Merge branch 'release' into ft-alignments-dynamic-programming

CHANGELOG.md

@@ -1,11 +1,22 @@
 # Changelog of pm4py
 
 
-## pm4py 2.7.12 (2024.03.XX)
+## pm4py 2.7.12 (2024.03.21)
 
 ### Added
+* 458ee9abf2fc155a7531be96992c9a0c27f8cb81
+  * maximum number of consecutive occurrences of the same activity in pm4py.get_variants
+* b4c914722605b37f787e156f407ea9333a8dd959
+  * more general between and activity split filters
 
 ### Changed
+* 100b95c22a47eace59fc631541b2c34c9179765d
+  09d4e7a07f92fddd90c1b1bbe572308380d7c8f3
+  * changed BPMN visualizer
+* f7b44a41a79760e4f092be2bf98087ea48b63de4
+  * changed BPMN conversion
+* db98b6fbf16847eceab4b53216cc1a1096936785
+  * improved BPMN support (collaboration, gateways, ...)
 
 ### Deprecated
 
@@ -14,6 +25,10 @@
   * fixing random variables support
 * bb759da149b434d0e279256c8c6d397b06079729
   * fixing sampling
+* a816fb5f000a907b603b44aba1470463109028f0
+  * bug fix OC-DFG visualization
+* 419a95362472c0807b73f4eb3d601f70b3d7c986
+  * bug fix POWL visualizer
 
 ### Removed
 

Dockerfile

@@ -7,12 +7,12 @@ RUN apt-get -y install gcc g++ flex bison pkg-config automake autoconf cmake
 RUN apt-get -y install python3-dev python3-pydot python3-tk
 RUN apt-get -y install libopenblas-dev liblapack-dev libboost-all-dev libncurses5-dev libtool libssl-dev libjemalloc-dev libboost-dev libboost-filesystem-dev libboost-system-dev libboost-regex-dev libxml2-dev libxslt-dev libfreetype6-dev libsuitesparse-dev libclang-16-dev llvm-16-dev libthrift-dev libfftw3-dev
 RUN python3 -m pip install --upgrade pip
-RUN pip3 install deprecation==2.1.0 graphviz==0.20.3 intervaltree==3.1.0 networkx==3.4.2 packaging==24.1 python-dateutil==2.9.0.post0 pytz==2024.2 setuptools==75.3.0 six==1.16.0 sortedcontainers==2.4.0 tzdata==2024.2 wheel==0.44.0 
-RUN pip3 install colorama==0.4.6 cycler==0.12.1 pydotplus==2.0.2 pyparsing==3.2.0 tqdm==4.66.6 
+RUN pip3 install deprecation==2.1.0 graphviz==0.20.3 intervaltree==3.1.0 networkx==3.4.2 packaging==24.2 python-dateutil==2.9.0.post0 pytz==2024.2 setuptools==75.3.0 six==1.16.0 sortedcontainers==2.4.0 tzdata==2024.2 wheel==0.45.0 
+RUN pip3 install colorama==0.4.6 cycler==0.12.1 pydotplus==2.0.2 pyparsing==3.2.0 tqdm==4.67.0 
 RUN pip3 install lxml==5.3.0 numpy==2.1.3 pandas==2.2.3 scipy==1.14.1 
 RUN pip3 install contourpy==1.3.0 fonttools==4.54.1 kiwisolver==1.4.7 matplotlib==3.9.2 pillow==11.0.0 
-RUN pip3 install anyio==4.6.2.post1 asttokens==2.4.1 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.4.0 convertdate==2.4.0 decorator==5.1.1 distro==1.9.0 executing==2.1.0 h11==0.14.0 httpcore==1.0.6 httpx==0.27.2 idna==3.10 ipython==8.29.0 jedi==0.19.1 Jinja2==3.1.4 jsonpickle==3.4.2 jsonschema-specifications==2024.10.1 lunardate==0.2.2 MarkupSafe==3.0.2 matplotlib-inline==0.1.7 parso==0.8.4 prompt-toolkit==3.0.48 pure-eval==0.2.3 pydantic==2.9.2 Pygments==2.18.0 pyluach==2.2.0 PyMeeus==0.5.12 referencing==0.35.1 rpds-py==0.20.1 sniffio==1.3.1 stack-data==0.6.3 traitlets==5.14.3 typing_extensions==4.12.2 urllib3==2.2.3 wcwidth==0.2.13 
-RUN pip3 install jsonschema==4.23.0 openai==1.54.1 pyvis==0.3.2 requests==2.32.3 workalendar==17.0.0 
+RUN pip3 install anyio==4.6.2.post1 asttokens==2.4.1 attrs==24.2.0 certifi==2024.8.30 charset-normalizer==3.4.0 convertdate==2.4.0 decorator==5.1.1 distro==1.9.0 executing==2.1.0 h11==0.14.0 httpcore==1.0.6 httpx==0.27.2 idna==3.10 ipython==8.29.0 jedi==0.19.1 Jinja2==3.1.4 jsonpickle==3.4.2 jsonschema-specifications==2024.10.1 lunardate==0.2.2 MarkupSafe==3.0.2 matplotlib-inline==0.1.7 parso==0.8.4 prompt-toolkit==3.0.48 pure-eval==0.2.3 pydantic==2.9.2 Pygments==2.18.0 pyluach==2.2.0 PyMeeus==0.5.12 referencing==0.35.1 rpds-py==0.21.0 sniffio==1.3.1 stack-data==0.6.3 traitlets==5.14.3 typing_extensions==4.12.2 urllib3==2.2.3 wcwidth==0.2.13 
+RUN pip3 install jsonschema==4.23.0 openai==1.54.3 pyvis==0.3.2 requests==2.32.3 workalendar==17.0.0 
 RUN pip3 install -U meson-python==0.15.0 Cython==3.0.10 ninja==1.11.1.1 spin==0.8 build==1.2.1 setuptools_scm==8.0.4
 
 #RUN cd / && git clone https://github.com/numpy/numpy.git && cd /numpy && git submodule update --init && pip3 install .

README.md

@@ -1,14 +1,18 @@
-# pm4py
-pm4py is a python library that supports (state-of-the-art) process mining algorithms in python. 
-It is open source (licensed under GPL) and intended to be used in both academia and industry projects.
-pm4py is managed and developed by Process Intelligence Solutions (https://processintelligence.solutions/).
-pm4py was initially developed at the Fraunhofer Institute for Applied Information Technology FIT.
+# PM4Py
+PM4Py is a python library that supports state-of-the-art process mining algorithms in python. 
+It is open source and intended to be used in both academia and industry projects.
+
+PM4Py is managed and developed by Process Intelligence Solutions (https://processintelligence.solutions/),
+a spin-off from the Fraunhofer Institute for Applied Information Technology FIT where PM4Py was initially developed.
+
+Further information on the license options for using PM4Py closed source (especially in industry contexts) can be found at https://processintelligence.solutions/.
+
 
 ## Documentation / API
-The full documentation of pm4py can be found at https://processintelligence.solutions/
+The full documentation of PM4Py can be found at https://processintelligence.solutions/
 
 ## First Example
-A very simple example, to whet your appetite:
+Here is a simple example to spark your interest:
 
 ```python
 import pm4py
@@ -20,30 +24,31 @@ if __name__ == "__main__":
 ```
 
 ## Installation
-pm4py can be installed on Python 3.9.x / 3.10.x / 3.11.x / 3.12.x by invoking:
-*pip install -U pm4py*
+PM4Py can be installed on Python 3.9.x / 3.10.x / 3.11.x / 3.12.x by invoking:
 
-pm4py is also running on older Python environments with different requirements sets, including:
-- Python 3.8 (3.8.10): third_party/old_python_deps/requirements_py38.txt
+`pip install -U pm4py`
+
+PM4Py is also running on older Python environments with different requirements sets, including:
+- Python 3.8 (3.8.10): `third_party/old_python_deps/requirements_py38.txt`
 
 ## Requirements
-pm4py depends on some other Python packages, with different levels of importance:
+PM4Py depends on some other Python packages, with different levels of importance:
 * *Essential requirements*: numpy, pandas, deprecation, networkx
-* *Normal requirements* (installed by default with the pm4py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, tqdm
+* *Normal requirements* (installed by default with the PM4Py package, important for mainstream usage): graphviz, intervaltree, lxml, matplotlib, pydotplus, pytz, scipy, tqdm
 * *Optional requirements* (not installed by default): requests, pyvis, jsonschema, workalendar, pyarrow, scikit-learn, polars, openai, pyemd, pyaudio, pydub, pygame, pywin32, pygetwindow, pynput
 
 ## Release Notes
-To track the incremental updates, please refer to the *CHANGELOG* file.
+To track the incremental updates, please refer to the `CHANGELOG.md` file.
 
 ## Third Party Dependencies
 As scientific library in the Python ecosystem, we rely on external libraries to offer our features.
-In the */third_party* folder, we list all the licenses of our direct dependencies.
-Please check the */third_party/LICENSES_TRANSITIVE* file to get a full list of all transitive dependencies and the corresponding license.
+In the `/third_party` folder, we list all the licenses of our direct dependencies.
+Please check the `/third_party/LICENSES_TRANSITIVE` file to get a full list of all transitive dependencies and the corresponding license.
 
-## Citing pm4py
-If you are using pm4py in your scientific work, please cite pm4py as follows:
+## Citing PM4Py
+If you are using PM4Py in your scientific work, please cite PM4Py as follows:
 
-**Alessandro Berti, Sebastiaan van Zelst, Daniel Schuster**. (2023). *PM4Py: A process mining library for Python*. Software Impacts, 17, 100556. [DOI](https://doi.org/10.1016/j.simpa.2023.100556) | [Article Link](https://www.sciencedirect.com/science/article/pii/S2665963823000933)
+> **Alessandro Berti, Sebastiaan van Zelst, Daniel Schuster**. (2023). *PM4Py: A process mining library for Python*. Software Impacts, 17, 100556. [DOI](https://doi.org/10.1016/j.simpa.2023.100556) | [Article Link](https://www.sciencedirect.com/science/article/pii/S2665963823000933)
 
 BiBTeX:
 
@@ -61,3 +66,6 @@ author = {Alessandro Berti and Sebastiaan van Zelst and Daniel Schuster},
 }
 ```
 
+## Legal Notice
+
+This repository is managed by Process Intelligence Solutions (PIS). Further information about PIS can be found online at www.processintelligence.solutions.

docs/LICENSE_HEADER_GITHUB.txt

@@ -1,16 +1,21 @@
 '''
-    This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
+    PM4Py – A Process Mining Library for Python
+Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
 
-    PM4Py is free software: you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
-    the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU Affero General Public License as
+published by the Free Software Foundation, either version 3 of the
+License, or any later version.
 
-    PM4Py is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU Affero General Public License for more details.
 
-    You should have received a copy of the GNU General Public License
-    along with PM4Py.  If not, see <https://www.gnu.org/licenses/>.
+You should have received a copy of the GNU Affero General Public License
+along with this program.  If not, see this software project's root or
+visit <https://www.gnu.org/licenses/>.
+
+Website: https://processintelligence.solutions
+Contact: info@processintelligence.solutions
 '''

docs/header_script.py

@@ -7,7 +7,7 @@
         for filename in glob.iglob('../pm4py/' + '**/*.py', recursive=True):
             with open(filename, 'r', encoding='utf-8') as original:
                 data = original.read()
-                if (data.find(license) == -1):
+                if "Copyright (C) 2024 Process Intelligence Solutions UG" not in data:
                     with open(filename, 'w', encoding='utf-8') as modified:
                         print('adding license to: ' + filename)
                         modified.write(license + '\n' + data)

docs/source/getting_started.rst

@@ -63,13 +63,13 @@ In order to support interoperability between different process mining tools and
 
 In the remainder of this tutorial, we will use an oftenly used dummy example event log to explain the basic process mining operations. The process that we are considering is a simplified process related to customer complaint handling, i.e., *taken from the book of van der Aalst*. The process, and the event data we are going to use, looks as follows.
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/bpmn_running_example.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/bpmn_running_example.png
 
 *Figure 3: Running example BPMN-based process model describing the behavior of the simple process that we use in this tutorial.*
 
 Let’s get started! We have prepared a small sample event log, containing behavior similar equal to the process model in Figure 3. `You can find the sample event log here </static/assets/data/getting_started/running-example.csv>`_. Please download the file and store it somewhere on your computer, e.g., your Downloads folder (On Windows: this is 'C:/Users/user_name/Dowloads'). Consider Figure 4, in which we depict the first 25 rows of the example file.
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/csv_snapshot.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/csv_snapshot.png
 
 *Figure 4: Running example csv data set which we will use in this tutorial.*
 
@@ -146,7 +146,7 @@ Next to CSV files, event data can also be stored in an XML-based format, i.e., i
 Consider Figure 5, in which we depict a snapshot of the running example data stored in the .xes file format. The complete file can be downloaded
 `here <https://pm4py.fit.fraunhofer.de/static/assets/data/getting_started/running-example.xes>`_.
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/csv_snapshot.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/csv_snapshot.png
 
 *Figure 5: Running example xes data set.*
 
@@ -333,7 +333,7 @@ Interestingly, none of the algorithms implemented in PM4Py directly discovers a
 
 Note that the resulting process model is the following image:
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/bpmn_inductive_running_example.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/bpmn_inductive_running_example.png
 
 *Figure 6: BPMN model discovered based on the running example event data set, using the Inductive Miner implementation of PM4Py.*
 
@@ -353,7 +353,7 @@ As indicated, the algorithm used in this example actually discovers a Process Tr
         pm4py.view_process_tree(process_tree)
 
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/process_tree_running_example.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/process_tree_running_example.png
 
 *Figure 7: Process Tree model discovered based on the running example event data set, using the Inductive Miner implementation of PM4Py.*
 
@@ -376,7 +376,7 @@ Many `commercial process mining solutions <https://www.gartner.com/reviews/marke
 
 
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/dfg_running_example.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/dfg_running_example.png
 
 *Figure 8: Process Map (DFG-based) discovered based on the running example event data set.*
 
@@ -395,7 +395,7 @@ In PM4Py, we also implemented the `Heuristics Miner <https://ieeexplore.ieee.org
         pm4py.view_heuristics_net(map)
 
 
-.. image:: https://pm4py.fit.fraunhofer.de/static/assets/images/getting_started/hnet_running_example.png
+.. image:: https://processintelligence.solutions/static/images/getting_started/hnet_running_example.png
 
 *Figure 9: Process Map (HM-based) discovered based on the running example event data set.*
 

pm4py/__init__.py

@@ -1,18 +1,23 @@
 '''
-    This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
+    PM4Py – A Process Mining Library for Python
+Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
 
-    PM4Py is free software: you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
-    the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU Affero General Public License as
+published by the Free Software Foundation, either version 3 of the
+License, or any later version.
 
-    PM4Py is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU Affero General Public License for more details.
 
-    You should have received a copy of the GNU General Public License
-    along with PM4Py.  If not, see <https://www.gnu.org/licenses/>.
+You should have received a copy of the GNU Affero General Public License
+along with this program.  If not, see this software project's root or
+visit <https://www.gnu.org/licenses/>.
+
+Website: https://processintelligence.solutions
+Contact: info@processintelligence.solutions
 '''
 import time
 

pm4py/algo/__init__.py

@@ -1,17 +1,22 @@
 '''
-    This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
+    PM4Py – A Process Mining Library for Python
+Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
 
-    PM4Py is free software: you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
-    the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU Affero General Public License as
+published by the Free Software Foundation, either version 3 of the
+License, or any later version.
 
-    PM4Py is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU Affero General Public License for more details.
 
-    You should have received a copy of the GNU General Public License
-    along with PM4Py.  If not, see <https://www.gnu.org/licenses/>.
+You should have received a copy of the GNU Affero General Public License
+along with this program.  If not, see this software project's root or
+visit <https://www.gnu.org/licenses/>.
+
+Website: https://processintelligence.solutions
+Contact: info@processintelligence.solutions
 '''
 from pm4py.algo import discovery, conformance, analysis, evaluation, simulation, organizational_mining, transformation

pm4py/algo/analysis/__init__.py

@@ -1,17 +1,22 @@
 '''
-    This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).
+    PM4Py – A Process Mining Library for Python
+Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
 
-    PM4Py is free software: you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
-    the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
+This program is free software: you can redistribute it and/or modify
+it under the terms of the GNU Affero General Public License as
+published by the Free Software Foundation, either version 3 of the
+License, or any later version.
 
-    PM4Py is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
+This program is distributed in the hope that it will be useful,
+but WITHOUT ANY WARRANTY; without even the implied warranty of
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+GNU Affero General Public License for more details.
 
-    You should have received a copy of the GNU General Public License
-    along with PM4Py.  If not, see <https://www.gnu.org/licenses/>.
+You should have received a copy of the GNU Affero General Public License
+along with this program.  If not, see this software project's root or
+visit <https://www.gnu.org/licenses/>.
+
+Website: https://processintelligence.solutions
+Contact: info@processintelligence.solutions
 '''
 from pm4py.algo.analysis import extended_marking_equation, marking_equation, workflow_net, woflan