diff options
| author | tlacombe <lacombe1993@gmail.com> | 2020-02-14 11:24:17 +0100 |
|---|---|---|
| committer | tlacombe <lacombe1993@gmail.com> | 2020-02-14 11:24:17 +0100 |
| commit | 5ad0b45a5b5387f49fe72843a74e96a346c6d6fe (patch) | |
| tree | 69b389d16485c4b3e5187b14d312843b7e2dec93 | |
| parent | 6a6bed7ca21c1ffcf6de9ed09c2a6512ecb66585 (diff) | |
| parent | bed30b19e57669c0b8ad385f1124586ed3499a2d (diff) | |
update from upstream/master and merge CMakeLists
92 files changed, 1281 insertions, 802 deletions
diff --git a/.appveyor.yml b/.appveyor.yml index 4a76ea0a..34f42dea 100644 --- a/.appveyor.yml +++ b/.appveyor.yml @@ -39,6 +39,7 @@ init: install: + - git submodule update --init - vcpkg install tbb:x64-windows boost-disjoint-sets:x64-windows boost-serialization:x64-windows boost-date-time:x64-windows boost-system:x64-windows boost-filesystem:x64-windows boost-units:x64-windows boost-thread:x64-windows boost-program-options:x64-windows eigen3:x64-windows mpfr:x64-windows mpir:x64-windows cgal:x64-windows - SET PATH=c:\Tools\vcpkg\installed\x64-windows\bin;%PATH% - SET PATH=%PYTHON%;%PYTHON%\Scripts;%PYTHON%\Library\bin;%PATH% @@ -48,7 +49,7 @@ install: - pip --version - python -m pip install --upgrade pip - pip install -U setuptools numpy matplotlib scipy Cython pytest - - pip install -U POT + - pip install -U POT pybind11 build_script: - mkdir build diff --git a/.circleci/config.yml b/.circleci/config.yml index 5e45bc14..4f86cb12 100644 --- a/.circleci/config.yml +++ b/.circleci/config.yml @@ -45,11 +45,14 @@ jobs: python: docker: - image: gudhi/ci_for_gudhi:latest + parallelism: 4 steps: - checkout - run: name: Build and test python module. Generates and tests the python documentation command: | + git submodule init + git submodule update mkdir build; cd build; cmake -DUSER_VERSION_DIR=version ..; @@ -58,10 +61,13 @@ jobs: mkdir build; cd build; cmake -DCMAKE_BUILD_TYPE=Release -DWITH_GUDHI_EXAMPLE=OFF -DWITH_GUDHI_UTILITIES=OFF -DWITH_GUDHI_PYTHON=ON -DPython_ADDITIONAL_VERSIONS=3 ..; - make all; - ctest --output-on-failure; + cd python; + python3 setup.py build_ext -j 4 --inplace; make sphinx; - cp -R python/sphinx /tmp/sphinx; + cp -R sphinx /tmp/sphinx; + python3 setup.py install; + python3 setup.py clean --all; + ctest -j 4 --output-on-failure; - store_artifacts: path: /tmp/sphinx @@ -74,6 +80,8 @@ jobs: - run: name: Generates the C++ documentation with doxygen command: | + git submodule init + git submodule update mkdir build; cd build; cmake -DCMAKE_BUILD_TYPE=Release -DWITH_GUDHI_EXAMPLE=OFF -DWITH_GUDHI_TEST=OFF -DWITH_GUDHI_UTILITIES=OFF -DWITH_GUDHI_PYTHON=OFF -DUSER_VERSION_DIR=version ..; @@ -93,4 +101,4 @@ workflows: - tests - utils - python - - doxygen
\ No newline at end of file + - doxygen diff --git a/.gitmodules b/.gitmodules new file mode 100644 index 00000000..6e8b3ab1 --- /dev/null +++ b/.gitmodules @@ -0,0 +1,3 @@ +[submodule "ext/hera"] + path = ext/hera + url = https://bitbucket.org/grey_narn/hera.git diff --git a/.travis.yml b/.travis.yml index d6c82e70..8980be10 100644 --- a/.travis.yml +++ b/.travis.yml @@ -36,10 +36,13 @@ cache: - $HOME/.cache/pip - $HOME/Library/Caches/Homebrew +before_install: + - brew update && brew unlink python@2 && brew upgrade python + addons: homebrew: - update: true packages: + - python3 - cmake - graphviz - doxygen @@ -49,7 +52,6 @@ addons: - mpfr - tbb - cgal - - python3 before_cache: - rm -f $HOME/.cache/pip/log/debug.log @@ -59,7 +61,7 @@ before_cache: install: - python3 -m pip install --upgrade pip setuptools wheel - python3 -m pip install --user pytest Cython sphinx sphinxcontrib-bibtex sphinx-paramlinks matplotlib numpy scipy scikit-learn - - python3 -m pip install --user POT + - python3 -m pip install --user POT pybind11 script: - rm -rf build diff --git a/CMakeGUDHIVersion.txt b/CMakeGUDHIVersion.txt index eb2a0666..0f827b9e 100644 --- a/CMakeGUDHIVersion.txt +++ b/CMakeGUDHIVersion.txt @@ -1,6 +1,6 @@ set (GUDHI_MAJOR_VERSION 3) -set (GUDHI_MINOR_VERSION 0) -set (GUDHI_PATCH_VERSION 0) +set (GUDHI_MINOR_VERSION 1) +set (GUDHI_PATCH_VERSION 1) set(GUDHI_VERSION ${GUDHI_MAJOR_VERSION}.${GUDHI_MINOR_VERSION}.${GUDHI_PATCH_VERSION}) message(STATUS "GUDHI version : ${GUDHI_VERSION}") diff --git a/CMakeLists.txt b/CMakeLists.txt index 5dcc6803..d9244dc0 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -65,5 +65,7 @@ include(GUDHI_user_version_target) # For "make doxygen" - Requires GUDHI_USER_VERSION_DIR to be set - Done in GUDHI_user_version_target for dev version include(GUDHI_doxygen_target) +configure_file(${CMAKE_SOURCE_DIR}/for_dev/for_maintainers/new_gudhi_version_creation.md "${CMAKE_CURRENT_BINARY_DIR}/" @ONLY) + message("++ GUDHI_MODULES list is:\"${GUDHI_MODULES}\"") message("++ GUDHI_MISSING_MODULES list is:\"${GUDHI_MISSING_MODULES}\"") diff --git a/Conventions.txt b/Conventions.txt deleted file mode 100644 index e4ae7925..00000000 --- a/Conventions.txt +++ /dev/null @@ -1 +0,0 @@ -Please refer to the Wiki: https://gforge.inria.fr/plugins/mediawiki/wiki/gudhi/index.php/Conventions
\ No newline at end of file diff --git a/Dockerfile_for_circleci_image b/Dockerfile_for_circleci_image index f0c73d76..ebd2f366 100644 --- a/Dockerfile_for_circleci_image +++ b/Dockerfile_for_circleci_image @@ -25,6 +25,7 @@ ENV LC_ALL en_US.UTF-8 # Required for Gudhi compilation RUN apt-get install -y make \ + git \ g++ \ cmake \ graphviz \ @@ -43,10 +44,12 @@ RUN apt-get install -y make \ python3-pip \ python3-pytest \ python3-tk \ + python3-pybind11 \ libfreetype6-dev \ pkg-config RUN pip3 install \ + setuptools \ numpy \ matplotlib \ scipy \ @@ -55,7 +58,8 @@ RUN pip3 install \ scikit-learn \ sphinx \ sphinx-paramlinks \ - sphinxcontrib-bibtex + sphinxcontrib-bibtex \ + tensorflow # apt clean up RUN apt autoremove && rm -rf /var/lib/apt/lists/* diff --git a/Dockerfile_gudhi_installation b/Dockerfile_gudhi_installation index 9fe20730..f9e8813b 100644 --- a/Dockerfile_gudhi_installation +++ b/Dockerfile_gudhi_installation @@ -42,6 +42,7 @@ RUN apt-get install -y make \ python3-pip \ python3-pytest \ python3-tk \ + python3-pybind11 \ libfreetype6-dev \ pkg-config \ curl @@ -50,16 +51,18 @@ RUN pip3 install \ numpy \ matplotlib \ scipy \ - Cython + Cython \ + POT \ + scikit-learn # apt clean up RUN apt autoremove && rm -rf /var/lib/apt/lists/* -RUN curl -LO "https://github.com/GUDHI/gudhi-devel/releases/download/tags%2Fgudhi-release-3.0.0/gudhi.3.0.0.tar.gz" \ -&& tar xf gudhi.3.0.0.tar.gz \ -&& cd gudhi.3.0.0 \ +RUN curl -LO "https://github.com/GUDHI/gudhi-devel/releases/download/tags%2Fgudhi-release-3.1.1/gudhi.3.1.1.tar.gz" \ +&& tar xf gudhi.3.1.1.tar.gz \ +&& cd gudhi.3.1.1 \ && mkdir build && cd build && cmake -DCMAKE_BUILD_TYPE=Release -DWITH_GUDHI_PYTHON=OFF -DPython_ADDITIONAL_VERSIONS=3 .. \ && make all test install \ && cmake -DWITH_GUDHI_PYTHON=ON . \ && cd python \ -&& python3 setup.py install
\ No newline at end of file +&& python3 setup.py install @@ -10,6 +10,15 @@ The GUDHI library is a generic open source C++ library, with a Python interface, for Topological Data Analysis (TDA) and Higher Dimensional Geometry Understanding. The library offers state-of-the-art data structures and algorithms to construct simplicial complexes and compute persistent homology. +# Source code + +We recommend that users get official releases from [the GUDHI website](https://gudhi.inria.fr/). + +For potential contributors, to fully checkout GUDHI, after cloning the git repository, you may also need to checkout its submodules using +```sh +git submodule update --init +``` + # Compilation and installation To install GUDHI, you can follow the [C++ compilation procedure](https://gudhi.inria.fr/doc/latest/installation.html), the [Python compilation procedure](https://gudhi.inria.fr/python/latest/installation.html), use our [conda-forge package](https://gudhi.inria.fr/conda/), or [go with Docker](https://gudhi.inria.fr/dockerfile/). diff --git a/biblio/bibliography.bib b/biblio/bibliography.bib index a1b951e0..3bbe7960 100644 --- a/biblio/bibliography.bib +++ b/biblio/bibliography.bib @@ -1180,3 +1180,15 @@ language={English} booktitle = {In Neural Information Processing Systems}, year = {2007} } +@inproceedings{10.5555/3327546.3327645, +author = {Lacombe, Th\'{e}o and Cuturi, Marco and Oudot, Steve}, +title = {Large Scale Computation of Means and Clusters for Persistence Diagrams Using Optimal Transport}, +year = {2018}, +publisher = {Curran Associates Inc.}, +address = {Red Hook, NY, USA}, +booktitle = {Proceedings of the 32nd International Conference on Neural Information Processing Systems}, +pages = {9792–9802}, +numpages = {11}, +location = {Montr\'{e}al, Canada}, +series = {NIPS’18} +} diff --git a/ext/hera b/ext/hera new file mode 160000 +Subproject 9a89971855acefe39dce0e2adadf53b88ca8f68 diff --git a/for_dev/code_conventions.md b/for_dev/code_conventions.md new file mode 100644 index 00000000..5882f78e --- /dev/null +++ b/for_dev/code_conventions.md @@ -0,0 +1,26 @@ +# Naming conventions + +## C++ + +### In the code: +* The classes and functions of a package should be in a sub-namespace of the `Gudhi` namespace. The sub-namespace names are in lowercase and use underscore separators. E.g. `Gudhi::package_name::` +* Concepts are named with camel case starting with uppercase. E.g. `PersistentHomology` for the concept of Persitence homology. +* Classes start with an uppercase letter and use underscore separators. E.g. `Skeleton_blocker_contractor`. +* Member functions and free functions are in lowercase and use underscore separators. E.g. `int num_vertices()`. +* Constants and macros are in uppercase. +* Macros should begin with the prefix `GUDHI_`. + +### File names: +* All headers are named *.h and all sources are named *.cpp. +* If a single class or function is provided in a file, its name (with the same letter case) should be used for the file name. +* If a file does not contain a single class, its name should not begin with a capital letter. +* Test files should be called `test_[what_is_tested].cpp`. E.g. `test_sparsify_point_set.cpp` +* Example files should be called `example_[what_it_is].cpp`. E.g. `example_sparsify_point_set.cpp` + +### In CMakeLists.txt files: +* The name of the "project" should be in this form: `Package_[tests|examples|…]`. E.g. `project(Simplex_tree_examples)`. +* The name if each "target" (first parameter of add_executable) should be in this form: `Package_{name of the cpp file without extension}`. E.g `add_executable(Subsampling_test_sparsify_point_set test_sparsify_point_set.cpp)`. + +## Python + +In progress...
\ No newline at end of file diff --git a/for_dev/for_maintainers/new_gudhi_version_creation.md b/for_dev/for_maintainers/new_gudhi_version_creation.md new file mode 100644 index 00000000..4a40f373 --- /dev/null +++ b/for_dev/for_maintainers/new_gudhi_version_creation.md @@ -0,0 +1,97 @@ +# Create a new GUDHI version + +We will consider that all operations will be performed in a brand new clone of the main project: +```bash +git clone https://github.com/GUDHI/gudhi-devel.git +cd gudhi-devel +``` + +## Version file modification + +**Edit the file CMakeGUDHIVersion.txt**, and increment major, minor, or patch version number, in function of the version new delivery. +```bash +# cf. .gitignore - ignore this if it is a fresh clone version +rm -rf data/points/COIL_database/lucky_cat.off_dist data/points/COIL_database/lucky_cat.off_sc.dot data/points/KleinBottle5D.off_dist data/points/KleinBottle5D.off_sc.dot data/points/human.off_dist data/points/human.off_sc.off data/points/human.off_sc.txt +``` + +Checkin the modifications, build and test the version: +```bash +mkdir build +cd build +cmake -DCGAL_DIR=/your/path/to/CGAL -DWITH_GUDHI_EXAMPLE=ON -DWITH_GUDHI_BENCHMARK=ON -DUSER_VERSION_DIR=gudhi.@GUDHI_VERSION@ -DPython_ADDITIONAL_VERSIONS=3 .. +make user_version +date +"%d-%m-%Y-%T" > gudhi.@GUDHI_VERSION@/timestamp.txt +tar -czvf gudhi.@GUDHI_VERSION@.tar.gz gudhi.@GUDHI_VERSION@ +md5sum gudhi.@GUDHI_VERSION@.tar.gz > md5sum.txt +sha256sum gudhi.@GUDHI_VERSION@.tar.gz > sha256sum.txt +sha512sum gudhi.@GUDHI_VERSION@.tar.gz > sha512sum.txt + +make -j all test +``` + +***[Check there are no error]*** + +## Create the documentation +```bash +mkdir gudhi.doc.@GUDHI_VERSION@ +make doxygen 2>&1 | tee dox.log && grep warning dox.log +``` + +***[Check there are no error and the warnings]*** + +```bash +cp -R gudhi.@GUDHI_VERSION@/doc/html gudhi.doc.@GUDHI_VERSION@/cpp +cd gudhi.@GUDHI_VERSION@ +rm -rf build; mkdir build; cd build; cmake -DCGAL_DIR=/your/path/to/CGAL -DWITH_GUDHI_EXAMPLE=ON -DPython_ADDITIONAL_VERSIONS=3 .. +export LC_ALL=en_US.UTF-8 # cf. bug +make sphinx +``` + +***[Check there are no error]*** + +```bash +cp -R python/sphinx ../../gudhi.doc.@GUDHI_VERSION@/python +cd ../.. +tar -czvf gudhi.doc.@GUDHI_VERSION@.tar.gz gudhi.doc.@GUDHI_VERSION@ + +cd gudhi.@GUDHI_VERSION@/build +make all test +``` + +***[Check there are no error]*** + +## Upload the documentation + +Upload by ftp the content of the directory gudhi.doc.@GUDHI_VERSION@/cpp in a new directory on ForgeLogin@scm.gforge.inria.fr:/home/groups/gudhi/htdocs/doc/@GUDHI_VERSION@ + +Upload by ftp the content of the directory gudhi.doc.@GUDHI_VERSION@/python in a new directory on ForgeLogin@scm.gforge.inria.fr:/home/groups/gudhi/htdocs/python/@GUDHI_VERSION@ + +Through ssh, make the **latest** link to your new version of the documentation: +```bash +ssh ForgeLogin@scm.gforge.inria.fr +cd /home/groups/gudhi/htdocs/doc +rm latest +ln -s @GUDHI_VERSION@ latest +cd /home/groups/gudhi/htdocs/python +rm latest +ln -s @GUDHI_VERSION@ latest +``` + +## Put a version label on files + +* Go on page https://github.com/GUDHI/gudhi-devel/releases/new +* Name the tag: tags/gudhi-release-@GUDHI_VERSION@ +* Name the release GUDHI @GUDHI_VERSION@ +* Write the release note +* Drag'n drop *gudhi.@GUDHI_VERSION@.tar.gz*, *md5sum.txt*, *sha256sum.txt*, *sha512sum.txt* files +* Tick the *This is a pre-release* check button if this is a release candidate (untick if this is an official version) +* Click the *Publish the release* button + +***[Where X, Y and Z corresponds respectively to the major, minor, and patch version number]*** + + +## Mail sending +Send version mail to the following lists : +* gudhi-devel@lists.gforge.inria.fr +* gudhi-users@lists.gforge.inria.fr (not for release candidate) + diff --git a/for_dev/for_maintainers/next_release_template.md b/for_dev/for_maintainers/next_release_template.md new file mode 100644 index 00000000..a2805a55 --- /dev/null +++ b/for_dev/for_maintainers/next_release_template.md @@ -0,0 +1,28 @@ +We are pleased to announce the release 3.X.X of the GUDHI library. + +As a major new feature, the GUDHI library now offers ... + +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.X-1.X-1: + +- [Module](link) + - ... + +- [Module](link) + - ... + +- Miscellaneous + - The [list of bugs that were solved since GUDHI-3.X-1.X-1](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.1.1+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. + +We kindly ask users to cite the GUDHI library as appropriately as possible in their papers, and to mention the use of the GUDHI library on the web pages of their projects using GUDHI and provide us with links to these web pages. + +We provide [bibtex entries](https://gudhi.inria.fr/doc/latest/_citation.html) for the modules of the User and Reference Manual, as well as for publications directly related to the GUDHI library. + +Feel free to [contact us](https://gudhi.inria.fr/contact/) in case you have any questions or remarks. + +For further information about downloading and installing the library ([C++](https://gudhi.inria.fr/doc/latest/installation.html) or [Python](https://gudhi.inria.fr/python/latest/installation.html)), please visit the [GUDHI web site](https://gudhi.inria.fr/). + diff --git a/for_dev/next_release.md b/for_dev/next_release.md new file mode 100644 index 00000000..a2805a55 --- /dev/null +++ b/for_dev/next_release.md @@ -0,0 +1,28 @@ +We are pleased to announce the release 3.X.X of the GUDHI library. + +As a major new feature, the GUDHI library now offers ... + +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.X-1.X-1: + +- [Module](link) + - ... + +- [Module](link) + - ... + +- Miscellaneous + - The [list of bugs that were solved since GUDHI-3.X-1.X-1](https://github.com/GUDHI/gudhi-devel/issues?q=label%3A3.1.1+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. + +We kindly ask users to cite the GUDHI library as appropriately as possible in their papers, and to mention the use of the GUDHI library on the web pages of their projects using GUDHI and provide us with links to these web pages. + +We provide [bibtex entries](https://gudhi.inria.fr/doc/latest/_citation.html) for the modules of the User and Reference Manual, as well as for publications directly related to the GUDHI library. + +Feel free to [contact us](https://gudhi.inria.fr/contact/) in case you have any questions or remarks. + +For further information about downloading and installing the library ([C++](https://gudhi.inria.fr/doc/latest/installation.html) or [Python](https://gudhi.inria.fr/python/latest/installation.html)), please visit the [GUDHI web site](https://gudhi.inria.fr/). + diff --git a/src/Alpha_complex/doc/Intro_alpha_complex.h b/src/Alpha_complex/doc/Intro_alpha_complex.h index 3c32a1e6..a8b1a106 100644 --- a/src/Alpha_complex/doc/Intro_alpha_complex.h +++ b/src/Alpha_complex/doc/Intro_alpha_complex.h @@ -31,8 +31,8 @@ namespace alpha_complex { * circumsphere is empty (the simplex is then said to be Gabriel), and as the minimum of the filtration * values of the codimension 1 cofaces that make it not Gabriel otherwise. * - * All simplices that have a filtration value strictly greater than a given alpha squared value are not inserted into - * the complex. + * All simplices that have a filtration value \f$ > \alpha^2 \f$ are removed from the Delaunay complex + * when creating the simplicial complex if it is specified. * * \image html "alpha_complex_representation.png" "Alpha-complex representation" * @@ -46,8 +46,8 @@ namespace alpha_complex { * \cite cgal:s-gkd-19b from CGAL as template parameter. * * \remark - * - When the simplicial complex is constructed with an infinite value of alpha, the complex is a Delaunay - * complex. + * - When an \f$\alpha\f$-complex is constructed with an infinite value of \f$ \alpha^2 \f$, the complex is a Delaunay + * complex (with special filtration values). * - For people only interested in the topology of the \ref alpha_complex (for instance persistence), * \ref alpha_complex is equivalent to the \ref cech_complex and much smaller if you do not bound the radii. * \ref cech_complex can still make sense in higher dimension precisely because you can bound the radii. @@ -135,13 +135,13 @@ namespace alpha_complex { * * \subsubsection nondecreasing Non decreasing filtration values * - * As the squared radii computed by CGAL are an approximation, it might happen that these alpha squared values do not - * quite define a proper filtration (i.e. non-decreasing with respect to inclusion). + * As the squared radii computed by CGAL are an approximation, it might happen that these \f$ \alpha^2 \f$ values do + * not quite define a proper filtration (i.e. non-decreasing with respect to inclusion). * We fix that up by calling `SimplicialComplexForAlpha::make_filtration_non_decreasing()`. * * \subsubsection pruneabove Prune above given filtration value * - * The simplex tree is pruned from the given maximum alpha squared value (cf. + * The simplex tree is pruned from the given maximum \f$ \alpha^2 \f$ value (cf. * `SimplicialComplexForAlpha::prune_above_filtration()`). * In the following example, the value is given by the user as argument of the program. * diff --git a/src/Alpha_complex/doc/alpha_complex_representation.ipe b/src/Alpha_complex/doc/alpha_complex_representation.ipe index e8096b93..40ff1d0f 100644 --- a/src/Alpha_complex/doc/alpha_complex_representation.ipe +++ b/src/Alpha_complex/doc/alpha_complex_representation.ipe @@ -1,7 +1,7 @@ <?xml version="1.0"?> <!DOCTYPE ipe SYSTEM "ipe.dtd"> -<ipe version="70107" creator="Ipe 7.1.10"> -<info created="D:20150603143945" modified="D:20160404172133"/> +<ipe version="70206" creator="Ipe 7.2.7"> +<info created="D:20150603143945" modified="D:20200110100102"/> <ipestyle name="basic"> <symbol name="arrow/arc(spx)"> <path stroke="sym-stroke" fill="sym-stroke" pen="sym-pen"> @@ -305,7 +305,7 @@ h 108.275 743.531 m 166.45 743.531 l </path> -<text matrix="1 0 0 1 142.618 -109.867" transformations="translations" pos="127.397 746.763" stroke="darkgray" type="label" width="6.41" height="4.289" depth="0" valign="baseline">$\alpha$</text> +<text matrix="1 0 0 1 126.618 -109.867" transformations="translations" pos="127.397 746.763" stroke="darkgray" type="label" width="45.707" height="9.041" depth="1.32" valign="baseline" style="math">\alpha = \sqrt{32.0}</text> <use matrix="1 0 0 1 -209.478 12.0238" name="mark/fdisk(sfx)" pos="300 720" size="normal" stroke="black" fill="white"/> <use matrix="1 0 0 1 -210.178 22.1775" name="mark/fdisk(sfx)" pos="280 660" size="normal" stroke="black" fill="white"/> <use matrix="1 0 0 1 -210.178 22.1775" name="mark/fdisk(sfx)" pos="370 690" size="normal" stroke="black" fill="white"/> diff --git a/src/Alpha_complex/doc/alpha_complex_representation.png b/src/Alpha_complex/doc/alpha_complex_representation.png Binary files differindex 7b81cd69..5ebb1e75 100644 --- a/src/Alpha_complex/doc/alpha_complex_representation.png +++ b/src/Alpha_complex/doc/alpha_complex_representation.png diff --git a/src/Alpha_complex/include/gudhi/Alpha_complex.h b/src/Alpha_complex/include/gudhi/Alpha_complex.h index 6b4d8463..f2a05e95 100644 --- a/src/Alpha_complex/include/gudhi/Alpha_complex.h +++ b/src/Alpha_complex/include/gudhi/Alpha_complex.h @@ -121,8 +121,8 @@ class Alpha_complex { // size_type type from CGAL. typedef typename Delaunay_triangulation::size_type size_type; - // Map type to switch from simplex tree vertex handle to CGAL vertex iterator. - typedef typename std::map< std::size_t, CGAL_vertex_iterator > Vector_vertex_iterator; + // Structure to switch from simplex tree vertex handle to CGAL vertex iterator. + typedef typename std::vector< CGAL_vertex_iterator > Vector_vertex_iterator; private: /** \brief Vertex iterator vector to switch from simplex tree vertex handle to CGAL vertex iterator. @@ -191,14 +191,6 @@ class Alpha_complex { return vertex_handle_to_iterator_.at(vertex)->point(); } - /** \brief number_of_vertices returns the number of vertices (same as the number of points). - * - * @return The number of vertices. - */ - std::size_t number_of_vertices() const { - return vertex_handle_to_iterator_.size(); - } - private: template<typename InputPointRange > void init_from_range(const InputPointRange& points) { @@ -238,14 +230,16 @@ class Alpha_complex { hint = pos->full_cell(); } // -------------------------------------------------------------------------------------------- - // double map to retrieve simplex tree vertex handles from CGAL vertex iterator and vice versa + // structure to retrieve CGAL points from vertex handle - one vertex handle per point. + // Needs to be constructed before as vertex handles arrives in no particular order. + vertex_handle_to_iterator_.resize(point_cloud.size()); // Loop on triangulation vertices list for (CGAL_vertex_iterator vit = triangulation_->vertices_begin(); vit != triangulation_->vertices_end(); ++vit) { if (!triangulation_->is_infinite(*vit)) { #ifdef DEBUG_TRACES std::cout << "Vertex insertion - " << vit->data() << " -> " << vit->point() << std::endl; #endif // DEBUG_TRACES - vertex_handle_to_iterator_.emplace(vit->data(), vit); + vertex_handle_to_iterator_[vit->data()] = vit; } } // -------------------------------------------------------------------------------------------- diff --git a/src/Alpha_complex/test/Alpha_complex_unit_test.cpp b/src/Alpha_complex/test/Alpha_complex_unit_test.cpp index 40b3fe09..27b671dd 100644 --- a/src/Alpha_complex/test/Alpha_complex_unit_test.cpp +++ b/src/Alpha_complex/test/Alpha_complex_unit_test.cpp @@ -53,20 +53,12 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(Alpha_complex_from_OFF_file, TestedKernel, list_of Gudhi::alpha_complex::Alpha_complex<TestedKernel> alpha_complex_from_file(off_file_name); - std::cout << "alpha_complex_from_points.number_of_vertices()=" << alpha_complex_from_file.number_of_vertices() - << std::endl; - BOOST_CHECK(alpha_complex_from_file.number_of_vertices() == 7); - Gudhi::Simplex_tree<> simplex_tree_60; BOOST_CHECK(alpha_complex_from_file.create_complex(simplex_tree_60, max_alpha_square_value)); std::cout << "simplex_tree_60.dimension()=" << simplex_tree_60.dimension() << std::endl; BOOST_CHECK(simplex_tree_60.dimension() == 2); - std::cout << "alpha_complex_from_points.number_of_vertices()=" << alpha_complex_from_file.number_of_vertices() - << std::endl; - BOOST_CHECK(alpha_complex_from_file.number_of_vertices() == 7); - std::cout << "simplex_tree_60.num_vertices()=" << simplex_tree_60.num_vertices() << std::endl; BOOST_CHECK(simplex_tree_60.num_vertices() == 7); @@ -128,10 +120,6 @@ BOOST_AUTO_TEST_CASE(Alpha_complex_from_points) { Gudhi::Simplex_tree<> simplex_tree; BOOST_CHECK(alpha_complex_from_points.create_complex(simplex_tree)); - std::cout << "alpha_complex_from_points.number_of_vertices()=" << alpha_complex_from_points.number_of_vertices() - << std::endl; - BOOST_CHECK(alpha_complex_from_points.number_of_vertices() == points.size()); - // Another way to check num_simplices std::cout << "Iterator on alpha complex simplices in the filtration order, with [filtration value]:" << std::endl; int num_simplices = 0; @@ -151,7 +139,7 @@ BOOST_AUTO_TEST_CASE(Alpha_complex_from_points) { std::cout << "simplex_tree.dimension()=" << simplex_tree.dimension() << std::endl; BOOST_CHECK(simplex_tree.dimension() == 3); std::cout << "simplex_tree.num_vertices()=" << simplex_tree.num_vertices() << std::endl; - BOOST_CHECK(simplex_tree.num_vertices() == 4); + BOOST_CHECK(simplex_tree.num_vertices() == points.size()); for (auto f_simplex : simplex_tree.filtration_simplex_range()) { switch (simplex_tree.dimension(f_simplex)) { @@ -261,10 +249,6 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(Alpha_complex_from_empty_points, TestedKernel, lis Gudhi::Simplex_tree<> simplex_tree; BOOST_CHECK(!alpha_complex_from_points.create_complex(simplex_tree)); - std::cout << "alpha_complex_from_points.number_of_vertices()=" << alpha_complex_from_points.number_of_vertices() - << std::endl; - BOOST_CHECK(alpha_complex_from_points.number_of_vertices() == points.size()); - std::cout << "simplex_tree.num_simplices()=" << simplex_tree.num_simplices() << std::endl; BOOST_CHECK(simplex_tree.num_simplices() == 0); @@ -272,5 +256,45 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(Alpha_complex_from_empty_points, TestedKernel, lis BOOST_CHECK(simplex_tree.dimension() == -1); std::cout << "simplex_tree.num_vertices()=" << simplex_tree.num_vertices() << std::endl; - BOOST_CHECK(simplex_tree.num_vertices() == 0); + BOOST_CHECK(simplex_tree.num_vertices() == points.size()); +} + +using Inexact_kernel_2 = CGAL::Epick_d< CGAL::Dimension_tag<2> >; +using Exact_kernel_2 = CGAL::Epeck_d< CGAL::Dimension_tag<2> >; +using list_of_kernel_2_variants = boost::mpl::list<Inexact_kernel_2, Exact_kernel_2>; + +BOOST_AUTO_TEST_CASE_TEMPLATE(Alpha_complex_with_duplicated_points, TestedKernel, list_of_kernel_2_variants) { + std::cout << "========== Alpha_complex_with_duplicated_points ==========" << std::endl; + + using Point = typename TestedKernel::Point_d; + using Vector_of_points = std::vector<Point>; + + // ---------------------------------------------------------------------------- + // Init of a list of points + // ---------------------------------------------------------------------------- + Vector_of_points points; + points.push_back(Point(1.0, 1.0)); + points.push_back(Point(7.0, 0.0)); + points.push_back(Point(4.0, 6.0)); + points.push_back(Point(9.0, 6.0)); + points.push_back(Point(0.0, 14.0)); + points.push_back(Point(2.0, 19.0)); + points.push_back(Point(9.0, 17.0)); + // duplicated points + points.push_back(Point(1.0, 1.0)); + points.push_back(Point(7.0, 0.0)); + + // ---------------------------------------------------------------------------- + // Init of an alpha complex from the list of points + // ---------------------------------------------------------------------------- + std::cout << "Init" << std::endl; + Gudhi::alpha_complex::Alpha_complex<TestedKernel> alpha_complex_from_points(points); + + Gudhi::Simplex_tree<> simplex_tree; + std::cout << "create_complex" << std::endl; + BOOST_CHECK(alpha_complex_from_points.create_complex(simplex_tree)); + + std::cout << "simplex_tree.num_vertices()=" << simplex_tree.num_vertices() + << std::endl; + BOOST_CHECK(simplex_tree.num_vertices() < points.size()); } diff --git a/src/Bottleneck_distance/include/gudhi/Persistence_graph.h b/src/Bottleneck_distance/include/gudhi/Persistence_graph.h index f791e37c..e1e3522e 100644 --- a/src/Bottleneck_distance/include/gudhi/Persistence_graph.h +++ b/src/Bottleneck_distance/include/gudhi/Persistence_graph.h @@ -25,7 +25,7 @@ namespace Gudhi { namespace persistence_diagram { -/** \internal \brief Structure representing an euclidean bipartite graph containing +/** \internal \brief Structure representing a Euclidean bipartite graph containing * the points from the two persistence diagrams (including the projections). * * \ingroup bottleneck_distance diff --git a/src/Bottleneck_distance/test/bottleneck_unit_test.cpp b/src/Bottleneck_distance/test/bottleneck_unit_test.cpp index 3fc6fc7b..2c520045 100644 --- a/src/Bottleneck_distance/test/bottleneck_unit_test.cpp +++ b/src/Bottleneck_distance/test/bottleneck_unit_test.cpp @@ -15,6 +15,7 @@ #include <random> #include <gudhi/Bottleneck.h> +#include <gudhi/Unitary_tests_utils.h> using namespace Gudhi::persistence_diagram; @@ -59,24 +60,24 @@ BOOST_AUTO_TEST_CASE(persistence_graph) { BOOST_CHECK(g.size() == (n1 + n2)); // BOOST_CHECK((int) d.size() == (n1 + n2)*(n1 + n2) + n1 + n2 + 1); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, 0)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n1 - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n2 - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n2)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, (n1 + n2) - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, 0)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n1 - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n2 - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n2)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, (n1 + n2) - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, 0)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n1 - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n2 - 1)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n2)) > 0); - BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, (n1 + n2) - 1)) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(0, 0))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(0, n1 - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(0, n1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(0, n2 - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(0, n2))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(0, (n1 + n2) - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(n1, 0))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(n1, n1 - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(n1, n1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(n1, n2 - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(n1, n2))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance(n1, (n1 + n2) - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance((n1 + n2) - 1, 0))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance((n1 + n2) - 1, n1 - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance((n1 + n2) - 1, n1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance((n1 + n2) - 1, n2 - 1))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance((n1 + n2) - 1, n2))) > 0); + BOOST_CHECK(std::count(d.begin(), d.end(), GUDHI_PROTECT_FLOAT(g.distance((n1 + n2) - 1, (n1 + n2) - 1))) > 0); } BOOST_AUTO_TEST_CASE(neighbors_finder) { diff --git a/src/Nerve_GIC/include/gudhi/GIC.h b/src/Nerve_GIC/include/gudhi/GIC.h index b8169c59..2a6d4788 100644 --- a/src/Nerve_GIC/include/gudhi/GIC.h +++ b/src/Nerve_GIC/include/gudhi/GIC.h @@ -14,7 +14,7 @@ #ifdef GUDHI_USE_TBB #include <tbb/parallel_for.h> -#include <tbb/mutex.h> +#include <mutex> #endif #include <gudhi/Debug_utils.h> @@ -459,7 +459,7 @@ class Cover_complex { // This cannot be parallelized if thread_local is not defined // thread_local is not defined for XCode < v.8 #if defined(GUDHI_USE_TBB) && defined(GUDHI_CAN_USE_CXX11_THREAD_LOCAL) - tbb::mutex deltamutex; + std::mutex deltamutex; tbb::parallel_for(0, N, [&](int i){ std::vector<int> samples(m); SampleWithoutReplacement(n, m, samples); @@ -707,7 +707,7 @@ class Cover_complex { // Sort points according to function values std::vector<int> points(n); for (int i = 0; i < n; i++) points[i] = i; - std::sort(points.begin(), points.end(), [=](const int & p1, const int & p2){return (this->func[p1] < this->func[p2]);}); + std::sort(points.begin(), points.end(), [this](int p1, int p2){return (this->func[p1] < this->func[p2]);}); int id = 0; int pos = 0; @@ -765,7 +765,7 @@ class Cover_complex { #ifdef GUDHI_USE_TBB if (verbose) std::cout << "Computing connected components (parallelized)..." << std::endl; - tbb::mutex covermutex, idmutex; + std::mutex covermutex, idmutex; tbb::parallel_for(0, res, [&](int i){ // Compute connected components Graph G = one_skeleton.create_subgraph(); @@ -895,7 +895,7 @@ class Cover_complex { // Compute the geodesic distances to subsamples with Dijkstra #ifdef GUDHI_USE_TBB if (verbose) std::cout << "Computing geodesic distances (parallelized)..." << std::endl; - tbb::mutex coverMutex; tbb::mutex mindistMutex; + std::mutex coverMutex; std::mutex mindistMutex; tbb::parallel_for(0, m, [&](int i){ int seed = voronoi_subsamples[i]; std::vector<double> dmap(n); diff --git a/src/Persistence_representations/include/gudhi/Persistence_intervals.h b/src/Persistence_representations/include/gudhi/Persistence_intervals.h index e2db4572..ea4220ea 100644 --- a/src/Persistence_representations/include/gudhi/Persistence_intervals.h +++ b/src/Persistence_representations/include/gudhi/Persistence_intervals.h @@ -6,6 +6,8 @@ * * Modification(s): * - YYYY/MM Author: Description of the modification + * - 2019/12 Vincent Rouvreau: Fix #118 - Make histogram_of_lengths and cumulative_histogram_of_lengths + * return the exact number_of_bins (was failing on x86) */ #ifndef PERSISTENCE_INTERVALS_H_ @@ -335,6 +337,9 @@ std::vector<size_t> Persistence_intervals::histogram_of_lengths(size_t number_of getchar(); } } + // we want number of bins equals to number_of_bins (some unexpected results on x86) + result[number_of_bins-1]+=result[number_of_bins]; + result.resize(number_of_bins); if (dbg) { for (size_t i = 0; i != result.size(); ++i) std::cerr << result[i] << std::endl; diff --git a/src/Persistence_representations/test/persistence_intervals_test.cpp b/src/Persistence_representations/test/persistence_intervals_test.cpp index 3b7a2049..02ea8edb 100644 --- a/src/Persistence_representations/test/persistence_intervals_test.cpp +++ b/src/Persistence_representations/test/persistence_intervals_test.cpp @@ -6,6 +6,8 @@ * * Modification(s): * - YYYY/MM Author: Description of the modification + * - 2019/12 Vincent Rouvreau: Fix #118 - Make histogram_of_lengths and cumulative_histogram_of_lengths + * return the exact number_of_bins (was failing on x86) */ #define BOOST_TEST_DYN_LINK @@ -32,17 +34,8 @@ BOOST_AUTO_TEST_CASE(check_min_max_function) { BOOST_AUTO_TEST_CASE(check_length_of_dominant_intervals) { Persistence_intervals p("data/file_with_diagram"); std::vector<double> dominant_ten_intervals_length = p.length_of_dominant_intervals(10); - std::vector<double> dominant_intervals_length; - dominant_intervals_length.push_back(0.862625); - dominant_intervals_length.push_back(0.800893); - dominant_intervals_length.push_back(0.762061); - dominant_intervals_length.push_back(0.756501); - dominant_intervals_length.push_back(0.729367); - dominant_intervals_length.push_back(0.718177); - dominant_intervals_length.push_back(0.708395); - dominant_intervals_length.push_back(0.702844); - dominant_intervals_length.push_back(0.700468); - dominant_intervals_length.push_back(0.622177); + std::vector<double> dominant_intervals_length{0.862625, 0.800893, 0.762061, 0.756501, 0.729367, + 0.718177, 0.708395, 0.702844, 0.700468, 0.622177}; for (size_t i = 0; i != dominant_ten_intervals_length.size(); ++i) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(dominant_ten_intervals_length[i], dominant_intervals_length[i], Gudhi::Persistence_representations::epsi); @@ -52,17 +45,11 @@ BOOST_AUTO_TEST_CASE(check_dominant_intervals) { Persistence_intervals p("data/file_with_diagram"); std::vector<std::pair<double, double> > ten_dominant_intervals = p.dominant_intervals(10); - std::vector<std::pair<double, double> > templ; - templ.push_back(std::pair<double, double>(0.114718, 0.977343)); - templ.push_back(std::pair<double, double>(0.133638, 0.93453)); - templ.push_back(std::pair<double, double>(0.104599, 0.866659)); - templ.push_back(std::pair<double, double>(0.149798, 0.906299)); - templ.push_back(std::pair<double, double>(0.247352, 0.976719)); - templ.push_back(std::pair<double, double>(0.192675, 0.910852)); - templ.push_back(std::pair<double, double>(0.191836, 0.900231)); - templ.push_back(std::pair<double, double>(0.284998, 0.987842)); - templ.push_back(std::pair<double, double>(0.294069, 0.994537)); - templ.push_back(std::pair<double, double>(0.267421, 0.889597)); + std::vector<std::pair<double, double> > templ{ {0.114718, 0.977343}, {0.133638, 0.93453}, + {0.104599, 0.866659}, {0.149798, 0.906299}, + {0.247352, 0.976719}, {0.192675, 0.910852}, + {0.191836, 0.900231}, {0.284998, 0.987842}, + {0.294069, 0.994537}, {0.267421, 0.889597} }; for (size_t i = 0; i != ten_dominant_intervals.size(); ++i) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(ten_dominant_intervals[i].first, templ[i].first, @@ -75,18 +62,7 @@ BOOST_AUTO_TEST_CASE(check_dominant_intervals) { BOOST_AUTO_TEST_CASE(check_histogram_of_lengths) { Persistence_intervals p("data/file_with_diagram"); std::vector<size_t> histogram = p.histogram_of_lengths(10); - std::vector<size_t> template_histogram; - template_histogram.push_back(10); - template_histogram.push_back(5); - template_histogram.push_back(3); - template_histogram.push_back(4); - template_histogram.push_back(4); - template_histogram.push_back(3); - template_histogram.push_back(6); - template_histogram.push_back(1); - template_histogram.push_back(7); - template_histogram.push_back(1); - template_histogram.push_back(1); + std::vector<size_t> template_histogram{10, 5, 3, 4, 4, 3, 6, 1, 7, 2}; for (size_t i = 0; i != histogram.size(); ++i) { BOOST_CHECK(histogram[i] == template_histogram[i]); } @@ -95,18 +71,7 @@ BOOST_AUTO_TEST_CASE(check_histogram_of_lengths) { BOOST_AUTO_TEST_CASE(check_cumulative_histograms_of_lengths) { Persistence_intervals p("data/file_with_diagram"); std::vector<size_t> cumulative_histogram = p.cumulative_histogram_of_lengths(10); - std::vector<size_t> template_cumulative_histogram; - template_cumulative_histogram.push_back(10); - template_cumulative_histogram.push_back(15); - template_cumulative_histogram.push_back(18); - template_cumulative_histogram.push_back(22); - template_cumulative_histogram.push_back(26); - template_cumulative_histogram.push_back(29); - template_cumulative_histogram.push_back(35); - template_cumulative_histogram.push_back(36); - template_cumulative_histogram.push_back(43); - template_cumulative_histogram.push_back(44); - template_cumulative_histogram.push_back(45); + std::vector<size_t> template_cumulative_histogram{10, 15, 18, 22, 26, 29, 35, 36, 43, 45}; for (size_t i = 0; i != cumulative_histogram.size(); ++i) { BOOST_CHECK(cumulative_histogram[i] == template_cumulative_histogram[i]); @@ -116,17 +81,8 @@ BOOST_AUTO_TEST_CASE(check_characteristic_function_of_diagram) { Persistence_intervals p("data/file_with_diagram"); std::pair<double, double> min_max_ = p.get_x_range(); std::vector<double> char_funct_diag = p.characteristic_function_of_diagram(min_max_.first, min_max_.second); - std::vector<double> template_char_funct_diag; - template_char_funct_diag.push_back(0.370665); - template_char_funct_diag.push_back(0.84058); - template_char_funct_diag.push_back(1.24649); - template_char_funct_diag.push_back(1.3664); - template_char_funct_diag.push_back(1.34032); - template_char_funct_diag.push_back(1.31904); - template_char_funct_diag.push_back(1.14076); - template_char_funct_diag.push_back(0.991259); - template_char_funct_diag.push_back(0.800714); - template_char_funct_diag.push_back(0.0676303); + std::vector<double> template_char_funct_diag{0.370665, 0.84058, 1.24649, 1.3664, 1.34032, + 1.31904, 1.14076, 0.991259, 0.800714, 0.0676303}; for (size_t i = 0; i != char_funct_diag.size(); ++i) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(char_funct_diag[i], template_char_funct_diag[i], @@ -139,18 +95,8 @@ BOOST_AUTO_TEST_CASE(check_cumulative_characteristic_function_of_diagram) { std::pair<double, double> min_max_ = p.get_x_range(); std::vector<double> cumul_char_funct_diag = p.cumulative_characteristic_function_of_diagram(min_max_.first, min_max_.second); - std::vector<double> template_char_funct_diag_cumul; - - template_char_funct_diag_cumul.push_back(0.370665); - template_char_funct_diag_cumul.push_back(1.21125); - template_char_funct_diag_cumul.push_back(2.45774); - template_char_funct_diag_cumul.push_back(3.82414); - template_char_funct_diag_cumul.push_back(5.16446); - template_char_funct_diag_cumul.push_back(6.4835); - template_char_funct_diag_cumul.push_back(7.62426); - template_char_funct_diag_cumul.push_back(8.61552); - template_char_funct_diag_cumul.push_back(9.41623); - template_char_funct_diag_cumul.push_back(9.48386); + std::vector<double> template_char_funct_diag_cumul{0.370665, 1.21125, 2.45774, 3.82414, 5.16446, + 6.4835, 7.62426, 8.61552, 9.41623, 9.48386}; for (size_t i = 0; i != cumul_char_funct_diag.size(); ++i) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(cumul_char_funct_diag[i], template_char_funct_diag_cumul[i], @@ -160,97 +106,29 @@ BOOST_AUTO_TEST_CASE(check_cumulative_characteristic_function_of_diagram) { BOOST_AUTO_TEST_CASE(check_compute_persistent_betti_numbers) { Persistence_intervals p("data/file_with_diagram"); - std::vector<std::pair<double, size_t> > pbns; - pbns.push_back(std::pair<double, size_t>(0.0290362, 1)); - pbns.push_back(std::pair<double, size_t>(0.0307676, 2)); - pbns.push_back(std::pair<double, size_t>(0.0366312, 3)); - pbns.push_back(std::pair<double, size_t>(0.0544614, 4)); - pbns.push_back(std::pair<double, size_t>(0.0920033, 5)); - pbns.push_back(std::pair<double, size_t>(0.104599, 6)); - pbns.push_back(std::pair<double, size_t>(0.114718, 7)); - pbns.push_back(std::pair<double, size_t>(0.117379, 8)); - pbns.push_back(std::pair<double, size_t>(0.123493, 9)); - pbns.push_back(std::pair<double, size_t>(0.133638, 10)); - pbns.push_back(std::pair<double, size_t>(0.137798, 9)); - pbns.push_back(std::pair<double, size_t>(0.149798, 10)); - pbns.push_back(std::pair<double, size_t>(0.155421, 11)); - pbns.push_back(std::pair<double, size_t>(0.158443, 12)); - pbns.push_back(std::pair<double, size_t>(0.176956, 13)); - pbns.push_back(std::pair<double, size_t>(0.183234, 12)); - pbns.push_back(std::pair<double, size_t>(0.191069, 13)); - pbns.push_back(std::pair<double, size_t>(0.191333, 14)); - pbns.push_back(std::pair<double, size_t>(0.191836, 15)); - pbns.push_back(std::pair<double, size_t>(0.192675, 16)); - pbns.push_back(std::pair<double, size_t>(0.208564, 17)); - pbns.push_back(std::pair<double, size_t>(0.218425, 18)); - pbns.push_back(std::pair<double, size_t>(0.219902, 17)); - pbns.push_back(std::pair<double, size_t>(0.23233, 16)); - pbns.push_back(std::pair<double, size_t>(0.234558, 17)); - pbns.push_back(std::pair<double, size_t>(0.237166, 16)); - pbns.push_back(std::pair<double, size_t>(0.247352, 17)); - pbns.push_back(std::pair<double, size_t>(0.267421, 18)); - pbns.push_back(std::pair<double, size_t>(0.268093, 19)); - pbns.push_back(std::pair<double, size_t>(0.278734, 18)); - pbns.push_back(std::pair<double, size_t>(0.284722, 19)); - pbns.push_back(std::pair<double, size_t>(0.284998, 20)); - pbns.push_back(std::pair<double, size_t>(0.294069, 21)); - pbns.push_back(std::pair<double, size_t>(0.306293, 22)); - pbns.push_back(std::pair<double, size_t>(0.322361, 21)); - pbns.push_back(std::pair<double, size_t>(0.323152, 22)); - pbns.push_back(std::pair<double, size_t>(0.371021, 23)); - pbns.push_back(std::pair<double, size_t>(0.372395, 24)); - pbns.push_back(std::pair<double, size_t>(0.387744, 25)); - pbns.push_back(std::pair<double, size_t>(0.435537, 26)); - pbns.push_back(std::pair<double, size_t>(0.462911, 25)); - pbns.push_back(std::pair<double, size_t>(0.483569, 26)); - pbns.push_back(std::pair<double, size_t>(0.489209, 25)); - pbns.push_back(std::pair<double, size_t>(0.517115, 24)); - pbns.push_back(std::pair<double, size_t>(0.522197, 23)); - pbns.push_back(std::pair<double, size_t>(0.532665, 22)); - pbns.push_back(std::pair<double, size_t>(0.545262, 23)); - pbns.push_back(std::pair<double, size_t>(0.587227, 22)); - pbns.push_back(std::pair<double, size_t>(0.593036, 23)); - pbns.push_back(std::pair<double, size_t>(0.602647, 24)); - pbns.push_back(std::pair<double, size_t>(0.605044, 25)); - pbns.push_back(std::pair<double, size_t>(0.621962, 24)); - pbns.push_back(std::pair<double, size_t>(0.629449, 23)); - pbns.push_back(std::pair<double, size_t>(0.636719, 22)); - pbns.push_back(std::pair<double, size_t>(0.64957, 21)); - pbns.push_back(std::pair<double, size_t>(0.650781, 22)); - pbns.push_back(std::pair<double, size_t>(0.654951, 23)); - pbns.push_back(std::pair<double, size_t>(0.683489, 24)); - pbns.push_back(std::pair<double, size_t>(0.687172, 23)); - pbns.push_back(std::pair<double, size_t>(0.69703, 22)); - pbns.push_back(std::pair<double, size_t>(0.701174, 21)); - pbns.push_back(std::pair<double, size_t>(0.717623, 22)); - pbns.push_back(std::pair<double, size_t>(0.722023, 21)); - pbns.push_back(std::pair<double, size_t>(0.722298, 20)); - pbns.push_back(std::pair<double, size_t>(0.725347, 19)); - pbns.push_back(std::pair<double, size_t>(0.73071, 18)); - pbns.push_back(std::pair<double, size_t>(0.758355, 17)); - pbns.push_back(std::pair<double, size_t>(0.770913, 18)); - pbns.push_back(std::pair<double, size_t>(0.790833, 17)); - pbns.push_back(std::pair<double, size_t>(0.821211, 16)); - pbns.push_back(std::pair<double, size_t>(0.849305, 17)); - pbns.push_back(std::pair<double, size_t>(0.853669, 16)); - pbns.push_back(std::pair<double, size_t>(0.866659, 15)); - pbns.push_back(std::pair<double, size_t>(0.872896, 16)); - pbns.push_back(std::pair<double, size_t>(0.889597, 15)); - pbns.push_back(std::pair<double, size_t>(0.900231, 14)); - pbns.push_back(std::pair<double, size_t>(0.903847, 13)); - pbns.push_back(std::pair<double, size_t>(0.906299, 12)); - pbns.push_back(std::pair<double, size_t>(0.910852, 11)); - pbns.push_back(std::pair<double, size_t>(0.93453, 10)); - pbns.push_back(std::pair<double, size_t>(0.944757, 9)); - pbns.push_back(std::pair<double, size_t>(0.947812, 8)); - pbns.push_back(std::pair<double, size_t>(0.959154, 7)); - pbns.push_back(std::pair<double, size_t>(0.975654, 6)); - pbns.push_back(std::pair<double, size_t>(0.976719, 5)); - pbns.push_back(std::pair<double, size_t>(0.977343, 4)); - pbns.push_back(std::pair<double, size_t>(0.980129, 3)); - pbns.push_back(std::pair<double, size_t>(0.987842, 2)); - pbns.push_back(std::pair<double, size_t>(0.990127, 1)); - pbns.push_back(std::pair<double, size_t>(0.994537, 0)); + std::vector<std::pair<double, size_t> > pbns{ {0.0290362, 1}, {0.0307676, 2}, {0.0366312, 3}, {0.0544614, 4}, + {0.0920033, 5}, {0.104599, 6}, {0.114718, 7}, {0.117379, 8}, + {0.123493, 9}, {0.133638, 10}, {0.137798, 9}, {0.149798, 10}, + {0.155421, 11}, {0.158443, 12}, {0.176956, 13}, {0.183234, 12}, + {0.191069, 13}, {0.191333, 14}, {0.191836, 15}, {0.192675, 16}, + {0.208564, 17}, {0.218425, 18}, {0.219902, 17}, {0.23233, 16}, + {0.234558, 17}, {0.237166, 16}, {0.247352, 17}, {0.267421, 18}, + {0.268093, 19}, {0.278734, 18}, {0.284722, 19}, {0.284998, 20}, + {0.294069, 21}, {0.306293, 22}, {0.322361, 21}, {0.323152, 22}, + {0.371021, 23}, {0.372395, 24}, {0.387744, 25}, {0.435537, 26}, + {0.462911, 25}, {0.483569, 26}, {0.489209, 25}, {0.517115, 24}, + {0.522197, 23}, {0.532665, 22}, {0.545262, 23}, {0.587227, 22}, + {0.593036, 23}, {0.602647, 24}, {0.605044, 25}, {0.621962, 24}, + {0.629449, 23}, {0.636719, 22}, {0.64957, 21}, {0.650781, 22}, + {0.654951, 23}, {0.683489, 24}, {0.687172, 23}, {0.69703, 22}, + {0.701174, 21}, {0.717623, 22}, {0.722023, 21}, {0.722298, 20}, + {0.725347, 19}, {0.73071, 18}, {0.758355, 17}, {0.770913, 18}, + {0.790833, 17}, {0.821211, 16}, {0.849305, 17}, {0.853669, 16}, + {0.866659, 15}, {0.872896, 16}, {0.889597, 15}, {0.900231, 14}, + {0.903847, 13}, {0.906299, 12}, {0.910852, 11}, {0.93453, 10}, + {0.944757, 9}, {0.947812, 8}, {0.959154, 7}, {0.975654, 6}, + {0.976719, 5}, {0.977343, 4}, {0.980129, 3}, {0.987842, 2}, + {0.990127, 1}, {0.994537, 0} }; std::vector<std::pair<double, size_t> > pbns_new = p.compute_persistent_betti_numbers(); for (size_t i = 0; i != pbns.size(); ++i) { @@ -262,17 +140,8 @@ BOOST_AUTO_TEST_CASE(check_compute_persistent_betti_numbers) { BOOST_AUTO_TEST_CASE(check_k_n_n) { Persistence_intervals p("data/file_with_diagram"); std::vector<double> knn = p.k_n_n(5); - std::vector<double> knn_template; - knn_template.push_back(1.04208); - knn_template.push_back(1.00344); - knn_template.push_back(0.979395); - knn_template.push_back(0.890643); - knn_template.push_back(0.874769); - knn_template.push_back(0.845787); - knn_template.push_back(0.819713); - knn_template.push_back(0.803984); - knn_template.push_back(0.799864); - knn_template.push_back(0.786945); + std::vector<double> knn_template{1.04208, 1.00344, 0.979395, 0.890643, 0.874769, + 0.845787, 0.819713, 0.803984, 0.799864, 0.786945}; for (size_t i = 0; i != knn.size(); ++i) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(knn[i], knn_template[i], Gudhi::Persistence_representations::epsi); diff --git a/src/Simplex_tree/example/CMakeLists.txt b/src/Simplex_tree/example/CMakeLists.txt index f99b164c..8a8cac58 100644 --- a/src/Simplex_tree/example/CMakeLists.txt +++ b/src/Simplex_tree/example/CMakeLists.txt @@ -16,6 +16,9 @@ endif() add_test(NAME Simplex_tree_example_simple_simplex_tree COMMAND $<TARGET_FILE:Simplex_tree_example_simple_simplex_tree>) add_executable ( Simplex_tree_example_mini_simplex_tree mini_simplex_tree.cpp ) +if (TBB_FOUND) + target_link_libraries(Simplex_tree_example_mini_simplex_tree ${TBB_LIBRARIES}) +endif() add_test(NAME Simplex_tree_example_mini_simplex_tree COMMAND $<TARGET_FILE:Simplex_tree_example_mini_simplex_tree>) # An example with Simplex-tree using CGAL alpha_shapes_3 diff --git a/src/Simplex_tree/include/gudhi/Simplex_tree.h b/src/Simplex_tree/include/gudhi/Simplex_tree.h index fafdb01c..76608008 100644 --- a/src/Simplex_tree/include/gudhi/Simplex_tree.h +++ b/src/Simplex_tree/include/gudhi/Simplex_tree.h @@ -1378,7 +1378,7 @@ class Simplex_tree { private: bool rec_prune_above_filtration(Siblings* sib, Filtration_value filt) { auto&& list = sib->members(); - auto last = std::remove_if(list.begin(), list.end(), [=](Dit_value_t& simplex) { + auto last = std::remove_if(list.begin(), list.end(), [this,filt](Dit_value_t& simplex) { if (simplex.second.filtration() <= filt) return false; if (has_children(&simplex)) rec_delete(simplex.second.children()); // dimension may need to be lowered diff --git a/src/Tangential_complex/include/gudhi/Tangential_complex.h b/src/Tangential_complex/include/gudhi/Tangential_complex.h index f058fa9f..f007bdd5 100644 --- a/src/Tangential_complex/include/gudhi/Tangential_complex.h +++ b/src/Tangential_complex/include/gudhi/Tangential_complex.h @@ -60,7 +60,7 @@ #ifdef GUDHI_USE_TBB #include <tbb/parallel_for.h> #include <tbb/combinable.h> -#include <tbb/mutex.h> +#include <mutex> #endif // #define GUDHI_TC_EXPORT_NORMALS // Only for 3D surfaces (k=2, d=3) @@ -147,7 +147,7 @@ class Tangential_complex { typedef typename Tr_traits::Vector_d Tr_vector; #if defined(GUDHI_USE_TBB) - typedef tbb::mutex Mutex_for_perturb; + typedef std::mutex Mutex_for_perturb; typedef Vector Translation_for_perturb; typedef std::vector<Atomic_wrapper<FT> > Weights; #else diff --git a/src/Witness_complex/example/CMakeLists.txt b/src/Witness_complex/example/CMakeLists.txt index 5860f3a3..2659798e 100644 --- a/src/Witness_complex/example/CMakeLists.txt +++ b/src/Witness_complex/example/CMakeLists.txt @@ -12,10 +12,18 @@ install(TARGETS Witness_complex_example_nearest_landmark_table DESTINATION bin) # CGAL and Eigen3 are required for Euclidean version of Witness if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) add_executable( Witness_complex_example_off example_witness_complex_off.cpp ) + if (TBB_FOUND) + target_link_libraries(Witness_complex_example_off ${TBB_LIBRARIES}) + endif() add_executable ( Witness_complex_example_sphere example_witness_complex_sphere.cpp ) + if (TBB_FOUND) + target_link_libraries(Witness_complex_example_sphere ${TBB_LIBRARIES}) + endif() add_executable( Witness_complex_example_strong_off example_strong_witness_complex_off.cpp ) - target_link_libraries(Witness_complex_example_strong_off) + if (TBB_FOUND) + target_link_libraries(Witness_complex_example_strong_off ${TBB_LIBRARIES}) + endif() add_test(NAME Witness_complex_example_off_test_torus COMMAND $<TARGET_FILE:Witness_complex_example_off> diff --git a/src/cmake/modules/GUDHI_third_party_libraries.cmake b/src/cmake/modules/GUDHI_third_party_libraries.cmake index 24a34150..359d1c12 100644 --- a/src/cmake/modules/GUDHI_third_party_libraries.cmake +++ b/src/cmake/modules/GUDHI_third_party_libraries.cmake @@ -35,6 +35,9 @@ if(CGAL_FOUND) include( ${CGAL_USE_FILE} ) endif() +# For those who dislike bundled dependencies, this indicates where to find a preinstalled Hera. +set(HERA_WASSERSTEIN_INCLUDE_DIR ${CMAKE_SOURCE_DIR}/ext/hera/geom_matching/wasserstein/include CACHE PATH "Directory where one can find Hera's wasserstein.h") + option(WITH_GUDHI_USE_TBB "Build with Intel TBB parallelization" ON) # Find TBB package for parallel sort - not mandatory, just optional. @@ -127,6 +130,7 @@ if( PYTHONINTERP_FOUND ) find_python_module("sphinx") find_python_module("sklearn") find_python_module("ot") + find_python_module("pybind11") endif() if(NOT GUDHI_PYTHON_PATH) diff --git a/src/cmake/modules/GUDHI_user_version_target.cmake b/src/cmake/modules/GUDHI_user_version_target.cmake index 4fa74330..5047252f 100644 --- a/src/cmake/modules/GUDHI_user_version_target.cmake +++ b/src/cmake/modules/GUDHI_user_version_target.cmake @@ -33,8 +33,6 @@ add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E copy_directory ${CMAKE_CURRENT_BINARY_DIR}/biblio ${GUDHI_USER_VERSION_DIR}/biblio) add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E - copy ${CMAKE_SOURCE_DIR}/Conventions.txt ${GUDHI_USER_VERSION_DIR}/Conventions.txt) -add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_SOURCE_DIR}/README.md ${GUDHI_USER_VERSION_DIR}/README.md) add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E copy ${CMAKE_SOURCE_DIR}/LICENSE ${GUDHI_USER_VERSION_DIR}/LICENSE) @@ -56,6 +54,9 @@ add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E copy_directory ${CMAKE_SOURCE_DIR}/src/GudhUI ${GUDHI_USER_VERSION_DIR}/GudhUI) +add_custom_command(TARGET user_version PRE_BUILD COMMAND ${CMAKE_COMMAND} -E + copy_directory ${CMAKE_SOURCE_DIR}/ext/hera/geom_matching/wasserstein/include ${GUDHI_USER_VERSION_DIR}/ext/hera/geom_matching/wasserstein/include) + set(GUDHI_DIRECTORIES "doc;example;concept;utilities") set(GUDHI_INCLUDE_DIRECTORIES "include/gudhi") @@ -95,4 +96,4 @@ foreach(GUDHI_MODULE ${GUDHI_MODULES_FULL_LIST}) endforeach() endforeach(GUDHI_INCLUDE_DIRECTORY ${GUDHI_INCLUDE_DIRECTORIES}) -endforeach(GUDHI_MODULE ${GUDHI_MODULES_FULL_LIST})
\ No newline at end of file +endforeach(GUDHI_MODULE ${GUDHI_MODULES_FULL_LIST}) diff --git a/src/common/doc/header.html b/src/common/doc/header.html index 9fdb2321..99ab6bb7 100644 --- a/src/common/doc/header.html +++ b/src/common/doc/header.html @@ -56,7 +56,7 @@ $extrastylesheet <a href="#">Download</a> <ul class="dropdown"> <li><a href="/licensing/">Licensing</a></li> - <li><a href="https://gforge.inria.fr/frs/download.php/latestzip/5253/library-latest.zip" target="_blank">Get the latest sources</a></li> + <li><a href="https://github.com/GUDHI/gudhi-devel/releases/latest" target="_blank">Get the latest sources</a></li> <li><a href="/conda/">Conda package</a></li> <li><a href="/dockerfile/">Dockerfile</a></li> </ul> diff --git a/src/common/doc/installation.h b/src/common/doc/installation.h index d70a2efa..ce2c5448 100644 --- a/src/common/doc/installation.h +++ b/src/common/doc/installation.h @@ -33,7 +33,7 @@ make \endverbatim * \subsection testsuites Test suites * To test your build, run the following command in a terminal: * \verbatim make test \endverbatim - * `make test` is using <a href="https://cmake.org/cmake/help/latest/manual/ctest.1.html">Ctest<\a> (CMake test driver + * `make test` is using <a href="https://cmake.org/cmake/help/latest/manual/ctest.1.html">Ctest</a> (CMake test driver * program). If some of the tests are failing, please send us the result of the following command: * \verbatim ctest --output-on-failure \endverbatim * diff --git a/src/common/doc/main_page.md b/src/common/doc/main_page.md index e8d11fdf..6ea10b88 100644 --- a/src/common/doc/main_page.md +++ b/src/common/doc/main_page.md @@ -4,8 +4,8 @@ \image html "Gudhi_banner.png" <br><br><br><br> -## Complexes {#Complexes} -### Cubical complex +## Data structures for cell complexes {#Complexes} +### Cubical complexes <table> <tr> @@ -29,246 +29,269 @@ </tr> </table> -### Simplicial complex - -#### Alpha complex +### Simplicial complexes +#### Simplex tree <table> <tr> <td width="35%" rowspan=2> - \image html "alpha_complex_representation.png" + \image html "Simplex_tree_representation.png" </td> <td width="50%"> - Alpha complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br> - The filtration value of each simplex is computed as the square of the circumradius of the simplex if the - circumsphere is empty (the simplex is then said to be Gabriel), and as the minimum of the filtration - values of the codimension 1 cofaces that make it not Gabriel otherwise. - All simplices that have a filtration value strictly greater than a given alpha squared value are not inserted into - the complex.<br> - For performances reasons, it is advised to use \ref cgal ≥ 5.0.0. + The simplex tree is an efficient and flexible + data structure for representing general (filtered) simplicial complexes. The data structure + is described in \cite boissonnatmariasimplextreealgorithmica . </td> <td width="15%"> - <b>Author:</b> Vincent Rouvreau<br> - <b>Introduced in:</b> GUDHI 1.3.0<br> - <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> - <b>Requires:</b> \ref eigen ≥ 3.1.0 and \ref cgal ≥ 4.11.0 + <b>Author:</b> Clément Maria<br> + <b>Introduced in:</b> GUDHI 1.0.0<br> + <b>Copyright:</b> MIT<br> </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref alpha_complex + <b>User manual:</b> \ref simplex_tree </td> </tr> </table> -#### Čech complex +#### Toplex Map <table> - <tr> + <tr> <td width="35%" rowspan=2> - \image html "cech_complex_representation.png" + \image html "map.png" </td> <td width="50%"> - The Čech complex is a simplicial complex constructed from a proximity graph. - The set of all simplices is filtered by the radius of their minimal enclosing ball. + The Toplex map data structure is composed firstly of a raw storage of toplices (the maximal simplices) + and secondly of a map which associate any vertex to a set of pointers toward all toplices + containing this vertex. </td> <td width="15%"> - <b>Author:</b> Vincent Rouvreau<br> - <b>Introduced in:</b> GUDHI 2.2.0<br> - <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> - <b>Includes:</b> [Miniball](https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html)<br> + <b>Author:</b> François Godi<br> + <b>Introduced in:</b> GUDHI 2.1.0<br> + <b>Copyright:</b> MIT<br> </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref cech_complex + <b>User manual:</b> \ref toplex_map </td> </tr> </table> -#### Rips complex +#### Skeleton blocker <table> <tr> <td width="35%" rowspan=2> - \image html "rips_complex_representation.png" + \image html "ds_representation.png" </td> <td width="50%"> - Rips complex is a simplicial complex constructed from a one skeleton graph.<br> - The filtration value of each edge is computed from a user-given distance function and is inserted until a - user-given threshold value.<br> - This complex can be built from a point cloud and a distance function, or from a distance matrix. + The Skeleton-Blocker data-structure proposes a light encoding for simplicial complexes by storing only an *implicit* + representation of its simplices \cite socg_blockers_2011,\cite blockers2012. Intuitively, it just stores the + 1-skeleton of a simplicial complex with a graph and the set of its "missing faces" that is very small in practice. + This data-structure handles all simplicial complexes operations such as simplex enumeration or simplex removal but + operations that are particularly efficient are operations that do not require simplex enumeration such as edge + iteration, link computation or simplex contraction. </td> <td width="15%"> - <b>Author:</b> Clément Maria, Pawel Dlotko, Vincent Rouvreau, Marc Glisse<br> - <b>Introduced in:</b> GUDHI 2.0.0<br> + <b>Author:</b> David Salinas<br> + <b>Introduced in:</b> GUDHI 1.1.0<br> <b>Copyright:</b> MIT<br> </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref rips_complex + <b>User manual:</b> \ref skbl </td> </tr> </table> -#### Witness complex +#### Basic operation: contraction <table> <tr> <td width="35%" rowspan=2> - \image html "Witness_complex_representation.png" + \image html "sphere_contraction_representation.png" </td> <td width="50%"> - Witness complex \f$ Wit(W,L) \f$ is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$. - The data structure is described in \cite boissonnatmariasimplextreealgorithmica . + The purpose of this package is to offer a user-friendly interface for edge contraction simplification of huge + simplicial complexes. It uses the \ref skbl data-structure whose size remains small during simplification of most + used geometrical complexes of topological data analysis such as the Rips or the Delaunay complexes. In practice, + the size of this data-structure is even much lower than the total number of simplices. </td> <td width="15%"> - <b>Author:</b> Siargey Kachanovich<br> - <b>Introduced in:</b> GUDHI 1.3.0<br> - <b>Copyright:</b> MIT ([GPL v3](../../licensing/) for Euclidean version)<br> - <b>Euclidean version requires:</b> \ref eigen ≥ 3.1.0 and \ref cgal ≥ 4.11.0 + <b>Author:</b> David Salinas<br> + <b>Introduced in:</b> GUDHI 1.1.0<br> + <b>Copyright:</b> MIT [(LGPL v3)](../../licensing/)<br> + <b>Requires:</b> \ref cgal ≥ 4.11.0 </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref witness_complex + <b>User manual:</b> \ref contr </td> </tr> </table> -### Cover Complexes +## Filtrations and reconstructions {#FiltrationsReconstructions} +### Alpha complex + <table> <tr> <td width="35%" rowspan=2> - \image html "gicvisu.jpg" + \image html "alpha_complex_representation.png" </td> <td width="50%"> - Nerves and Graph Induced Complexes are cover complexes, i.e. simplicial complexes that provably contain - topological information about the input data. They can be computed with a cover of the - data, that comes i.e. from the preimage of a family of intervals covering the image - of a scalar-valued function defined on the data. <br> + Alpha complex is a simplicial complex constructed from the finite cells of a Delaunay Triangulation.<br> + The filtration value of each simplex is computed as the square of the circumradius of the simplex if the + circumsphere is empty (the simplex is then said to be Gabriel), and as the minimum of the filtration + values of the codimension 1 cofaces that make it not Gabriel otherwise. + All simplices that have a filtration value \f$ > \alpha^2 \f$ are removed from the Delaunay complex + when creating the simplicial complex if it is specified.<br> + For performances reasons, it is advised to use \ref cgal ≥ 5.0.0. </td> <td width="15%"> - <b>Author:</b> Mathieu Carrière<br> - <b>Introduced in:</b> GUDHI 2.1.0<br> + <b>Author:</b> Vincent Rouvreau<br> + <b>Introduced in:</b> GUDHI 1.3.0<br> <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> - <b>Requires:</b> \ref cgal ≥ 4.11.0 + <b>Requires:</b> \ref eigen ≥ 3.1.0 and \ref cgal ≥ 4.11.0 </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref cover_complex + <b>User manual:</b> \ref alpha_complex </td> </tr> </table> -## Data structures and basic operations {#DataStructuresAndBasicOperations} +### Čech complex + +<table> + <tr> + <td width="35%" rowspan=2> + \image html "cech_complex_representation.png" + </td> + <td width="50%"> + The Čech complex is a simplicial complex constructed from a proximity graph. + The set of all simplices is filtered by the radius of their minimal enclosing ball. + </td> + <td width="15%"> + <b>Author:</b> Vincent Rouvreau<br> + <b>Introduced in:</b> GUDHI 2.2.0<br> + <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> + <b>Includes:</b> [Miniball](https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html)<br> + </td> + </tr> + <tr> + <td colspan=2 height="25"> + <b>User manual:</b> \ref cech_complex + </td> + </tr> +</table> -### Data structures +### Rips complex -#### Simplex tree <table> <tr> <td width="35%" rowspan=2> - \image html "Simplex_tree_representation.png" + \image html "rips_complex_representation.png" </td> <td width="50%"> - The simplex tree is an efficient and flexible - data structure for representing general (filtered) simplicial complexes. The data structure - is described in \cite boissonnatmariasimplextreealgorithmica . + Rips complex is a simplicial complex constructed from a one skeleton graph.<br> + The filtration value of each edge is computed from a user-given distance function and is inserted until a + user-given threshold value.<br> + This complex can be built from a point cloud and a distance function, or from a distance matrix. </td> <td width="15%"> - <b>Author:</b> Clément Maria<br> - <b>Introduced in:</b> GUDHI 1.0.0<br> + <b>Author:</b> Clément Maria, Pawel Dlotko, Vincent Rouvreau, Marc Glisse<br> + <b>Introduced in:</b> GUDHI 2.0.0<br> <b>Copyright:</b> MIT<br> </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref simplex_tree + <b>User manual:</b> \ref rips_complex </td> </tr> </table> -#### Skeleton blocker +### Witness complex <table> <tr> <td width="35%" rowspan=2> - \image html "ds_representation.png" + \image html "Witness_complex_representation.png" </td> <td width="50%"> - The Skeleton-Blocker data-structure proposes a light encoding for simplicial complexes by storing only an *implicit* - representation of its simplices \cite socg_blockers_2011,\cite blockers2012. Intuitively, it just stores the - 1-skeleton of a simplicial complex with a graph and the set of its "missing faces" that is very small in practice. - This data-structure handles all simplicial complexes operations such as simplex enumeration or simplex removal but - operations that are particularly efficient are operations that do not require simplex enumeration such as edge - iteration, link computation or simplex contraction. + Witness complex \f$ Wit(W,L) \f$ is a simplicial complex defined on two sets of points in \f$\mathbb{R}^D\f$. + The data structure is described in \cite boissonnatmariasimplextreealgorithmica . </td> <td width="15%"> - <b>Author:</b> David Salinas<br> - <b>Introduced in:</b> GUDHI 1.1.0<br> - <b>Copyright:</b> MIT<br> + <b>Author:</b> Siargey Kachanovich<br> + <b>Introduced in:</b> GUDHI 1.3.0<br> + <b>Copyright:</b> MIT ([GPL v3](../../licensing/) for Euclidean version)<br> + <b>Euclidean version requires:</b> \ref eigen ≥ 3.1.0 and \ref cgal ≥ 4.11.0 </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref skbl + <b>User manual:</b> \ref witness_complex </td> </tr> </table> -#### Toplex Map - +### Cover Complexes <table> <tr> <td width="35%" rowspan=2> - \image html "map.png" + \image html "gicvisu.jpg" </td> <td width="50%"> - The Toplex map data structure is composed firstly of a raw storage of toplices (the maximal simplices) - and secondly of a map which associate any vertex to a set of pointers toward all toplices - containing this vertex. + Nerves and Graph Induced Complexes are cover complexes, i.e. simplicial complexes that provably contain + topological information about the input data. They can be computed with a cover of the + data, that comes i.e. from the preimage of a family of intervals covering the image + of a scalar-valued function defined on the data. <br> </td> <td width="15%"> - <b>Author:</b> François Godi<br> + <b>Author:</b> Mathieu Carrière<br> <b>Introduced in:</b> GUDHI 2.1.0<br> - <b>Copyright:</b> MIT<br> + <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> + <b>Requires:</b> \ref cgal ≥ 4.11.0 </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref toplex_map + <b>User manual:</b> \ref cover_complex </td> </tr> </table> -### Basic operations - -#### Contraction +### Tangential complex <table> <tr> <td width="35%" rowspan=2> - \image html "sphere_contraction_representation.png" + \image html "tc_examples.png" </td> <td width="50%"> - The purpose of this package is to offer a user-friendly interface for edge contraction simplification of huge - simplicial complexes. It uses the \ref skbl data-structure whose size remains small during simplification of most - used geometrical complexes of topological data analysis such as the Rips or the Delaunay complexes. In practice, - the size of this data-structure is even much lower than the total number of simplices. + A Tangential Delaunay complex is a <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a> + designed to reconstruct a \f$ k \f$-dimensional manifold embedded in \f$ d \f$-dimensional Euclidean space. + The input is a point sample coming from an unknown manifold. + The running time depends only linearly on the extrinsic dimension \f$ d \f$ + and exponentially on the intrinsic dimension \f$ k \f$. </td> <td width="15%"> - <b>Author:</b> David Salinas<br> - <b>Introduced in:</b> GUDHI 1.1.0<br> - <b>Copyright:</b> MIT [(LGPL v3)](../../licensing/)<br> - <b>Requires:</b> \ref cgal ≥ 4.11.0 + <b>Author:</b> Clément Jamin<br> + <b>Introduced in:</b> GUDHI 2.0.0<br> + <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> + <b>Requires:</b> \ref eigen ≥ 3.1.0 and \ref cgal ≥ 4.11.0 </td> </tr> <tr> <td colspan=2 height="25"> - <b>User manual:</b> \ref contr + <b>User manual:</b> \ref tangential_complex </td> </tr> </table> @@ -305,36 +328,6 @@ </tr> </table> -## Manifold reconstruction {#ManifoldReconstruction} - -### Tangential complex - -<table> - <tr> - <td width="35%" rowspan=2> - \image html "tc_examples.png" - </td> - <td width="50%"> - A Tangential Delaunay complex is a <a target="_blank" href="https://en.wikipedia.org/wiki/Simplicial_complex">simplicial complex</a> - designed to reconstruct a \f$ k \f$-dimensional manifold embedded in \f$ d \f$-dimensional Euclidean space. - The input is a point sample coming from an unknown manifold. - The running time depends only linearly on the extrinsic dimension \f$ d \f$ - and exponentially on the intrinsic dimension \f$ k \f$. - </td> - <td width="15%"> - <b>Author:</b> Clément Jamin<br> - <b>Introduced in:</b> GUDHI 2.0.0<br> - <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> - <b>Requires:</b> \ref eigen ≥ 3.1.0 and \ref cgal ≥ 4.11.0 - </td> - </tr> - <tr> - <td colspan=2 height="25"> - <b>User manual:</b> \ref tangential_complex - </td> - </tr> -</table> - ## Topological descriptors tools {#TopologicalDescriptorsTools} ### Bottleneck distance @@ -390,3 +383,26 @@ </td> </tr> </table> + +## Point cloud utilities {#PointCloudUtils} + +<table> + <tr> + <td width="35%" rowspan=2> + \f$(x_1,\ldots,x_d)\f$ + </td> + <td width="50%"> + This contains various tools to handle point clouds: spatial searching, subsampling, etc. + </td> + <td width="15%"> + <b>Author:</b> Clément Jamin<br> + <b>Introduced in:</b> GUDHI 1.3.0<br> + <b>Copyright:</b> MIT [(GPL v3)](../../licensing/)<br> + </td> + </tr> + <tr> + <td colspan=2 height="25"> + <b>Manuals:</b> \ref spatial_searching, \ref subsampling + </td> + </tr> +</table> diff --git a/src/common/include/gudhi/Unitary_tests_utils.h b/src/common/include/gudhi/Unitary_tests_utils.h index 7d039304..9b86460a 100644 --- a/src/common/include/gudhi/Unitary_tests_utils.h +++ b/src/common/include/gudhi/Unitary_tests_utils.h @@ -26,4 +26,15 @@ void GUDHI_TEST_FLOAT_EQUALITY_CHECK(FloatingType a, FloatingType b, BOOST_CHECK(std::fabs(a - b) <= epsilon); } +// That's the usual x86 issue where a+b==a+b can return false (without any NaN) because one of them was stored in +// memory (and thus rounded to 64 bits) while the other is still in a register (80 bits). +template<typename FloatingType > +FloatingType GUDHI_PROTECT_FLOAT(FloatingType value) { + volatile FloatingType protected_value = value; +#ifdef DEBUG_TRACES + std::cout << "GUDHI_PROTECT_FLOAT - " << protected_value << std::endl; +#endif + return protected_value; +} + #endif // UNITARY_TESTS_UTILS_H_ diff --git a/src/python/CMakeLists.txt b/src/python/CMakeLists.txt index 7f9ff38f..8c36f7ee 100644 --- a/src/python/CMakeLists.txt +++ b/src/python/CMakeLists.txt @@ -32,6 +32,10 @@ function( add_gudhi_debug_info DEBUG_INFO ) endfunction( add_gudhi_debug_info ) if(PYTHONINTERP_FOUND) + if(PYBIND11_FOUND) + add_gudhi_debug_info("Pybind11 version ${PYBIND11_VERSION}") + set(GUDHI_PYTHON_MODULES_EXTRA "${GUDHI_PYTHON_MODULES_EXTRA}'hera', ") + endif() if(CYTHON_FOUND) set(GUDHI_PYTHON_MODULES "${GUDHI_PYTHON_MODULES}'off_reader', ") set(GUDHI_PYTHON_MODULES "${GUDHI_PYTHON_MODULES}'simplex_tree', ") @@ -87,6 +91,7 @@ if(PYTHONINTERP_FOUND) endif(MSVC) if(CMAKE_COMPILER_IS_GNUCXX) set(GUDHI_PYTHON_EXTRA_COMPILE_ARGS "${GUDHI_PYTHON_EXTRA_COMPILE_ARGS}'-frounding-math', ") + set(GUDHI_PYBIND11_EXTRA_COMPILE_ARGS "${GUDHI_PYBIND11_EXTRA_COMPILE_ARGS}'-fvisibility=hidden', ") endif(CMAKE_COMPILER_IS_GNUCXX) if (CMAKE_CXX_COMPILER_ID MATCHES Intel) set(GUDHI_PYTHON_EXTRA_COMPILE_ARGS "${GUDHI_PYTHON_EXTRA_COMPILE_ARGS}'-fp-model strict', ") @@ -115,9 +120,9 @@ if(PYTHONINTERP_FOUND) set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'nerve_gic', ") endif () if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) + set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'alpha_complex', ") set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'subsampling', ") set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'tangential_complex', ") - set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'alpha_complex', ") set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'euclidean_witness_complex', ") set(GUDHI_PYTHON_MODULES_TO_COMPILE "${GUDHI_PYTHON_MODULES_TO_COMPILE}'euclidean_strong_witness_complex', ") endif () @@ -163,10 +168,21 @@ if(PYTHONINTERP_FOUND) set(GUDHI_PYTHON_EXTRA_COMPILE_ARGS "${GUDHI_PYTHON_EXTRA_COMPILE_ARGS}'-DCGAL_USE_GMPXX', ") add_GUDHI_PYTHON_lib("${GMPXX_LIBRARIES}") set(GUDHI_PYTHON_LIBRARY_DIRS "${GUDHI_PYTHON_LIBRARY_DIRS}'${GMPXX_LIBRARIES_DIR}', ") - message("** Add gmpxx ${GMPXX_LIBRARIES_DIR}") + message("** Add gmpxx ${GMPXX_LIBRARIES_DIR}") endif(GMPXX_FOUND) endif(GMP_FOUND) - endif(CGAL_FOUND) + if(MPFR_FOUND) + add_gudhi_debug_info("MPFR_LIBRARIES = ${MPFR_LIBRARIES}") + set(GUDHI_PYTHON_EXTRA_COMPILE_ARGS "${GUDHI_PYTHON_EXTRA_COMPILE_ARGS}'-DCGAL_USE_MPFR', ") + add_GUDHI_PYTHON_lib("${MPFR_LIBRARIES}") + # In case CGAL is not header only, all MPFR variables are set except MPFR_LIBRARIES_DIR - Just set it + if(NOT MPFR_LIBRARIES_DIR) + get_filename_component(MPFR_LIBRARIES_DIR ${MPFR_LIBRARIES} PATH) + endif(NOT MPFR_LIBRARIES_DIR) + set(GUDHI_PYTHON_LIBRARY_DIRS "${GUDHI_PYTHON_LIBRARY_DIRS}'${MPFR_LIBRARIES_DIR}', ") + message("** Add mpfr ${MPFR_LIBRARIES}") + endif(MPFR_FOUND) +endif(CGAL_FOUND) # Specific for Mac if (${CMAKE_SYSTEM_NAME} MATCHES "Darwin") @@ -231,7 +247,6 @@ if(PYTHONINTERP_FOUND) COMMAND ${CMAKE_COMMAND} -E env "PYTHONPATH=${CMAKE_CURRENT_BINARY_DIR}" ${PYTHON_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/example/alpha_rips_persistence_bottleneck_distance.py" -f ${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off -t 0.15 -d 3) - if(MATPLOTLIB_FOUND AND NUMPY_FOUND) # Tangential add_test(NAME tangential_complex_plain_homology_from_off_file_example_py_test @@ -307,7 +322,6 @@ if(PYTHONINTERP_FOUND) WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR} COMMAND ${CMAKE_COMMAND} -E env "PYTHONPATH=${CMAKE_CURRENT_BINARY_DIR}" ${PYTHON_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/example/alpha_complex_from_points_example.py") - if(MATPLOTLIB_FOUND AND NUMPY_FOUND) add_test(NAME alpha_complex_diagram_persistence_from_off_file_example_py_test WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR} @@ -315,9 +329,7 @@ if(PYTHONINTERP_FOUND) ${PYTHON_EXECUTABLE} "${CMAKE_CURRENT_SOURCE_DIR}/example/alpha_complex_diagram_persistence_from_off_file_example.py" --no-diagram -f ${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off -a 0.6) endif() - add_gudhi_py_test(test_alpha_complex) - endif (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) @@ -385,10 +397,10 @@ if(PYTHONINTERP_FOUND) add_gudhi_py_test(test_reader_utils) # Wasserstein - if(OT_FOUND) + if(OT_FOUND AND PYBIND11_FOUND) add_gudhi_py_test(test_wasserstein_distance) add_gudhi_py_test(test_wasserstein_barycenter) - endif(OT_FOUND) + endif() # Representations if(SKLEARN_FOUND AND MATPLOTLIB_FOUND) @@ -402,32 +414,37 @@ if(PYTHONINTERP_FOUND) if(SCIPY_FOUND) if(SKLEARN_FOUND) if(OT_FOUND) - if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) - set (GUDHI_SPHINX_MESSAGE "Generating API documentation with Sphinx in ${CMAKE_CURRENT_BINARY_DIR}/sphinx/") - # User warning - Sphinx is a static pages generator, and configured to work fine with user_version - # Images and biblio warnings because not found on developper version - if (GUDHI_PYTHON_PATH STREQUAL "src/python") - set (GUDHI_SPHINX_MESSAGE "${GUDHI_SPHINX_MESSAGE} \n WARNING : Sphinx is configured for user version, you run it on developper version. Images and biblio will miss") - endif() - # sphinx target requires gudhi.so, because conf.py reads gudhi version from it - add_custom_target(sphinx - WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/doc - COMMAND ${CMAKE_COMMAND} -E env "PYTHONPATH=${CMAKE_CURRENT_BINARY_DIR}" - ${SPHINX_PATH} -b html ${CMAKE_CURRENT_SOURCE_DIR}/doc ${CMAKE_CURRENT_BINARY_DIR}/sphinx - DEPENDS "${CMAKE_CURRENT_BINARY_DIR}/gudhi.so" - COMMENT "${GUDHI_SPHINX_MESSAGE}" VERBATIM) + if(PYBIND11_FOUND) + if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) + set (GUDHI_SPHINX_MESSAGE "Generating API documentation with Sphinx in ${CMAKE_CURRENT_BINARY_DIR}/sphinx/") + # User warning - Sphinx is a static pages generator, and configured to work fine with user_version + # Images and biblio warnings because not found on developper version + if (GUDHI_PYTHON_PATH STREQUAL "src/python") + set (GUDHI_SPHINX_MESSAGE "${GUDHI_SPHINX_MESSAGE} \n WARNING : Sphinx is configured for user version, you run it on developper version. Images and biblio will miss") + endif() + # sphinx target requires gudhi.so, because conf.py reads gudhi version from it + add_custom_target(sphinx + WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/doc + COMMAND ${CMAKE_COMMAND} -E env "PYTHONPATH=${CMAKE_CURRENT_BINARY_DIR}" + ${SPHINX_PATH} -b html ${CMAKE_CURRENT_SOURCE_DIR}/doc ${CMAKE_CURRENT_BINARY_DIR}/sphinx + DEPENDS "${CMAKE_CURRENT_BINARY_DIR}/gudhi.so" + COMMENT "${GUDHI_SPHINX_MESSAGE}" VERBATIM) - add_test(NAME sphinx_py_test - WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR} - COMMAND ${CMAKE_COMMAND} -E env "PYTHONPATH=${CMAKE_CURRENT_BINARY_DIR}" - ${SPHINX_PATH} -b doctest ${CMAKE_CURRENT_SOURCE_DIR}/doc ${CMAKE_CURRENT_BINARY_DIR}/doctest) + add_test(NAME sphinx_py_test + WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR} + COMMAND ${CMAKE_COMMAND} -E env "PYTHONPATH=${CMAKE_CURRENT_BINARY_DIR}" + ${SPHINX_PATH} -b doctest ${CMAKE_CURRENT_SOURCE_DIR}/doc ${CMAKE_CURRENT_BINARY_DIR}/doctest) - # Set missing or not modules - set(GUDHI_MODULES ${GUDHI_MODULES} "python-documentation" CACHE INTERNAL "GUDHI_MODULES") - else(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) - message("++ Python documentation module will not be compiled because it requires a Eigen3 and CGAL version >= 4.11.0") + # Set missing or not modules + set(GUDHI_MODULES ${GUDHI_MODULES} "python-documentation" CACHE INTERNAL "GUDHI_MODULES") + else(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) + message("++ Python documentation module will not be compiled because it requires a Eigen3 and CGAL version >= 4.11.0") + set(GUDHI_MISSING_MODULES ${GUDHI_MISSING_MODULES} "python-documentation" CACHE INTERNAL "GUDHI_MISSING_MODULES") + endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) + else(PYBIND11_FOUND) + message("++ Python documentation module will not be compiled because pybind11 was not found") set(GUDHI_MISSING_MODULES ${GUDHI_MISSING_MODULES} "python-documentation" CACHE INTERNAL "GUDHI_MISSING_MODULES") - endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0) + endif(PYBIND11_FOUND) else(OT_FOUND) message("++ Python documentation module will not be compiled because POT was not found") set(GUDHI_MISSING_MODULES ${GUDHI_MISSING_MODULES} "python-documentation" CACHE INTERNAL "GUDHI_MISSING_MODULES") diff --git a/src/python/doc/_templates/layout.html b/src/python/doc/_templates/layout.html index 2f2d9c72..a672a281 100644 --- a/src/python/doc/_templates/layout.html +++ b/src/python/doc/_templates/layout.html @@ -201,7 +201,7 @@ <a href="#">Download</a> <ul class="dropdown"> <li><a href="/licensing/">Licensing</a></li> - <li><a href="https://gforge.inria.fr/frs/download.php/latestzip/5253/library-latest.zip" target="_blank">Get the latest sources</a></li> + <li><a href="https://github.com/GUDHI/gudhi-devel/releases/latest" target="_blank">Get the latest sources</a></li> <li><a href="/conda/">Conda package</a></li> <li><a href="/dockerfile/">Dockerfile</a></li> </ul> diff --git a/src/python/doc/alpha_complex_sum.inc b/src/python/doc/alpha_complex_sum.inc index c5ba9dc7..b5af0d27 100644 --- a/src/python/doc/alpha_complex_sum.inc +++ b/src/python/doc/alpha_complex_sum.inc @@ -5,16 +5,13 @@ | .. figure:: | Alpha complex is a simplicial complex constructed from the finite | :Author: Vincent Rouvreau | | ../../doc/Alpha_complex/alpha_complex_representation.png | cells of a Delaunay Triangulation. | | | :alt: Alpha complex representation | | :Introduced in: GUDHI 2.0.0 | - | :figclass: align-center | The filtration value of each simplex is computed as the square of the | | - | | circumradius of the simplex if the circumsphere is empty (the simplex | :Copyright: MIT (`GPL v3 </licensing/>`_) | - | | is then said to be Gabriel), and as the minimum of the filtration | | - | | values of the codimension 1 cofaces that make it not Gabriel | :Requires: `Eigen <installation.html#eigen>`__ :math:`\geq` 3.1.0 and `CGAL <installation.html#cgal>`__ :math:`\geq` 4.11.0 | - | | otherwise. All simplices that have a filtration value strictly | | - | | greater than a given alpha squared value are not inserted into the | | - | | complex. | | + | :figclass: align-center | The filtration value of each simplex is computed as the **square** of | | + | | the circumradius of the simplex if the circumsphere is empty (the | :Copyright: MIT (`GPL v3 </licensing/>`_) | + | | simplex is then said to be Gabriel), and as the minimum of the | | + | | filtration values of the codimension 1 cofaces that make it not | :Requires: `Eigen <installation.html#eigen>`__ :math:`\geq` 3.1.0 and `CGAL <installation.html#cgal>`__ :math:`\geq` 4.11.0 | + | | Gabriel otherwise. | | | | | | - | | This package requires having CGAL version 4.7 or higher (4.8.1 is | | - | | advised for better performance). | | + | | For performances reasons, it is advised to use CGAL ≥ 5.0.0. | | +----------------------------------------------------------------+------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------+ | * :doc:`alpha_complex_user` | * :doc:`alpha_complex_ref` | +----------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ diff --git a/src/python/doc/alpha_complex_user.rst b/src/python/doc/alpha_complex_user.rst index b7e69e12..60319e84 100644 --- a/src/python/doc/alpha_complex_user.rst +++ b/src/python/doc/alpha_complex_user.rst @@ -16,7 +16,8 @@ Definition Remarks ^^^^^^^ -When an :math:`\alpha`-complex is constructed with an infinite value of :math:`\alpha`, the complex is a Delaunay complex (with special filtration values). +When an :math:`\alpha`-complex is constructed with an infinite value of :math:`\alpha^2`, +the complex is a Delaunay complex (with special filtration values). Example from points ------------------- @@ -137,19 +138,20 @@ sets the filtration value (0 in case of a vertex - propagation will have no effe Non decreasing filtration values ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -As the squared radii computed by CGAL are an approximation, it might happen that these alpha squared values do not -quite define a proper filtration (i.e. non-decreasing with respect to inclusion). +As the squared radii computed by CGAL are an approximation, it might happen that these +:math:`\alpha^2` values do not quite define a proper filtration (i.e. non-decreasing with +respect to inclusion). We fix that up by calling :func:`~gudhi.SimplexTree.make_filtration_non_decreasing` (cf. `C++ version <http://gudhi.gforge.inria.fr/doc/latest/index.html>`_). Prune above given filtration value ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ -The simplex tree is pruned from the given maximum alpha squared value (cf. +The simplex tree is pruned from the given maximum :math:`\alpha^2` value (cf. :func:`~gudhi.SimplexTree.prune_above_filtration`). Note that this does not provide any kind of speed-up, since we always first build the full filtered complex, so it is recommended not to use :paramref:`~gudhi.AlphaComplex.create_simplex_tree.max_alpha_square`. -In the following example, a threshold of 59 is used. +In the following example, a threshold of :math:`\alpha^2 = 32.0` is used. Example from OFF file @@ -166,7 +168,7 @@ Then, it is asked to display information about the alpha complex: import gudhi alpha_complex = gudhi.AlphaComplex(off_file=gudhi.__root_source_dir__ + \ '/data/points/alphacomplexdoc.off') - simplex_tree = alpha_complex.create_simplex_tree(max_alpha_square=59.0) + simplex_tree = alpha_complex.create_simplex_tree(max_alpha_square=32.0) result_str = 'Alpha complex is of dimension ' + repr(simplex_tree.dimension()) + ' - ' + \ repr(simplex_tree.num_simplices()) + ' simplices - ' + \ repr(simplex_tree.num_vertices()) + ' vertices.' @@ -179,7 +181,7 @@ the program output is: .. testoutput:: - Alpha complex is of dimension 2 - 23 simplices - 7 vertices. + Alpha complex is of dimension 2 - 20 simplices - 7 vertices. [0] -> 0.00 [1] -> 0.00 [2] -> 0.00 @@ -200,9 +202,6 @@ the program output is: [4, 6] -> 22.74 [4, 5, 6] -> 22.74 [3, 6] -> 30.25 - [2, 6] -> 36.50 - [2, 3, 6] -> 36.50 - [2, 4, 6] -> 37.24 CGAL citations ============== diff --git a/src/python/doc/cubical_complex_user.rst b/src/python/doc/cubical_complex_user.rst index b13b500e..56cf0170 100644 --- a/src/python/doc/cubical_complex_user.rst +++ b/src/python/doc/cubical_complex_user.rst @@ -142,8 +142,7 @@ Or it can be defined as follows: .. testcode:: from gudhi import PeriodicCubicalComplex as pcc - periodic_cc = pcc(dimensions=[3,3], - top_dimensional_cells= [0, 0, 0, 0, 1, 0, 0, 0, 0], + periodic_cc = pcc(top_dimensional_cells = [[0, 0, 0], [0, 1, 0], [0, 0, 0]], periodic_dimensions=[True, False]) result_str = 'Periodic cubical complex is of dimension ' + repr(periodic_cc.dimension()) + ' - ' + \ repr(periodic_cc.num_simplices()) + ' simplices.' diff --git a/src/python/doc/reader_utils_ref.rst b/src/python/doc/diagram_readers_ref.rst index f3ecebad..c79daf9c 100644 --- a/src/python/doc/reader_utils_ref.rst +++ b/src/python/doc/diagram_readers_ref.rst @@ -2,13 +2,9 @@ .. To get rid of WARNING: document isn't included in any toctree -============================= -Reader utils reference manual -============================= - -.. autofunction:: gudhi.read_off - -.. autofunction:: gudhi.read_lower_triangular_matrix_from_csv_file +================================ +Diagram readers reference manual +================================ .. autofunction:: gudhi.read_persistence_intervals_grouped_by_dimension diff --git a/src/python/doc/index.rst b/src/python/doc/index.rst index c36a578f..3387a64f 100644 --- a/src/python/doc/index.rst +++ b/src/python/doc/index.rst @@ -6,8 +6,8 @@ GUDHI Python modules documentation :alt: Gudhi banner :figclass: align-center -Complexes -********* +Data structures for cell complexes +********************************** Cubical complexes ================= @@ -17,18 +17,26 @@ Cubical complexes Simplicial complexes ==================== +Simplex tree +------------ + +.. include:: simplex_tree_sum.inc + +Filtrations and reconstructions +******************************* + Alpha complex -------------- +============= .. include:: alpha_complex_sum.inc Rips complex ------------- +============ .. include:: rips_complex_sum.inc Witness complex ---------------- +=============== .. include:: witness_complex_sum.inc @@ -37,16 +45,10 @@ Cover complexes .. include:: nerve_gic_complex_sum.inc -Data structures and basic operations -************************************ - -Data structures -=============== - -Simplex tree ------------- +Tangential complex +================== -.. include:: simplex_tree_sum.inc +.. include:: tangential_complex_sum.inc Topological descriptors computation *********************************** @@ -56,15 +58,6 @@ Persistence cohomology .. include:: persistent_cohomology_sum.inc -Manifold reconstruction -*********************** - -Tangential complex -================== - -.. include:: tangential_complex_sum.inc - - Topological descriptors tools ***************************** @@ -88,6 +81,11 @@ Persistence graphical tools .. include:: persistence_graphical_tools_sum.inc +Point cloud utilities +********************* + +.. include:: point_cloud_sum.inc + Bibliography ************ diff --git a/src/python/doc/installation.rst b/src/python/doc/installation.rst index 50a697c7..d459145b 100644 --- a/src/python/doc/installation.rst +++ b/src/python/doc/installation.rst @@ -14,10 +14,11 @@ Compiling ********* The library uses c++14 and requires `Boost <https://www.boost.org/>`_ ≥ 1.56.0, `CMake <https://www.cmake.org/>`_ ≥ 3.1 to generate makefiles, -`NumPy <http://numpy.org>`_ and `Cython <https://www.cython.org/>`_ to compile +`NumPy <http://numpy.org>`_, `Cython <https://www.cython.org/>`_ and +`pybind11 <https://github.com/pybind/pybind11>`_ to compile the GUDHI Python module. It is a multi-platform library and compiles on Linux, Mac OSX and Visual -Studio 2015. +Studio 2017. On `Windows <https://wiki.python.org/moin/WindowsCompilers>`_ , only Python ≥ 3.5 are available because of the required Visual Studio version. @@ -257,6 +258,13 @@ The :doc:`Wasserstein distance </wasserstein_distance_user>` module requires `POT <https://pot.readthedocs.io/>`_, a library that provides several solvers for optimization problems related to Optimal Transport. +Scikit-learn +============ + +The :doc:`persistence representations </representations>` module require +`scikit-learn <https://scikit-learn.org/>`_, a Python-based ecosystem of +open-source software for machine learning. + SciPy ===== diff --git a/src/python/doc/persistence_graphical_tools_user.rst b/src/python/doc/persistence_graphical_tools_user.rst index f41a926b..80002db6 100644 --- a/src/python/doc/persistence_graphical_tools_user.rst +++ b/src/python/doc/persistence_graphical_tools_user.rst @@ -24,7 +24,7 @@ This function can display the persistence result as a barcode: import gudhi off_file = gudhi.__root_source_dir__ + '/data/points/tore3D_300.off' - point_cloud = gudhi.read_off(off_file=off_file) + point_cloud = gudhi.read_points_from_off_file(off_file=off_file) rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=0.7) simplex_tree = rips_complex.create_simplex_tree(max_dimension=3) diff --git a/src/python/doc/point_cloud.rst b/src/python/doc/point_cloud.rst new file mode 100644 index 00000000..d668428a --- /dev/null +++ b/src/python/doc/point_cloud.rst @@ -0,0 +1,22 @@ +:orphan: + +.. To get rid of WARNING: document isn't included in any toctree + +============================ +Point cloud utilities manual +============================ + +File Readers +------------ + +.. autofunction:: gudhi.read_points_from_off_file + +.. autofunction:: gudhi.read_lower_triangular_matrix_from_csv_file + +Subsampling +----------- + +.. automodule:: gudhi.subsampling + :members: + :special-members: + :show-inheritance: diff --git a/src/python/doc/point_cloud_sum.inc b/src/python/doc/point_cloud_sum.inc new file mode 100644 index 00000000..85d52de7 --- /dev/null +++ b/src/python/doc/point_cloud_sum.inc @@ -0,0 +1,15 @@ +.. table:: + :widths: 30 50 20 + + +----------------------------------------------------------------+------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------+ + | | :math:`(x_1, x_2, \ldots, x_d)` | Utilities to process point clouds: read from file, subsample, etc. | :Author: Vincent Rouvreau | + | | :math:`(y_1, y_2, \ldots, y_d)` | | | + | | | :Introduced in: GUDHI 2.0.0 | + | | | | + | | | :Copyright: MIT (`GPL v3 </licensing/>`_) | + | | Parts of this package require CGAL. | | + | | | :Requires: `Eigen <installation.html#eigen>`__ :math:`\geq` 3.1.0 and `CGAL <installation.html#cgal>`__ :math:`\geq` 4.11.0 | + | | | | + +----------------------------------------------------------------+------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------------------+ + | * :doc:`point_cloud` | + +----------------------------------------------------------------+------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+ diff --git a/src/python/doc/rips_complex_user.rst b/src/python/doc/rips_complex_user.rst index a8659542..a27573e8 100644 --- a/src/python/doc/rips_complex_user.rst +++ b/src/python/doc/rips_complex_user.rst @@ -136,7 +136,8 @@ Finally, it is asked to display information about the Rips complex. .. testcode:: import gudhi - point_cloud = gudhi.read_off(off_file=gudhi.__root_source_dir__ + '/data/points/alphacomplexdoc.off') + off_file = gudhi.__root_source_dir__ + '/data/points/alphacomplexdoc.off' + point_cloud = gudhi.read_points_from_off_file(off_file = off_file) rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=12.0) simplex_tree = rips_complex.create_simplex_tree(max_dimension=1) result_str = 'Rips complex is of dimension ' + repr(simplex_tree.dimension()) + ' - ' + \ diff --git a/src/python/doc/wasserstein_distance_sum.inc b/src/python/doc/wasserstein_distance_sum.inc index ffd4d312..a97f428d 100644 --- a/src/python/doc/wasserstein_distance_sum.inc +++ b/src/python/doc/wasserstein_distance_sum.inc @@ -2,12 +2,12 @@ :widths: 30 50 20 +-----------------------------------------------------------------+----------------------------------------------------------------------+------------------------------------------------------------------+ - | .. figure:: | The p-Wasserstein distance measures the similarity between two | :Author: Theo Lacombe | + | .. figure:: | The q-Wasserstein distance measures the similarity between two | :Author: Theo Lacombe | | ../../doc/Bottleneck_distance/perturb_pd.png | persistence diagrams. It's the minimum value c that can be achieved | | | :figclass: align-center | by a perfect matching between the points of the two diagrams (+ all | :Introduced in: GUDHI 3.1.0 | | | diagonal points), where the value of a matching is defined as the | | - | Wasserstein distance is the p-th root of the sum of the | p-th root of the sum of all edge lengths to the power p. Edge lengths| :Copyright: MIT | - | edge lengths to the power p. | are measured in norm q, for :math:`1 \leq q \leq \infty`. | | + | Wasserstein distance is the q-th root of the sum of the | q-th root of the sum of all edge lengths to the power q. Edge lengths| :Copyright: MIT | + | edge lengths to the power q. | are measured in norm p, for :math:`1 \leq p \leq \infty`. | | | | | :Requires: Python Optimal Transport (POT) :math:`\geq` 0.5.1 | +-----------------------------------------------------------------+----------------------------------------------------------------------+------------------------------------------------------------------+ | * :doc:`wasserstein_distance_user` | | diff --git a/src/python/doc/wasserstein_distance_user.rst b/src/python/doc/wasserstein_distance_user.rst index a049cfb5..94b454e2 100644 --- a/src/python/doc/wasserstein_distance_user.rst +++ b/src/python/doc/wasserstein_distance_user.rst @@ -9,17 +9,26 @@ Definition .. include:: wasserstein_distance_sum.inc -This implementation is based on ideas from "Large Scale Computation of Means and Cluster for Persistence Diagrams via Optimal Transport". +Functions +--------- +This implementation uses the Python Optimal Transport library and is based on +ideas from "Large Scale Computation of Means and Cluster for Persistence +Diagrams via Optimal Transport" :cite:`10.5555/3327546.3327645`. -Function --------- .. autofunction:: gudhi.wasserstein.wasserstein_distance +This other implementation comes from `Hera +<https://bitbucket.org/grey_narn/hera/src/master/>`_ (BSD-3-Clause) which is +based on "Geometry Helps to Compare Persistence Diagrams" +:cite:`Kerber:2017:GHC:3047249.3064175` by Michael Kerber, Dmitriy +Morozov, and Arnur Nigmetov. + +.. autofunction:: gudhi.hera.wasserstein_distance Basic example ------------- -This example computes the 1-Wasserstein distance from 2 persistence diagrams with euclidean ground metric. +This example computes the 1-Wasserstein distance from 2 persistence diagrams with Euclidean ground metric. Note that persistence diagrams must be submitted as (n x 2) numpy arrays and must not contain inf values. .. testcode:: @@ -30,7 +39,7 @@ Note that persistence diagrams must be submitted as (n x 2) numpy arrays and mus diag1 = np.array([[2.7, 3.7],[9.6, 14.],[34.2, 34.974]]) diag2 = np.array([[2.8, 4.45],[9.5, 14.1]]) - message = "Wasserstein distance value = " + '%.2f' % gudhi.wasserstein.wasserstein_distance(diag1, diag2, q=2., p=1.) + message = "Wasserstein distance value = " + '%.2f' % gudhi.wasserstein.wasserstein_distance(diag1, diag2, order=1., internal_p=2.) print(message) The output is: diff --git a/src/python/doc/witness_complex_user.rst b/src/python/doc/witness_complex_user.rst index 45ba5b3b..7087fa98 100644 --- a/src/python/doc/witness_complex_user.rst +++ b/src/python/doc/witness_complex_user.rst @@ -101,7 +101,7 @@ Let's start with a simple example, which reads an off point file and computes a print("#####################################################################") print("EuclideanWitnessComplex creation from points read in a OFF file") - witnesses = gudhi.read_off(off_file=args.file) + witnesses = gudhi.read_points_from_off_file(off_file=args.file) landmarks = gudhi.pick_n_random_points(points=witnesses, nb_points=args.number_of_landmarks) message = "EuclideanWitnessComplex with max_edge_length=" + repr(args.max_alpha_square) + \ diff --git a/src/python/example/alpha_complex_from_points_example.py b/src/python/example/alpha_complex_from_points_example.py index a746998c..844d7a82 100755 --- a/src/python/example/alpha_complex_from_points_example.py +++ b/src/python/example/alpha_complex_from_points_example.py @@ -52,4 +52,9 @@ print("star([0])=", simplex_tree.get_star([0])) print("coface([0], 1)=", simplex_tree.get_cofaces([0], 1)) print("point[0]=", alpha_complex.get_point(0)) -print("point[5]=", alpha_complex.get_point(5)) +try: + print("point[5]=", alpha_complex.get_point(5)) +except IndexError: + pass +else: + assert False diff --git a/src/python/example/alpha_rips_persistence_bottleneck_distance.py b/src/python/example/alpha_rips_persistence_bottleneck_distance.py index 086307ee..d5c33ec8 100755 --- a/src/python/example/alpha_rips_persistence_bottleneck_distance.py +++ b/src/python/example/alpha_rips_persistence_bottleneck_distance.py @@ -35,7 +35,7 @@ args = parser.parse_args() with open(args.file, "r") as f: first_line = f.readline() if (first_line == "OFF\n") or (first_line == "nOFF\n"): - point_cloud = gudhi.read_off(off_file=args.file) + point_cloud = gudhi.read_points_from_off_file(off_file=args.file) print("#####################################################################") print("RipsComplex creation from points read in a OFF file") diff --git a/src/python/example/euclidean_strong_witness_complex_diagram_persistence_from_off_file_example.py b/src/python/example/euclidean_strong_witness_complex_diagram_persistence_from_off_file_example.py index 0eedd140..4903667e 100755 --- a/src/python/example/euclidean_strong_witness_complex_diagram_persistence_from_off_file_example.py +++ b/src/python/example/euclidean_strong_witness_complex_diagram_persistence_from_off_file_example.py @@ -47,7 +47,7 @@ with open(args.file, "r") as f: print("#####################################################################") print("EuclideanStrongWitnessComplex creation from points read in a OFF file") - witnesses = gudhi.read_off(off_file=args.file) + witnesses = gudhi.read_points_from_off_file(off_file=args.file) landmarks = gudhi.pick_n_random_points( points=witnesses, nb_points=args.number_of_landmarks ) diff --git a/src/python/example/euclidean_witness_complex_diagram_persistence_from_off_file_example.py b/src/python/example/euclidean_witness_complex_diagram_persistence_from_off_file_example.py index 1fe55737..339a8577 100755 --- a/src/python/example/euclidean_witness_complex_diagram_persistence_from_off_file_example.py +++ b/src/python/example/euclidean_witness_complex_diagram_persistence_from_off_file_example.py @@ -46,7 +46,7 @@ with open(args.file, "r") as f: print("#####################################################################") print("EuclideanWitnessComplex creation from points read in a OFF file") - witnesses = gudhi.read_off(off_file=args.file) + witnesses = gudhi.read_points_from_off_file(off_file=args.file) landmarks = gudhi.pick_n_random_points( points=witnesses, nb_points=args.number_of_landmarks ) diff --git a/src/python/example/plot_rips_complex.py b/src/python/example/plot_rips_complex.py index 1c878db1..214a3c0a 100755 --- a/src/python/example/plot_rips_complex.py +++ b/src/python/example/plot_rips_complex.py @@ -2,7 +2,7 @@ import numpy as np import gudhi -points = np.array(gudhi.read_off('../../data/points/Kl.off')) +points = np.array(gudhi.read_points_from_off_file('../../data/points/Kl.off')) rc = gudhi.RipsComplex(points=points, max_edge_length=.2) st = rc.create_simplex_tree(max_dimension=2) # We are only going to plot the triangles diff --git a/src/python/example/rips_complex_diagram_persistence_from_off_file_example.py b/src/python/example/rips_complex_diagram_persistence_from_off_file_example.py index b9074cf9..c757aca7 100755 --- a/src/python/example/rips_complex_diagram_persistence_from_off_file_example.py +++ b/src/python/example/rips_complex_diagram_persistence_from_off_file_example.py @@ -48,7 +48,7 @@ with open(args.file, "r") as f: message = "RipsComplex with max_edge_length=" + repr(args.max_edge_length) print(message) - point_cloud = gudhi.read_off(off_file=args.file) + point_cloud = gudhi.read_points_from_off_file(off_file=args.file) rips_complex = gudhi.RipsComplex( points=point_cloud, max_edge_length=args.max_edge_length ) diff --git a/src/python/gudhi/__init__.py.in b/src/python/gudhi/__init__.py.in index 0c462b02..79e12fbc 100644 --- a/src/python/gudhi/__init__.py.in +++ b/src/python/gudhi/__init__.py.in @@ -1,5 +1,3 @@ -from importlib import import_module - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -9,6 +7,9 @@ from importlib import import_module # Modification(s): # - YYYY/MM Author: Description of the modification +from importlib import import_module +from sys import exc_info + __author__ = "GUDHI Editorial Board" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "https://gudhi.inria.fr/licensing/" @@ -17,9 +18,6 @@ __version__ = "@GUDHI_VERSION@" __root_source_dir__ = "@CMAKE_SOURCE_DIR@" __debug_info__ = @GUDHI_PYTHON_DEBUG_INFO@ -from sys import exc_info -from importlib import import_module - __all__ = [@GUDHI_PYTHON_MODULES@ @GUDHI_PYTHON_MODULES_EXTRA@] __available_modules = '' diff --git a/src/python/gudhi/alpha_complex.pyx b/src/python/gudhi/alpha_complex.pyx index 8f2c98d5..fff3e920 100644 --- a/src/python/gudhi/alpha_complex.pyx +++ b/src/python/gudhi/alpha_complex.pyx @@ -1,3 +1,12 @@ +# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. +# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. +# Author(s): Vincent Rouvreau +# +# Copyright (C) 2016 Inria +# +# Modification(s): +# - YYYY/MM Author: Description of the modification + from cython cimport numeric from libcpp.vector cimport vector from libcpp.utility cimport pair @@ -9,26 +18,17 @@ import os from gudhi.simplex_tree cimport * from gudhi.simplex_tree import SimplexTree -# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. -# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. -# Author(s): Vincent Rouvreau -# -# Copyright (C) 2016 Inria -# -# Modification(s): -# - YYYY/MM Author: Description of the modification - __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" cdef extern from "Alpha_complex_interface.h" namespace "Gudhi": cdef cppclass Alpha_complex_interface "Gudhi::alpha_complex::Alpha_complex_interface": - Alpha_complex_interface(vector[vector[double]] points) + Alpha_complex_interface(vector[vector[double]] points) except + # bool from_file is a workaround for cython to find the correct signature - Alpha_complex_interface(string off_file, bool from_file) - vector[double] get_point(int vertex) - void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) + Alpha_complex_interface(string off_file, bool from_file) except + + vector[double] get_point(int vertex) except + + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except + # AlphaComplex python interface cdef class AlphaComplex: @@ -66,10 +66,10 @@ cdef class AlphaComplex: """ # The real cython constructor - def __cinit__(self, points=None, off_file=''): + def __cinit__(self, points = None, off_file = ''): if off_file: if os.path.isfile(off_file): - self.thisptr = new Alpha_complex_interface(str.encode(off_file), True) + self.thisptr = new Alpha_complex_interface(off_file.encode('utf-8'), True) else: print("file " + off_file + " not found.") else: @@ -96,10 +96,9 @@ cdef class AlphaComplex: :rtype: list of float :returns: the point. """ - cdef vector[double] point = self.thisptr.get_point(vertex) - return point + return self.thisptr.get_point(vertex) - def create_simplex_tree(self, max_alpha_square=float('inf')): + def create_simplex_tree(self, max_alpha_square = float('inf')): """ :param max_alpha_square: The maximum alpha square threshold the simplices shall not exceed. Default is set to infinity, and diff --git a/src/python/gudhi/bottleneck.pyx b/src/python/gudhi/bottleneck.pyx index c2361024..af011e88 100644 --- a/src/python/gudhi/bottleneck.pyx +++ b/src/python/gudhi/bottleneck.pyx @@ -1,8 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -import os - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -12,6 +7,11 @@ import os # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +import os + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" diff --git a/src/python/gudhi/cubical_complex.pyx b/src/python/gudhi/cubical_complex.pyx index 011c407c..cbeda014 100644 --- a/src/python/gudhi/cubical_complex.pyx +++ b/src/python/gudhi/cubical_complex.pyx @@ -1,12 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libcpp.string cimport string -from libcpp cimport bool -import os - -from numpy import array as np_array - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -16,6 +7,15 @@ from numpy import array as np_array # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libcpp.string cimport string +from libcpp cimport bool +import os + +import numpy as np + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -47,7 +47,7 @@ cdef class CubicalComplex: # Fake constructor that does nothing but documenting the constructor def __init__(self, dimensions=None, top_dimensional_cells=None, - perseus_file=''): + perseus_file=''): """CubicalComplex constructor from dimensions and top_dimensional_cells or from a Perseus-style file name. @@ -58,6 +58,12 @@ cdef class CubicalComplex: Or + :param top_dimensional_cells: A multidimensional array of cells + filtration values. + :type top_dimensional_cells: anything convertible to a numpy ndarray + + Or + :param perseus_file: A Perseus-style file name. :type perseus_file: string """ @@ -65,11 +71,21 @@ cdef class CubicalComplex: # The real cython constructor def __cinit__(self, dimensions=None, top_dimensional_cells=None, perseus_file=''): - if (dimensions is not None) and (top_dimensional_cells is not None) and (perseus_file == ''): + if ((dimensions is not None) and (top_dimensional_cells is not None) + and (perseus_file == '')): + self.thisptr = new Bitmap_cubical_complex_base_interface(dimensions, top_dimensional_cells) + elif ((dimensions is None) and (top_dimensional_cells is not None) + and (perseus_file == '')): + top_dimensional_cells = np.array(top_dimensional_cells, + copy = False, + order = 'F') + dimensions = top_dimensional_cells.shape + top_dimensional_cells = top_dimensional_cells.ravel(order='F') self.thisptr = new Bitmap_cubical_complex_base_interface(dimensions, top_dimensional_cells) - elif (dimensions is None) and (top_dimensional_cells is None) and (perseus_file != ''): + elif ((dimensions is None) and (top_dimensional_cells is None) + and (perseus_file != '')): if os.path.isfile(perseus_file): - self.thisptr = new Bitmap_cubical_complex_base_interface(str.encode(perseus_file)) + self.thisptr = new Bitmap_cubical_complex_base_interface(perseus_file.encode('utf-8')) else: print("file " + perseus_file + " not found.") else: @@ -184,4 +200,4 @@ cdef class CubicalComplex: else: print("intervals_in_dim function requires persistence function" " to be launched first.") - return np_array(intervals_result) + return np.array(intervals_result) diff --git a/src/python/gudhi/euclidean_strong_witness_complex.pyx b/src/python/gudhi/euclidean_strong_witness_complex.pyx index e3f451f0..aca6084e 100644 --- a/src/python/gudhi/euclidean_strong_witness_complex.pyx +++ b/src/python/gudhi/euclidean_strong_witness_complex.pyx @@ -1,11 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libc.stdint cimport intptr_t - -from gudhi.simplex_tree cimport * -from gudhi.simplex_tree import SimplexTree - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -15,6 +7,14 @@ from gudhi.simplex_tree import SimplexTree # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libc.stdint cimport intptr_t + +from gudhi.simplex_tree cimport * +from gudhi.simplex_tree import SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" @@ -22,9 +22,9 @@ __license__ = "GPL v3" cdef extern from "Euclidean_strong_witness_complex_interface.h" namespace "Gudhi": cdef cppclass Euclidean_strong_witness_complex_interface "Gudhi::witness_complex::Euclidean_strong_witness_complex_interface": Euclidean_strong_witness_complex_interface(vector[vector[double]] landmarks, vector[vector[double]] witnesses) - void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square, - unsigned limit_dimension) + unsigned limit_dimension) except + vector[double] get_point(unsigned vertex) # EuclideanStrongWitnessComplex python interface diff --git a/src/python/gudhi/euclidean_witness_complex.pyx b/src/python/gudhi/euclidean_witness_complex.pyx index 84a8ea1a..fb0c2201 100644 --- a/src/python/gudhi/euclidean_witness_complex.pyx +++ b/src/python/gudhi/euclidean_witness_complex.pyx @@ -1,11 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libc.stdint cimport intptr_t - -from gudhi.simplex_tree cimport * -from gudhi.simplex_tree import SimplexTree - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -15,6 +7,14 @@ from gudhi.simplex_tree import SimplexTree # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libc.stdint cimport intptr_t + +from gudhi.simplex_tree cimport * +from gudhi.simplex_tree import SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" @@ -22,9 +22,9 @@ __license__ = "GPL v3" cdef extern from "Euclidean_witness_complex_interface.h" namespace "Gudhi": cdef cppclass Euclidean_witness_complex_interface "Gudhi::witness_complex::Euclidean_witness_complex_interface": Euclidean_witness_complex_interface(vector[vector[double]] landmarks, vector[vector[double]] witnesses) - void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square, - unsigned limit_dimension) + unsigned limit_dimension) except + vector[double] get_point(unsigned vertex) # EuclideanWitnessComplex python interface diff --git a/src/python/gudhi/hera.cc b/src/python/gudhi/hera.cc new file mode 100644 index 00000000..0d562b4c --- /dev/null +++ b/src/python/gudhi/hera.cc @@ -0,0 +1,71 @@ +/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. + * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. + * Author(s): Marc Glisse + * + * Copyright (C) 2020 Inria + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <pybind11/pybind11.h> +#include <pybind11/numpy.h> + +#include <boost/range/iterator_range.hpp> + +#include <wasserstein.h> // Hera + +#include <array> + +namespace py = pybind11; +typedef py::array_t<double, py::array::c_style | py::array::forcecast> Dgm; + +double wasserstein_distance( + Dgm d1, Dgm d2, + double wasserstein_power, double internal_p, + double delta) +{ + py::buffer_info buf1 = d1.request(); + py::buffer_info buf2 = d2.request(); + // shape (n,2) or (0) for empty + if((buf1.ndim!=2 || buf1.shape[1]!=2) && (buf1.ndim!=1 || buf1.shape[0]!=0)) + throw std::runtime_error("Diagram 1 must be an array of size n x 2"); + if((buf2.ndim!=2 || buf2.shape[1]!=2) && (buf2.ndim!=1 || buf2.shape[0]!=0)) + throw std::runtime_error("Diagram 2 must be an array of size n x 2"); + typedef std::array<double, 2> Point; + auto p1 = (Point*)buf1.ptr; + auto p2 = (Point*)buf2.ptr; + auto diag1 = boost::make_iterator_range(p1, p1+buf1.shape[0]); + auto diag2 = boost::make_iterator_range(p2, p2+buf2.shape[0]); + + hera::AuctionParams<double> params; + params.wasserstein_power = wasserstein_power; + // hera encodes infinity as -1... + if(std::isinf(internal_p)) internal_p = hera::get_infinity<double>(); + params.internal_p = internal_p; + params.delta = delta; + // The extra parameters are purposedly not exposed for now. + return hera::wasserstein_dist(diag1, diag2, params); +} + +PYBIND11_MODULE(hera, m) { + m.def("wasserstein_distance", &wasserstein_distance, + py::arg("X"), py::arg("Y"), + py::arg("order") = 1, + py::arg("internal_p") = std::numeric_limits<double>::infinity(), + py::arg("delta") = .01, + R"pbdoc( + Compute the Wasserstein distance between two diagrams. + Points at infinity are supported. + + Parameters: + X (n x 2 numpy array): First diagram + Y (n x 2 numpy array): Second diagram + order (float): Wasserstein exponent W_q + internal_p (float): Internal Minkowski norm L^p in R^2 + delta (float): Relative error 1+delta + + Returns: + float: Approximate Wasserstein distance W_q(X,Y) + )pbdoc"); +} diff --git a/src/python/gudhi/nerve_gic.pyx b/src/python/gudhi/nerve_gic.pyx index acb78564..382e71c5 100644 --- a/src/python/gudhi/nerve_gic.pyx +++ b/src/python/gudhi/nerve_gic.pyx @@ -1,3 +1,12 @@ +# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. +# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. +# Author(s): Vincent Rouvreau +# +# Copyright (C) 2018 Inria +# +# Modification(s): +# - YYYY/MM Author: Description of the modification + from cython cimport numeric from libcpp.vector cimport vector from libcpp.utility cimport pair @@ -9,15 +18,6 @@ from libc.stdint cimport intptr_t from gudhi.simplex_tree cimport * from gudhi.simplex_tree import SimplexTree -# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. -# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. -# Author(s): Vincent Rouvreau -# -# Copyright (C) 2018 Inria -# -# Modification(s): -# - YYYY/MM Author: Description of the modification - __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2018 Inria" __license__ = "GPL v3" @@ -180,7 +180,7 @@ cdef class CoverComplex: :returns: Read file status. """ if os.path.isfile(off_file): - return self.thisptr.read_point_cloud(str.encode(off_file)) + return self.thisptr.read_point_cloud(off_file.encode('utf-8')) else: print("file " + off_file + " not found.") return False @@ -212,7 +212,7 @@ cdef class CoverComplex: :type color_file_name: string """ if os.path.isfile(color_file_name): - self.thisptr.set_color_from_file(str.encode(color_file_name)) + self.thisptr.set_color_from_file(color_file_name.encode('utf-8')) else: print("file " + color_file_name + " not found.") @@ -233,7 +233,7 @@ cdef class CoverComplex: :type cover_file_name: string """ if os.path.isfile(cover_file_name): - self.thisptr.set_cover_from_file(str.encode(cover_file_name)) + self.thisptr.set_cover_from_file(cover_file_name.encode('utf-8')) else: print("file " + cover_file_name + " not found.") @@ -266,7 +266,7 @@ cdef class CoverComplex: :type func_file_name: string """ if os.path.isfile(func_file_name): - self.thisptr.set_function_from_file(str.encode(func_file_name)) + self.thisptr.set_function_from_file(func_file_name.encode('utf-8')) else: print("file " + func_file_name + " not found.") @@ -307,7 +307,7 @@ cdef class CoverComplex: :type graph_file_name: string """ if os.path.isfile(graph_file_name): - self.thisptr.set_graph_from_file(str.encode(graph_file_name)) + self.thisptr.set_graph_from_file(graph_file_name.encode('utf-8')) else: print("file " + graph_file_name + " not found.") @@ -368,7 +368,7 @@ cdef class CoverComplex: :param type: either "GIC" or "Nerve". :type type: string """ - self.thisptr.set_type(str.encode(type)) + self.thisptr.set_type(type.encode('utf-8')) def set_verbose(self, verbose): """Specifies whether the program should display information or not. diff --git a/src/python/gudhi/off_reader.pyx b/src/python/gudhi/off_reader.pyx index 225e981c..7e6d9d80 100644 --- a/src/python/gudhi/off_reader.pyx +++ b/src/python/gudhi/off_reader.pyx @@ -1,8 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.string cimport string -import os - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -12,6 +7,11 @@ import os # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.string cimport string +import os + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -19,18 +19,18 @@ __license__ = "MIT" cdef extern from "Off_reader_interface.h" namespace "Gudhi": vector[vector[double]] read_points_from_OFF_file(string off_file) -def read_off(off_file=''): +def read_points_from_off_file(off_file=''): """Read points from OFF file. :param off_file: An OFF file style name. :type off_file: string :returns: The point set. - :rtype: vector[vector[double]] + :rtype: List[List[float]] """ if off_file: if os.path.isfile(off_file): - return read_points_from_OFF_file(str.encode(off_file)) + return read_points_from_OFF_file(off_file.encode('utf-8')) else: print("file " + off_file + " not found.") return [] diff --git a/src/python/gudhi/periodic_cubical_complex.pyx b/src/python/gudhi/periodic_cubical_complex.pyx index c89055db..37f76201 100644 --- a/src/python/gudhi/periodic_cubical_complex.pyx +++ b/src/python/gudhi/periodic_cubical_complex.pyx @@ -1,12 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libcpp.string cimport string -from libcpp cimport bool -import os - -from numpy import array as np_array - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -16,6 +7,15 @@ from numpy import array as np_array # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libcpp.string cimport string +from libcpp cimport bool +import os + +import numpy as np + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -47,7 +47,7 @@ cdef class PeriodicCubicalComplex: # Fake constructor that does nothing but documenting the constructor def __init__(self, dimensions=None, top_dimensional_cells=None, - periodic_dimensions=None, perseus_file=''): + periodic_dimensions=None, perseus_file=''): """PeriodicCubicalComplex constructor from dimensions and top_dimensional_cells or from a Perseus-style file name. @@ -60,6 +60,14 @@ cdef class PeriodicCubicalComplex: Or + :param top_dimensional_cells: A multidimensional array of cells + filtration values. + :type top_dimensional_cells: anything convertible to a numpy ndarray + :param periodic_dimensions: A list of top dimensional cells periodicity value. + :type periodic_dimensions: list of boolean + + Or + :param perseus_file: A Perseus-style file name. :type perseus_file: string """ @@ -67,16 +75,32 @@ cdef class PeriodicCubicalComplex: # The real cython constructor def __cinit__(self, dimensions=None, top_dimensional_cells=None, periodic_dimensions=None, perseus_file=''): - if (dimensions is not None) and (top_dimensional_cells is not None) and (periodic_dimensions is not None) and (perseus_file == ''): - self.thisptr = new Periodic_cubical_complex_base_interface(dimensions, top_dimensional_cells, periodic_dimensions) - elif (dimensions is None) and (top_dimensional_cells is None) and (periodic_dimensions is None) and (perseus_file != ''): + if ((dimensions is not None) and (top_dimensional_cells is not None) + and (periodic_dimensions is not None) and (perseus_file == '')): + self.thisptr = new Periodic_cubical_complex_base_interface(dimensions, + top_dimensional_cells, + periodic_dimensions) + elif ((dimensions is None) and (top_dimensional_cells is not None) + and (periodic_dimensions is not None) and (perseus_file == '')): + top_dimensional_cells = np.array(top_dimensional_cells, + copy = False, + order = 'F') + dimensions = top_dimensional_cells.shape + top_dimensional_cells = top_dimensional_cells.ravel(order='F') + self.thisptr = new Periodic_cubical_complex_base_interface(dimensions, + top_dimensional_cells, + periodic_dimensions) + elif ((dimensions is None) and (top_dimensional_cells is None) + and (periodic_dimensions is None) and (perseus_file != '')): if os.path.isfile(perseus_file): - self.thisptr = new Periodic_cubical_complex_base_interface(str.encode(perseus_file)) + self.thisptr = new Periodic_cubical_complex_base_interface(perseus_file.encode('utf-8')) else: print("file " + perseus_file + " not found.") else: - print("CubicalComplex can be constructed from dimensions and " - "top_dimensional_cells or from a Perseus-style file name.") + print("CubicalComplex can be constructed from dimensions, " + "top_dimensional_cells and periodic_dimensions, or from " + "top_dimensional_cells and periodic_dimensions or from " + "a Perseus-style file name.") def __dealloc__(self): if self.thisptr != NULL: @@ -186,4 +210,4 @@ cdef class PeriodicCubicalComplex: else: print("intervals_in_dim function requires persistence function" " to be launched first.") - return np_array(intervals_result) + return np.array(intervals_result) diff --git a/src/python/gudhi/persistence_graphical_tools.py b/src/python/gudhi/persistence_graphical_tools.py index 7d232c85..246280de 100644 --- a/src/python/gudhi/persistence_graphical_tools.py +++ b/src/python/gudhi/persistence_graphical_tools.py @@ -1,10 +1,3 @@ -from os import path -from math import isfinite -import numpy as np - -from gudhi.reader_utils import read_persistence_intervals_in_dimension -from gudhi.reader_utils import read_persistence_intervals_grouped_by_dimension - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau, Bertrand Michel @@ -14,6 +7,13 @@ from gudhi.reader_utils import read_persistence_intervals_grouped_by_dimension # Modification(s): # - YYYY/MM Author: Description of the modification +from os import path +from math import isfinite +import numpy as np + +from gudhi.reader_utils import read_persistence_intervals_in_dimension +from gudhi.reader_utils import read_persistence_intervals_grouped_by_dimension + __author__ = "Vincent Rouvreau, Bertrand Michel" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/gudhi/reader_utils.pyx b/src/python/gudhi/reader_utils.pyx index 6994c4f9..fe1c3a2e 100644 --- a/src/python/gudhi/reader_utils.pyx +++ b/src/python/gudhi/reader_utils.pyx @@ -1,12 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.string cimport string -from libcpp.map cimport map -from libcpp.pair cimport pair - -from os import path -from numpy import array as np_array - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -16,6 +7,15 @@ from numpy import array as np_array # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.string cimport string +from libcpp.map cimport map +from libcpp.pair cimport pair + +from os import path +from numpy import array as np_array + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2017 Inria" __license__ = "MIT" @@ -34,30 +34,30 @@ def read_lower_triangular_matrix_from_csv_file(csv_file='', separator=';'): :type separator: char :returns: The lower triangular matrix. - :rtype: vector[vector[double]] + :rtype: List[List[float]] """ if csv_file: if path.isfile(csv_file): - return read_matrix_from_csv_file(str.encode(csv_file), ord(separator[0])) + return read_matrix_from_csv_file(csv_file.encode('utf-8'), ord(separator[0])) print("file " + csv_file + " not set or not found.") return [] def read_persistence_intervals_grouped_by_dimension(persistence_file=''): """Reads a file containing persistence intervals. Each line might contain 2, 3 or 4 values: [[field] dimension] birth death - The return value is an `map[dim, vector[pair[birth, death]]]` - where `dim` is an `int`, `birth` a `double`, and `death` a `double`. + The return value is a `dict(dim, list(tuple(birth, death)))` + where `dim` is an `int`, `birth` a `float`, and `death` a `float`. Note: the function does not check that birth <= death. :param persistence_file: A persistence file style name. :type persistence_file: string :returns: The persistence pairs grouped by dimension. - :rtype: map[int, vector[pair[double, double]]] + :rtype: Dict[int, List[Tuple[float, float]]] """ if persistence_file: if path.isfile(persistence_file): - return read_pers_intervals_grouped_by_dimension(str.encode(persistence_file)) + return read_pers_intervals_grouped_by_dimension(persistence_file.encode('utf-8')) print("file " + persistence_file + " not set or not found.") return [] @@ -80,7 +80,7 @@ def read_persistence_intervals_in_dimension(persistence_file='', only_this_dim=- """ if persistence_file: if path.isfile(persistence_file): - return np_array(read_pers_intervals_in_dimension(str.encode( - persistence_file), only_this_dim)) + return np_array(read_pers_intervals_in_dimension(persistence_file.encode( + 'utf-8'), only_this_dim)) print("file " + persistence_file + " not set or not found.") return [] diff --git a/src/python/gudhi/rips_complex.pyx b/src/python/gudhi/rips_complex.pyx index cbbbab0d..deb8057a 100644 --- a/src/python/gudhi/rips_complex.pyx +++ b/src/python/gudhi/rips_complex.pyx @@ -1,3 +1,12 @@ +# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. +# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. +# Author(s): Vincent Rouvreau +# +# Copyright (C) 2016 Inria +# +# Modification(s): +# - YYYY/MM Author: Description of the modification + from cython cimport numeric from libcpp.vector cimport vector from libcpp.utility cimport pair @@ -8,15 +17,6 @@ from libc.stdint cimport intptr_t from gudhi.simplex_tree cimport * from gudhi.simplex_tree import SimplexTree -# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. -# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. -# Author(s): Vincent Rouvreau -# -# Copyright (C) 2016 Inria -# -# Modification(s): -# - YYYY/MM Author: Description of the modification - __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -28,7 +28,7 @@ cdef extern from "Rips_complex_interface.h" namespace "Gudhi": void init_matrix(vector[vector[double]] values, double threshold) void init_points_sparse(vector[vector[double]] values, double threshold, double sparse) void init_matrix_sparse(vector[vector[double]] values, double threshold, double sparse) - void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, int dim_max) + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, int dim_max) except + # RipsComplex python interface cdef class RipsComplex: diff --git a/src/python/gudhi/simplex_tree.pxd b/src/python/gudhi/simplex_tree.pxd index 5f86cfe2..96d14079 100644 --- a/src/python/gudhi/simplex_tree.pxd +++ b/src/python/gudhi/simplex_tree.pxd @@ -1,19 +1,18 @@ +# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. +# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. +# Author(s): Vincent Rouvreau +# +# Copyright (C) 2016 Inria +# +# Modification(s): +# - YYYY/MM Author: Description of the modification + from cython cimport numeric from libcpp.vector cimport vector from libcpp.utility cimport pair from libcpp cimport bool from libcpp.string cimport string -""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. - See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. - Author(s): Vincent Rouvreau - - Copyright (C) 2016 Inria - - Modification(s): - - YYYY/MM Author: Description of the modification -""" - __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -40,7 +39,7 @@ cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": vector[pair[vector[int], double]] get_star(vector[int] simplex) vector[pair[vector[int], double]] get_cofaces(vector[int] simplex, int dimension) - void expansion(int max_dim) + void expansion(int max_dim) except + void remove_maximal_simplex(vector[int] simplex) bool prune_above_filtration(double filtration) bool make_filtration_non_decreasing() diff --git a/src/python/gudhi/simplex_tree.pyx b/src/python/gudhi/simplex_tree.pyx index 4a3cd9bc..b18627c4 100644 --- a/src/python/gudhi/simplex_tree.pyx +++ b/src/python/gudhi/simplex_tree.pyx @@ -1,7 +1,3 @@ -from libc.stdint cimport intptr_t -from numpy import array as np_array -cimport simplex_tree - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -11,6 +7,10 @@ cimport simplex_tree # Modification(s): # - YYYY/MM Author: Description of the modification +from libc.stdint cimport intptr_t +from numpy import array as np_array +cimport simplex_tree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -508,7 +508,7 @@ cdef class SimplexTree: """ if self.pcohptr != NULL: if persistence_file != '': - self.pcohptr.write_output_diagram(str.encode(persistence_file)) + self.pcohptr.write_output_diagram(persistence_file.encode('utf-8')) else: print("persistence_file must be specified") else: diff --git a/src/python/gudhi/strong_witness_complex.pyx b/src/python/gudhi/strong_witness_complex.pyx index 66d49b49..9f89d3ae 100644 --- a/src/python/gudhi/strong_witness_complex.pyx +++ b/src/python/gudhi/strong_witness_complex.pyx @@ -1,11 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libc.stdint cimport intptr_t - -from gudhi.simplex_tree cimport * -from gudhi.simplex_tree import SimplexTree - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -15,6 +7,14 @@ from gudhi.simplex_tree import SimplexTree # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libc.stdint cimport intptr_t + +from gudhi.simplex_tree cimport * +from gudhi.simplex_tree import SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -22,9 +22,9 @@ __license__ = "MIT" cdef extern from "Strong_witness_complex_interface.h" namespace "Gudhi": cdef cppclass Strong_witness_complex_interface "Gudhi::witness_complex::Strong_witness_complex_interface": Strong_witness_complex_interface(vector[vector[pair[size_t, double]]] nearest_landmark_table) - void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square, - unsigned limit_dimension) + unsigned limit_dimension) except + # StrongWitnessComplex python interface cdef class StrongWitnessComplex: diff --git a/src/python/gudhi/subsampling.pyx b/src/python/gudhi/subsampling.pyx index e0cd1348..f77c6f75 100644 --- a/src/python/gudhi/subsampling.pyx +++ b/src/python/gudhi/subsampling.pyx @@ -1,9 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.string cimport string -from libcpp cimport bool -import os - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -13,6 +7,12 @@ import os # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.string cimport string +from libcpp cimport bool +import os + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" @@ -33,13 +33,15 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi The iteration starts with the landmark `starting point`. :param points: The input point set. - :type points: vector[vector[double]]. + :type points: Iterable[Iterable[float]]. Or :param off_file: An OFF file style name. :type off_file: string + And in both cases + :param nb_points: Number of points of the subsample. :type nb_points: unsigned. :param starting_point: The iteration starts with the landmark `starting \ @@ -47,15 +49,15 @@ def choose_n_farthest_points(points=None, off_file='', nb_points=0, starting_poi index is chosen randomly. :type starting_point: unsigned. :returns: The subsample point set. - :rtype: vector[vector[double]] + :rtype: List[List[float]]. """ if off_file: if os.path.isfile(off_file): if starting_point == '': - return subsampling_n_farthest_points_from_file(str.encode(off_file), + return subsampling_n_farthest_points_from_file(off_file.encode('utf-8'), nb_points) else: - return subsampling_n_farthest_points_from_file(str.encode(off_file), + return subsampling_n_farthest_points_from_file(off_file.encode('utf-8'), nb_points, starting_point) else: @@ -74,21 +76,23 @@ def pick_n_random_points(points=None, off_file='', nb_points=0): """Subsample a point set by picking random vertices. :param points: The input point set. - :type points: vector[vector[double]]. + :type points: Iterable[Iterable[float]]. Or :param off_file: An OFF file style name. :type off_file: string + And in both cases + :param nb_points: Number of points of the subsample. :type nb_points: unsigned. :returns: The subsample point set. - :rtype: vector[vector[double]] + :rtype: List[List[float]] """ if off_file: if os.path.isfile(off_file): - return subsampling_n_random_points_from_file(str.encode(off_file), + return subsampling_n_random_points_from_file(off_file.encode('utf-8'), nb_points) else: print("file " + off_file + " not found.") @@ -103,22 +107,24 @@ def sparsify_point_set(points=None, off_file='', min_squared_dist=0.0): between any two points is greater than or equal to min_squared_dist. :param points: The input point set. - :type points: vector[vector[double]]. + :type points: Iterable[Iterable[float]]. Or :param off_file: An OFF file style name. :type off_file: string + And in both cases + :param min_squared_dist: Minimum squared distance separating the output \ points. :type min_squared_dist: float. :returns: The subsample point set. - :rtype: vector[vector[double]] + :rtype: List[List[float]] """ if off_file: if os.path.isfile(off_file): - return subsampling_sparsify_points_from_file(str.encode(off_file), + return subsampling_sparsify_points_from_file(off_file.encode('utf-8'), min_squared_dist) else: print("file " + off_file + " not found.") diff --git a/src/python/gudhi/tangential_complex.pyx b/src/python/gudhi/tangential_complex.pyx index f4c8b079..6391488c 100644 --- a/src/python/gudhi/tangential_complex.pyx +++ b/src/python/gudhi/tangential_complex.pyx @@ -1,3 +1,12 @@ +# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. +# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. +# Author(s): Vincent Rouvreau +# +# Copyright (C) 2016 Inria +# +# Modification(s): +# - YYYY/MM Author: Description of the modification + from cython cimport numeric from libcpp.vector cimport vector from libcpp.utility cimport pair @@ -9,15 +18,6 @@ import os from gudhi.simplex_tree cimport * from gudhi.simplex_tree import SimplexTree -# This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. -# See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. -# Author(s): Vincent Rouvreau -# -# Copyright (C) 2016 Inria -# -# Modification(s): -# - YYYY/MM Author: Description of the modification - __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "GPL v3" @@ -66,7 +66,7 @@ cdef class TangentialComplex: def __cinit__(self, intrisic_dim, points=None, off_file=''): if off_file: if os.path.isfile(off_file): - self.thisptr = new Tangential_complex_interface(intrisic_dim, str.encode(off_file), True) + self.thisptr = new Tangential_complex_interface(intrisic_dim, off_file.encode('utf-8'), True) else: print("file " + off_file + " not found.") else: diff --git a/src/python/gudhi/wasserstein.py b/src/python/gudhi/wasserstein.py index d8a3104c..13102094 100644 --- a/src/python/gudhi/wasserstein.py +++ b/src/python/gudhi/wasserstein.py @@ -1,10 +1,3 @@ -import numpy as np -import scipy.spatial.distance as sc -try: - import ot -except ImportError: - print("POT (Python Optimal Transport) package is not installed. Try to run $ conda install -c conda-forge pot ; or $ pip install POT") - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Theo Lacombe @@ -14,6 +7,13 @@ except ImportError: # Modification(s): # - YYYY/MM Author: Description of the modification +import numpy as np +import scipy.spatial.distance as sc +try: + import ot +except ImportError: + print("POT (Python Optimal Transport) package is not installed. Try to run $ conda install -c conda-forge pot ; or $ pip install POT") + def _proj_on_diag(X): ''' :param X: (n x 2) array encoding the points of a persistent diagram. @@ -23,26 +23,26 @@ def _proj_on_diag(X): return np.array([Z , Z]).T -def _build_dist_matrix(X, Y, p=2., q=2.): +def _build_dist_matrix(X, Y, order=2., internal_p=2.): ''' :param X: (n x 2) numpy.array encoding the (points of the) first diagram. :param Y: (m x 2) numpy.array encoding the second diagram. - :param q: Ground metric (i.e. norm l_q). - :param p: exponent for the Wasserstein metric. + :param order: exponent for the Wasserstein metric. + :param internal_p: Ground metric (i.e. norm L^p). :returns: (n+1) x (m+1) np.array encoding the cost matrix C. For 1 <= i <= n, 1 <= j <= m, C[i,j] encodes the distance between X[i] and Y[j], while C[i, m+1] (resp. C[n+1, j]) encodes the distance (to the p) between X[i] (resp Y[j]) and its orthogonal proj onto the diagonal. note also that C[n+1, m+1] = 0 (it costs nothing to move from the diagonal to the diagonal). ''' Xdiag = _proj_on_diag(X) Ydiag = _proj_on_diag(Y) - if np.isinf(q): - C = sc.cdist(X,Y, metric='chebyshev')**p - Cxd = np.linalg.norm(X - Xdiag, ord=q, axis=1)**p - Cdy = np.linalg.norm(Y - Ydiag, ord=q, axis=1)**p + if np.isinf(internal_p): + C = sc.cdist(X,Y, metric='chebyshev')**order + Cxd = np.linalg.norm(X - Xdiag, ord=internal_p, axis=1)**order + Cdy = np.linalg.norm(Y - Ydiag, ord=internal_p, axis=1)**order else: - C = sc.cdist(X,Y, metric='minkowski', p=q)**p - Cxd = np.linalg.norm(X - Xdiag, ord=q, axis=1)**p - Cdy = np.linalg.norm(Y - Ydiag, ord=q, axis=1)**p + C = sc.cdist(X,Y, metric='minkowski', p=internal_p)**order + Cxd = np.linalg.norm(X - Xdiag, ord=internal_p, axis=1)**order + Cdy = np.linalg.norm(Y - Ydiag, ord=internal_p, axis=1)**order Cf = np.hstack((C, Cxd[:,None])) Cdy = np.append(Cdy, 0) @@ -51,24 +51,24 @@ def _build_dist_matrix(X, Y, p=2., q=2.): return Cf -def _perstot(X, p, q): +def _perstot(X, order, internal_p): ''' :param X: (n x 2) numpy.array (points of a given diagram). - :param q: Ground metric on the (upper-half) plane (i.e. norm l_q in R^2); Default value is 2 (Euclidean norm). - :param p: exponent for Wasserstein; Default value is 2. + :param order: exponent for Wasserstein. Default value is 2. + :param internal_p: Ground metric on the (upper-half) plane (i.e. norm L^p in R^2); Default value is 2 (Euclidean norm). :returns: float, the total persistence of the diagram (that is, its distance to the empty diagram). ''' Xdiag = _proj_on_diag(X) - return (np.sum(np.linalg.norm(X - Xdiag, ord=q, axis=1)**p))**(1./p) + return (np.sum(np.linalg.norm(X - Xdiag, ord=internal_p, axis=1)**order))**(1./order) -def wasserstein_distance(X, Y, p=2., q=2.): +def wasserstein_distance(X, Y, order=2., internal_p=2.): ''' :param X: (n x 2) numpy.array encoding the (finite points of the) first diagram. Must not contain essential points (i.e. with infinite coordinate). :param Y: (m x 2) numpy.array encoding the second diagram. - :param q: Ground metric on the (upper-half) plane (i.e. norm l_q in R^2); Default value is 2 (euclidean norm). - :param p: exponent for Wasserstein; Default value is 2. - :returns: the p-Wasserstein distance (1 <= p < infinity) with respect to the q-norm as ground metric. + :param order: exponent for Wasserstein; Default value is 2. + :param internal_p: Ground metric on the (upper-half) plane (i.e. norm L^p in R^2); Default value is 2 (Euclidean norm). + :returns: the Wasserstein distance of order q (1 <= q < infinity) between persistence diagrams with respect to the internal_p-norm as ground metric. :rtype: float ''' n = len(X) @@ -79,20 +79,19 @@ def wasserstein_distance(X, Y, p=2., q=2.): if Y.size == 0: return 0. else: - return _perstot(Y, p, q) + return _perstot(Y, order, internal_p) elif Y.size == 0: - return _perstot(X, p, q) + return _perstot(X, order, internal_p) - M = _build_dist_matrix(X, Y, p=p, q=q) + M = _build_dist_matrix(X, Y, order=order, internal_p=internal_p) a = np.full(n+1, 1. / (n + m) ) # weight vector of the input diagram. Uniform here. a[-1] = a[-1] * m # normalized so that we have a probability measure, required by POT b = np.full(m+1, 1. / (n + m) ) # weight vector of the input diagram. Uniform here. b[-1] = b[-1] * n # so that we have a probability measure, required by POT # Comptuation of the otcost using the ot.emd2 library. - # Note: it is the squared Wasserstein distance. + # Note: it is the Wasserstein distance to the power q. # The default numItermax=100000 is not sufficient for some examples with 5000 points, what is a good value? ot_cost = (n+m) * ot.emd2(a, b, M, numItermax=2000000) - return ot_cost ** (1./p) - + return ot_cost ** (1./order) diff --git a/src/python/gudhi/witness_complex.pyx b/src/python/gudhi/witness_complex.pyx index 153fc615..e589d006 100644 --- a/src/python/gudhi/witness_complex.pyx +++ b/src/python/gudhi/witness_complex.pyx @@ -1,11 +1,3 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libc.stdint cimport intptr_t - -from gudhi.simplex_tree cimport * -from gudhi.simplex_tree import SimplexTree - # This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. # See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. # Author(s): Vincent Rouvreau @@ -15,6 +7,14 @@ from gudhi.simplex_tree import SimplexTree # Modification(s): # - YYYY/MM Author: Description of the modification +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libc.stdint cimport intptr_t + +from gudhi.simplex_tree cimport * +from gudhi.simplex_tree import SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -22,9 +22,9 @@ __license__ = "MIT" cdef extern from "Witness_complex_interface.h" namespace "Gudhi": cdef cppclass Witness_complex_interface "Gudhi::witness_complex::Witness_complex_interface": Witness_complex_interface(vector[vector[pair[size_t, double]]] nearest_landmark_table) - void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square) except + void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, double max_alpha_square, - unsigned limit_dimension) + unsigned limit_dimension) except + # WitnessComplex python interface cdef class WitnessComplex: diff --git a/src/python/include/Alpha_complex_interface.h b/src/python/include/Alpha_complex_interface.h index 96353cc4..8614eee3 100644 --- a/src/python/include/Alpha_complex_interface.h +++ b/src/python/include/Alpha_complex_interface.h @@ -13,6 +13,7 @@ #include <gudhi/Simplex_tree.h> #include <gudhi/Alpha_complex.h> +#include <CGAL/Epeck_d.h> #include <CGAL/Epick_d.h> #include <boost/range/adaptor/transformed.hpp> @@ -28,7 +29,7 @@ namespace Gudhi { namespace alpha_complex { class Alpha_complex_interface { - using Dynamic_kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >; + using Dynamic_kernel = CGAL::Epeck_d< CGAL::Dynamic_dimension_tag >; using Point_d = Dynamic_kernel::Point_d; public: @@ -49,13 +50,9 @@ class Alpha_complex_interface { std::vector<double> get_point(int vh) { std::vector<double> vd; - try { - Point_d const& ph = alpha_complex_->get_point(vh); - for (auto coord = ph.cartesian_begin(); coord < ph.cartesian_end(); coord++) - vd.push_back(CGAL::to_double(*coord)); - } catch (std::out_of_range const&) { - // std::out_of_range is thrown in case not found. Other exceptions must be re-thrown - } + Point_d const& ph = alpha_complex_->get_point(vh); + for (auto coord = ph.cartesian_begin(); coord != ph.cartesian_end(); coord++) + vd.push_back(CGAL::to_double(*coord)); return vd; } diff --git a/src/python/setup.py.in b/src/python/setup.py.in index 3f1d4424..f968bd59 100644 --- a/src/python/setup.py.in +++ b/src/python/setup.py.in @@ -1,7 +1,3 @@ -from setuptools import setup, Extension -from Cython.Build import cythonize -from numpy import get_include as numpy_get_include - """This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -12,6 +8,12 @@ from numpy import get_include as numpy_get_include - YYYY/MM Author: Description of the modification """ +from setuptools import setup, Extension, find_packages +from Cython.Build import cythonize +from numpy import get_include as numpy_get_include +import sys +import pybind11 + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -38,16 +40,29 @@ for module in modules: libraries=libraries, library_dirs=library_dirs, include_dirs=include_dirs, - runtime_library_dirs=runtime_library_dirs,)) + runtime_library_dirs=runtime_library_dirs, + cython_directives = {'language_level': str(sys.version_info[0])},)) + +ext_modules = cythonize(ext_modules) + +ext_modules.append(Extension( + 'gudhi.hera', + sources = [source_dir + 'hera.cc'], + language = 'c++', + include_dirs = include_dirs + + ['@HERA_WASSERSTEIN_INCLUDE_DIR@', + pybind11.get_include(False), pybind11.get_include(True)], + extra_compile_args=extra_compile_args + [@GUDHI_PYBIND11_EXTRA_COMPILE_ARGS@], + )) setup( name = 'gudhi', - packages=["gudhi",], + packages=find_packages(), # find_namespace_packages(include=["gudhi*"]) author='GUDHI Editorial Board', author_email='gudhi-contact@lists.gforge.inria.fr', version='@GUDHI_VERSION@', url='http://gudhi.gforge.inria.fr/', - ext_modules = cythonize(ext_modules), + ext_modules = ext_modules, install_requires = ['cython','numpy >= 1.9',], - setup_requires = ['numpy >= 1.9',], + setup_requires = ['numpy >= 1.9','pybind11',], ) diff --git a/src/python/test/test_alpha_complex.py b/src/python/test/test_alpha_complex.py index 24f8bf53..3761fe16 100755 --- a/src/python/test/test_alpha_complex.py +++ b/src/python/test/test_alpha_complex.py @@ -1,5 +1,3 @@ -from gudhi import AlphaComplex, SimplexTree - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,17 @@ from gudhi import AlphaComplex, SimplexTree - YYYY/MM Author: Description of the modification """ +from gudhi import AlphaComplex, SimplexTree +import math +import numpy as np +import pytest +try: + # python3 + from itertools import zip_longest +except ImportError: + # python2 + from itertools import izip_longest as zip_longest + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -56,8 +65,18 @@ def test_infinite_alpha(): assert point_list[1] == alpha_complex.get_point(1) assert point_list[2] == alpha_complex.get_point(2) assert point_list[3] == alpha_complex.get_point(3) - assert alpha_complex.get_point(4) == [] - assert alpha_complex.get_point(125) == [] + try: + alpha_complex.get_point(4) == [] + except IndexError: + pass + else: + assert False + try: + alpha_complex.get_point(125) == [] + except IndexError: + pass + else: + assert False def test_filtered_alpha(): @@ -73,8 +92,18 @@ def test_filtered_alpha(): assert point_list[1] == filtered_alpha.get_point(1) assert point_list[2] == filtered_alpha.get_point(2) assert point_list[3] == filtered_alpha.get_point(3) - assert filtered_alpha.get_point(4) == [] - assert filtered_alpha.get_point(125) == [] + try: + filtered_alpha.get_point(4) == [] + except IndexError: + pass + else: + assert False + try: + filtered_alpha.get_point(125) == [] + except IndexError: + pass + else: + assert False assert simplex_tree.get_filtration() == [ ([0], 0.0), @@ -88,3 +117,28 @@ def test_filtered_alpha(): ] assert simplex_tree.get_star([0]) == [([0], 0.0), ([0, 1], 0.25), ([0, 2], 0.25)] assert simplex_tree.get_cofaces([0], 1) == [([0, 1], 0.25), ([0, 2], 0.25)] + +def test_safe_alpha_persistence_comparison(): + #generate periodic signal + time = np.arange(0, 10, 1) + signal = [math.sin(x) for x in time] + delta = math.pi + delayed = [math.sin(x + delta) for x in time] + + #construct embedding + embedding1 = [[signal[i], -signal[i]] for i in range(len(time))] + embedding2 = [[signal[i], delayed[i]] for i in range(len(time))] + + #build alpha complex and simplex tree + alpha_complex1 = AlphaComplex(points=embedding1) + simplex_tree1 = alpha_complex1.create_simplex_tree() + + alpha_complex2 = AlphaComplex(points=embedding2) + simplex_tree2 = alpha_complex2.create_simplex_tree() + + diag1 = simplex_tree1.persistence() + diag2 = simplex_tree2.persistence() + + for (first_p, second_p) in zip_longest(diag1, diag2): + assert first_p[0] == pytest.approx(second_p[0]) + assert first_p[1] == pytest.approx(second_p[1]) diff --git a/src/python/test/test_bottleneck_distance.py b/src/python/test/test_bottleneck_distance.py index f5f019b9..70b2abad 100755 --- a/src/python/test/test_bottleneck_distance.py +++ b/src/python/test/test_bottleneck_distance.py @@ -1,5 +1,3 @@ -import gudhi - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ import gudhi - YYYY/MM Author: Description of the modification """ +import gudhi + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/test/test_cover_complex.py b/src/python/test/test_cover_complex.py index 8cd12272..32bc5a26 100755 --- a/src/python/test/test_cover_complex.py +++ b/src/python/test/test_cover_complex.py @@ -1,5 +1,3 @@ -from gudhi import CoverComplex - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ from gudhi import CoverComplex - YYYY/MM Author: Description of the modification """ +from gudhi import CoverComplex + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2018 Inria" __license__ = "MIT" diff --git a/src/python/test/test_cubical_complex.py b/src/python/test/test_cubical_complex.py index 68f54fbe..8c1b2600 100755 --- a/src/python/test/test_cubical_complex.py +++ b/src/python/test/test_cubical_complex.py @@ -1,5 +1,3 @@ -from gudhi import CubicalComplex - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,9 @@ from gudhi import CubicalComplex - YYYY/MM Author: Description of the modification """ +from gudhi import CubicalComplex, PeriodicCubicalComplex +import numpy as np + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" @@ -56,7 +57,7 @@ def test_dimension_or_perseus_file_constructor(): assert cub.__is_persistence_defined() == False -def test_dimension_simple_constructor(): +def simple_constructor(cub): cub = CubicalComplex( dimensions=[3, 3], top_dimensional_cells=[1, 2, 3, 4, 5, 6, 7, 8, 9] ) @@ -67,12 +68,22 @@ def test_dimension_simple_constructor(): assert cub.betti_numbers() == [1, 0, 0] assert cub.persistent_betti_numbers(0, 1000) == [0, 0, 0] - -def test_user_case_simple_constructor(): +def test_simple_constructor_from_top_cells(): cub = CubicalComplex( dimensions=[3, 3], - top_dimensional_cells=[float("inf"), 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0], + top_dimensional_cells=[1, 2, 3, 4, 5, 6, 7, 8, 9], ) + simple_constructor(cub) + +def test_simple_constructor_from_numpy_array(): + cub = CubicalComplex( + top_dimensional_cells=np.array([[1, 2, 3], + [4, 5, 6], + [7, 8, 9]]) + ) + simple_constructor(cub) + +def user_case_simple_constructor(cub): assert cub.__is_defined() == True assert cub.__is_persistence_defined() == False assert cub.persistence() == [(1, (0.0, 1.0)), (0, (0.0, float("inf")))] @@ -83,6 +94,20 @@ def test_user_case_simple_constructor(): ) assert other_cub.persistence() == [(1, (0.0, 1.0)), (0, (0.0, float("inf")))] +def test_user_case_simple_constructor_from_top_cells(): + cub = CubicalComplex( + dimensions=[3, 3], + top_dimensional_cells=[float("inf"), 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0], + ) + user_case_simple_constructor(cub) + +def test_user_case_simple_constructor_from_numpy_array(): + cub = CubicalComplex( + top_dimensional_cells=np.array([[float("inf"), 0.0, 0.0], + [0.0, 1.0, 0.0], + [0.0, 0.0, 0.0]]) + ) + user_case_simple_constructor(cub) def test_dimension_file_constructor(): # Create test file @@ -96,3 +121,29 @@ def test_dimension_file_constructor(): assert cub.__is_persistence_defined() == True assert cub.betti_numbers() == [1, 0, 0] assert cub.persistent_betti_numbers(0, 1000) == [1, 0, 0] + +def test_connected_sublevel_sets(): + array_cells = np.array([[3, 3], [2, 2], [4, 4]]) + linear_cells = [3, 3, 2, 2, 4, 4] + dimensions = [2, 3] + periodic_dimensions = [False, False] + # with a numpy array version + cub = CubicalComplex(top_dimensional_cells = array_cells) + assert cub.persistence() == [(0, (2.0, float("inf")))] + assert cub.betti_numbers() == [1, 0, 0] + # with vector of dimensions + cub = CubicalComplex(dimensions = dimensions, + top_dimensional_cells = linear_cells) + assert cub.persistence() == [(0, (2.0, float("inf")))] + assert cub.betti_numbers() == [1, 0, 0] + # periodic with a numpy array version + cub = PeriodicCubicalComplex(top_dimensional_cells = array_cells, + periodic_dimensions = periodic_dimensions) + assert cub.persistence() == [(0, (2.0, float("inf")))] + assert cub.betti_numbers() == [1, 0, 0] + # periodic with vector of dimensions + cub = PeriodicCubicalComplex(dimensions = dimensions, + top_dimensional_cells = linear_cells, + periodic_dimensions = periodic_dimensions) + assert cub.persistence() == [(0, (2.0, float("inf")))] + assert cub.betti_numbers() == [1, 0, 0] diff --git a/src/python/test/test_euclidean_witness_complex.py b/src/python/test/test_euclidean_witness_complex.py index f5eae5fa..c18d2484 100755 --- a/src/python/test/test_euclidean_witness_complex.py +++ b/src/python/test/test_euclidean_witness_complex.py @@ -1,5 +1,3 @@ -import gudhi - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ import gudhi - YYYY/MM Author: Description of the modification """ +import gudhi + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/test/test_reader_utils.py b/src/python/test/test_reader_utils.py index 4c7b32c2..90da6651 100755 --- a/src/python/test/test_reader_utils.py +++ b/src/python/test/test_reader_utils.py @@ -1,6 +1,3 @@ -import gudhi -import numpy as np - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -11,6 +8,9 @@ import numpy as np - YYYY/MM Author: Description of the modification """ +import gudhi +import numpy as np + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2017 Inria" __license__ = "MIT" diff --git a/src/python/test/test_representations.py b/src/python/test/test_representations.py index 4ff65f98..dba7f952 100755 --- a/src/python/test/test_representations.py +++ b/src/python/test/test_representations.py @@ -1,11 +1,12 @@ import os import sys import matplotlib.pyplot as plt -# Disable graphics for testing purposes -plt.show = lambda:None -here = os.path.dirname(os.path.realpath(__file__)) -sys.path.append(here + "/../example") -import diagram_vectorizations_distances_kernels -# pytest is unhappy if there are 0 tests -def test_nothing(): + +def test_representations_examples(): + # Disable graphics for testing purposes + plt.show = lambda:None + here = os.path.dirname(os.path.realpath(__file__)) + sys.path.append(here + "/../example") + import diagram_vectorizations_distances_kernels + return None diff --git a/src/python/test/test_rips_complex.py b/src/python/test/test_rips_complex.py index d55ae22f..b02a68e1 100755 --- a/src/python/test/test_rips_complex.py +++ b/src/python/test/test_rips_complex.py @@ -1,6 +1,3 @@ -from gudhi import RipsComplex -from math import sqrt - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -11,6 +8,9 @@ from math import sqrt - YYYY/MM Author: Description of the modification """ +from gudhi import RipsComplex +from math import sqrt + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/test/test_simplex_tree.py b/src/python/test/test_simplex_tree.py index 8d8971c1..1822c43b 100755 --- a/src/python/test/test_simplex_tree.py +++ b/src/python/test/test_simplex_tree.py @@ -1,5 +1,3 @@ -from gudhi import SimplexTree - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ from gudhi import SimplexTree - YYYY/MM Author: Description of the modification """ +from gudhi import SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/test/test_subsampling.py b/src/python/test/test_subsampling.py index c816e203..fe0985fa 100755 --- a/src/python/test/test_subsampling.py +++ b/src/python/test/test_subsampling.py @@ -1,5 +1,3 @@ -import gudhi - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ import gudhi - YYYY/MM Author: Description of the modification """ +import gudhi + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/test/test_tangential_complex.py b/src/python/test/test_tangential_complex.py index 0f828d8e..e650e99c 100755 --- a/src/python/test/test_tangential_complex.py +++ b/src/python/test/test_tangential_complex.py @@ -1,5 +1,3 @@ -from gudhi import TangentialComplex, SimplexTree - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ from gudhi import TangentialComplex, SimplexTree - YYYY/MM Author: Description of the modification """ +from gudhi import TangentialComplex, SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" diff --git a/src/python/test/test_wasserstein_distance.py b/src/python/test/test_wasserstein_distance.py index a6bf9901..6a6b217b 100755 --- a/src/python/test/test_wasserstein_distance.py +++ b/src/python/test/test_wasserstein_distance.py @@ -1,9 +1,6 @@ -from gudhi.wasserstein import wasserstein_distance -import numpy as np - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. - Author(s): Theo Lacombe + Author(s): Theo Lacombe, Marc Glisse Copyright (C) 2019 Inria @@ -11,38 +8,66 @@ import numpy as np - YYYY/MM Author: Description of the modification """ +from gudhi.wasserstein import wasserstein_distance as pot +from gudhi.hera import wasserstein_distance as hera +import numpy as np +import pytest + __author__ = "Theo Lacombe" __copyright__ = "Copyright (C) 2019 Inria" __license__ = "MIT" - -def test_basic_wasserstein(): +def _basic_wasserstein(wasserstein_distance, delta, test_infinity=True): diag1 = np.array([[2.7, 3.7], [9.6, 14.0], [34.2, 34.974]]) diag2 = np.array([[2.8, 4.45], [9.5, 14.1]]) diag3 = np.array([[0, 2], [4, 6]]) diag4 = np.array([[0, 3], [4, 8]]) - emptydiag = np.array([[]]) + emptydiag = np.array([]) + + # We just need to handle positive numbers here + def approx(x): + return pytest.approx(x, rel=delta) + + assert wasserstein_distance(emptydiag, emptydiag, internal_p=2., order=1.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, internal_p=np.inf, order=1.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, internal_p=np.inf, order=2.) == 0. + assert wasserstein_distance(emptydiag, emptydiag, internal_p=2., order=2.) == 0. + + assert wasserstein_distance(diag3, emptydiag, internal_p=np.inf, order=1.) == approx(2.) + assert wasserstein_distance(diag3, emptydiag, internal_p=1., order=1.) == approx(4.) + + assert wasserstein_distance(diag4, emptydiag, internal_p=1., order=2.) == approx(5.) # thank you Pythagorician triplets + assert wasserstein_distance(diag4, emptydiag, internal_p=np.inf, order=2.) == approx(2.5) + assert wasserstein_distance(diag4, emptydiag, internal_p=2., order=2.) == approx(3.5355339059327378) + + assert wasserstein_distance(diag1, diag2, internal_p=2., order=1.) == approx(1.4453593023967701) + assert wasserstein_distance(diag1, diag2, internal_p=2.35, order=1.74) == approx(0.9772734057168739) + + assert wasserstein_distance(diag1, emptydiag, internal_p=2.35, order=1.7863) == approx(3.141592214572228) - assert wasserstein_distance(emptydiag, emptydiag, q=2., p=1.) == 0. - assert wasserstein_distance(emptydiag, emptydiag, q=np.inf, p=1.) == 0. - assert wasserstein_distance(emptydiag, emptydiag, q=np.inf, p=2.) == 0. - assert wasserstein_distance(emptydiag, emptydiag, q=2., p=2.) == 0. + assert wasserstein_distance(diag3, diag4, internal_p=1., order=1.) == approx(3.) + assert wasserstein_distance(diag3, diag4, internal_p=np.inf, order=1.) == approx(3.) # no diag matching here + assert wasserstein_distance(diag3, diag4, internal_p=np.inf, order=2.) == approx(np.sqrt(5)) + assert wasserstein_distance(diag3, diag4, internal_p=1., order=2.) == approx(np.sqrt(5)) + assert wasserstein_distance(diag3, diag4, internal_p=4.5, order=2.) == approx(np.sqrt(5)) - assert wasserstein_distance(diag3, emptydiag, q=np.inf, p=1.) == 2. - assert wasserstein_distance(diag3, emptydiag, q=1., p=1.) == 4. + if(not test_infinity): + return - assert wasserstein_distance(diag4, emptydiag, q=1., p=2.) == 5. # thank you Pythagorician triplets - assert wasserstein_distance(diag4, emptydiag, q=np.inf, p=2.) == 2.5 - assert wasserstein_distance(diag4, emptydiag, q=2., p=2.) == 3.5355339059327378 + diag5 = np.array([[0, 3], [4, np.inf]]) + diag6 = np.array([[7, 8], [4, 6], [3, np.inf]]) - assert wasserstein_distance(diag1, diag2, q=2., p=1.) == 1.4453593023967701 - assert wasserstein_distance(diag1, diag2, q=2.35, p=1.74) == 0.9772734057168739 + assert wasserstein_distance(diag4, diag5) == np.inf + assert wasserstein_distance(diag5, diag6, order=1, internal_p=np.inf) == approx(4.) - assert wasserstein_distance(diag1, emptydiag, q=2.35, p=1.7863) == 3.141592214572228 +def hera_wrap(delta): + def fun(*kargs,**kwargs): + return hera(*kargs,**kwargs,delta=delta) + return fun - assert wasserstein_distance(diag3, diag4, q=1., p=1.) == 3. - assert wasserstein_distance(diag3, diag4, q=np.inf, p=1.) == 3. # no diag matching here - assert wasserstein_distance(diag3, diag4, q=np.inf, p=2.) == np.sqrt(5) - assert wasserstein_distance(diag3, diag4, q=1., p=2.) == np.sqrt(5) - assert wasserstein_distance(diag3, diag4, q=4.5, p=2.) == np.sqrt(5) +def test_wasserstein_distance_pot(): + _basic_wasserstein(pot, 1e-15, test_infinity=False) +def test_wasserstein_distance_hera(): + _basic_wasserstein(hera_wrap(1e-12), 1e-12) + _basic_wasserstein(hera_wrap(.1), .1) diff --git a/src/python/test/test_witness_complex.py b/src/python/test/test_witness_complex.py index 36ced635..7baf18c9 100755 --- a/src/python/test/test_witness_complex.py +++ b/src/python/test/test_witness_complex.py @@ -1,5 +1,3 @@ -from gudhi import WitnessComplex, StrongWitnessComplex, SimplexTree - """ This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. Author(s): Vincent Rouvreau @@ -10,6 +8,8 @@ from gudhi import WitnessComplex, StrongWitnessComplex, SimplexTree - YYYY/MM Author: Description of the modification """ +from gudhi import WitnessComplex, StrongWitnessComplex, SimplexTree + __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 Inria" __license__ = "MIT" |
