process discovery, conformance checking
MiLin
Discover Process Models With the Heuristics Miner
library(heuristicsmineR)
library(eventdataR)
library(tidyverse)## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──## ✓ ggplot2 3.3.5 ✓ purrr 0.3.4
## ✓ tibble 3.1.3 ✓ dplyr 1.0.7
## ✓ tidyr 1.1.3 ✓ stringr 1.4.0
## ✓ readr 2.1.2 ✓ forcats 0.5.1## Warning: package 'readr' was built under R version 4.1.2## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()library(petrinetR)
patients %>% head()## Log of 6 events consisting of:
## 1 trace
## 6 cases
## 6 instances of 1 activity
## 1 resource
## Events occurred from 2017-01-02 11:41:53 until 2017-01-04 16:07:47
##
## Variables were mapped as follows:
## Case identifier: patient
## Activity identifier: handling
## Resource identifier: employee
## Activity instance identifier: handling_id
## Timestamp: time
## Lifecycle transition: registration_type
##
## # A tibble: 6 × 7
## handling patient employee handling_id registration_type time
## <fct> <chr> <fct> <chr> <fct> <dttm>
## 1 Registration 1 r1 1 start 2017-01-02 11:41:53
## 2 Registration 2 r1 2 start 2017-01-02 11:41:53
## 3 Registration 3 r1 3 start 2017-01-04 01:34:05
## 4 Registration 4 r1 4 start 2017-01-04 01:34:04
## 5 Registration 5 r1 5 start 2017-01-04 16:07:47
## 6 Registration 6 r1 6 start 2017-01-04 16:07:47
## # … with 1 more variable: .order <int>Dependency graph and matrix
dependency_matrix(patients)## consequent
## antecedent Blood test Check-out Discuss Results End
## Blood test 0.0000000 0.0000000 0.0000000 0.0000000
## Check-out 0.0000000 0.0000000 0.0000000 0.9979716
## Discuss Results 0.0000000 0.9979716 0.0000000 0.0000000
## End 0.0000000 0.0000000 0.0000000 0.0000000
## MRI SCAN 0.0000000 0.0000000 0.9957806 0.0000000
## Registration 0.0000000 0.0000000 0.0000000 0.0000000
## Start 0.0000000 0.0000000 0.0000000 0.0000000
## Triage and Assessment 0.9957983 0.0000000 0.0000000 0.0000000
## X-Ray 0.0000000 0.0000000 0.9961538 0.0000000
## consequent
## antecedent MRI SCAN Registration Start Triage and Assessment
## Blood test 0.9957806 0.000000 0 0.000000
## Check-out 0.0000000 0.000000 0 0.000000
## Discuss Results 0.0000000 0.000000 0 0.000000
## End 0.0000000 0.000000 0 0.000000
## MRI SCAN 0.0000000 0.000000 0 0.000000
## Registration 0.0000000 0.000000 0 0.998004
## Start 0.0000000 0.998004 0 0.000000
## Triage and Assessment 0.0000000 0.000000 0 0.000000
## X-Ray 0.0000000 0.000000 0 0.000000
## consequent
## antecedent X-Ray
## Blood test 0.0000000
## Check-out 0.0000000
## Discuss Results 0.0000000
## End 0.0000000
## MRI SCAN 0.0000000
## Registration 0.0000000
## Start 0.0000000
## Triage and Assessment 0.9961832
## X-Ray 0.0000000
## attr(,"class")
## [1] "dependency_matrix" "matrix" "array"
Causal graph
causal_net(patients)## Nodes
## # A tibble: 9 × 12
## act from_id n n_distinct_cases bindings_input bindings_output label
## <chr> <int> <dbl> <dbl> <list> <list> <chr>
## 1 Blood t… 1 237 237 <list [1]> <list [1]> "Blood…
## 2 Check-o… 2 492 492 <list [1]> <list [1]> "Check…
## 3 Discuss… 3 495 495 <list [2]> <list [1]> "Discu…
## 4 End 4 500 500 <list [1]> <list [0]> "End"
## 5 MRI SCAN 5 236 236 <list [1]> <list [1]> "MRI S…
## 6 Registr… 6 500 500 <list [1]> <list [1]> "Regis…
## 7 Start 7 500 500 <list [0]> <list [1]> "Start"
## 8 Triage … 8 500 500 <list [1]> <list [2]> "Triag…
## 9 X-Ray 9 261 261 <list [1]> <list [1]> "X-Ray…
## # … with 5 more variables: color_level <dbl>, shape <chr>, fontcolor <chr>,
## # color <chr>, tooltip <chr>
## Edges
## # A tibble: 9 × 8
## antecedent consequent dep from_id to_id n label penwidth
## <chr> <chr> <dbl> <int> <int> <dbl> <chr> <dbl>
## 1 Triage and Assessment Blood test 0.996 8 1 237 237 2.90
## 2 Discuss Results Check-out 0.998 3 2 495 495 4.96
## 3 MRI SCAN Discuss Results 0.996 5 3 236 236 2.89
## 4 X-Ray Discuss Results 0.996 9 3 261 261 3.09
## 5 Check-out End 0.998 2 4 492 492 4.94
## 6 Blood test MRI SCAN 0.996 1 5 237 237 2.90
## 7 Start Registration 0.998 7 6 500 500 5
## 8 Registration Triage and Ass… 0.998 6 8 500 500 5
## 9 Triage and Assessment X-Ray 0.996 8 9 261 261 3.09
Petri net
causal_net(patients) %>% as.petrinet() %>% render_PN()processcheckR- rule-based conformance checking
- contains: activity occurs n times or more
- contains_exactly: activity occurs exactly n times
- absent: activity does not occur more than n - 1 times
- starts: case starts with activity
- ends: case ends with activity
- and: two activities always exist together
- succession: if activity A happens, B should happen after. 8. If B happens, A should have happened before.
- response: if activity A happens, B should happen after
- precedence: if activity B happens, A should have happend 11. before
- responded_existence: if activity A happens, B should also (have) happen(ed) (i.e. before or after A)
for example :Each patient should be registered at least once.
library(bupaR)##
## Attaching package: 'bupaR'## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:utils':
##
## timestamplibrary(processcheckR)##
## Attaching package: 'processcheckR'## The following object is masked from 'package:dplyr':
##
## contains## The following object is masked from 'package:tidyr':
##
## contains## The following object is masked from 'package:base':
##
## xorpatients %>%
check_rule(contains("Registration"))## Log of 5442 events consisting of:
## 7 traces
## 500 cases
## 2721 instances of 7 activities
## 7 resources
## Events occurred from 2017-01-02 11:41:53 until 2018-05-05 07:16:02
##
## Variables were mapped as follows:
## Case identifier: patient
## Activity identifier: handling
## Resource identifier: employee
## Activity instance identifier: handling_id
## Timestamp: time
## Lifecycle transition: registration_type
##
## # A tibble: 5,442 × 8
## handling patient employee handling_id registration_type time
## <fct> <chr> <fct> <chr> <fct> <dttm>
## 1 Registration 1 r1 1 start 2017-01-02 11:41:53
## 2 Registration 2 r1 2 start 2017-01-02 11:41:53
## 3 Registration 3 r1 3 start 2017-01-04 01:34:05
## 4 Registration 4 r1 4 start 2017-01-04 01:34:04
## 5 Registration 5 r1 5 start 2017-01-04 16:07:47
## 6 Registration 6 r1 6 start 2017-01-04 16:07:47
## 7 Registration 7 r1 7 start 2017-01-05 04:56:11
## 8 Registration 8 r1 8 start 2017-01-05 04:56:11
## 9 Registration 9 r1 9 start 2017-01-06 05:58:54
## 10 Registration 10 r1 10 start 2017-01-06 05:58:54
## # … with 5,432 more rows, and 2 more variables: .order <int>,
## # contains_Registration_1 <lgl>