diff options
Diffstat (limited to 'src/python')
| -rw-r--r-- | src/python/CMakeLists.txt | 60 | ||||
| -rw-r--r-- | src/python/doc/installation.rst | 5 | ||||
| -rw-r--r-- | src/python/doc/wasserstein_distance_user.rst | 17 | ||||
| -rw-r--r-- | src/python/gudhi/hera.cc | 71 | ||||
| -rw-r--r-- | src/python/gudhi/wasserstein.py | 6 | ||||
| -rw-r--r-- | src/python/setup.py.in | 17 | ||||
| -rwxr-xr-x | src/python/test/test_wasserstein_distance.py | 61 |
7 files changed, 183 insertions, 54 deletions
diff --git a/src/python/CMakeLists.txt b/src/python/CMakeLists.txt index b558d4c4..090a7446 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', ") @@ -86,6 +90,7 @@ 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', ") @@ -390,9 +395,9 @@ endif(CGAL_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) - endif(OT_FOUND) + endif() # Representations if(SKLEARN_FOUND AND MATPLOTLIB_FOUND) @@ -406,32 +411,37 @@ endif(CGAL_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/installation.rst b/src/python/doc/installation.rst index 40f3f44b..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. diff --git a/src/python/doc/wasserstein_distance_user.rst b/src/python/doc/wasserstein_distance_user.rst index 32999a0c..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:: 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/wasserstein.py b/src/python/gudhi/wasserstein.py index db5ddff2..13102094 100644 --- a/src/python/gudhi/wasserstein.py +++ b/src/python/gudhi/wasserstein.py @@ -27,8 +27,8 @@ 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 internal_p: Ground metric (i.e. norm l_p). :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). @@ -54,8 +54,8 @@ def _build_dist_matrix(X, Y, order=2., internal_p=2.): def _perstot(X, order, internal_p): ''' :param X: (n x 2) numpy.array (points of a given diagram). - :param internal_p: Ground metric on the (upper-half) plane (i.e. norm l_p in R^2); Default value is 2 (Euclidean norm). :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) @@ -66,8 +66,8 @@ 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 internal_p: Ground metric on the (upper-half) plane (i.e. norm l_p in R^2); Default value is 2 (euclidean norm). :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 ''' diff --git a/src/python/setup.py.in b/src/python/setup.py.in index bd7fb180..f968bd59 100644 --- a/src/python/setup.py.in +++ b/src/python/setup.py.in @@ -12,6 +12,7 @@ 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" @@ -42,6 +43,18 @@ for module in modules: 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=find_packages(), # find_namespace_packages(include=["gudhi*"]) @@ -49,7 +62,7 @@ setup( 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_wasserstein_distance.py b/src/python/test/test_wasserstein_distance.py index 43dda77e..6a6b217b 100755 --- a/src/python/test/test_wasserstein_distance.py +++ b/src/python/test/test_wasserstein_distance.py @@ -1,6 +1,6 @@ """ 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 @@ -8,41 +8,66 @@ - YYYY/MM Author: Description of the modification """ -from gudhi.wasserstein import wasserstein_distance +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.) == 2. - assert wasserstein_distance(diag3, emptydiag, internal_p=1., order=1.) == 4. + 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(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)) + + if(not test_infinity): + return - assert wasserstein_distance(diag4, emptydiag, internal_p=1., order=2.) == 5. # thank you Pythagorician triplets - assert wasserstein_distance(diag4, emptydiag, internal_p=np.inf, order=2.) == 2.5 - assert wasserstein_distance(diag4, emptydiag, internal_p=2., order=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, internal_p=2., order=1.) == 1.4453593023967701 - assert wasserstein_distance(diag1, diag2, internal_p=2.35, order=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, internal_p=2.35, order=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, internal_p=1., order=1.) == 3. - assert wasserstein_distance(diag3, diag4, internal_p=np.inf, order=1.) == 3. # no diag matching here - assert wasserstein_distance(diag3, diag4, internal_p=np.inf, order=2.) == np.sqrt(5) - assert wasserstein_distance(diag3, diag4, internal_p=1., order=2.) == np.sqrt(5) - assert wasserstein_distance(diag3, diag4, internal_p=4.5, order=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) |