R/fitness_alignments.R

In fmannhardt/pm4py: Interface to the 'PM4py' Process Mining Library

# FITNESS ALIGNMENTS ------------------------------------------------------
#' @title Apply the __fitness__ alignments algorithm between a log and a process model
#'
#' @description The calculation of the replay fitness aim to calculate how much of the behavior in the log is admitted by the process model.
#' @param marked_petrinet A Marked Petrinet as defined by petrinetR, e.g. the output of [discover_inductive] or [discover_alpha].
#' @inheritParams discover_inductive
#' @return fitness alignments.
#' @examples
#' \dontrun{
#' library(pm4py)
#' library(eventdataR)
#'
#' model <- discover_alpha(patients)
#' fitness_alignments(patients, model)
#'
#' }
#' @export
fitness_alignments <- function(log,
                               marked_petrinet,
                               multi_processing = FALSE,
                               convert = TRUE) {
  UseMethod("fitness_alignments")
}

#' @export
fitness_alignments.log <- function(log,
                                        marked_petrinet,
                                        multi_processing = FALSE,
                                        convert = TRUE) {
  pm4py_conformance <- reticulate::import("pm4py.conformance", convert = convert)

  if(n_events(log) > n_activity_instances(log)) {
    cli::cli_warn("Activity instances with multiple events found in log: using only complete events.")


    if("eventlog" %in% class(log)) {
      log %>%
        filter(.data[[lifecycle_id(log)]] == "complete") -> log
    }
  }

  log %>%
    mutate(across(activity_id(log), as.character)) -> log
  # prepare arguments for pm4py module
  py_log <- r_to_py(log)
  py_pn <- as_py_value(marked_petrinet$petrinet)
  im <- as_pm4py_marking(marked_petrinet$initial_marking, py_pn)
  fm <- as_pm4py_marking(marked_petrinet$final_marking, py_pn)
  activity_key <- bupaR::activity_id(log)
  timestamp_key <- bupaR::timestamp(log)
  case_id_key <- bupaR::case_id(log)
  multi_processing <- r_to_py(multi_processing)

  pm4py_conformance$fitness_alignments(log = py_log, petri_net = py_pn,
                                       initial_marking = im,
                                       final_marking = fm,
                                       activity_key = activity_key,
                                       timestamp_key = timestamp_key,
                                       case_id_key = case_id_key,
                                       multi_processing = multi_processing)
}