Merge branch 'GUDHI:master' into persistence_matrix

.github/changelog.md

@@ -1,15 +1,63 @@
 Release History
 ===============
 
+
+[Release 3.9.0](https://github.com/GUDHI/gudhi-devel/releases/tag/tags%2Fgudhi-release-3.9.0)
+-----------
+
+Release date: December 2023
+
+Below is a list of changes made since GUDHI 3.8.0:
+
+- [CubicalPersistence](https://gudhi.inria.fr/python/latest/cubical_complex_sklearn_itf_ref.html)
+     - Much faster implementation for the 2d case with input from top-dimensional cells.
+
+- [Simplex_tree](https://gudhi.inria.fr/doc/latest/group__simplex__tree.html)
+     - A helper `for_each_simplex` that applies a given function object on each simplex
+     - A new method `num_simplices_by_dimension` is now available thanks to this helper.
+     - A `clear` method to empty the data stucture.
+     - A new argument `ignore_infinite_values` for `initialize_filtration` method to skip infinite values. As a side effect, this change enhances the persistence computation.
+     - `Simplex_tree_options_full_featured` has been renamed `Simplex_tree_options_default` and `Simplex_tree_options_python`.
+     These are respectively the default options used by the `Simplex_tree` and by the python interface of the `SimplexTree` (as before this version).
+     - From GUDHI 3.9.0, `Simplex_tree_options_full_featured` now activates `link_nodes_by_label` and `stable_simplex_handles` (making it slower, except for browsing cofaces).
+
+     | Simplex_tree_options_*  | :warning: full_featured | default | python | minimal |
+     | ---- | ---- | ---- | ---- | ---- |
+     | store_key              | 1       | 1      | 1      | 0 |
+     | store_filtration       | 1       | 1      | 1      | 0 |
+     | contiguous_vertices    | 0       | 0      | 0      | 0 |
+     | link_nodes_by_label    | ***1*** | 0      | 0      | 0 |
+     | stable_simplex_handles | ***1*** | 0      | 0      | 0 |
+     | Filtration_value       | double  | double | double |   |
+
+- [Simplex_tree options](https://gudhi.inria.fr/doc/latest/struct_simplex_tree_options.html)
+     - A new option `link_nodes_by_label` to speed up cofaces and stars access, when set to true.
+     - A new option `stable_simplex_handles` to keep Simplex handles valid even after insertions or removals, when set to true.
+
+- [Čech complex](https://gudhi.inria.fr/doc/latest/group__cech__complex.html)
+     - A function `assign_MEB_filtration` that assigns to each simplex a filtration value equal to the squared radius of its minimal enclosing ball (MEB), given a simplicial complex and an embedding of its vertices. Applied on a Delaunay triangulation, it computes the Delaunay-Čech filtration.
+
+- [Edge collapse](https://gudhi.inria.fr/python/latest/edge_collapse.html)
+     - A Python function `reduce_graph` to simplify a clique filtration (represented as a sparse weighted graph), while preserving its persistent homology.
+
+- [Mapper/GIC/Nerve complexes](https://gudhi.inria.fr/python/latest/cover_complex_sklearn_isk_ref.html)
+     - A new method `save_to_html` to ease the Keppler Mapper visualization
+
+- Installation
+     - Boost ≥ 1.71.0 is now required (was ≥ 1.66.0).
+     - cython >= 3.0.0 is now supported.
+     - Python 3.12 pip package.
+
+- Miscellaneous
+     - The [list of bugs that were solved since GUDHI-3.8.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.9.0+is%3Aclosed) is available on GitHub.
+
 [Release 3.8.0](https://github.com/GUDHI/gudhi-devel/releases/tag/tags%2Fgudhi-release-3.8.0)
 -----------
 
 Release date: April 2023
 
 As a major new feature, the GUDHI library now offers Perslay, a Tensorflow model for the representations module, scikit-learn like interfaces for Cover Complexes, a new function to compute persistence of a function on ℝ and the possibility to build a Cubical Complex as a lower-star filtration from vertices.
 
-We are now using GitHub to develop the GUDHI library, do not hesitate to [fork the GUDHI project on GitHub](https://github.com/GUDHI/gudhi-devel). From a user point of view, we recommend to download GUDHI user version (gudhi.3.X.X.tar.gz).
-
 Below is a list of changes made since GUDHI 3.7.1:
 
 - [Perslay](https://gudhi.inria.fr/python/latest/representations_tflow_itf_ref.html)

.github/for_maintainers/switcher.json

@@ -1,9 +1,14 @@
 [
     {
-        "name": "v3.8.0 (latest)",
-        "version": "3.8.0",
+        "name": "v3.9.0 (latest)",
+        "version": "3.9.0",
         "url": "https://gudhi.inria.fr/python/latest/"
     },
+    {
+        "name": "v3.8.0",
+        "version": "3.8.0",
+        "url": "https://gudhi.inria.fr/python/3.8.0/"
+    },
     {
         "name": "v3.7.1",
         "version": "3.7.1",

.github/next_release.md

@@ -1,26 +1,17 @@
-We are pleased to announce the release 3.9.0 of the GUDHI library.
-
-As a major new feature, the GUDHI library now offers ...
+We are pleased to announce the release 3.10.0 of the GUDHI library.
 
 We are now using GitHub to develop the GUDHI library, do not hesitate to [fork the GUDHI project on GitHub](https://github.com/GUDHI/gudhi-devel). From a user point of view, we recommend to download GUDHI user version (gudhi.3.X.X.tar.gz).
 
-Below is a list of changes made since GUDHI 3.8.0:
+Below is a list of changes made since GUDHI 3.9.0:
 
-- [Module](link)
-     - **...**
+- [Rips complex](https://gudhi.inria.fr/python/latest/rips_complex_sklearn_itf_ref.html)
+     - Rips complex persistence scikit-learn like interface
 
 - [Module](link)
      - **...**
 
-- [CubicalPersistence](https://gudhi.inria.fr/python/latest/cubical_complex_sklearn_itf_ref.html)
-     - Much faster implementation for the 2d case with input from top-dimensional cells.
-
-- Installation
-     - Boost ≥ 1.71.0 is now required (was ≥ 1.66.0).
-     - cython >= 3.0.0 is now supported.
-
 - Miscellaneous
-     - The [list of bugs that were solved since GUDHI-3.8.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.9.0+is%3Aclosed) is available on GitHub.
+     - The [list of bugs that were solved since GUDHI-3.9.0](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.10.0+is%3Aclosed) is available on GitHub.
 
 All modules are distributed under the terms of the MIT license.
 However, there are still GPL dependencies for many modules. We invite you to check our [license dedicated web page](https://gudhi.inria.fr/licensing/) for further details.
@@ -36,4 +27,4 @@ For further information about downloading and installing the library ([C++](http
 ## Contributors
 
 - **...**
-- **...**
+- **...**

.github/workflows/pip-build-linux.yml

@@ -7,30 +7,30 @@ jobs:
     name: build pip wheel
     runs-on: ubuntu-latest
     # cf. https://github.com/GUDHI/gudhi-deploy/blob/main/Dockerfile_for_pip
-    container: gudhi/pip_for_gudhi:latest
+    container: gudhi/pip_for_gudhi:2023.12.01
     steps:
       - uses: actions/checkout@v3
         with:
           submodules: true
-      - name: Build wheel for Python 3.6
+      - name: Build wheel for Python 3.8
         run: |
-          mkdir build_36
-          cd build_36
-          cmake -DCMAKE_BUILD_TYPE=Release -DPYTHON_EXECUTABLE=$PYTHON36/bin/python ..
+          mkdir build_38
+          cd build_38
+          cmake -DCMAKE_BUILD_TYPE=Release -DPYTHON_EXECUTABLE=$PYTHON38/bin/python ..
           cd src/python
-          $PYTHON36/bin/python -m build -n -w
+          $PYTHON38/bin/python -m build -n -w
           auditwheel repair dist/*.whl
-      - name: Install and test wheel for Python 3.6
+      - name: Install and test wheel for Python 3.8
         run: |
-          $PYTHON36/bin/python -m pip install --user pytest build_36/src/python/dist/*.whl
-          $PYTHON36/bin/python -m pip install numpy --upgrade
-          $PYTHON36/bin/python -c "import gudhi; print(gudhi.__version__)"
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_alpha_complex.py
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_bottleneck_distance.py
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_cubical_complex.py
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_rips_complex.py
+          $PYTHON38/bin/python -m pip install --user pytest build_38/src/python/dist/*.whl
+          $PYTHON38/bin/python -m pip install numpy --upgrade
+          $PYTHON38/bin/python -c "import gudhi; print(gudhi.__version__)"
+          $PYTHON38/bin/python -m pytest -v src/python/test/test_alpha_complex.py
+          $PYTHON38/bin/python -m pytest -v src/python/test/test_bottleneck_distance.py
+          $PYTHON38/bin/python -m pytest -v src/python/test/test_cubical_complex.py
+          $PYTHON38/bin/python -m pytest -v src/python/test/test_rips_complex.py
       - name: Upload linux python wheel
         uses: actions/upload-artifact@v3
         with:
           name: linux python wheel
-          path: build_36/src/python/wheelhouse/*.whl
+          path: build_38/src/python/wheelhouse/*.whl

.github/workflows/pip-build-windows.yml

@@ -8,10 +8,10 @@ jobs:
     strategy:
       max-parallel: 4
       matrix:
-        python-version: ['3.7']
+        python-version: ['3.8']
         include:
-          - python-version: '3.7'
-            numpy-version: '1.15.0'
+          - python-version: '3.8'
+            numpy-version: '1.21.4'
     name: Build wheels for Python ${{ matrix.python-version }}
     steps:
       - uses: actions/checkout@v3

.github/workflows/pip-packaging-linux.yml

@@ -9,45 +9,11 @@ jobs:
     name: build pip wheel
     runs-on: ubuntu-latest
     # cf. https://github.com/GUDHI/gudhi-deploy/blob/main/Dockerfile_for_pip
-    container: gudhi/pip_for_gudhi:latest
+    container: gudhi/pip_for_gudhi:2023.12.01
     steps:
       - uses: actions/checkout@v3
         with:
           submodules: true
-      - name: Build wheel for Python 3.6
-        run: |
-          mkdir build_36
-          cd build_36
-          cmake -DCMAKE_BUILD_TYPE=Release -DPYTHON_EXECUTABLE=$PYTHON36/bin/python ..
-          cd src/python
-          $PYTHON36/bin/python -m build -n -w
-          auditwheel repair dist/*.whl
-      - name: Install and test wheel for Python 3.6
-        run: |
-          $PYTHON36/bin/python -m pip install --user pytest build_36/src/python/dist/*.whl
-          $PYTHON36/bin/python -m pip install numpy --upgrade
-          $PYTHON36/bin/python -c "import gudhi; print(gudhi.__version__)"
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_alpha_complex.py
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_bottleneck_distance.py
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_cubical_complex.py
-          $PYTHON36/bin/python -m pytest -v src/python/test/test_rips_complex.py
-      - name: Build wheel for Python 3.7
-        run: |
-          mkdir build_37
-          cd build_37
-          cmake -DCMAKE_BUILD_TYPE=Release -DPYTHON_EXECUTABLE=$PYTHON37/bin/python ..
-          cd src/python
-          $PYTHON37/bin/python -m build -n -w
-          auditwheel repair dist/*.whl
-      - name: Install and test wheel for Python 3.7
-        run: |
-          $PYTHON37/bin/python -m pip install --user pytest build_37/src/python/dist/*.whl
-          $PYTHON37/bin/python -m pip install numpy --upgrade
-          $PYTHON37/bin/python -c "import gudhi; print(gudhi.__version__)"
-          $PYTHON37/bin/python -m pytest -v src/python/test/test_alpha_complex.py
-          $PYTHON37/bin/python -m pytest -v src/python/test/test_bottleneck_distance.py
-          $PYTHON37/bin/python -m pytest -v src/python/test/test_cubical_complex.py
-          $PYTHON37/bin/python -m pytest -v src/python/test/test_rips_complex.py
       - name: Build wheel for Python 3.8
         run: |
           mkdir build_38
@@ -116,14 +82,30 @@ jobs:
           $PYTHON311/bin/python -m pytest -v src/python/test/test_bottleneck_distance.py
           $PYTHON311/bin/python -m pytest -v src/python/test/test_cubical_complex.py
           $PYTHON311/bin/python -m pytest -v src/python/test/test_rips_complex.py
+      - name: Build wheel for Python 3.12
+        run: |
+          mkdir build_312
+          cd build_312
+          cmake -DCMAKE_BUILD_TYPE=Release -DPYTHON_EXECUTABLE=$PYTHON312/bin/python ..
+          cd src/python
+          $PYTHON312/bin/python -m build -n -w
+          auditwheel repair dist/*.whl
+      - name: Install and test wheel for Python 3.12
+        run: |
+          $PYTHON312/bin/python -m pip install --user pytest build_312/src/python/dist/*.whl
+          $PYTHON312/bin/python -m pip install numpy --upgrade
+          $PYTHON312/bin/python -c "import gudhi; print(gudhi.__version__)"
+          $PYTHON312/bin/python -m pytest -v src/python/test/test_alpha_complex.py
+          $PYTHON312/bin/python -m pytest -v src/python/test/test_bottleneck_distance.py
+          $PYTHON312/bin/python -m pytest -v src/python/test/test_cubical_complex.py
+          $PYTHON312/bin/python -m pytest -v src/python/test/test_rips_complex.py
       - name: Publish on PyPi
         env:
           TWINE_USERNAME: __token__
           TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
         run: |
-          $PYTHON36/bin/python -m twine upload build_36/src/python/wheelhouse/*.whl
-          $PYTHON36/bin/python -m twine upload build_37/src/python/wheelhouse/*.whl
-          $PYTHON36/bin/python -m twine upload build_38/src/python/wheelhouse/*.whl
-          $PYTHON36/bin/python -m twine upload build_39/src/python/wheelhouse/*.whl
-          $PYTHON36/bin/python -m twine upload build_310/src/python/wheelhouse/*.whl
-          $PYTHON36/bin/python -m twine upload build_311/src/python/wheelhouse/*.whl
+          $PYTHON38/bin/python -m twine upload build_38/src/python/wheelhouse/*.whl
+          $PYTHON38/bin/python -m twine upload build_39/src/python/wheelhouse/*.whl
+          $PYTHON38/bin/python -m twine upload build_310/src/python/wheelhouse/*.whl
+          $PYTHON38/bin/python -m twine upload build_311/src/python/wheelhouse/*.whl
+          $PYTHON38/bin/python -m twine upload build_312/src/python/wheelhouse/*.whl

.github/workflows/pip-packaging-osx.yml

@@ -17,7 +17,7 @@ jobs:
       matrix:
         # numpy packages for osx x86 and arm are only available from 1.21.2, but stable for both versions from 1.21.4
         # and python 3.8+
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
         include:
         # numpy >= 1.21.4 fort osx x86 and arm, but minimal numpy version for python 3.10 is 1.21.6 for instance
         # numpy~=1.21.6 means any numpy=1.21.*, but also numpy>=1.21.6 (numpy~=1.21 do not work as it means any numpy==1.*)
@@ -29,6 +29,8 @@ jobs:
             numpy-version: '1.21.6'
           - python-version: '3.11'
             numpy-version: '1.23.2'
+          - python-version: '3.12'
+            numpy-version: '1.26.0'
     name: Build wheels for Python ${{ matrix.python-version }}
     steps:
       - uses: actions/checkout@v3

.github/workflows/pip-packaging-windows.yml

@@ -10,12 +10,10 @@ jobs:
     strategy:
       max-parallel: 4
       matrix:
-        python-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
         # gudhi requires numpy >= 1.15.0, but minimal numpy version for python 3.8 is 1.17.3 for instance
         # numpy~=1.17.3 means any numpy=1.17.*, but also numpy>=1.17.3 (numpy~=1.17 do not work as it means any numpy==1.*)
         include:
-          - python-version: '3.7'
-            numpy-version: '1.15.0'
           - python-version: '3.8'
             numpy-version: '1.17.3'
           - python-version: '3.9'
@@ -24,6 +22,8 @@ jobs:
             numpy-version: '1.21.6'
           - python-version: '3.11'
             numpy-version: '1.23.2'
+          - python-version: '3.12'
+            numpy-version: '1.26.0'
     name: Build wheels for Python ${{ matrix.python-version }}
     steps:
       - uses: actions/checkout@v3

CMakeGUDHIVersion.txt

@@ -1,6 +1,6 @@
 # Must be conform to pep440 - https://www.python.org/dev/peps/pep-0440/#pre-releases
 set (GUDHI_MAJOR_VERSION 3)
-set (GUDHI_MINOR_VERSION 9)
+set (GUDHI_MINOR_VERSION 10)
 # GUDHI_PATCH_VERSION can be 'ZaN' for Alpha release, 'ZbN' for Beta release, 'ZrcN' for release candidate or 'Z' for a final release.
 set (GUDHI_PATCH_VERSION 0a1)
 set(GUDHI_VERSION ${GUDHI_MAJOR_VERSION}.${GUDHI_MINOR_VERSION}.${GUDHI_PATCH_VERSION})

biblio/bibliography.bib

@@ -1387,6 +1387,18 @@ @misc{arxivpers1d
   year = {2023},
   copyright = {arXiv.org perpetual, non-exclusive license}
 }
+
+@misc{icml2014,
+  doi = {10.48550/ARXIV.1406.1901},
+  url = {https://arxiv.org/abs/1406.1901},
+  author = {Chazal, Frédéric and Fasy, Brittany Terese and Lecci, Fabrizio and Michel, Bertrand and Rinaldo, Alessandro and Wasserman, Larry},
+  keywords = {Algebraic Topology (math.AT), Computational Geometry (cs.CG), Applications (stat.AP), FOS: Mathematics, FOS: Mathematics, FOS: Computer and information sciences, FOS: Computer and information sciences},
+  title = {Subsampling Methods for Persistent Homology},
+  publisher = {arXiv},
+  year = {2014},
+  copyright = {arXiv.org perpetual, non-exclusive license}
+}
+
 @InProceedings{chubet_et_al:LIPIcs.SoCG.2023.64,
   author =	{Chubet, Oliver A. and Macnichol, Paul and Parikh, Parth and Sheehy, Donald R. and Sheth, Siddharth S.},
   title =	{{Greedy Permutations and Finite Voronoi Diagrams}},

src/Alpha_complex/utilities/alpha_complex_3d_persistence.cpp

@@ -288,7 +288,12 @@ void program_options(int argc, char *argv[], std::string &off_file_points, bool
     std::clog << std::endl;
     std::clog << "Compute the persistent homology with coefficient field Z/pZ \n";
     std::clog << "of a 3D Alpha complex defined on a set of input points.\n";
-    std::clog << "3D Alpha complex can be safe (by default) exact or fast, weighted and/or periodic\n\n";
+    std::clog << "Different versions of 3D Alpha complex computation are available:\n";
+    std::clog << " * fast: right combinatorics, values can be arbitrarily bad\n";
+    std::clog << " * safe (default): values can have a relative error at most 1e-5\n";
+    std::clog << " * exact: true values rounded to double.\n \n";
+    std::clog << "3D Alpha complex can be, or not, weighted (requires a file containing weights values)\n";
+    std::clog << "and/or periodic (requires a file describing the periodic domain).\n\n";
     std::clog << "The output diagram contains one bar per line, written with the convention: \n";
     std::clog << "   p   dim b d \n";
     std::clog << "where dim is the dimension of the homological feature,\n";

src/Alpha_complex/utilities/alpha_complex_persistence.cpp

@@ -187,6 +187,11 @@ void program_options(int argc, char *argv[], std::string &off_file_points, bool
     std::clog << std::endl;
     std::clog << "Compute the persistent homology with coefficient field Z/pZ \n";
     std::clog << "of an Alpha complex defined on a set of input points.\n \n";
+    std::clog << "Different versions of Alpha complex computation are available:\n";
+    std::clog << " * fast: right combinatorics, values can be arbitrarily bad\n";
+    std::clog << " * safe (default): values can have a relative error at most 1e-5\n";
+    std::clog << " * exact: true values rounded to double.\n \n";
+    std::clog << "Alpha complex can be, or not, weighted (requires a file containing weights values).\n\n";
     std::clog << "The output diagram contains one bar per line, written with the convention: \n";
     std::clog << "   p   dim b d \n";
     std::clog << "where dim is the dimension of the homological feature,\n";