PM4Py Feature Overview
An overview of key process mining concepts, algorithms, and approaches implemented in PM4Py.
A detailed and complete introduction to the various functions, algorithms and their variants can be found in the API documentation.
| Area | Concept/Algorithm | Description/Reference | Object | Links | Min pm4py version |
|---|---|---|---|---|---|
| Process Modeling | Petri Nets (PN) Workflow Nets (WF-nets) | The Application of Petri Nets to Workflow Management by van der Aalst | Petri Net | Code | 2.0.0 |
| Translating workflow nets to process trees: an algorithmic approach by van Zelst et al. | Petri NetProcess Tree | Code Example | 2.0.1 | |
| Diagnosing workflow processes using woflan by Verbeek et al. | Petri Net | Code Example | 2.0.0 | |
| Discovering object-centric Petri nets by van der Aalst et al. | LogOC-Petri Net | Code Example | 2.2.16 | |
| Causal Nets | Causal Nets: A Modeling Language Tailored towards Process Discovery by van der Aalst et. al. | DFGCausal Net | Code | 2.0.0 | |
| Directly-Follows Graph (DFG) | A practitioner’s guide to process mining: Limitations of the directly-follows graph by van der Aalst | DFG | Code Code (Discovery) Example | 2.0.0 | |
| Directly Follows-Based Process Mining: Exploration & a Case Study by Leemans et al. | DFGPetri Net | Code | 2.0.0 | |
| OC-PM: analyzing object-centric event logs and process models by Berti et al. | LogOC-DFG | Code Example | 2.2.16 | |
| Business Process Modeling Notation (BPMN) | Business Process Model and Notation (BMPN) by Object Management Group (OMG) | BPMNPetri Net | Code Example | 2.1.0 | |
| Transition System | Process Mining - Data Science in Action by van der Aalst | LogTransition System | Code Example | 2.0.0 | |
| Process Tree | Process Tree | Code Example | 2.0.0 | ||
| PTandLogGenerator: A generator for artificial event data by Jouck et al. | Process Tree | Code | 2.0.0 | |
| Prefix Tree | Prefix Tree | Code Example | 2.0.0 | ||
| Event Data | Event Log | Import/Export event logs. XES support | Log | Code | 2.0.0 |
| based on, e.g., LTL formulas, prefixes, attributes, DFG-paths, rework, temporal constraints, and many more | LogAttributesCasesActivities | Code Example | 2.0.0 | |
| including various temporal process performance statistics | LogAttributesActivitiesTimes | Code | 2.0.0 | |
| Supporting automatic system dynamics model generation for simulation in the context of process mining by Pourbafrani et al. | LogFeatures | Code Example | 2.3.4 | |
| Object-Centric Event Log (OCEL) | supporting the standards OCEL 1.0 and OCEL 2.0 | OCEL | Code | 2.2.15 | |
| based on, e.g., object types, event attributes, object counts, and many more | OCELActivitiesEventsObjectsEndpoints | Code Example | 2.2.16 | |
| including, object count statistics, edge metrics, and many more | OCELActivitiesObjects | Code | 2.2.18 | |
| Graph-based feature extraction on object-centric event logs by Berti et al. | OCELFeatures | Code Example | 2.2.18 | |
| Trace Clustering (hierarchical) | A generic framework for attribute-driven hierarchical trace clustering by van Zelst et al. | LogTrace AttributesHierarchical Cluester Tree | Code Example | 2.3.0 | |
| Process Discovery | Alpha Mining | 2.0.0 | |||
| Workflow Mining: Discovering Process Models from Event Logs by van der Aalst et al. | LogPetri Net | Code Example | 2.0.0 | |
| Workflow Mining: Current status and future directions by Alves De Medeiros al. | LogPetri Net | Code | 2.0.0 | |
| Inductive Mining | Various Inductive Mining algorithms are available | Code | 2.0.0 | ||
| Discovering block-structured process models from event logs - A constructive approach by Leemans et al. | LogPetri NetProcess Tree | Code Example | 2.0.0 | |
| Discovering block-structured process models from event logs containing infrequent behaviour by Leemans et al. | LogProcess TreePetri Net | Code Example | 2.0.0 | |
| Scalable Process Discovery with Guarantess by Leemans et al. | DFGProcess TreePetri Net | Code Example | 2.0.0 | |
| Heuristic Miner | Flexible heuristics miner (FHM) by Weijters et al. | LogPetri Net | Code Example | 2.0.0 | |
| ILP Miner | ILP-based process discovery using hybrid regions by van Zelst et al. | LogPetri Net | Code Example | 2.6.0 | |
| Correlation Miner | Correlation miner: Mining business process models and event correlations without case identifiers by Pourmirza et al. | LogDFG | Code Example | 2.0.0 | |
| Prefix Tree Approach | Skeletal algorithms in process mining by Przybylek | LogPrefix Tree | Code Example | 2.0.0 | |
| Declarative Process Models | User-guided discovery of declarative process models by Maggi et al. | Log | Code Example | 2.0.0 | |
| Log skeleton | The log skeleton visualizer in prom 6.9 by Verbeek | LogLog Skeleton Model | Code Example | 2.2.11 | |
| Partially Ordered Workflow Language (POWL) Miner | POWL: partially ordered workflow language by Kourani et al. | Log | Code Example | 2.7.5.2 | |
| Conformance Checking | Footprints | Process Mining - Data Science in Action by van der Aalst | LogPetri NetFootprint Table | Code (Discovery) Code (Conformance) Example | 2.0.0 |
| Token-Based Replay | A novel token-based replay technique to speed up conformance checking and process enhancement by Berti et al. | LogPetri NetDiagnostics | Code Example | 2.0.0 | |
| Alignments | Conformance checking using cost-based fitness analysis by Adriansyah et al. | LogPetri NetAlignments | Code Example | 2.0.0 | |
| Recomposing conformance: Closing the circle on decomposed alignment-based conformance checking in process mining by Lee et al. | LogPetri NetAlignments (decomposed) | Code Example | 2.0.0 | |
| Anti-alignments - measuring the precision of process models and event logs by Chatain et al. | LogPetri NetAnti-Alignments | Code Example | 2.0.0 | |
| Optimized SAT encoding of conformance checking artefacts by Boltenhagen et al. | LogPetri NetMulti-Alignments | Code Example | 2.0.0 | |
| Alignment approximation for process trees by Schuster et al. | Process TreeAlignments | Code | 2.0.0 | |
| Process Tree alignments by Schwanen et al. | Process TreeAlignments | Code | 2.0.0 | |
| A Dynamic Programming Approach for Alignments on Process Trees by Schwanen et al. | Process TreeAlignments | Code | 2.0.0 | |
| Efficiently computing alignments by van Dongen | Log | Code Example | 2.0.0 | |
| Log skeleton | The log skeleton visualizer in PROM 6.9 by Verbeek | LogLog Skeleton ModelAlignments | Code Example | 2.0.0 | |
| Earth Mover Distance (EMD) | Stochastic process mining: Earth movers' stochastic conformance by Leemans et al. | LogPetri Net | Code Example | 2.0.0 | |
| LTL Checking | Process mining and verification of properties: An approach based on temporal logic by van der Aalst et al. | Log | Code | 2.0.0 | |
| Temporal Profile | Temporal Conformance Checking at Runtime based on Time-infused Process Models by Stertz et al. | Log | Code Example | 2.0.0 | |
| Evaluation of Log-Model | Fitness | Token-based replay, Alignment based | LogPetri NetFitness | Code Example | 2.0.0 |
| Precision | A fresh look at precision in process conformance by J. Munoz-Gama et al. (TBR) Measuring precision of modeled behavior by A. Adriansyah et al. (Alignments) | LogPetri NetPrecision | Code Example | 2.0.0 | |
| Generalization | Quality dimensions in process discovery: The importance of fitness, precision, generalization and simplicity by Buijs et al. | LogPetri NetGeneralization | Code Example | 2.0.0 | |
| Simplicity | ProDiGen: Mining complete, precise and minimal structure process models with a genetic algorithm by Vázquez-Barreiros et al. | LogPetri NetSimplicity | Code Example | 2.0.0 | |
| Process Simulation | Monte Carlo Simulation | LogPetri Net | Code Example (Petri net replay) Example (manual edit stochastic map) | 2.0.0 | |
| Play Out | Process Mining - Data Science in Action by van der Aalst | LogPetri Net | Code | 2.0.0 | |
| Event log generation from a DFG | DFGLog | Code Example | 2.0.0 | |
| Event log generation from a Petri net | Petri NetLog | Code Example | 2.0.0 | |
| Event log generation from a process tree | Process TreeLog | Code Example | 2.0.0 | |
| Organizational Mining | Social Network Analysis | Discovering social networks from event logs by van der Aalst et al. | LogNetwork Analysis | Code Example | 2.0.0 |
| Organizational Roles | Business models enhancement through discovery of roles by Burattin et al. | LogRoles | Code Example | 2.0.0 | |
| Resource Profiles | Mining resource profiles from event logs by Pika et al. | Log | Code Example | 2.2.4 | |
| Operational Support | Predict Next Activity | LSTM model for predicting the next activity | Log | Example | 2.0.0 |
| Predict Remaining Time | LSTM model for predicting the remaining cycle time | Log | Example | 2.0.0 | |
| Process Enhancement and Analysis | Decision Mining | Data-aware process mining: discovering decisions in processes using alignments by de Leoni et al. | LogPetri Net (Decision points) | Code Example | 2.0.0 |
| Concept Drift Detection | Dealing with concept drifts in process mining by R.P.J.C. Bose et al. | Log | Code Example | 2.7.17 | |
| Process Cubes | Compute bi-dimensional slices of the event log | Log | Code Example | 2.0.0 | |
| Other | Performance Spectrum | The performance spectrum miner: Visual analytics for fine-grained performance analysis of processes by Denisov et al. | Code Example | 2.2.7 | |
| Differential Privacy | PRIPEL: privacy-preserving event log publishing including contextual information by Fahrenkrog-Petersen et al. | Log | Code Example | 2.0.0 | |
| Batch Detection | Batch processing: Definition and event log identification by Martin et al. | LogBatches | Code Example | 2.2.9 | |
| Label Splitting | Context-Based Activity Label-Splitting by van Zelst et al. | Log | Code Example | 2.7.9 | |
| Visualization | Petri Net | Petri Net | Code Example | 2.0.0 | |
| OC-PN | OC-PN | Code Example | 2.2.16 | ||
| DFG | DFG | Code Example | 2.0.0 | ||
| OC-DFG | OC-DFG | Code Example | 2.2.16 | ||
| BPMN | BPMN | Code Example | 2.1.0 | ||
| Transition System | Transition System | Code Example | 2.0.0 | ||
| Process Tree | Process Tree | Code Example | 2.0.0 | ||
| Prefix Tree | Prefix Tree | Code Example | 2.2.5 | ||
| POWL | POWL | Code Example | 2.7.5.2 | ||
| Dotted Chart | Log | Code Example | 2.2.7 | ||
| Heuristics Net | Heuristics Net | Code Example | 2.0.0 | ||
| Footprints | Footprint Table | Code Example | 2.0.0 | ||
| Alignment Table | LogAlignments | Code Example | 2.7.4 | ||
| Decision Tree | Decision Tree | Code Example | 2.0.0 | ||
| Social Network Analysis | Network Analysis | Code Example | 2.0.0 |
