA}
eventLog.Base<-eventlog(csvLog,
        case_id = "Voornaam",
        activity_id = "Mapping",
        activity_instance_id = "activity_instance",
        lifecycle_id = "status",
        timestamp = "timestamp",
        resource_id = "SentimentGem"
    )

Map met SentimentGem

De getallen en de kleuren in de activiteiten geven het gemiddelde sentiment weer. De getallen, kleuren en dikte van de lijnen geven het aantal malen weer dat dat pad doorlopen is.

fileName <- "SentimentGem"
agregationInst = list( enriched_frequency(value = "absolute", columnName = "aantal"),enriched_column_aggregate( FUN = mean, columnNameIn = "SentimentGem", columnNameOut = "SentimentGem", edgeOperation = "to") )
map<-enriched_process_map(eventLog.Base, aggregationInstructions = agregationInst )
map <- map %>%
    processmapR::color_activities( column = "SentimentGem",
                      colorCaption = "black",
                      colorUpperbound = "darkseagreen1",
                      colorLowerbound = "lightsalmon1") %>%
    label_activities(columns =c("activity_name","SentimentGem")) %>%
    color_transitions(column = "aantal",
          colorCaption = "black",
          colorUpperbound = "gray0",
          colorLowerbound = "gray50") %>%
    label_transitions(columns = c("aantal")) 

x<- get_node_df(map)

map %>% export_graph(file_name = "Z:/Dump/SentimentGem.svg",  file_type = "SVG")