From 5b6bebd9a8072d8998b0c741e5b40de0cfe5dc8e Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Fri, 12 Aug 2016 15:29:48 +0000 Subject: Move cython/src/* in cython/ git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/ST_cythonize@1436 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 8f971ef16ef6df597d5d3667db0eecbca94233b2 --- src/cython/CMakeLists.txt | 25 +- src/cython/cython/alpha_complex.pyx | 398 +++++++++++++++++++++ src/cython/cython/cubical_complex.pyx | 180 ++++++++++ src/cython/cython/mini_simplex_tree.pyx | 352 ++++++++++++++++++ src/cython/cython/periodic_cubical_complex.pyx | 181 ++++++++++ src/cython/cython/persistence_graphical_tools.py | 155 ++++++++ src/cython/cython/rips_complex.pyx | 369 +++++++++++++++++++ src/cython/cython/simplex_tree.pyx | 352 ++++++++++++++++++ src/cython/cython/witness_complex.pyx | 322 +++++++++++++++++ src/cython/doc/Makefile | 177 +++++++++ src/cython/doc/alpha_complex_ref.rst | 10 + src/cython/doc/alpha_complex_sum.rst | 21 ++ src/cython/doc/alpha_complex_user.rst | 192 ++++++++++ src/cython/doc/biblio.rst | 7 + src/cython/doc/cgal_citation.rst | 8 + src/cython/doc/conf.py | 271 ++++++++++++++ src/cython/doc/cubical_complex_ref.rst | 9 + src/cython/doc/cubical_complex_sum.rst | 12 + src/cython/doc/cubical_complex_user.rst | 150 ++++++++ src/cython/doc/index.rst | 63 ++++ src/cython/doc/make.bat | 242 +++++++++++++ src/cython/doc/periodic_cubical_complex_ref.rst | 9 + src/cython/doc/persistent_cohomology_sum.rst | 28 ++ src/cython/doc/persistent_cohomology_user.rst | 104 ++++++ src/cython/doc/simplex_tree_ref.rst | 10 + src/cython/doc/simplex_tree_sum.rst | 13 + src/cython/doc/simplex_tree_user.rst | 67 ++++ src/cython/doc/witness_complex_ref.rst | 10 + src/cython/doc/witness_complex_sum.rst | 25 ++ src/cython/doc/witness_complex_user.rst | 31 ++ src/cython/gudhi.pyx.in | 14 +- src/cython/include/Alpha_complex_interface.h | 142 ++++++++ src/cython/include/Cubical_complex_interface.h | 58 +++ .../include/Persistent_cohomology_interface.h | 90 +++++ src/cython/include/Simplex_tree_interface.h | 132 +++++++ src/cython/include/Witness_complex_interface.h | 187 ++++++++++ src/cython/src/cython/alpha_complex.pyx | 398 --------------------- src/cython/src/cython/cubical_complex.pyx | 180 ---------- src/cython/src/cython/mini_simplex_tree.pyx | 352 ------------------ src/cython/src/cython/periodic_cubical_complex.pyx | 181 ---------- .../src/cython/persistence_graphical_tools.py | 155 -------- src/cython/src/cython/rips_complex.pyx | 369 ------------------- src/cython/src/cython/simplex_tree.pyx | 352 ------------------ src/cython/src/cython/witness_complex.pyx | 322 ----------------- src/cython/src/doc/Makefile | 177 --------- src/cython/src/doc/alpha_complex_ref.rst | 10 - src/cython/src/doc/alpha_complex_sum.rst | 21 -- src/cython/src/doc/alpha_complex_user.rst | 192 ---------- src/cython/src/doc/biblio.rst | 7 - src/cython/src/doc/cgal_citation.rst | 8 - src/cython/src/doc/conf.py | 271 -------------- src/cython/src/doc/cubical_complex_ref.rst | 9 - src/cython/src/doc/cubical_complex_sum.rst | 12 - src/cython/src/doc/cubical_complex_user.rst | 150 -------- src/cython/src/doc/index.rst | 63 ---- src/cython/src/doc/make.bat | 242 ------------- .../src/doc/periodic_cubical_complex_ref.rst | 9 - src/cython/src/doc/persistent_cohomology_sum.rst | 28 -- src/cython/src/doc/persistent_cohomology_user.rst | 104 ------ src/cython/src/doc/simplex_tree_ref.rst | 10 - src/cython/src/doc/simplex_tree_sum.rst | 13 - src/cython/src/doc/simplex_tree_user.rst | 67 ---- src/cython/src/doc/witness_complex_ref.rst | 10 - src/cython/src/doc/witness_complex_sum.rst | 25 -- src/cython/src/doc/witness_complex_user.rst | 31 -- src/cython/src/include/Alpha_complex_interface.h | 142 -------- src/cython/src/include/Cubical_complex_interface.h | 58 --- .../src/include/Persistent_cohomology_interface.h | 90 ----- src/cython/src/include/Simplex_tree_interface.h | 132 ------- src/cython/src/include/Witness_complex_interface.h | 187 ---------- 70 files changed, 4397 insertions(+), 4396 deletions(-) create mode 100644 src/cython/cython/alpha_complex.pyx create mode 100644 src/cython/cython/cubical_complex.pyx create mode 100644 src/cython/cython/mini_simplex_tree.pyx create mode 100644 src/cython/cython/periodic_cubical_complex.pyx create mode 100755 src/cython/cython/persistence_graphical_tools.py create mode 100644 src/cython/cython/rips_complex.pyx create mode 100644 src/cython/cython/simplex_tree.pyx create mode 100644 src/cython/cython/witness_complex.pyx create mode 100644 src/cython/doc/Makefile create mode 100644 src/cython/doc/alpha_complex_ref.rst create mode 100644 src/cython/doc/alpha_complex_sum.rst create mode 100644 src/cython/doc/alpha_complex_user.rst create mode 100644 src/cython/doc/biblio.rst create mode 100644 src/cython/doc/cgal_citation.rst create mode 100755 src/cython/doc/conf.py create mode 100644 src/cython/doc/cubical_complex_ref.rst create mode 100644 src/cython/doc/cubical_complex_sum.rst create mode 100644 src/cython/doc/cubical_complex_user.rst create mode 100644 src/cython/doc/index.rst create mode 100644 src/cython/doc/make.bat create mode 100644 src/cython/doc/periodic_cubical_complex_ref.rst create mode 100644 src/cython/doc/persistent_cohomology_sum.rst create mode 100644 src/cython/doc/persistent_cohomology_user.rst create mode 100644 src/cython/doc/simplex_tree_ref.rst create mode 100644 src/cython/doc/simplex_tree_sum.rst create mode 100644 src/cython/doc/simplex_tree_user.rst create mode 100644 src/cython/doc/witness_complex_ref.rst create mode 100644 src/cython/doc/witness_complex_sum.rst create mode 100644 src/cython/doc/witness_complex_user.rst create mode 100644 src/cython/include/Alpha_complex_interface.h create mode 100644 src/cython/include/Cubical_complex_interface.h create mode 100644 src/cython/include/Persistent_cohomology_interface.h create mode 100644 src/cython/include/Simplex_tree_interface.h create mode 100644 src/cython/include/Witness_complex_interface.h delete mode 100644 src/cython/src/cython/alpha_complex.pyx delete mode 100644 src/cython/src/cython/cubical_complex.pyx delete mode 100644 src/cython/src/cython/mini_simplex_tree.pyx delete mode 100644 src/cython/src/cython/periodic_cubical_complex.pyx delete mode 100755 src/cython/src/cython/persistence_graphical_tools.py delete mode 100644 src/cython/src/cython/rips_complex.pyx delete mode 100644 src/cython/src/cython/simplex_tree.pyx delete mode 100644 src/cython/src/cython/witness_complex.pyx delete mode 100644 src/cython/src/doc/Makefile delete mode 100644 src/cython/src/doc/alpha_complex_ref.rst delete mode 100644 src/cython/src/doc/alpha_complex_sum.rst delete mode 100644 src/cython/src/doc/alpha_complex_user.rst delete mode 100644 src/cython/src/doc/biblio.rst delete mode 100644 src/cython/src/doc/cgal_citation.rst delete mode 100755 src/cython/src/doc/conf.py delete mode 100644 src/cython/src/doc/cubical_complex_ref.rst delete mode 100644 src/cython/src/doc/cubical_complex_sum.rst delete mode 100644 src/cython/src/doc/cubical_complex_user.rst delete mode 100644 src/cython/src/doc/index.rst delete mode 100644 src/cython/src/doc/make.bat delete mode 100644 src/cython/src/doc/periodic_cubical_complex_ref.rst delete mode 100644 src/cython/src/doc/persistent_cohomology_sum.rst delete mode 100644 src/cython/src/doc/persistent_cohomology_user.rst delete mode 100644 src/cython/src/doc/simplex_tree_ref.rst delete mode 100644 src/cython/src/doc/simplex_tree_sum.rst delete mode 100644 src/cython/src/doc/simplex_tree_user.rst delete mode 100644 src/cython/src/doc/witness_complex_ref.rst delete mode 100644 src/cython/src/doc/witness_complex_sum.rst delete mode 100644 src/cython/src/doc/witness_complex_user.rst delete mode 100644 src/cython/src/include/Alpha_complex_interface.h delete mode 100644 src/cython/src/include/Cubical_complex_interface.h delete mode 100644 src/cython/src/include/Persistent_cohomology_interface.h delete mode 100644 src/cython/src/include/Simplex_tree_interface.h delete mode 100644 src/cython/src/include/Witness_complex_interface.h diff --git a/src/cython/CMakeLists.txt b/src/cython/CMakeLists.txt index bb90ad5b..823d5bb6 100644 --- a/src/cython/CMakeLists.txt +++ b/src/cython/CMakeLists.txt @@ -26,9 +26,10 @@ if(PYTHON_PATH AND CYTHON_PATH) set(GUDHI_CYTHON_INCLUDE_DIRS "${GUDHI_CYTHON_INCLUDE_DIRS}'${EIGEN3_INCLUDE_DIR}', ") endif (EIGEN3_FOUND) - # Copy recursively src and test repositories before packages finding + # Copy recursively include, cython and test repositories before packages finding # Some tests files are removed in case some packages are not found - file(COPY src DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) + file(COPY include DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) + file(COPY cython DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) file(COPY test DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) if (CGAL_FOUND) @@ -48,7 +49,7 @@ if(PYTHON_PATH AND CYTHON_PATH) endif(GMPXX_FOUND) endif(GMP_FOUND) - set(GUDHI_CYTHON_ALPHA_COMPLEX "include 'src/cython/alpha_complex.pyx'") + set(GUDHI_CYTHON_ALPHA_COMPLEX "include 'cython/alpha_complex.pyx'") else (NOT CGAL_VERSION VERSION_LESS 4.7.0) # Remove alpha complex unitary tests file(REMOVE ${CMAKE_CURRENT_BINARY_DIR}/test/test_alpha_complex.py) @@ -60,7 +61,7 @@ if(PYTHON_PATH AND CYTHON_PATH) foreach(GUDHI_INCLUDE_DIRECTORY ${GUDHI_INCLUDE_DIRECTORIES}) set(GUDHI_CYTHON_INCLUDE_DIRS "${GUDHI_CYTHON_INCLUDE_DIRS}'${GUDHI_INCLUDE_DIRECTORY}', ") endforeach() - set(GUDHI_CYTHON_INCLUDE_DIRS "${GUDHI_CYTHON_INCLUDE_DIRS}'${CMAKE_SOURCE_DIR}/${GUDHI_CYTHON_PATH}/src/include', ") + set(GUDHI_CYTHON_INCLUDE_DIRS "${GUDHI_CYTHON_INCLUDE_DIRS}'${CMAKE_SOURCE_DIR}/${GUDHI_CYTHON_PATH}/include', ") # Generate cythonize_gudhi.py file to cythonize Gudhi configure_file(cythonize_gudhi.py.in "${CMAKE_CURRENT_BINARY_DIR}/cythonize_gudhi.py" @ONLY) @@ -88,27 +89,27 @@ if(PYTHON_PATH AND CYTHON_PATH) # Documentation generation is available through sphinx find_program( SPHINX_PATH sphinx-build ) if(SPHINX_PATH) - file(COPY src/doc DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) + file(COPY doc DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) # Developper version file(GLOB GUDHI_DEV_DOC_IMAGES "${CMAKE_SOURCE_DIR}/src/*/doc/*.png") - file(COPY ${GUDHI_DEV_DOC_IMAGES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/src/doc/img") + file(COPY ${GUDHI_DEV_DOC_IMAGES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/doc/img") # User version file(GLOB GUDHI_USER_DOC_IMAGES "${CMAKE_SOURCE_DIR}/doc/*/*.png") - file(COPY ${GUDHI_USER_DOC_IMAGES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/src/doc/img") + file(COPY ${GUDHI_USER_DOC_IMAGES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/doc/img") # Biblio file(GLOB GUDHI_BIB_FILES "${CMAKE_SOURCE_DIR}/biblio/*.bib") - file(COPY ${GUDHI_BIB_FILES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/src/doc/") + file(COPY ${GUDHI_BIB_FILES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/doc/") # Cubical complex perseus doc example file(GLOB GUDHI_CUBICAL_PERSEUS_FILES "${CMAKE_SOURCE_DIR}/data/bitmap/*cubicalcomplexdoc.txt") - file(COPY ${GUDHI_CUBICAL_PERSEUS_FILES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/src/doc/") - file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/src/doc/") + file(COPY ${GUDHI_CUBICAL_PERSEUS_FILES} DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/doc/") + file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION "${CMAKE_CURRENT_BINARY_DIR}/doc/") if (UNIX) add_custom_target(html - WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/src/doc + WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/doc COMMAND make html && make doctest) else (UNIX) add_custom_target(html - WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/src/doc + WORKING_DIRECTORY ${CMAKE_CURRENT_BINARY_DIR}/doc COMMAND make.bat html) endif (UNIX) endif(SPHINX_PATH) diff --git a/src/cython/cython/alpha_complex.pyx b/src/cython/cython/alpha_complex.pyx new file mode 100644 index 00000000..44da8c9d --- /dev/null +++ b/src/cython/cython/alpha_complex.pyx @@ -0,0 +1,398 @@ +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 + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__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::alphacomplex::Alpha_complex_interface": + Alpha_complex_interface(vector[vector[double]] points, double max_alpha_square) + # bool from_file is a workaround fro cython to find the correct signature + Alpha_complex_interface(string off_file, double max_alpha_square, bool from_file) + double filtration() + double simplex_filtration(vector[int] simplex) + void set_filtration(double filtration) + void initialize_filtration() + int num_vertices() + int num_simplices() + void set_dimension(int dimension) + int dimension() + bint find_simplex(vector[int] simplex) + bint insert_simplex_and_subfaces(vector[int] simplex, + double filtration) + vector[pair[vector[int], double]] get_filtered_tree() + vector[pair[vector[int], double]] get_skeleton_tree(int dimension) + vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) + vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, + int dimension) + void remove_maximal_simplex(vector[int] simplex) + vector[double] get_point(int vertex) + +cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": + cdef cppclass Alpha_complex_persistence_interface "Gudhi::Persistent_cohomology_interface >>": + Alpha_complex_persistence_interface(Alpha_complex_interface * st) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] betti_numbers() + vector[int] persistent_betti_numbers(double from_value, double to_value) + +# AlphaComplex python interface +cdef class AlphaComplex: + """AlphaComplex is a simplicial complex constructed from the finite cells + of a Delaunay Triangulation. + + 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. + + .. note:: + + When Alpha_complex is constructed with an infinite value of alpha, the + complex is a Delaunay complex. + + """ + + cdef Alpha_complex_interface * thisptr + + cdef Alpha_complex_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, points=None, off_file='', max_alpha_square=float('inf')): + """AlphaComplex constructor. + + :param points: A list of points in d-Dimension. + :type points: list of list of double + + Or + + :param off_file: An OFF file style name. + :type off_file: string + + :param max_alpha_square: Maximum Alpha square value. Default is :math:`\infty` + :type max_alpha_square: double + """ + + # The real cython constructor + def __cinit__(self, points=[], off_file='', max_alpha_square=float('inf')): + if off_file is not '': + if os.path.isfile(off_file): + self.thisptr = new Alpha_complex_interface(off_file, + max_alpha_square, True) + else: + print("file " + off_file + " not found.") + else: + self.thisptr = new Alpha_complex_interface(points, + max_alpha_square) + + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if AlphaComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def get_filtration(self): + """This function returns the main simplicial complex filtration value. + + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.filtration() + + def filtration(self, simplex): + """This function returns the simplicial complex filtration value for a + given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.simplex_filtration(simplex) + + def set_filtration(self, filtration): + """This function sets the main simplicial complex filtration value. + + :param filtration: The filtration value. + :type filtration: float. + """ + self.thisptr.set_filtration( filtration) + + def initialize_filtration(self): + """This function initializes and sorts the simplicial complex + filtration vector. + + .. note:: + + This function must be launched before persistence, betti_numbers, + persistent_betti_numbers or get_filtered_tree after inserting or + removing simplices. + """ + self.thisptr.initialize_filtration() + + def num_vertices(self): + """This function returns the number of vertices of the simplicial + complex. + + :returns: int -- the simplicial complex number of vertices. + """ + return self.thisptr.num_vertices() + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def set_dimension(self, dimension): + """This function sets the dimension of the simplicial complex. + + :param dimension: The new dimension value. + :type dimension: int. + """ + self.thisptr.set_dimension(dimension) + + def find(self, simplex): + """This function returns if the N-simplex was found in the simplicial + complex or not. + + :param simplex: The N-simplex to find, represented by a list of vertex. + :type simplex: list of int. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.find_simplex(complex) + + def insert(self, simplex, filtration=0.0): + """This function inserts the given N-simplex with the given filtration + value (default value is '0.0'). + + :param simplex: The N-simplex to insert, represented by a list of + vertex. + :type simplex: list of int. + :param filtration: The filtration value of the simplex. + :type filtration: float. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.insert_simplex_and_subfaces(complex, + filtration) + + def get_filtered_tree(self): + """This function returns the tree sorted by increasing filtration + values. + + :returns: list of tuples(simplex, filtration) -- the tree sorted by + increasing filtration values. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_filtered_tree() + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_skeleton_tree(self, dimension): + """This function returns the tree skeleton of a maximum given + dimension. + + :param dimension: The skeleton dimension value. + :type dimension: int. + :returns: list of tuples(simplex, filtration) -- the skeleton tree + of a maximum dimension. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_skeleton_tree(dimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_star_tree(self, simplex): + """This function returns the star tree of a given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: list of tuples(simplex, filtration) -- the star tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_star_tree(complex) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_coface_tree(self, simplex, codimension): + """This function returns the coface tree of a given N-simplex with a + given codimension. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :param codimension: The codimension. If codimension = 0, all cofaces + are returned (equivalent of get_star_tree function) + :type codimension: int. + :returns: list of tuples(simplex, filtration) -- the coface tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_coface_tree(complex, codimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def remove_maximal_simplex(self, simplex): + """This function removes a given maximal N-simplex from the simplicial + complex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + """ + self.thisptr.remove_maximal_simplex(simplex) + + def get_point(self, vertex): + """This function returns the point corresponding to a given vertex. + + :param vertex: The vertex. + :type vertex: int. + :returns: list of float -- the point. + """ + cdef vector[double] point = self.thisptr.get_point(vertex) + return point + + def persistence(self, homology_coeff_field=11, min_persistence=0.0): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :returns: list of tuples(dimension, tuple(birth, death)) -- the + persistence of the simplicial complex. + """ + if self.pcohptr != NULL: + del self.pcohptr + self.pcohptr = new Alpha_complex_persistence_interface(self.thisptr) + cdef vector[pair[int, pair[double, double]]] persistence_result + if self.pcohptr != NULL: + persistence_result \ + = self.pcohptr.get_persistence(homology_coeff_field, + min_persistence) + return persistence_result + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + cdef vector[int] bn_result + if self.pcohptr != NULL: + bn_result = self.pcohptr.betti_numbers() + else: + print("betti_numbers function requires persistence function" + " to be launched first.") + return bn_result + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result \ + = self.pcohptr.persistent_betti_numbers(from_value, + to_value) + else: + print("persistent_betti_numbers function requires persistence " + "function to be launched first.") + return pbn_result diff --git a/src/cython/cython/cubical_complex.pyx b/src/cython/cython/cubical_complex.pyx new file mode 100644 index 00000000..3441b2e9 --- /dev/null +++ b/src/cython/cython/cubical_complex.pyx @@ -0,0 +1,180 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libcpp.string cimport string +import os + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +cdef extern from "Cubical_complex_interface.h" namespace "Gudhi": + cdef cppclass Bitmap_cubical_complex_base_interface "Gudhi::Cubical_complex::Cubical_complex_interface<>": + Bitmap_cubical_complex_base_interface(vector[unsigned] dimensions, vector[double] top_dimensional_cells) + Bitmap_cubical_complex_base_interface(string perseus_file) + int num_simplices() + int dimension() + +cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": + cdef cppclass Cubical_complex_persistence_interface "Gudhi::Persistent_cohomology_interface>": + Cubical_complex_persistence_interface(Bitmap_cubical_complex_base_interface * st) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] betti_numbers() + vector[int] persistent_betti_numbers(double from_value, double to_value) + + +# CubicalComplex python interface +cdef class CubicalComplex: + """The CubicalComplex is an example of a structured complex useful in + computational mathematics (specially rigorous numerics) and image + analysis. + """ + cdef Bitmap_cubical_complex_base_interface * thisptr + + cdef Cubical_complex_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, dimensions=None, top_dimensional_cells=None, + perseus_file=''): + """CubicalComplex constructor from dimensions and + top_dimensional_cells or from a perseus file style name. + + :param dimensions: A list of number of top dimensional cells. + :type dimensions: list of int + :param top_dimensional_cells: A list of top dimensional cells. + :type top_dimensional_cells: list of double + + Or + + :param perseus_file: A perseus file style name. + :type perseus_file: string + """ + + # The real cython constructor + def __cinit__(self, dimensions=None, top_dimensional_cells=None, + perseus_file=''): + if ((dimensions is not None) or (top_dimensional_cells is not None) and + (perseus_file is not '')): + print("CubicalComplex can be constructed from dimensions and " + "top_dimensional_cells or from a perseus file style name.") + else: + if dimensions is not None: + if top_dimensional_cells is not None: + self.thisptr = new Bitmap_cubical_complex_base_interface(dimensions, top_dimensional_cells) + else: + if perseus_file is not '': + if os.path.isfile(perseus_file): + self.thisptr = new Bitmap_cubical_complex_base_interface(perseus_file) + else: + print("file " + perseus_file + " not found.") + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if CubicalComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def persistence(self, homology_coeff_field=11, min_persistence=0): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :returns: list of pairs(dimension, pair(birth, death)) -- the + persistence of the simplicial complex. + """ + if self.pcohptr != NULL: + del self.pcohptr + if self.thisptr != NULL: + self.pcohptr = new Cubical_complex_persistence_interface(self.thisptr) + cdef vector[pair[int, pair[double, double]]] persistence_result + if self.pcohptr != NULL: + persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) + return persistence_result + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + cdef vector[int] bn_result + if self.pcohptr != NULL: + bn_result = self.pcohptr.betti_numbers() + return bn_result + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) + return pbn_result diff --git a/src/cython/cython/mini_simplex_tree.pyx b/src/cython/cython/mini_simplex_tree.pyx new file mode 100644 index 00000000..3ba7e853 --- /dev/null +++ b/src/cython/cython/mini_simplex_tree.pyx @@ -0,0 +1,352 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": + cdef cppclass Simplex_tree_options_mini: + pass + + cdef cppclass Simplex_tree_interface_mini "Gudhi::Simplex_tree_interface": + Simplex_tree() + double filtration() + double simplex_filtration(vector[int] simplex) + void set_filtration(double filtration) + void initialize_filtration() + int num_vertices() + int num_simplices() + void set_dimension(int dimension) + int dimension() + bint find_simplex(vector[int] simplex) + bint insert_simplex_and_subfaces(vector[int] simplex, + double filtration) + vector[pair[vector[int], double]] get_filtered_tree() + vector[pair[vector[int], double]] get_skeleton_tree(int dimension) + vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) + vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, + int dimension) + void remove_maximal_simplex(vector[int] simplex) + +cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": + cdef cppclass Mini_simplex_tree_persistence_interface "Gudhi::Persistent_cohomology_interface>": + Mini_simplex_tree_persistence_interface(Simplex_tree_interface_mini * st) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] betti_numbers() + vector[int] persistent_betti_numbers(double from_value, double to_value) + +# MiniSimplexTree python interface +cdef class MiniSimplexTree: + """The simplex tree is an efficient and flexible data structure for + representing general (filtered) simplicial complexes. The data structure + is described in Jean-Daniel Boissonnat and Clément Maria. The Simplex + Tree: An Efficient Data Structure for General Simplicial Complexes. + Algorithmica, pages 1–22, 2014. + + This class is a non-filtered, with keys, and non contiguous vertices + version of the simplex tree. + """ + cdef Simplex_tree_interface_mini * thisptr + + cdef Mini_simplex_tree_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, points=[], max_alpha_square=float('inf')): + """MiniSimplexTree constructor. + """ + + # The real cython constructor + def __cinit__(self): + self.thisptr = new Simplex_tree_interface_mini() + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if MiniSimplexTree pointer is not NULL. + """ + return self.thisptr != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def get_filtration(self): + """This function returns the main simplicial complex filtration value. + + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.filtration() + + def filtration(self, simplex): + """This function returns the simplicial complex filtration value for a + given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.simplex_filtration(simplex) + + def set_filtration(self, filtration): + """This function sets the main simplicial complex filtration value. + + :param filtration: The filtration value. + :type filtration: float. + """ + self.thisptr.set_filtration( filtration) + + def initialize_filtration(self): + """This function initializes and sorts the simplicial complex + filtration vector. + + .. note:: + + This function must be launched before persistence, betti_numbers, + persistent_betti_numbers or get_filtered_tree after inserting or + removing simplices. + """ + self.thisptr.initialize_filtration() + + def num_vertices(self): + """This function returns the number of vertices of the simplicial + complex. + + :returns: int -- the simplicial complex number of vertices. + """ + return self.thisptr.num_vertices() + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def set_dimension(self, dimension): + """This function sets the dimension of the simplicial complex. + + :param dimension: The new dimension value. + :type dimension: int. + """ + self.thisptr.set_dimension(dimension) + + def find(self, simplex): + """This function returns if the N-simplex was found in the simplicial + complex or not. + + :param simplex: The N-simplex to find, represented by a list of vertex. + :type simplex: list of int. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.find_simplex(complex) + + def insert(self, simplex, filtration=0.0): + """This function inserts the given N-simplex with the given filtration + value (default value is '0.0'). + + :param simplex: The N-simplex to insert, represented by a list of + vertex. + :type simplex: list of int. + :param filtration: The filtration value of the simplex. + :type filtration: float. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.insert_simplex_and_subfaces(complex, + filtration) + + def get_filtered_tree(self): + """This function returns the tree sorted by increasing filtration + values. + + :returns: list of tuples(simplex, filtration) -- the tree sorted by + increasing filtration values. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_filtered_tree() + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_skeleton_tree(self, dimension): + """This function returns the tree skeleton of a maximum given + dimension. + + :param dimension: The skeleton dimension value. + :type dimension: int. + :returns: list of tuples(simplex, filtration) -- the skeleton tree + of a maximum dimension. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_skeleton_tree(dimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_star_tree(self, simplex): + """This function returns the star tree of a given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: list of tuples(simplex, filtration) -- the star tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_star_tree(complex) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_coface_tree(self, simplex, codimension): + """This function returns the coface tree of a given N-simplex with a + given codimension. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :param codimension: The codimension. If codimension = 0, all cofaces + are returned (equivalent of get_star_tree function) + :type codimension: int. + :returns: list of tuples(simplex, filtration) -- the coface tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_coface_tree(complex, codimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def remove_maximal_simplex(self, simplex): + """This function removes a given maximal N-simplex from the simplicial + complex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + """ + self.thisptr.remove_maximal_simplex(simplex) + + def persistence(self, homology_coeff_field=11): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :returns: list of pairs(dimension, pair(birth, death)) -- the + persistence of the simplicial complex. + """ + if self.pcohptr != NULL: + del self.pcohptr + self.pcohptr = new Mini_simplex_tree_persistence_interface(self.thisptr) + cdef vector[pair[int, pair[double, double]]] persistence_result + if self.pcohptr != NULL: + persistence_result = self.pcohptr.get_persistence(homology_coeff_field, 0) + return persistence_result + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + cdef vector[int] bn_result + if self.pcohptr != NULL: + bn_result = self.pcohptr.betti_numbers() + else: + print("betti_numbers function requires persistence function" + " to be launched first.") + return bn_result + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) + else: + print("persistent_betti_numbers function requires persistence function" + " to be launched first.") + return pbn_result diff --git a/src/cython/cython/periodic_cubical_complex.pyx b/src/cython/cython/periodic_cubical_complex.pyx new file mode 100644 index 00000000..d56eb5b1 --- /dev/null +++ b/src/cython/cython/periodic_cubical_complex.pyx @@ -0,0 +1,181 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair +from libcpp.string cimport string +import os + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +cdef extern from "Cubical_complex_interface.h" namespace "Gudhi": + cdef cppclass Periodic_cubical_complex_base_interface "Gudhi::Cubical_complex::Cubical_complex_interface>": + Periodic_cubical_complex_base_interface(vector[unsigned] dimensions, vector[double] top_dimensional_cells) + Periodic_cubical_complex_base_interface(string perseus_file) + int num_simplices() + int dimension() + +cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": + cdef cppclass Periodic_cubical_complex_persistence_interface "Gudhi::Persistent_cohomology_interface>>": + Periodic_cubical_complex_persistence_interface(Periodic_cubical_complex_base_interface * st) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] betti_numbers() + vector[int] persistent_betti_numbers(double from_value, double to_value) + + +# PeriodicCubicalComplex python interface +cdef class PeriodicCubicalComplex: + """The PeriodicCubicalComplex is an example of a structured complex useful + in computational mathematics (specially rigorous numerics) and image + analysis. + """ + cdef Periodic_cubical_complex_base_interface * thisptr + + cdef Periodic_cubical_complex_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, dimensions=None, top_dimensional_cells=None, + perseus_file=''): + """PeriodicCubicalComplex constructor from dimensions and + top_dimensional_cells or from a perseus file style name. + + :param dimensions: A list of number of top dimensional cells. + :type dimensions: list of int + :param top_dimensional_cells: A list of top dimensional cells. + :type top_dimensional_cells: list of double + + Or + + :param perseus_file: A perseus file style name. + :type perseus_file: string + """ + + # The real cython constructor + def __cinit__(self, dimensions=None, top_dimensional_cells=None, + perseus_file=''): + if ((dimensions is not None) or (top_dimensional_cells is not None) and + (perseus_file is not '')): + print("PeriodicCubicalComplex can be constructed from dimensions" + " and top_dimensional_cells or from a perseus file style " + "name.") + else: + if dimensions is not None: + if top_dimensional_cells is not None: + self.thisptr = new Periodic_cubical_complex_base_interface(dimensions, top_dimensional_cells) + else: + if perseus_file is not '': + if os.path.isfile(perseus_file): + self.thisptr = new Periodic_cubical_complex_base_interface(perseus_file) + else: + print("file " + perseus_file + " not found.") + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if PeriodicCubicalComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def persistence(self, homology_coeff_field=11, min_persistence=0): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :returns: list of pairs(dimension, pair(birth, death)) -- the + persistence of the simplicial complex. + """ + if self.pcohptr != NULL: + del self.pcohptr + if self.thisptr != NULL: + self.pcohptr = new Periodic_cubical_complex_persistence_interface(self.thisptr) + cdef vector[pair[int, pair[double, double]]] persistence_result + if self.pcohptr != NULL: + persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) + return persistence_result + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + cdef vector[int] bn_result + if self.pcohptr != NULL: + bn_result = self.pcohptr.betti_numbers() + return bn_result + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) + return pbn_result diff --git a/src/cython/cython/persistence_graphical_tools.py b/src/cython/cython/persistence_graphical_tools.py new file mode 100755 index 00000000..247e119e --- /dev/null +++ b/src/cython/cython/persistence_graphical_tools.py @@ -0,0 +1,155 @@ +import matplotlib.pyplot as plt +import numpy as np + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +def __min_birth_max_death(persistence): + """This function returns (min_birth, max_death) from the persistence. + + :param persistence: The persistence to plot. + :type persistence: list of tuples(dimension, tuple(birth, death)). + :returns: (float, float) -- (min_birth, max_death). + """ + # Look for minimum birth date and maximum death date for plot optimisation + max_death = 0 + min_birth = persistence[0][1][0] + for interval in reversed(persistence): + if float(interval[1][1]) != float('inf'): + if float(interval[1][1]) > max_death: + max_death = float(interval[1][1]) + if float(interval[1][0]) > max_death: + max_death = float(interval[1][0]) + if float(interval[1][0]) < min_birth: + min_birth = float(interval[1][0]) + return (min_birth, max_death) + +""" +Only 13 colors for the palette +""" +palette = ['#ff0000', '#00ff00', '#0000ff', '#00ffff', '#ff00ff', '#ffff00', + '#000000', '#880000', '#008800', '#000088', '#888800', '#880088', + '#008888'] + +def show_palette_values(alpha=0.6): + """This function shows palette color values in function of the dimension. + + :param alpha: alpha value in [0.0, 1.0] for horizontal bars (default is + 0.6). + :type alpha: float. + :returns: plot -- An horizontal bar plot of dimensions color. + """ + colors = [] + for color in palette: + colors.append(color) + + y_pos = np.arange(len(palette)) + + plt.barh(y_pos, y_pos + 1, align='center', alpha=alpha, color=colors) + plt.ylabel('Dimension') + plt.title('Dimension palette values') + + plt.show() + +def barcode_persistence(persistence, alpha=0.6): + """This function plots the persistence bar code. + + :param persistence: The persistence to plot. + :type persistence: list of tuples(dimension, tuple(birth, death)). + :param alpha: alpha value in [0.0, 1.0] for horizontal bars (default is + 0.6). + :type alpha: float. + :returns: plot -- An horizontal bar plot of persistence. + """ + (min_birth, max_death) = __min_birth_max_death(persistence) + ind = 0 + delta = ((max_death - min_birth) / 10.0) + # Replace infinity values with max_death + delta for bar code to be more + # readable + infinity = max_death + delta + axis_start = min_birth - delta + # Draw horizontal bars in loop + for interval in reversed(persistence): + if float(interval[1][1]) != float('inf'): + # Finite death case + plt.barh(ind, (interval[1][1] - interval[1][0]), height=0.8, + left = interval[1][0], alpha=alpha, + color = palette[interval[0]]) + else: + # Infinite death case for diagram to be nicer + plt.barh(ind, (infinity - interval[1][0]), height=0.8, + left = interval[1][0], alpha=alpha, + color = palette[interval[0]]) + ind = ind + 1 + + plt.title('Persistence barcode') + # Ends plot on infinity value and starts a little bit before min_birth + plt.axis([axis_start, infinity, 0, ind]) + plt.show() + +def diagram_persistence(persistence, alpha=0.6): + """This function plots the persistence diagram. + + :param persistence: The persistence to plot. + :type persistence: list of tuples(dimension, tuple(birth, death)). + :param alpha: alpha value in [0.0, 1.0] for points and horizontal infinity + line (default is 0.6). + :type alpha: float. + :returns: plot -- An diagram plot of persistence. + """ + (min_birth, max_death) = __min_birth_max_death(persistence) + ind = 0 + delta = ((max_death - min_birth) / 10.0) + # Replace infinity values with max_death + delta for diagram to be more + # readable + infinity = max_death + delta + axis_start = min_birth - delta + + # line display of equation : birth = death + x = np.linspace(axis_start, infinity, 1000) + # infinity line and text + plt.plot(x, x, color='k', linewidth=1.0) + plt.plot(x, [infinity] * len(x), linewidth=1.0, color='k', alpha=alpha) + plt.text(axis_start, infinity, r'$\infty$', color='k', alpha=alpha) + + # Draw points in loop + for interval in reversed(persistence): + if float(interval[1][1]) != float('inf'): + # Finite death case + plt.scatter(interval[1][0], interval[1][1], alpha=alpha, + color = palette[interval[0]]) + else: + # Infinite death case for diagram to be nicer + plt.scatter(interval[1][0], infinity, alpha=alpha, + color = palette[interval[0]]) + ind = ind + 1 + + plt.title('Persistence diagram') + plt.xlabel('Birth') + plt.ylabel('Death') + # Ends plot on infinity value and starts a little bit before min_birth + plt.axis([axis_start, infinity, axis_start, infinity + delta]) + plt.show() diff --git a/src/cython/cython/rips_complex.pyx b/src/cython/cython/rips_complex.pyx new file mode 100644 index 00000000..ee4c34b0 --- /dev/null +++ b/src/cython/cython/rips_complex.pyx @@ -0,0 +1,369 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": + cdef cppclass Simplex_tree_options_full_featured: + pass + + cdef cppclass Rips_complex_interface "Gudhi::Simplex_tree_interface": + Simplex_tree() + double filtration() + double simplex_filtration(vector[int] simplex) + void set_filtration(double filtration) + void initialize_filtration() + int num_vertices() + int num_simplices() + void set_dimension(int dimension) + int dimension() + bint find_simplex(vector[int] simplex) + bint insert_simplex_and_subfaces(vector[int] simplex, + double filtration) + vector[pair[vector[int], double]] get_filtered_tree() + vector[pair[vector[int], double]] get_skeleton_tree(int dimension) + vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) + vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, + int dimension) + void remove_maximal_simplex(vector[int] simplex) + void graph_expansion(vector[vector[double]] points, int max_dimension, + double max_edge_length) + +cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": + cdef cppclass Rips_complex_persistence_interface "Gudhi::Persistent_cohomology_interface>": + Rips_complex_persistence_interface(Rips_complex_interface * st) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] betti_numbers() + vector[int] persistent_betti_numbers(double from_value, double to_value) + +# RipsComplex python interface +cdef class RipsComplex: + """RipsComplex is a simplicial complex constructed from a list of points. + + Each point Pn is inserted as a vertex in the simplicial complex with a + null filtration value. + + A N-simplex represented by the list of vertices Vi, ..., Vj is inserted in + the simplicial complex if all the points Pi, ..., Pj corresponding to the + vertices are within a distance less or equal to a given maximum edge length + value, and if N (dimension of the N-simplex) is less or equal to a given + maximum dimension. + """ + cdef Rips_complex_interface * thisptr + + cdef Rips_complex_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, points=[], max_dimension=3, + max_edge_length=float('inf')): + """RipsComplex constructor. + + :param points: A list of points in d-Dimension. + :type points: list of list of double + :param max_dimension: Maximum dimension of the complex to be expanded. + :type max_dimension: int + :param max_edge_length: Maximum edge length value (rips radius). + :type max_edge_length: double + """ + + # The real cython constructor + def __cinit__(self, points=[], max_dimension=3, + max_edge_length=float('inf')): + self.thisptr = new Rips_complex_interface() + # Constructor from graph expansion + if points is not None: + self.thisptr.graph_expansion(points, max_dimension, + max_edge_length) + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if RipsComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def get_filtration(self): + """This function returns the main simplicial complex filtration value. + + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.filtration() + + def filtration(self, simplex): + """This function returns the simplicial complex filtration value for a + given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.simplex_filtration(simplex) + + def set_filtration(self, filtration): + """This function sets the main simplicial complex filtration value. + + :param filtration: The filtration value. + :type filtration: float. + """ + self.thisptr.set_filtration( filtration) + + def initialize_filtration(self): + """This function initializes and sorts the simplicial complex + filtration vector. + + .. note:: + + This function must be launched before persistence, betti_numbers, + persistent_betti_numbers or get_filtered_tree after inserting or + removing simplices. + """ + self.thisptr.initialize_filtration() + + def num_vertices(self): + """This function returns the number of vertices of the simplicial + complex. + + :returns: int -- the simplicial complex number of vertices. + """ + return self.thisptr.num_vertices() + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def set_dimension(self, dimension): + """This function sets the dimension of the simplicial complex. + + :param dimension: The new dimension value. + :type dimension: int. + """ + self.thisptr.set_dimension(dimension) + + def find(self, simplex): + """This function returns if the N-simplex was found in the simplicial + complex or not. + + :param simplex: The N-simplex to find, represented by a list of vertex. + :type simplex: list of int. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.find_simplex(complex) + + def insert(self, simplex, filtration=0.0): + """This function inserts the given N-simplex with the given filtration + value (default value is '0.0'). + + :param simplex: The N-simplex to insert, represented by a list of + vertex. + :type simplex: list of int. + :param filtration: The filtration value of the simplex. + :type filtration: float. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.insert_simplex_and_subfaces(complex, + filtration) + + def get_filtered_tree(self): + """This function returns the tree sorted by increasing filtration + values. + + :returns: list of tuples(simplex, filtration) -- the tree sorted by + increasing filtration values. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_filtered_tree() + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_skeleton_tree(self, dimension): + """This function returns the tree skeleton of a maximum given + dimension. + + :param dimension: The skeleton dimension value. + :type dimension: int. + :returns: list of tuples(simplex, filtration) -- the skeleton tree + of a maximum dimension. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_skeleton_tree(dimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_star_tree(self, simplex): + """This function returns the star tree of a given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: list of tuples(simplex, filtration) -- the star tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_star_tree(complex) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_coface_tree(self, simplex, codimension): + """This function returns the coface tree of a given N-simplex with a + given codimension. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :param codimension: The codimension. If codimension = 0, all cofaces + are returned (equivalent of get_star_tree function) + :type codimension: int. + :returns: list of tuples(simplex, filtration) -- the coface tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_coface_tree(complex, codimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def remove_maximal_simplex(self, simplex): + """This function removes a given maximal N-simplex from the simplicial + complex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + """ + self.thisptr.remove_maximal_simplex(simplex) + + def persistence(self, homology_coeff_field=11, min_persistence=0): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :note: list of pairs(dimension, pair(birth, death)) -- the + persistence of the simplicial complex. + """ + if self.pcohptr != NULL: + del self.pcohptr + self.pcohptr = new Rips_complex_persistence_interface(self.thisptr) + cdef vector[pair[int, pair[double, double]]] persistence_result + if self.pcohptr != NULL: + persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) + return persistence_result + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + cdef vector[int] bn_result + if self.pcohptr != NULL: + bn_result = self.pcohptr.betti_numbers() + else: + print("betti_numbers function requires persistence function" + " to be launched first.") + return bn_result + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) + else: + print("persistent_betti_numbers function requires persistence function" + " to be launched first.") + return pbn_result diff --git a/src/cython/cython/simplex_tree.pyx b/src/cython/cython/simplex_tree.pyx new file mode 100644 index 00000000..bf91e812 --- /dev/null +++ b/src/cython/cython/simplex_tree.pyx @@ -0,0 +1,352 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": + cdef cppclass Simplex_tree_options_full_featured: + pass + + cdef cppclass Simplex_tree_interface_full_featured "Gudhi::Simplex_tree_interface": + Simplex_tree() + double filtration() + double simplex_filtration(vector[int] simplex) + void set_filtration(double filtration) + void initialize_filtration() + int num_vertices() + int num_simplices() + void set_dimension(int dimension) + int dimension() + bint find_simplex(vector[int] simplex) + bint insert_simplex_and_subfaces(vector[int] simplex, + double filtration) + vector[pair[vector[int], double]] get_filtered_tree() + vector[pair[vector[int], double]] get_skeleton_tree(int dimension) + vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) + vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, + int dimension) + void remove_maximal_simplex(vector[int] simplex) + +cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": + cdef cppclass Simplex_tree_persistence_interface "Gudhi::Persistent_cohomology_interface>": + Simplex_tree_persistence_interface(Simplex_tree_interface_full_featured * st) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] betti_numbers() + vector[int] persistent_betti_numbers(double from_value, double to_value) + +# SimplexTree python interface +cdef class SimplexTree: + """The simplex tree is an efficient and flexible data structure for + representing general (filtered) simplicial complexes. The data structure + is described in Jean-Daniel Boissonnat and Clément Maria. The Simplex + Tree: An Efficient Data Structure for General Simplicial Complexes. + Algorithmica, pages 1–22, 2014. + + This class is a filtered, with keys, and non contiguous vertices version + of the simplex tree. + """ + cdef Simplex_tree_interface_full_featured * thisptr + + cdef Simplex_tree_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, points=[], max_alpha_square=float('inf')): + """SimplexTree constructor. + """ + + # The real cython constructor + def __cinit__(self): + self.thisptr = new Simplex_tree_interface_full_featured() + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if SimplexTree pointer is not NULL. + """ + return self.thisptr != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def get_filtration(self): + """This function returns the main simplicial complex filtration value. + + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.filtration() + + def filtration(self, simplex): + """This function returns the simplicial complex filtration value for a + given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.simplex_filtration(simplex) + + def set_filtration(self, filtration): + """This function sets the main simplicial complex filtration value. + + :param filtration: The filtration value. + :type filtration: float. + """ + self.thisptr.set_filtration( filtration) + + def initialize_filtration(self): + """This function initializes and sorts the simplicial complex + filtration vector. + + .. note:: + + This function must be launched before persistence, betti_numbers, + persistent_betti_numbers or get_filtered_tree after inserting or + removing simplices. + """ + self.thisptr.initialize_filtration() + + def num_vertices(self): + """This function returns the number of vertices of the simplicial + complex. + + :returns: int -- the simplicial complex number of vertices. + """ + return self.thisptr.num_vertices() + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def set_dimension(self, dimension): + """This function sets the dimension of the simplicial complex. + + :param dimension: The new dimension value. + :type dimension: int. + """ + self.thisptr.set_dimension(dimension) + + def find(self, simplex): + """This function returns if the N-simplex was found in the simplicial + complex or not. + + :param simplex: The N-simplex to find, represented by a list of vertex. + :type simplex: list of int. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.find_simplex(complex) + + def insert(self, simplex, filtration=0.0): + """This function inserts the given N-simplex with the given filtration + value (default value is '0.0'). + + :param simplex: The N-simplex to insert, represented by a list of + vertex. + :type simplex: list of int. + :param filtration: The filtration value of the simplex. + :type filtration: float. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.insert_simplex_and_subfaces(complex, + filtration) + + def get_filtered_tree(self): + """This function returns the tree sorted by increasing filtration + values. + + :returns: list of tuples(simplex, filtration) -- the tree sorted by + increasing filtration values. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_filtered_tree() + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_skeleton_tree(self, dimension): + """This function returns the tree skeleton of a maximum given + dimension. + + :param dimension: The skeleton dimension value. + :type dimension: int. + :returns: list of tuples(simplex, filtration) -- the skeleton tree + of a maximum dimension. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_skeleton_tree(dimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_star_tree(self, simplex): + """This function returns the star tree of a given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: list of tuples(simplex, filtration) -- the star tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_star_tree(complex) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_coface_tree(self, simplex, codimension): + """This function returns the coface tree of a given N-simplex with a + given codimension. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :param codimension: The codimension. If codimension = 0, all cofaces + are returned (equivalent of get_star_tree function) + :type codimension: int. + :returns: list of tuples(simplex, filtration) -- the coface tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_coface_tree(complex, codimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def remove_maximal_simplex(self, simplex): + """This function removes a given maximal N-simplex from the simplicial + complex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + """ + self.thisptr.remove_maximal_simplex(simplex) + + def persistence(self, homology_coeff_field=11, min_persistence=0): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :note: list of pairs(dimension, pair(birth, death)) -- the + persistence of the simplicial complex. + """ + if self.pcohptr != NULL: + del self.pcohptr + self.pcohptr = new Simplex_tree_persistence_interface(self.thisptr) + cdef vector[pair[int, pair[double, double]]] persistence_result + if self.pcohptr != NULL: + persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) + return persistence_result + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + cdef vector[int] bn_result + if self.pcohptr != NULL: + bn_result = self.pcohptr.betti_numbers() + else: + print("betti_numbers function requires persistence function" + " to be launched first.") + return bn_result + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) + else: + print("persistent_betti_numbers function requires persistence function" + " to be launched first.") + return pbn_result diff --git a/src/cython/cython/witness_complex.pyx b/src/cython/cython/witness_complex.pyx new file mode 100644 index 00000000..835244cf --- /dev/null +++ b/src/cython/cython/witness_complex.pyx @@ -0,0 +1,322 @@ +from cython cimport numeric +from libcpp.vector cimport vector +from libcpp.utility cimport pair + +"""This file is part of the Gudhi Library. The Gudhi library + (Geometric Understanding in Higher Dimensions) is a generic C++ + library for computational topology. + + Author(s): Vincent Rouvreau + + Copyright (C) 2016 INRIA + + This program is free software: you can redistribute it and/or modify + it under the terms of the GNU General Public License as published by + the Free Software Foundation, either version 3 of the License, or + (at your option) any later version. + + This program is distributed in the hope that it will be useful, + but WITHOUT ANY WARRANTY; without even the implied warranty of + MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License + along with this program. If not, see . +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 INRIA" +__license__ = "GPL v3" + +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[double]] points, int number_of_landmarks) + double filtration() + double simplex_filtration(vector[int] simplex) + void set_filtration(double filtration) + void initialize_filtration() + int num_vertices() + int num_simplices() + void set_dimension(int dimension) + int dimension() + bint find_simplex(vector[int] simplex) + bint insert_simplex_and_subfaces(vector[int] simplex, + double filtration) + vector[pair[vector[int], double]] get_filtered_tree() + vector[pair[vector[int], double]] get_skeleton_tree(int dimension) + vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) + vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, + int dimension) + void remove_maximal_simplex(vector[int] simplex) + vector[double] get_point(int vertex) + vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) + vector[int] get_betti_numbers() + vector[int] get_persistent_betti_numbers(double from_value, double to_value) + +# WitnessComplex python interface +cdef class WitnessComplex: + """WitnessComplex is a simplicial complex constructed from ... + + """ + + cdef Witness_complex_interface * thisptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self, points=[], number_of_landmarks=5): + """WitnessComplex constructor. + + :param points: A list of points in d-Dimension. + :type points: list of list of double + :param number_of_landmarks: Number of landmarks to build the + WitnessComplex. + :type number_of_landmarks: int + """ + + # The real cython constructor + def __cinit__(self, points=None, number_of_landmarks=5): + if points is not None: + self.thisptr = new Witness_complex_interface(points, + number_of_landmarks) + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + + def __is_defined(self): + """Returns true if AlphaComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def get_filtration(self): + """This function returns the main simplicial complex filtration value. + + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.filtration() + + def filtration(self, simplex): + """This function returns the simplicial complex filtration value for a + given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: float -- the simplicial complex filtration value. + """ + return self.thisptr.simplex_filtration(simplex) + + def set_filtration(self, filtration): + """This function sets the main simplicial complex filtration value. + + :param filtration: The filtration value. + :type filtration: float. + """ + self.thisptr.set_filtration( filtration) + + def initialize_filtration(self): + """This function initializes and sorts the simplicial complex + filtration vector. + + .. note:: + + This function must be launched before persistence, betti_numbers, + persistent_betti_numbers or get_filtered_tree after inserting or + removing simplices. + """ + self.thisptr.initialize_filtration() + + def num_vertices(self): + """This function returns the number of vertices of the simplicial + complex. + + :returns: int -- the simplicial complex number of vertices. + """ + return self.thisptr.num_vertices() + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: int -- the simplicial complex number of simplices. + """ + return self.thisptr.num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: int -- the simplicial complex dimension. + """ + return self.thisptr.dimension() + + def set_dimension(self, dimension): + """This function sets the dimension of the simplicial complex. + + :param dimension: The new dimension value. + :type dimension: int. + """ + self.thisptr.set_dimension(dimension) + + def find(self, simplex): + """This function returns if the N-simplex was found in the simplicial + complex or not. + + :param simplex: The N-simplex to find, represented by a list of vertex. + :type simplex: list of int. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.find_simplex(complex) + + def insert(self, simplex, filtration=0.0): + """This function inserts the given N-simplex with the given filtration + value (default value is '0.0'). + + :param simplex: The N-simplex to insert, represented by a list of + vertex. + :type simplex: list of int. + :param filtration: The filtration value of the simplex. + :type filtration: float. + :returns: bool -- true if the simplex was found, false otherwise. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + return self.thisptr.insert_simplex_and_subfaces(complex, + filtration) + + def get_filtered_tree(self): + """This function returns the tree sorted by increasing filtration + values. + + :returns: list of tuples(simplex, filtration) -- the tree sorted by + increasing filtration values. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_filtered_tree() + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_skeleton_tree(self, dimension): + """This function returns the tree skeleton of a maximum given + dimension. + + :param dimension: The skeleton dimension value. + :type dimension: int. + :returns: list of tuples(simplex, filtration) -- the skeleton tree + of a maximum dimension. + """ + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_skeleton_tree(dimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_star_tree(self, simplex): + """This function returns the star tree of a given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: list of tuples(simplex, filtration) -- the star tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_star_tree(complex) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_coface_tree(self, simplex, codimension): + """This function returns the coface tree of a given N-simplex with a + given codimension. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :param codimension: The codimension. If codimension = 0, all cofaces + are returned (equivalent of get_star_tree function) + :type codimension: int. + :returns: list of tuples(simplex, filtration) -- the coface tree of a + simplex. + """ + cdef vector[int] complex + for i in simplex: + complex.push_back(i) + cdef vector[pair[vector[int], double]] coface_tree \ + = self.thisptr.get_coface_tree(complex, codimension) + ct = [] + for filtered_complex in coface_tree: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def remove_maximal_simplex(self, simplex): + """This function removes a given maximal N-simplex from the simplicial + complex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + """ + self.thisptr.remove_maximal_simplex(simplex) + + def persistence(self, homology_coeff_field=11, min_persistence=0): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number + :type homology_coeff_field: int. + :param min_persistence: The minimum persistence value to take into + account (strictly greater than min_persistence). Default value is + 0.0. + Sets min_persistence to -1.0 to see all values. + :type min_persistence: float. + :note: list of pairs(dimension, pair(birth, death)) -- the + persistence of the simplicial complex. + """ + return self.thisptr.get_persistence(homology_coeff_field, min_persistence) + + def betti_numbers(self): + """This function returns the Betti numbers of the simplicial complex. + + :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). + + :note: betti_numbers function requires persistence function to be + launched first. + """ + return self.thisptr.get_betti_numbers() + + def persistent_betti_numbers(self, from_value, to_value): + """This function returns the persistent Betti numbers of the + simplicial complex. + + :param from_value: The persistence birth limit to be added in the + numbers (persistent birth <= from_value). + :type from_value: float. + :param to_value: The persistence death limit to be added in the + numbers (persistent death > to_value). + :type to_value: float. + + :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., + Bn]). + + :note: persistent_betti_numbers function requires persistence + function to be launched first. + """ + return self.thisptr.get_persistent_betti_numbers(from_value, to_value) diff --git a/src/cython/doc/Makefile b/src/cython/doc/Makefile new file mode 100644 index 00000000..fc353a37 --- /dev/null +++ b/src/cython/doc/Makefile @@ -0,0 +1,177 @@ +# Makefile for Sphinx documentation +# + +# You can set these variables from the command line. +SPHINXOPTS = +SPHINXBUILD = sphinx-build +PAPER = +BUILDDIR = _build + +# User-friendly check for sphinx-build +ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) +$(error The '$(SPHINXBUILD)' command was not found. 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The pseudo-XML files are in $(BUILDDIR)/pseudoxml." diff --git a/src/cython/doc/alpha_complex_ref.rst b/src/cython/doc/alpha_complex_ref.rst new file mode 100644 index 00000000..6a122b09 --- /dev/null +++ b/src/cython/doc/alpha_complex_ref.rst @@ -0,0 +1,10 @@ +============================== +Alpha complex reference manual +============================== + +.. autoclass:: gudhi.AlphaComplex + :members: + :undoc-members: + :show-inheritance: + + .. automethod:: gudhi.AlphaComplex.__init__ diff --git a/src/cython/doc/alpha_complex_sum.rst b/src/cython/doc/alpha_complex_sum.rst new file mode 100644 index 00000000..b608050e --- /dev/null +++ b/src/cython/doc/alpha_complex_sum.rst @@ -0,0 +1,21 @@ +===================================== ===================================== ===================================== +:Author: Vincent Rouvreau :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++-------------------------------------------+----------------------------------------------------------------------+ +| .. image:: | Alpha_complex is a simplicial complex constructed from the finite | +| img/alpha_complex_representation.png | cells of a Delaunay Triangulation. | +| | | +| | 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. | +| | | +| | This package requires having CGAL version 4.7 or higher (4.8.1 is | +| | advised for better perfomances). | ++-------------------------------------------+----------------------------------------------------------------------+ +| :doc:`alpha_complex_user` | :doc:`alpha_complex_ref` | ++-------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/doc/alpha_complex_user.rst b/src/cython/doc/alpha_complex_user.rst new file mode 100644 index 00000000..b6b6e550 --- /dev/null +++ b/src/cython/doc/alpha_complex_user.rst @@ -0,0 +1,192 @@ +========================= +Alpha complex user manual +========================= +Definition +---------- + +.. include:: alpha_complex_sum.rst + +Alpha_complex is constructing a :doc:`Simplex_tree ` using +`Delaunay Triangulation `_ +:cite:`cgal:hdj-t-15b` from `CGAL `_ (the Computational Geometry Algorithms Library +:cite:`cgal:eb-15b`). + +Remarks +^^^^^^^ +When Alpha_complex is constructed with an infinite value of :math:`\alpha`, the complex is a Delaunay complex. + +Example from points +------------------- + +This example builds the Delaunay triangulation from the given points, and initializes the alpha complex with it: + +.. testcode:: + + import gudhi + alpha_complex = gudhi.AlphaComplex(points=[[1, 1], [7, 0], [4, 6], [9, 6], [0, 14], [2, 19], [9, 17]], + max_alpha_square=60.0) + result_str = 'Alpha complex is of dimension ' + repr(alpha_complex.dimension()) + ' - ' + \ + repr(alpha_complex.num_simplices()) + ' simplices - ' + \ + repr(alpha_complex.num_vertices()) + ' vertices.' + print(result_str) + for fitered_value in alpha_complex.get_filtered_tree(): + print(fitered_value) + +The output is: + +.. testoutput:: + + Alpha complex is of dimension 2 - 25 simplices - 7 vertices. + ([0], 0.0) + ([1], 0.0) + ([2], 0.0) + ([3], 0.0) + ([4], 0.0) + ([5], 0.0) + ([6], 0.0) + ([2, 3], 6.25) + ([4, 5], 7.25) + ([0, 2], 8.5) + ([0, 1], 9.25) + ([1, 3], 10.0) + ([1, 2], 11.25) + ([1, 2, 3], 12.5) + ([0, 1, 2], 12.995867768595042) + ([5, 6], 13.25) + ([2, 4], 20.0) + ([4, 6], 22.736686390532547) + ([4, 5, 6], 22.736686390532547) + ([3, 6], 30.25) + ([2, 6], 36.5) + ([2, 3, 6], 36.5) + ([2, 4, 6], 37.24489795918368) + ([0, 4], 59.710743801652896) + ([0, 2, 4], 59.710743801652896) + + +Algorithm +--------- + +Data structure +^^^^^^^^^^^^^^ + +In order to build the alpha complex, first, a Simplex tree is built from the cells of a Delaunay Triangulation. +(The filtration value is set to NaN, which stands for unknown value): + +.. image:: + img/alpha_complex_doc.png + :align: center + :alt: Simplex tree structure construction example + +Filtration value computation algorithm +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + + **for** i : dimension :math:`\rightarrow` 0 **do** + **for all** :math:`\sigma` of dimension i + **if** filtration(:math:`\sigma`) is NaN **then** + filtration(:math:`\sigma`) = :math:`\alpha^2(\sigma)` + **end if** + + *//propagate alpha filtration value* + + **for all** :math:`\tau` face of :math:`\sigma` + **if** filtration(:math:`\tau`) is not NaN **then** + filtration(:math:`\tau`) = filtration(:math:`\sigma`) + **end if** + **end for** + **end for** + **end for** + + make_filtration_non_decreasing() + + prune_above_filtration() + +Dimension 2 +^^^^^^^^^^^ + +From the example above, it means the algorithm looks into each triangle ([0,1,2], [0,2,4], [1,2,3], ...), +computes the filtration value of the triangle, and then propagates the filtration value as described +here: + +.. image:: + img/alpha_complex_doc_420.png + :align: center + :alt: Filtration value propagation example + +Dimension 1 +^^^^^^^^^^^ + +Then, the algorithm looks into each edge ([0,1], [0,2], [1,2], ...), +computes the filtration value of the edge (in this case, propagation will have no effect). + +Dimension 0 +^^^^^^^^^^^ + +Finally, the algorithm looks into each vertex ([0], [1], [2], [3], [4], [5] and [6]) and +sets the filtration value (0 in case of a vertex - propagation will have no effect). + +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). +We fix that up by calling `Simplex_tree::make_filtration_non_decreasing()` (cf. +`C++ version `_). + +Prune above given filtration value +^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ + +The simplex tree is pruned from the given maximum alpha squared value (cf. `Simplex_tree::prune_above_filtration()` +int he `C++ version `_). +In the following example, the value is given by the user as argument of the program. + + +Example from OFF file +^^^^^^^^^^^^^^^^^^^^^ + +This example builds the Delaunay triangulation from the points given by an OFF file, and initializes the alpha complex +with it. + + +Then, it is asked to display information about the alpha complex: + +.. testcode:: + + import gudhi + alpha_complex = gudhi.AlphaComplex(off_file='alphacomplexdoc.off', + max_alpha_square=59.0) + result_str = 'Alpha complex is of dimension ' + repr(alpha_complex.dimension()) + ' - ' + \ + repr(alpha_complex.num_simplices()) + ' simplices - ' + \ + repr(alpha_complex.num_vertices()) + ' vertices.' + print(result_str) + for fitered_value in alpha_complex.get_filtered_tree(): + print(fitered_value) + +the program output is: + +.. testoutput:: + + Alpha complex is of dimension 2 - 23 simplices - 7 vertices. + ([0], 0.0) + ([1], 0.0) + ([2], 0.0) + ([3], 0.0) + ([4], 0.0) + ([5], 0.0) + ([6], 0.0) + ([2, 3], 6.25) + ([4, 5], 7.25) + ([0, 2], 8.5) + ([0, 1], 9.25) + ([1, 3], 10.0) + ([1, 2], 11.25) + ([1, 2, 3], 12.5) + ([0, 1, 2], 12.995867768595042) + ([5, 6], 13.25) + ([2, 4], 20.0) + ([4, 6], 22.736686390532547) + ([4, 5, 6], 22.736686390532547) + ([3, 6], 30.25) + ([2, 6], 36.5) + ([2, 3, 6], 36.5) + ([2, 4, 6], 37.24489795918368) diff --git a/src/cython/doc/biblio.rst b/src/cython/doc/biblio.rst new file mode 100644 index 00000000..b8e733ed --- /dev/null +++ b/src/cython/doc/biblio.rst @@ -0,0 +1,7 @@ +============ +Bibliography +============ + +.. bibliography:: bibliography.bib + :filter: docnames + :style: unsrt diff --git a/src/cython/doc/cgal_citation.rst b/src/cython/doc/cgal_citation.rst new file mode 100644 index 00000000..bbc4ef9e --- /dev/null +++ b/src/cython/doc/cgal_citation.rst @@ -0,0 +1,8 @@ +============== +CGAL citations +============== + +.. + bibliography:: how_to_cite_cgal.bib + :filter: docnames + :style: unsrt diff --git a/src/cython/doc/conf.py b/src/cython/doc/conf.py new file mode 100755 index 00000000..bc138025 --- /dev/null +++ b/src/cython/doc/conf.py @@ -0,0 +1,271 @@ +# -*- coding: utf-8 -*- +# +# GUDHI documentation build configuration file, created by +# sphinx-quickstart on Thu Jun 30 09:55:51 2016. +# +# This file is execfile()d with the current directory set to its +# containing dir. +# +# Note that not all possible configuration values are present in this +# autogenerated file. +# +# All configuration values have a default; values that are commented out +# serve to show the default. + +import sys +import os + +# If extensions (or modules to document with autodoc) are in another directory, +# add these directories to sys.path here. If the directory is relative to the +# documentation root, use os.path.abspath to make it absolute, like shown here. +#sys.path.insert(0, os.path.abspath('.')) + +# Path to Gudhi.so from source path +sys.path.insert(0, os.path.abspath('../..')) + +# -- General configuration ------------------------------------------------ + +# If your documentation needs a minimal Sphinx version, state it here. +#needs_sphinx = '1.0' + +# Add any Sphinx extension module names here, as strings. They can be +# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom +# ones. +extensions = [ + 'sphinx.ext.autodoc', + 'sphinx.ext.doctest', + 'sphinx.ext.todo', + 'sphinx.ext.coverage', + 'sphinx.ext.mathjax', + 'sphinx.ext.ifconfig', + 'sphinx.ext.viewcode', + 'sphinxcontrib.bibtex', +] + +todo_include_todos = True +# Add any paths that contain templates here, relative to this directory. +templates_path = ['_templates'] + +# The suffix of source filenames. +source_suffix = '.rst' + +# The encoding of source files. +#source_encoding = 'utf-8-sig' + +# The master toctree document. +master_doc = 'index' + +# General information about the project. +project = u'GUDHI' +copyright = u'2016, Vincent Rouvreau' + +# The version info for the project you're documenting, acts as replacement for +# |version| and |release|, also used in various other places throughout the +# built documents. +# +# The short X.Y version. +version = '1.3.1' +# The full version, including alpha/beta/rc tags. +release = '1.3.1' + +# The language for content autogenerated by Sphinx. Refer to documentation +# for a list of supported languages. +#language = None + +# There are two options for replacing |today|: either, you set today to some +# non-false value, then it is used: +#today = '' +# Else, today_fmt is used as the format for a strftime call. +#today_fmt = '%B %d, %Y' + +# List of patterns, relative to source directory, that match files and +# directories to ignore when looking for source files. +exclude_patterns = ['_build'] + +# The reST default role (used for this markup: `text`) to use for all +# documents. +#default_role = None + +# If true, '()' will be appended to :func: etc. cross-reference text. +#add_function_parentheses = True + +# If true, the current module name will be prepended to all description +# unit titles (such as .. function::). +#add_module_names = True + +# If true, sectionauthor and moduleauthor directives will be shown in the +# output. They are ignored by default. +#show_authors = False + +# The name of the Pygments (syntax highlighting) style to use. +pygments_style = 'sphinx' + +# A list of ignored prefixes for module index sorting. +#modindex_common_prefix = [] + +# If true, keep warnings as "system message" paragraphs in the built documents. +#keep_warnings = False + + +# -- Options for HTML output ---------------------------------------------- + +# The theme to use for HTML and HTML Help pages. See the documentation for +# a list of builtin themes. +html_theme = 'default' + +# Theme options are theme-specific and customize the look and feel of a theme +# further. For a list of options available for each theme, see the +# documentation. +#html_theme_options = {} + +# Add any paths that contain custom themes here, relative to this directory. +#html_theme_path = [] + +# The name for this set of Sphinx documents. If None, it defaults to +# " v documentation". +#html_title = None + +# A shorter title for the navigation bar. Default is the same as html_title. +#html_short_title = None + +# The name of an image file (relative to this directory) to place at the top +# of the sidebar. +#html_logo = None + +# The name of an image file (within the static path) to use as favicon of the +# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 +# pixels large. +#html_favicon = None + +# Add any paths that contain custom static files (such as style sheets) here, +# relative to this directory. They are copied after the builtin static files, +# so a file named "default.css" will overwrite the builtin "default.css". +html_static_path = ['_static'] + +# Add any extra paths that contain custom files (such as robots.txt or +# .htaccess) here, relative to this directory. These files are copied +# directly to the root of the documentation. +#html_extra_path = [] + +# If not '', a 'Last updated on:' timestamp is inserted at every page bottom, +# using the given strftime format. +#html_last_updated_fmt = '%b %d, %Y' + +# If true, SmartyPants will be used to convert quotes and dashes to +# typographically correct entities. +#html_use_smartypants = True + +# Custom sidebar templates, maps document names to template names. +#html_sidebars = {} + +# Additional templates that should be rendered to pages, maps page names to +# template names. +#html_additional_pages = {} + +# If false, no module index is generated. +#html_domain_indices = True + +# If false, no index is generated. +#html_use_index = True + +# If true, the index is split into individual pages for each letter. +#html_split_index = False + +# If true, links to the reST sources are added to the pages. +#html_show_sourcelink = True + +# If true, "Created using Sphinx" is shown in the HTML footer. Default is True. +#html_show_sphinx = True + +# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. +#html_show_copyright = True + +# If true, an OpenSearch description file will be output, and all pages will +# contain a tag referring to it. The value of this option must be the +# base URL from which the finished HTML is served. +#html_use_opensearch = '' + +# This is the file name suffix for HTML files (e.g. ".xhtml"). +#html_file_suffix = None + +# Output file base name for HTML help builder. +htmlhelp_basename = 'GUDHIdoc' + + +# -- Options for LaTeX output --------------------------------------------- + +latex_elements = { +# The paper size ('letterpaper' or 'a4paper'). +#'papersize': 'letterpaper', + +# The font size ('10pt', '11pt' or '12pt'). +#'pointsize': '10pt', + +# Additional stuff for the LaTeX preamble. +#'preamble': '', +} + +# Grouping the document tree into LaTeX files. List of tuples +# (source start file, target name, title, +# author, documentclass [howto, manual, or own class]). +latex_documents = [ + ('index', 'GUDHI.tex', u'GUDHI Documentation', + u'Vincent Rouvreau', 'manual'), +] + +# The name of an image file (relative to this directory) to place at the top of +# the title page. +#latex_logo = None + +# For "manual" documents, if this is true, then toplevel headings are parts, +# not chapters. +#latex_use_parts = False + +# If true, show page references after internal links. +#latex_show_pagerefs = False + +# If true, show URL addresses after external links. +#latex_show_urls = False + +# Documents to append as an appendix to all manuals. +#latex_appendices = [] + +# If false, no module index is generated. +#latex_domain_indices = True + + +# -- Options for manual page output --------------------------------------- + +# One entry per manual page. List of tuples +# (source start file, name, description, authors, manual section). +man_pages = [ + ('index', 'gudhi', u'GUDHI Documentation', + [u'Vincent Rouvreau'], 1) +] + +# If true, show URL addresses after external links. +#man_show_urls = False + + +# -- Options for Texinfo output ------------------------------------------- + +# Grouping the document tree into Texinfo files. List of tuples +# (source start file, target name, title, author, +# dir menu entry, description, category) +texinfo_documents = [ + ('index', 'GUDHI', u'GUDHI Documentation', + u'Vincent Rouvreau', 'GUDHI', 'One line description of project.', + 'Miscellaneous'), +] + +# Documents to append as an appendix to all manuals. +#texinfo_appendices = [] + +# If false, no module index is generated. +#texinfo_domain_indices = True + +# How to display URL addresses: 'footnote', 'no', or 'inline'. +#texinfo_show_urls = 'footnote' + +# If true, do not generate a @detailmenu in the "Top" node's menu. +#texinfo_no_detailmenu = False diff --git a/src/cython/doc/cubical_complex_ref.rst b/src/cython/doc/cubical_complex_ref.rst new file mode 100644 index 00000000..84aa4223 --- /dev/null +++ b/src/cython/doc/cubical_complex_ref.rst @@ -0,0 +1,9 @@ +Cubical complex reference manual +################################ + +.. autoclass:: gudhi.CubicalComplex + :members: + :undoc-members: + :show-inheritance: + + .. automethod:: gudhi.CubicalComplex.__init__ diff --git a/src/cython/doc/cubical_complex_sum.rst b/src/cython/doc/cubical_complex_sum.rst new file mode 100644 index 00000000..4008a1fd --- /dev/null +++ b/src/cython/doc/cubical_complex_sum.rst @@ -0,0 +1,12 @@ +===================================== ===================================== ===================================== +:Author: Pawel Dlotko :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++---------------------------------------------+----------------------------------------------------------------------+ +| .. image:: | The cubical complex is an example of a structured complex useful in | +| img/Cubical_complex_representation.png | computational mathematics (specially rigorous numerics) and image | +| | analysis. | ++---------------------------------------------+----------------------------------------------------------------------+ +| :doc:`cubical_complex_user` | * :doc:`cubical_complex_ref` | +| | * :doc:`periodic_cubical_complex_ref` | ++---------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/doc/cubical_complex_user.rst b/src/cython/doc/cubical_complex_user.rst new file mode 100644 index 00000000..2cd85c0a --- /dev/null +++ b/src/cython/doc/cubical_complex_user.rst @@ -0,0 +1,150 @@ +=========================== +Cubical complex user manual +=========================== +Definition +---------- + +===================================== ===================================== ===================================== +:Author: Pawel Dlotko :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++---------------------------------------------+----------------------------------------------------------------------+ +| :doc:`cubical_complex_user` | * :doc:`cubical_complex_ref` | +| | * :doc:`periodic_cubical_complex_ref` | ++---------------------------------------------+----------------------------------------------------------------------+ + +The cubical complex is an example of a structured complex useful in computational mathematics (specially rigorous +numerics) and image analysis. + +An *elementary interval* is an interval of a form :math:`[n,n+1]`, or :math:`[n,n]`, for :math:`n \in \mathcal{Z}`. +The first one is called *non-degenerate*, while the second one is a *degenerate* interval. A +*boundary of a elementary interval* is a chain :math:`\partial [n,n+1] = [n+1,n+1]-[n,n]` in case of +non-degenerated elementary interval and :math:`\partial [n,n] = 0` in case of degenerate elementary interval. An +*elementary cube* :math:`C` is a product of elementary intervals, :math:`C=I_1 \times \ldots \times I_n`. +*Embedding dimension* of a cube is n, the number of elementary intervals (degenerate or not) in the product. +A *dimension of a cube* :math:`C=I_1 \times ... \times I_n` is the number of non degenerate elementary +intervals in the product. A *boundary of a cube* :math:`C=I_1 \times \ldots \times I_n` is a chain obtained +in the following way: + +.. math:: + + \partial C = (\partial I_1 \times \ldots \times I_n) + (I_1 \times \partial I_2 \times \ldots \times I_n) + + \ldots + (I_1 \times I_2 \times \ldots \times \partial I_n). + +A *cubical complex* :math:`\mathcal{K}` is a collection of cubes closed under operation of taking boundary +(i.e. boundary of every cube from the collection is in the collection). A cube :math:`C` in cubical complex +:math:`\mathcal{K}` is *maximal* if it is not in a boundary of any other cube in :math:`\mathcal{K}`. A +*support* of a cube :math:`C` is the set in :math:`\mathbb{R}^n` occupied by :math:`C` (:math:`n` is the embedding +dimension of :math:`C`). + +Cubes may be equipped with a filtration values in which case we have filtered cubical complex. All the cubical +complexes considered in this implementation are filtered cubical complexes (although, the range of a filtration may +be a set of two elements). + +For further details and theory of cubical complexes, please consult :cite:`kaczynski2004computational` as well as the +following paper :cite:`peikert2012topological`. + +Data structure. +--------------- + +The implementation of Cubical complex provides a representation of complexes that occupy a rectangular region in +:math:`\mathbb{R}^n`. This extra assumption allows for a memory efficient way of storing cubical complexes in a form +of so called bitmaps. Let +:math:`R = [b_1,e_1] \times \ldots \times [b_n,e_n]`, for :math:`b_1,...b_n,e_1,...,e_n \in \mathbb{Z}`, +:math:`b_i \leq d_i` be the considered rectangular region and let :math:`\mathcal{K}` be a filtered +cubical complex having the rectangle :math:`R` as its support. Note that the structure of the coordinate system gives +a way a lexicographical ordering of cells of :math:`\mathcal{K}`. This ordering is a base of the presented +bitmap-based implementation. In this implementation, the whole cubical complex is stored as a vector of the values +of filtration. This, together with dimension of :math:`\mathcal{K}` and the sizes of :math:`\mathcal{K}` in all +directions, allows to determine, dimension, neighborhood, boundary and coboundary of every cube +:math:`C \in \mathcal{K}`. + +.. image:: + img/Cubical_complex_representation.png + :align: center + :alt: Cubical complex. + +Note that the cubical complex in the figure above is, in a natural way, a product of one dimensional cubical +complexes in :math:`\mathbb{R}`. The number of all cubes in each direction is equal :math:`2n+1`, where :math:`n` is +the number of maximal cubes in the considered direction. Let us consider a cube at the position :math:`k` in the +bitmap. +Knowing the sizes of the bitmap, by a series of modulo operation, we can determine which elementary intervals are +present in the product that gives the cube :math:`C`. In a similar way, we can compute boundary and the coboundary of +each cube. Further details can be found in the literature. + +Input Format. +------------- + +In the current implantation, filtration is given at the maximal cubes, and it is then extended by the lower star +filtration to all cubes. There are a number of constructors that can be used to construct cubical complex by users +who want to use the code directly. They can be found in the :doc:`cubical_complex_ref`. +Currently one input from a text file is used. It uses a format used already in +`Perseus software `_ by Vidit Nanda. +Below we are providing a description of the format. The first line contains a number d begin the dimension of the +bitmap (2 in the example below). Next d lines are the numbers of top dimensional cubes in each dimensions (3 and 3 +in the example below). Next, in lexicographical order, the filtration of top dimensional cubes is given (1 4 6 8 +20 4 7 6 5 in the example below). + +.. image:: + img/exampleBitmap.png + :align: center + :alt: Example of a input data. + +The input file for the following complex is: + +.. literalinclude:: cubicalcomplexdoc.txt + +.. centered:: cubicalcomplexdoc.txt + +.. testcode:: + + import gudhi + cubical_complex = gudhi.CubicalComplex(perseus_file='cubicalcomplexdoc.txt') + result_str = 'Cubical complex is of dimension ' + repr(cubical_complex.dimension()) + ' - ' + \ + repr(cubical_complex.num_simplices()) + ' simplices.' + print(result_str) + +the program output is: + +.. testoutput:: + + Cubical complex is of dimension 2 - 49 simplices. + +Periodic boundary conditions. +----------------------------- + +Often one would like to impose periodic boundary conditions to the cubical complex (cf. +:doc:`periodic_cubical_complex_ref`). +Let :math:`I_1\times ... \times I_n` be a box that is decomposed with a cubical complex :math:`\mathcal{K}`. +Imposing periodic boundary conditions in the direction i, means that the left and the right side of a complex +:math:`\mathcal{K}` are considered the same. In particular, if for a bitmap :math:`\mathcal{K}` periodic boundary +conditions are imposed in all directions, then complex :math:`\mathcal{K}` became n-dimensional torus. One can use +various constructors from the file Bitmap_cubical_complex_periodic_boundary_conditions_base.h to construct cubical +complex with periodic boundary conditions. One can also use Perseus style input files. To indicate periodic boundary +conditions in a given direction, then number of top dimensional cells in this direction have to be multiplied by -1. +For instance: + +.. literalinclude:: periodiccubicalcomplexdoc.txt + +.. centered:: periodiccubicalcomplexdoc.txt + +Indicate that we have imposed periodic boundary conditions in the direction x, but not in the direction y. + +.. testcode:: + + import gudhi + periodic_cc = gudhi.PeriodicCubicalComplex(perseus_file='periodiccubicalcomplexdoc.txt') + result_str = 'Periodic cubical complex is of dimension ' + repr(periodic_cc.dimension()) + ' - ' + \ + repr(periodic_cc.num_simplices()) + ' simplices.' + print(result_str) + +the program output is: + +.. testoutput:: + + Periodic cubical complex is of dimension 2 - 42 simplices. + +Examples. +--------- + +End user programs are available in cython/example/ folder. diff --git a/src/cython/doc/index.rst b/src/cython/doc/index.rst new file mode 100644 index 00000000..5245d69d --- /dev/null +++ b/src/cython/doc/index.rst @@ -0,0 +1,63 @@ +.. GUDHI documentation master file, created by + sphinx-quickstart on Thu Jun 30 09:55:51 2016. + You can adapt this file completely to your liking, but it should at least + contain the root `toctree` directive. + +GUDHI's documentation +##################### + +.. image:: img/Gudhi_banner.png + :align: center + +Introduction +************ + +The Gudhi library (Geometry Understanding in Higher Dimensions) is a generic +open source C++ library for Computational Topology and Topological Data +Analysis (`TDA `_). +The GUDHI library intends to help the development of new algorithmic solutions +in TDA and their transfer to applications. It provides robust, efficient, +flexible and easy to use implementations of state-of-the-art algorithms and +data structures. + +The current release of the GUDHI library includes: + +* Data structures to represent, construct and manipulate simplicial complexes. +* Algorithms to compute persistent homology and multi-field persistent homology. +* Simplication of simplicial complexes by edge contraction. + +All data-structures are generic and several of their aspects can be +parameterized via template classes. We refer to :cite:`gudhilibrary_ICMS14` +for a detailed description of the design of the library. + +Data structures +*************** + +Alpha complex +============= + +.. include:: alpha_complex_sum.rst + +Cubical complex +=============== + +.. include:: cubical_complex_sum.rst + +Simplex tree +============ + +.. include:: simplex_tree_sum.rst + +Witness complex +=============== + +.. include:: witness_complex_sum.rst + + +Toolbox +******* + +Persistence cohomology +====================== + +.. include:: persistent_cohomology_sum.rst diff --git a/src/cython/doc/make.bat b/src/cython/doc/make.bat new file mode 100644 index 00000000..656c0105 --- /dev/null +++ b/src/cython/doc/make.bat @@ -0,0 +1,242 @@ +@ECHO OFF + +REM Command file for Sphinx documentation + +if "%SPHINXBUILD%" == "" ( + set SPHINXBUILD=sphinx-build +) +set BUILDDIR=_build +set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% . +set I18NSPHINXOPTS=%SPHINXOPTS% . +if NOT "%PAPER%" == "" ( + set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS% + set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS% +) + +if "%1" == "" goto help + +if "%1" == "help" ( + :help + echo.Please use `make ^` where ^ is one of + echo. html to make standalone HTML files + echo. dirhtml to make HTML files named index.html in directories + echo. singlehtml to make a single large HTML file + echo. pickle to make pickle files + echo. json to make JSON files + echo. htmlhelp to make HTML files and a HTML help project + echo. qthelp to make HTML files and a qthelp project + echo. devhelp to make HTML files and a Devhelp project + echo. epub to make an epub + echo. latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter + echo. text to make text files + echo. man to make manual pages + echo. texinfo to make Texinfo files + echo. gettext to make PO message catalogs + echo. changes to make an overview over all changed/added/deprecated items + echo. xml to make Docutils-native XML files + echo. pseudoxml to make pseudoxml-XML files for display purposes + echo. linkcheck to check all external links for integrity + echo. doctest to run all doctests embedded in the documentation if enabled + goto end +) + +if "%1" == "clean" ( + for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i + del /q /s %BUILDDIR%\* + goto end +) + + +%SPHINXBUILD% 2> nul +if errorlevel 9009 ( + echo. + echo.The 'sphinx-build' command was not found. 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The XML files are in %BUILDDIR%/xml. + goto end +) + +if "%1" == "pseudoxml" ( + %SPHINXBUILD% -b pseudoxml %ALLSPHINXOPTS% %BUILDDIR%/pseudoxml + if errorlevel 1 exit /b 1 + echo. + echo.Build finished. The pseudo-XML files are in %BUILDDIR%/pseudoxml. + goto end +) + +:end diff --git a/src/cython/doc/periodic_cubical_complex_ref.rst b/src/cython/doc/periodic_cubical_complex_ref.rst new file mode 100644 index 00000000..c6190a1b --- /dev/null +++ b/src/cython/doc/periodic_cubical_complex_ref.rst @@ -0,0 +1,9 @@ +Periodic cubical complex reference manual +######################################### + +.. autoclass:: gudhi.PeriodicCubicalComplex + :members: + :undoc-members: + :show-inheritance: + + .. automethod:: gudhi.PeriodicCubicalComplex.__init__ diff --git a/src/cython/doc/persistent_cohomology_sum.rst b/src/cython/doc/persistent_cohomology_sum.rst new file mode 100644 index 00000000..081399a5 --- /dev/null +++ b/src/cython/doc/persistent_cohomology_sum.rst @@ -0,0 +1,28 @@ +===================================== ===================================== ===================================== +:Author: Clément Maria :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++---------------------------------------------+----------------------------------------------------------------------+ +| .. image:: | The theory of homology consists in attaching to a topological space | +| img/3DTorus_poch.png | a sequence of (homology) groups, capturing global topological | +| | features like connected components, holes, cavities, etc. Persistent | +| | homology studies the evolution -- birth, life and death -- of these | +| | features when the topological space is changing. Consequently, the | +| | theory is essentially composed of three elements: topological spaces,| +| | their homology groups and an evolution scheme. | +| | | +| | Computation of persistent cohomology using the algorithm of | +| | :cite:`DBLP:journals/dcg/SilvaMV11` and | +| | :cite:`DBLP:journals/corr/abs-1208-5018` and the Compressed | +| | Annotation Matrix implementation of | +| | :cite:`DBLP:conf/esa/BoissonnatDM13`. | +| | | ++---------------------------------------------+----------------------------------------------------------------------+ +| :doc:`persistent_cohomology_user` | Please refer to each data structure that contains persistence | +| | feature for reference: | +| | | +| | * :doc:`alpha_complex_ref` | +| | * :doc:`cubical_complex_ref` | +| | * :doc:`simplex_tree_ref` | +| | * :doc:`witness_complex_ref` | ++---------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/doc/persistent_cohomology_user.rst b/src/cython/doc/persistent_cohomology_user.rst new file mode 100644 index 00000000..33b19ce2 --- /dev/null +++ b/src/cython/doc/persistent_cohomology_user.rst @@ -0,0 +1,104 @@ +================================= +Persistent cohomology user manual +================================= +Definition +---------- +===================================== ===================================== ===================================== +:Author: Clément Maria :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++---------------------------------------------+----------------------------------------------------------------------+ +| :doc:`persistent_cohomology_user` | Please refer to each data structure that contains persistence | +| | feature for reference: | +| | | +| | * :doc:`alpha_complex_ref` | +| | * :doc:`cubical_complex_ref` | +| | * :doc:`simplex_tree_ref` | +| | * :doc:`witness_complex_ref` | ++---------------------------------------------+----------------------------------------------------------------------+ + + +Computation of persistent cohomology using the algorithm of :cite:`DBLP:journals/dcg/SilvaMV11` and +:cite:`DBLP:journals/corr/abs-1208-5018` and the Compressed Annotation Matrix implementation of +:cite:`DBLP:conf/esa/BoissonnatDM13`. + +The theory of homology consists in attaching to a topological space a sequence of (homology) groups, capturing global +topological features like connected components, holes, cavities, etc. Persistent homology studies the evolution -- +birth, life and death -- of these features when the topological space is changing. Consequently, the theory is +essentially composed of three elements: + +* topological spaces +* their homology groups +* an evolution scheme. + +Topological Spaces +------------------ + +Topological spaces are represented by simplicial complexes. +Let :math:`V = \{1, \cdots ,|V|\}` be a set of *vertices*. +A *simplex* :math:`\sigma` is a subset of vertices :math:`\sigma \subseteq V`. +A *simplicial complex* :math:`\mathbf{K}` on :math:`V` is a collection of simplices :math:`\{\sigma\}`, +:math:`\sigma \subseteq V`, such that :math:`\tau \subseteq \sigma \in \mathbf{K} \Rightarrow \tau \in \mathbf{K}`. +The dimension :math:`n=|\sigma|-1` of :math:`\sigma` is its number of elements minus 1. +A *filtration* of a simplicial complex is a function :math:`f:\mathbf{K} \rightarrow \mathbb{R}` satisfying +:math:`f(\tau)\leq f(\sigma)` whenever :math:`\tau \subseteq \sigma`. + +Homology +-------- + +For a ring :math:`\mathcal{R}`, the group of *n-chains*, denoted :math:`\mathbf{C}_n(\mathbf{K},\mathcal{R})`, of +:math:`\mathbf{K}` is the group of formal sums of n-simplices with :math:`\mathcal{R}` coefficients. The +*boundary operator* is a linear operator +:math:`\partial_n: \mathbf{C}_n(\mathbf{K},\mathcal{R}) \rightarrow \mathbf{C}_{n-1}(\mathbf{K},\mathcal{R})` +such that :math:`\partial_n \sigma = \partial_n [v_0, \cdots , v_n] = \sum_{i=0}^n (-1)^{i}[v_0,\cdots ,\widehat{v_i}, \cdots,v_n]`, +where :math:`\widehat{v_i}` means :math:`v_i` is omitted from the list. The chain groups form a sequence: + +.. math:: + + \cdots \ \ \mathbf{C}_n(\mathbf{K},\mathcal{R}) \xrightarrow{\ \partial_n\ } + \mathbf{C}_{n-1}(\mathbf{K},\mathcal{R}) \xrightarrow{\partial_{n-1}} \cdots \xrightarrow{\ \partial_2 \ } + \mathbf{C}_1(\mathbf{K},\mathcal{R}) \xrightarrow{\ \partial_1 \ } \mathbf{C}_0(\mathbf{K},\mathcal{R}) + +of finitely many groups :math:`\mathbf{C}_n(\mathbf{K},\mathcal{R})` and homomorphisms :math:`\partial_n`, indexed by +the dimension :math:`n \geq 0`. The boundary operators satisfy the property :math:`\partial_n \circ \partial_{n+1}=0` +for every :math:`n > 0` and we define the homology groups: + +.. math:: + + \mathbf{H}_n(\mathbf{K},\mathcal{R}) = \ker \partial_n / \mathrm{im} \ \partial_{n+1} + +We refer to :cite:`Munkres-elementsalgtop1984` for an introduction to homology +theory and to :cite:`DBLP:books/daglib/0025666` for an introduction to persistent homology. + +Indexing Scheme +--------------- + +"Changing" a simplicial complex consists in applying a simplicial map. An *indexing scheme* is a directed graph +together with a traversal order, such that two consecutive nodes in the graph are connected by an arrow (either forward +or backward). +The nodes represent simplicial complexes and the directed edges simplicial maps. + +From the computational point of view, there are two types of indexing schemes of interest in persistent homology: + +* linear ones + :math:`\bullet \longrightarrow \bullet \longrightarrow \cdots \longrightarrow \bullet \longrightarrow \bullet` + in persistent homology :cite:`DBLP:journals/dcg/ZomorodianC05`, +* zigzag ones + :math:`\bullet \longrightarrow \bullet \longleftarrow \cdots \longrightarrow \bullet \longleftarrow \bullet` + in zigzag persistent homology :cite:`DBLP:journals/focm/CarlssonS10`. + +These indexing schemes have a natural left-to-right traversal order, and we describe them with ranges and iterators. +In the current release of the Gudhi library, only the linear case is implemented. + +In the following, we consider the case where the indexing scheme is induced by a filtration. + +Ordering the simplices by increasing filtration values (breaking ties so as a simplex appears after its subsimplices of +same filtration value) provides an indexing scheme. + +Examples +-------- + +We provide several example files: run these examples with -h for details on their use. + +.. todo:: + examples for persistence diff --git a/src/cython/doc/simplex_tree_ref.rst b/src/cython/doc/simplex_tree_ref.rst new file mode 100644 index 00000000..6d196843 --- /dev/null +++ b/src/cython/doc/simplex_tree_ref.rst @@ -0,0 +1,10 @@ +============================= +Simplex tree reference manual +============================= + +.. autoclass:: gudhi.SimplexTree + :members: + :undoc-members: + :show-inheritance: + + .. automethod:: gudhi.SimplexTree.__init__ diff --git a/src/cython/doc/simplex_tree_sum.rst b/src/cython/doc/simplex_tree_sum.rst new file mode 100644 index 00000000..ffdb2cf4 --- /dev/null +++ b/src/cython/doc/simplex_tree_sum.rst @@ -0,0 +1,13 @@ +===================================== ===================================== ===================================== +:Author: Clément Maria :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++-------------------------------------------+----------------------------------------------------------------------+ +| .. image:: | The simplex tree is an efficient and flexible data structure for | +| img/Simplex_tree_representation.png | representing general (filtered) simplicial complexes. | +| | | +| | The data structure is described in | +| | :cite:`boissonnatmariasimplextreealgorithmica` | ++-------------------------------------------+----------------------------------------------------------------------+ +| :doc:`simplex_tree_user` | :doc:`simplex_tree_ref` | ++-------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/doc/simplex_tree_user.rst b/src/cython/doc/simplex_tree_user.rst new file mode 100644 index 00000000..3a00f1ac --- /dev/null +++ b/src/cython/doc/simplex_tree_user.rst @@ -0,0 +1,67 @@ +======================== +Simplex tree user manual +======================== +Definition +---------- + +.. include:: simplex_tree_sum.rst + +A simplicial complex :math:`\mathbf{K}` on a set of vertices :math:`V = \{1, \cdots ,|V|\}` is a collection of +simplices :math:`\{\sigma\}`, :math:`\sigma \subseteq V` such that +:math:`\tau \subseteq \sigma \in \mathbf{K} \rightarrow \tau \in \mathbf{K}`. The dimension :math:`n=|\sigma|-1` of +:math:`\sigma` is its number of elements minus `1`. + +A filtration of a simplicial complex is a function :math:`f:\mathbf{K} \rightarrow \mathbb{R}` satisfying +:math:`f(\tau)\leq f(\sigma)` whenever :math:`\tau \subseteq \sigma`. Ordering the simplices by increasing filtration +values (breaking ties so as a simplex appears after its subsimplices of same filtration value) provides an indexing +scheme. + + +Implementation +-------------- + +There are two implementation of complexes. The first on is the Simplex_tree data structure. +The simplex tree is an efficient and flexible data structure for representing general (filtered) simplicial complexes. +The data structure is described in :cite`boissonnatmariasimplextreealgorithmica`. + +The second one is the Hasse_complex. The Hasse complex is a data structure representing explicitly all co-dimension 1 +incidence relations in a complex. It is consequently faster when accessing the boundary of a simplex, but is less +compact and harder to construct from scratch. + +Example +------- + +.. testcode:: + + import gudhi + st = gudhi.SimplexTree() + if st.insert([0, 1]): + print("[0, 1] inserted") + if st.insert([0, 1, 2], filtration=4.0): + print("[0, 1, 2] inserted") + if st.find([0, 1]): + print("[0, 1] found") + print("num_vertices=", st.num_vertices()) + print("num_simplices=", st.num_simplices()) + print("skeleton_tree(2) =") + for sk_value in st.get_skeleton_tree(2): + print(sk_value) + + +The output is: + +.. testoutput:: + + [0, 1] inserted + [0, 1, 2] inserted + [0, 1] found + ('num_vertices=', 3) + ('num_simplices=', 7) + skeleton_tree(2) = + ([0, 1, 2], 4.0) + ([0, 1], 0.0) + ([0, 2], 4.0) + ([0], 0.0) + ([1, 2], 4.0) + ([1], 0.0) + ([2], 4.0) diff --git a/src/cython/doc/witness_complex_ref.rst b/src/cython/doc/witness_complex_ref.rst new file mode 100644 index 00000000..c78760cb --- /dev/null +++ b/src/cython/doc/witness_complex_ref.rst @@ -0,0 +1,10 @@ +================================ +Witness complex reference manual +================================ + +.. autoclass:: gudhi.WitnessComplex + :members: + :undoc-members: + :show-inheritance: + + .. automethod:: gudhi.WitnessComplex.__init__ diff --git a/src/cython/doc/witness_complex_sum.rst b/src/cython/doc/witness_complex_sum.rst new file mode 100644 index 00000000..0d65d420 --- /dev/null +++ b/src/cython/doc/witness_complex_sum.rst @@ -0,0 +1,25 @@ +===================================== ===================================== ===================================== +:Author: Siargey Kachanovich :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 +===================================== ===================================== ===================================== + ++---------------------------------------------+----------------------------------------------------------------------+ +| .. image:: | Witness complex :math:`Wit(W,L)` is a simplicial complex defined on | +| img/Witness_complex_representation.png | two sets of points in :math:`\mathbb{R}^D`:Wit(W,L)` is a simplicial | +| | complex defined on two sets of points in :math:`\mathbb{R}^D`: | +| | | +| | * :math:`W` set of **witnesses** and | +| | * :math:`L \subseteq W` set of **landmarks**. | +| | | +| | The simplices are based on landmarks and a simplex belongs to the | +| | witness complex if and only if it is witnessed, that is: | +| | | +| | :math:`\sigma \subset L` is witnessed if there exists a point | +| | :math:`w \in W` such that w is closer to the vertices of | +| | :math:`\sigma` than other points in :math:`L` and all of its faces | +| | are witnessed as well. | +| | | +| | The data structure is described in | +| | :cite:`boissonnatmariasimplextreealgorithmica`. | ++---------------------------------------------+----------------------------------------------------------------------+ +| :doc:`witness_complex_user` | :doc:`witness_complex_ref` | ++---------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/doc/witness_complex_user.rst b/src/cython/doc/witness_complex_user.rst new file mode 100644 index 00000000..604c7357 --- /dev/null +++ b/src/cython/doc/witness_complex_user.rst @@ -0,0 +1,31 @@ +=========================== +Witness complex user manual +=========================== +Definition +---------- + +.. include:: witness_complex_sum.rst + +Implementation +-------------- + +The principal class of this module is Gudhi::Witness_complex. + +In both cases, the constructor for this class takes a {witness}x{closest_landmarks} table, where each row represents a +witness and consists of landmarks sorted by distance to this witness. + +.. todo:: + This table can be constructed by two additional classes Landmark_choice_by_furthest_point and + Landmark_choice_by_random_point also included in the module. + +.. figure:: + img/bench_Cy8.png + :align: center + + Running time as function on number of landmarks. + +.. figure:: + img/bench_sphere.png + :align: center + + Running time as function on number of witnesses for |L|=300. diff --git a/src/cython/gudhi.pyx.in b/src/cython/gudhi.pyx.in index 5f7809d6..1b8a669b 100644 --- a/src/cython/gudhi.pyx.in +++ b/src/cython/gudhi.pyx.in @@ -24,11 +24,11 @@ __author__ = "Vincent Rouvreau" __copyright__ = "Copyright (C) 2016 INRIA Saclay (France)" __license__ = "GPL v3" -include "src/cython/simplex_tree.pyx" -include "src/cython/mini_simplex_tree.pyx" -include "src/cython/rips_complex.pyx" -include "src/cython/cubical_complex.pyx" -include "src/cython/periodic_cubical_complex.pyx" -include "src/cython/persistence_graphical_tools.py" -include "src/cython/witness_complex.pyx" +include "cython/simplex_tree.pyx" +include "cython/mini_simplex_tree.pyx" +include "cython/rips_complex.pyx" +include "cython/cubical_complex.pyx" +include "cython/periodic_cubical_complex.pyx" +include "cython/persistence_graphical_tools.py" +include "cython/witness_complex.pyx" @GUDHI_CYTHON_ALPHA_COMPLEX@ diff --git a/src/cython/include/Alpha_complex_interface.h b/src/cython/include/Alpha_complex_interface.h new file mode 100644 index 00000000..e2e6d100 --- /dev/null +++ b/src/cython/include/Alpha_complex_interface.h @@ -0,0 +1,142 @@ +/* This file is part of the Gudhi Library. The Gudhi library + * (Geometric Understanding in Higher Dimensions) is a generic C++ + * library for computational topology. + * + * Author(s): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * This program is free software: you can redistribute it and/or modify + * it under the terms of the GNU General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program. If not, see . + */ + +#ifndef ALPHA_COMPLEX_INTERFACE_H +#define ALPHA_COMPLEX_INTERFACE_H + +#include +#include + +#include +#include // std::pair +#include + +namespace Gudhi { + +namespace alpha_complex { + +class Alpha_complex_interface : public Alpha_complex< CGAL::Epick_d< CGAL::Dynamic_dimension_tag > > { + using Alpha_complex = Alpha_complex< CGAL::Epick_d< CGAL::Dynamic_dimension_tag > > ; + typedef typename Alpha_complex::Simplex_handle Simplex_handle; + typedef typename std::pair Insertion_result; + using Simplex = std::vector; + using Filtered_complex = std::pair; + using Complex_tree = std::vector; + using Point_d = Alpha_complex::Point_d; + + public: + + Alpha_complex_interface(std::vector>&points, double max_alpha_square) + : Alpha_complex(points, max_alpha_square) { + } + + // bool from_file is a workaround fro cython to find the correct signature + Alpha_complex_interface(const std::string& off_file, double max_alpha_square, bool from_file) + : Alpha_complex(off_file, max_alpha_square) { + } + + bool find_simplex(const Simplex& vh) { + return (Alpha_complex::find(vh) != Alpha_complex::null_simplex()); + } + + bool insert_simplex_and_subfaces(const Simplex& complex, Filtration_value filtration = 0) { + Insertion_result result = Alpha_complex::insert_simplex_and_subfaces(complex, filtration); + return (result.second); + } + + Filtration_value simplex_filtration(const Simplex& complex) { + return Alpha_complex::filtration(Alpha_complex::find(complex)); + } + + void remove_maximal_simplex(const Simplex& complex) { + return Alpha_complex::remove_maximal_simplex(Alpha_complex::find(complex)); + } + + Complex_tree get_filtered_tree() { + Complex_tree filtered_tree; + for (auto f_simplex : Alpha_complex::filtration_simplex_range()) { + Simplex simplex; + for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + filtered_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); + } + return filtered_tree; + + } + + Complex_tree get_skeleton_tree(int dimension) { + Complex_tree skeleton_tree; + for (auto f_simplex : Alpha_complex::skeleton_simplex_range(dimension)) { + Simplex simplex; + for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + skeleton_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); + } + return skeleton_tree; + } + + Complex_tree get_star_tree(const Simplex& complex) { + Complex_tree star_tree; + for (auto f_simplex : Alpha_complex::star_simplex_range(Alpha_complex::find(complex))) { + Simplex simplex; + for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + star_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); + } + return star_tree; + } + + Complex_tree get_coface_tree(const Simplex& complex, int dimension) { + Complex_tree coface_tree; + for (auto f_simplex : Alpha_complex::cofaces_simplex_range(Alpha_complex::find(complex), dimension)) { + Simplex simplex; + for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + coface_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); + } + return coface_tree; + } + + std::vector get_point(int vh) { + std::vector vd; + try { + Point_d ph = Alpha_complex::get_point(vh); + for (auto coord = ph.cartesian_begin(); coord < ph.cartesian_end(); coord++) + vd.push_back(*coord); + } catch (std::out_of_range outofrange) { + // std::out_of_range is thrown in case not found. Other exceptions must be re-thrown + } + return vd; + } + +}; + +} // namespace alpha_complex + +} // namespace Gudhi + +#endif // ALPHA_COMPLEX_INTERFACE_H + diff --git a/src/cython/include/Cubical_complex_interface.h b/src/cython/include/Cubical_complex_interface.h new file mode 100644 index 00000000..5d17ff6b --- /dev/null +++ b/src/cython/include/Cubical_complex_interface.h @@ -0,0 +1,58 @@ +/* This file is part of the Gudhi Library. The Gudhi library + * (Geometric Understanding in Higher Dimensions) is a generic C++ + * library for computational topology. + * + * Author(s): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * This program is free software: you can redistribute it and/or modify + * it under the terms of the GNU General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program. If not, see . + */ + +#ifndef CUBICAL_COMPLEX_INTERFACE_H +#define CUBICAL_COMPLEX_INTERFACE_H + +#include +#include +#include + +#include +#include // std::pair +#include + +namespace Gudhi { + +namespace cubical_complex { + +template> +class Cubical_complex_interface : public Bitmap_cubical_complex { + public: + + Cubical_complex_interface(const std::vector& dimensions, + const std::vector& top_dimensional_cells) + : Bitmap_cubical_complex(dimensions, top_dimensional_cells) { + } + + Cubical_complex_interface(const std::string& perseus_file) + : Bitmap_cubical_complex(perseus_file.c_str()) { + } + +}; + +} // namespace cubical_complex + +} // namespace Gudhi + +#endif // CUBICAL_COMPLEX_INTERFACE_H + diff --git a/src/cython/include/Persistent_cohomology_interface.h b/src/cython/include/Persistent_cohomology_interface.h new file mode 100644 index 00000000..58421799 --- /dev/null +++ b/src/cython/include/Persistent_cohomology_interface.h @@ -0,0 +1,90 @@ +/* This file is part of the Gudhi Library. The Gudhi library + * (Geometric Understanding in Higher Dimensions) is a generic C++ + * library for computational topology. + * + * Author(s): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * This program is free software: you can redistribute it and/or modify + * it under the terms of the GNU General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program. If not, see . + */ + +#ifndef PERSISTENT_COHOMOLOGY_INTERFACE_H +#define PERSISTENT_COHOMOLOGY_INTERFACE_H + +#include + +#include +#include // for std::pair + +namespace Gudhi { + +template +class Persistent_cohomology_interface : public +persistent_cohomology::Persistent_cohomology { + private: + /* + * Compare two intervals by dimension, then by length. + */ + struct cmp_intervals_by_dim_then_length { + + explicit cmp_intervals_by_dim_then_length(FilteredComplex * sc) + : sc_(sc) { } + + template + bool operator()(const Persistent_interval & p1, const Persistent_interval & p2) { + if (sc_->dimension(get < 0 > (p1)) == sc_->dimension(get < 0 > (p2))) + return (sc_->filtration(get < 1 > (p1)) - sc_->filtration(get < 0 > (p1)) + > sc_->filtration(get < 1 > (p2)) - sc_->filtration(get < 0 > (p2))); + else + return (sc_->dimension(get < 0 > (p1)) > sc_->dimension(get < 0 > (p2))); + } + FilteredComplex* sc_; + }; + + public: + + Persistent_cohomology_interface(FilteredComplex* stptr) + : persistent_cohomology::Persistent_cohomology(*stptr), + stptr_(stptr) { } + + std::vector>> get_persistence(int homology_coeff_field, double min_persistence) { + persistent_cohomology::Persistent_cohomology::init_coefficients(homology_coeff_field); + persistent_cohomology::Persistent_cohomology::compute_persistent_cohomology(min_persistence); + + // Custom sort and output persistence + cmp_intervals_by_dim_then_length cmp(stptr_); + auto persistent_pairs = persistent_cohomology::Persistent_cohomology::get_persistent_pairs(); + std::sort(std::begin(persistent_pairs), std::end(persistent_pairs), cmp); + + std::vector>> persistence; + for (auto pair : persistent_pairs) { + persistence.push_back(std::make_pair(stptr_->dimension(get<0>(pair)), + std::make_pair(stptr_->filtration(get<0>(pair)), + stptr_->filtration(get<1>(pair))))); + } + return persistence; + + } + + private: + // A copy + FilteredComplex* stptr_; + +}; + +} // namespace Gudhi + +#endif // PERSISTENT_COHOMOLOGY_INTERFACE_H + diff --git a/src/cython/include/Simplex_tree_interface.h b/src/cython/include/Simplex_tree_interface.h new file mode 100644 index 00000000..9aee630b --- /dev/null +++ b/src/cython/include/Simplex_tree_interface.h @@ -0,0 +1,132 @@ +/* This file is part of the Gudhi Library. The Gudhi library + * (Geometric Understanding in Higher Dimensions) is a generic C++ + * library for computational topology. + * + * Author(s): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * This program is free software: you can redistribute it and/or modify + * it under the terms of the GNU General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program. If not, see . + */ + +#ifndef SIMPLEX_TREE_INTERFACE_H +#define SIMPLEX_TREE_INTERFACE_H + +#include +#include +#include + +#include +#include // std::pair +#include + +namespace Gudhi { + +template +class Simplex_tree_interface : public Simplex_tree { + typedef typename Simplex_tree::Simplex_handle Simplex_handle; + typedef typename std::pair Insertion_result; + using Simplex = std::vector; + using Filtered_complex = std::pair; + using Complex_tree = std::vector; + + public: + + bool find_simplex(const Simplex& vh) { + return (Simplex_tree::find(vh) != Simplex_tree::null_simplex()); + } + + bool insert_simplex_and_subfaces(const Simplex& complex, Filtration_value filtration = 0) { + Insertion_result result = Simplex_tree::insert_simplex_and_subfaces(complex, filtration); + return (result.second); + } + + Filtration_value simplex_filtration(const Simplex& complex) { + return Simplex_tree::filtration(Simplex_tree::find(complex)); + } + + void remove_maximal_simplex(const Simplex& complex) { + return Simplex_tree::remove_maximal_simplex(Simplex_tree::find(complex)); + } + + Complex_tree get_filtered_tree() { + Complex_tree filtered_tree; + for (auto f_simplex : Simplex_tree::filtration_simplex_range()) { + Simplex simplex; + for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + filtered_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); + } + return filtered_tree; + + } + + Complex_tree get_skeleton_tree(int dimension) { + Complex_tree skeleton_tree; + for (auto f_simplex : Simplex_tree::skeleton_simplex_range(dimension)) { + Simplex simplex; + for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + skeleton_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); + } + return skeleton_tree; + } + + Complex_tree get_star_tree(const Simplex& complex) { + Complex_tree star_tree; + for (auto f_simplex : Simplex_tree::star_simplex_range(Simplex_tree::find(complex))) { + Simplex simplex; + for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + star_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); + } + return star_tree; + } + + Complex_tree get_coface_tree(const Simplex& complex, int dimension) { + Complex_tree coface_tree; + for (auto f_simplex : Simplex_tree::cofaces_simplex_range(Simplex_tree::find(complex), dimension)) { + Simplex simplex; + for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + coface_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); + } + return coface_tree; + } + + void graph_expansion(std::vector>&points, int max_dimension, double max_edge_length) { + Graph_t prox_graph = compute_proximity_graph(points, max_edge_length, euclidean_distance>); + Simplex_tree::insert_graph(prox_graph); + Simplex_tree::expansion(max_dimension); + Simplex_tree::initialize_filtration(); + } + +}; + +struct Simplex_tree_options_mini : Simplex_tree_options_full_featured { + // Not doing persistence, so we don't need those + static const bool store_key = true; + static const bool store_filtration = false; + // I have few vertices + typedef short Vertex_handle; +}; + +} // namespace Gudhi + +#endif // SIMPLEX_TREE_INTERFACE_H + diff --git a/src/cython/include/Witness_complex_interface.h b/src/cython/include/Witness_complex_interface.h new file mode 100644 index 00000000..bdfea91f --- /dev/null +++ b/src/cython/include/Witness_complex_interface.h @@ -0,0 +1,187 @@ +/* This file is part of the Gudhi Library. The Gudhi library + * (Geometric Understanding in Higher Dimensions) is a generic C++ + * library for computational topology. + * + * Author(s): Vincent Rouvreau + * + * Copyright (C) 2016 INRIA + * + * This program is free software: you can redistribute it and/or modify + * it under the terms of the GNU General Public License as published by + * the Free Software Foundation, either version 3 of the License, or + * (at your option) any later version. + * + * This program is distributed in the hope that it will be useful, + * but WITHOUT ANY WARRANTY; without even the implied warranty of + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the + * GNU General Public License for more details. + * + * You should have received a copy of the GNU General Public License + * along with this program. If not, see . + */ + +#ifndef WITNESS_COMPLEX_INTERFACE_H +#define WITNESS_COMPLEX_INTERFACE_H + +#include +#include +#include + +#include "Persistent_cohomology_interface.h" + +#include +#include // std::pair +#include + +namespace Gudhi { + +namespace witness_complex { + +class Witness_complex_interface { + typedef typename Simplex_tree<>::Simplex_handle Simplex_handle; + typedef typename std::pair Insertion_result; + using Simplex = std::vector; + using Filtered_complex = std::pair; + using Complex_tree = std::vector; + + public: + Witness_complex_interface(std::vector>&points, int number_of_landmarks) + : pcoh_(nullptr) { + std::vector > knn; + + Gudhi::witness_complex::landmark_choice_by_furthest_point(points, number_of_landmarks, knn); + Gudhi::witness_complex::witness_complex(knn, number_of_landmarks, points[0].size(), simplex_tree_); + + } + + bool find_simplex(const Simplex& vh) { + return (simplex_tree_.find(vh) != simplex_tree_.null_simplex()); + } + + bool insert_simplex_and_subfaces(const Simplex& complex, Filtration_value filtration = 0) { + Insertion_result result = simplex_tree_.insert_simplex_and_subfaces(complex, filtration); + return (result.second); + } + + Filtration_value simplex_filtration(const Simplex& complex) { + return simplex_tree_.filtration(simplex_tree_.find(complex)); + } + + void remove_maximal_simplex(const Simplex& complex) { + return simplex_tree_.remove_maximal_simplex(simplex_tree_.find(complex)); + } + + Complex_tree get_filtered_tree() { + Complex_tree filtered_tree; + for (auto f_simplex : simplex_tree_.filtration_simplex_range()) { + Simplex simplex; + for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + filtered_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); + } + return filtered_tree; + + } + + Complex_tree get_skeleton_tree(int dimension) { + Complex_tree skeleton_tree; + for (auto f_simplex : simplex_tree_.skeleton_simplex_range(dimension)) { + Simplex simplex; + for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + skeleton_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); + } + return skeleton_tree; + } + + Complex_tree get_star_tree(const Simplex& complex) { + Complex_tree star_tree; + for (auto f_simplex : simplex_tree_.star_simplex_range(simplex_tree_.find(complex))) { + Simplex simplex; + for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + star_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); + } + return star_tree; + } + + Complex_tree get_coface_tree(const Simplex& complex, int dimension) { + Complex_tree coface_tree; + for (auto f_simplex : simplex_tree_.cofaces_simplex_range(simplex_tree_.find(complex), dimension)) { + Simplex simplex; + for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { + simplex.insert(simplex.begin(), vertex); + } + coface_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); + } + return coface_tree; + } + + // Specific to Witness complex because no inheritance + Filtration_value filtration() const { + return simplex_tree_.filtration(); + } + + void set_filtration(Filtration_value fil) { + simplex_tree_.set_filtration(fil); + } + + void initialize_filtration() { + simplex_tree_.initialize_filtration(); + } + + size_t num_vertices() const { + return simplex_tree_.num_vertices(); + } + + size_t num_simplices() { + return simplex_tree_.num_simplices(); + } + + int dimension() const { + return simplex_tree_.dimension(); + } + + void set_dimension(int dimension) { + simplex_tree_.set_dimension(dimension); + } + + std::vector>> get_persistence(int homology_coeff_field, double min_persistence) { + if (pcoh_ != nullptr) { + delete pcoh_; + } + pcoh_ = new Persistent_cohomology_interface>(&simplex_tree_); + return pcoh_->get_persistence(homology_coeff_field, min_persistence); + } + + std::vector get_betti_numbers() const { + if (pcoh_ != nullptr) { + return pcoh_->betti_numbers(); + } + std::vector betti_numbers; + return betti_numbers; + } + + std::vector get_persistent_betti_numbers(Filtration_value from, Filtration_value to) const { + if (pcoh_ != nullptr) { + return pcoh_->persistent_betti_numbers(from, to); + } + std::vector persistent_betti_numbers; + return persistent_betti_numbers; + } + + private: + Simplex_tree<> simplex_tree_; + Persistent_cohomology_interface>* pcoh_; + +}; + +} // namespace witness_complex + +} // namespace Gudhi + +#endif // WITNESS_COMPLEX_INTERFACE_H + diff --git a/src/cython/src/cython/alpha_complex.pyx b/src/cython/src/cython/alpha_complex.pyx deleted file mode 100644 index 44da8c9d..00000000 --- a/src/cython/src/cython/alpha_complex.pyx +++ /dev/null @@ -1,398 +0,0 @@ -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 - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__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::alphacomplex::Alpha_complex_interface": - Alpha_complex_interface(vector[vector[double]] points, double max_alpha_square) - # bool from_file is a workaround fro cython to find the correct signature - Alpha_complex_interface(string off_file, double max_alpha_square, bool from_file) - double filtration() - double simplex_filtration(vector[int] simplex) - void set_filtration(double filtration) - void initialize_filtration() - int num_vertices() - int num_simplices() - void set_dimension(int dimension) - int dimension() - bint find_simplex(vector[int] simplex) - bint insert_simplex_and_subfaces(vector[int] simplex, - double filtration) - vector[pair[vector[int], double]] get_filtered_tree() - vector[pair[vector[int], double]] get_skeleton_tree(int dimension) - vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) - vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, - int dimension) - void remove_maximal_simplex(vector[int] simplex) - vector[double] get_point(int vertex) - -cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": - cdef cppclass Alpha_complex_persistence_interface "Gudhi::Persistent_cohomology_interface >>": - Alpha_complex_persistence_interface(Alpha_complex_interface * st) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] betti_numbers() - vector[int] persistent_betti_numbers(double from_value, double to_value) - -# AlphaComplex python interface -cdef class AlphaComplex: - """AlphaComplex is a simplicial complex constructed from the finite cells - of a Delaunay Triangulation. - - 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. - - .. note:: - - When Alpha_complex is constructed with an infinite value of alpha, the - complex is a Delaunay complex. - - """ - - cdef Alpha_complex_interface * thisptr - - cdef Alpha_complex_persistence_interface * pcohptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, points=None, off_file='', max_alpha_square=float('inf')): - """AlphaComplex constructor. - - :param points: A list of points in d-Dimension. - :type points: list of list of double - - Or - - :param off_file: An OFF file style name. - :type off_file: string - - :param max_alpha_square: Maximum Alpha square value. Default is :math:`\infty` - :type max_alpha_square: double - """ - - # The real cython constructor - def __cinit__(self, points=[], off_file='', max_alpha_square=float('inf')): - if off_file is not '': - if os.path.isfile(off_file): - self.thisptr = new Alpha_complex_interface(off_file, - max_alpha_square, True) - else: - print("file " + off_file + " not found.") - else: - self.thisptr = new Alpha_complex_interface(points, - max_alpha_square) - - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - if self.pcohptr != NULL: - del self.pcohptr - - def __is_defined(self): - """Returns true if AlphaComplex pointer is not NULL. - """ - return self.thisptr != NULL - - def __is_persistence_defined(self): - """Returns true if Persistence pointer is not NULL. - """ - return self.pcohptr != NULL - - def get_filtration(self): - """This function returns the main simplicial complex filtration value. - - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.filtration() - - def filtration(self, simplex): - """This function returns the simplicial complex filtration value for a - given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.simplex_filtration(simplex) - - def set_filtration(self, filtration): - """This function sets the main simplicial complex filtration value. - - :param filtration: The filtration value. - :type filtration: float. - """ - self.thisptr.set_filtration( filtration) - - def initialize_filtration(self): - """This function initializes and sorts the simplicial complex - filtration vector. - - .. note:: - - This function must be launched before persistence, betti_numbers, - persistent_betti_numbers or get_filtered_tree after inserting or - removing simplices. - """ - self.thisptr.initialize_filtration() - - def num_vertices(self): - """This function returns the number of vertices of the simplicial - complex. - - :returns: int -- the simplicial complex number of vertices. - """ - return self.thisptr.num_vertices() - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def set_dimension(self, dimension): - """This function sets the dimension of the simplicial complex. - - :param dimension: The new dimension value. - :type dimension: int. - """ - self.thisptr.set_dimension(dimension) - - def find(self, simplex): - """This function returns if the N-simplex was found in the simplicial - complex or not. - - :param simplex: The N-simplex to find, represented by a list of vertex. - :type simplex: list of int. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.find_simplex(complex) - - def insert(self, simplex, filtration=0.0): - """This function inserts the given N-simplex with the given filtration - value (default value is '0.0'). - - :param simplex: The N-simplex to insert, represented by a list of - vertex. - :type simplex: list of int. - :param filtration: The filtration value of the simplex. - :type filtration: float. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.insert_simplex_and_subfaces(complex, - filtration) - - def get_filtered_tree(self): - """This function returns the tree sorted by increasing filtration - values. - - :returns: list of tuples(simplex, filtration) -- the tree sorted by - increasing filtration values. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_filtered_tree() - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_skeleton_tree(self, dimension): - """This function returns the tree skeleton of a maximum given - dimension. - - :param dimension: The skeleton dimension value. - :type dimension: int. - :returns: list of tuples(simplex, filtration) -- the skeleton tree - of a maximum dimension. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_skeleton_tree(dimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_star_tree(self, simplex): - """This function returns the star tree of a given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: list of tuples(simplex, filtration) -- the star tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_star_tree(complex) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_coface_tree(self, simplex, codimension): - """This function returns the coface tree of a given N-simplex with a - given codimension. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :param codimension: The codimension. If codimension = 0, all cofaces - are returned (equivalent of get_star_tree function) - :type codimension: int. - :returns: list of tuples(simplex, filtration) -- the coface tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_coface_tree(complex, codimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def remove_maximal_simplex(self, simplex): - """This function removes a given maximal N-simplex from the simplicial - complex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - """ - self.thisptr.remove_maximal_simplex(simplex) - - def get_point(self, vertex): - """This function returns the point corresponding to a given vertex. - - :param vertex: The vertex. - :type vertex: int. - :returns: list of float -- the point. - """ - cdef vector[double] point = self.thisptr.get_point(vertex) - return point - - def persistence(self, homology_coeff_field=11, min_persistence=0.0): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :returns: list of tuples(dimension, tuple(birth, death)) -- the - persistence of the simplicial complex. - """ - if self.pcohptr != NULL: - del self.pcohptr - self.pcohptr = new Alpha_complex_persistence_interface(self.thisptr) - cdef vector[pair[int, pair[double, double]]] persistence_result - if self.pcohptr != NULL: - persistence_result \ - = self.pcohptr.get_persistence(homology_coeff_field, - min_persistence) - return persistence_result - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - cdef vector[int] bn_result - if self.pcohptr != NULL: - bn_result = self.pcohptr.betti_numbers() - else: - print("betti_numbers function requires persistence function" - " to be launched first.") - return bn_result - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - cdef vector[int] pbn_result - if self.pcohptr != NULL: - pbn_result \ - = self.pcohptr.persistent_betti_numbers(from_value, - to_value) - else: - print("persistent_betti_numbers function requires persistence " - "function to be launched first.") - return pbn_result diff --git a/src/cython/src/cython/cubical_complex.pyx b/src/cython/src/cython/cubical_complex.pyx deleted file mode 100644 index 3441b2e9..00000000 --- a/src/cython/src/cython/cubical_complex.pyx +++ /dev/null @@ -1,180 +0,0 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libcpp.string cimport string -import os - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -cdef extern from "Cubical_complex_interface.h" namespace "Gudhi": - cdef cppclass Bitmap_cubical_complex_base_interface "Gudhi::Cubical_complex::Cubical_complex_interface<>": - Bitmap_cubical_complex_base_interface(vector[unsigned] dimensions, vector[double] top_dimensional_cells) - Bitmap_cubical_complex_base_interface(string perseus_file) - int num_simplices() - int dimension() - -cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": - cdef cppclass Cubical_complex_persistence_interface "Gudhi::Persistent_cohomology_interface>": - Cubical_complex_persistence_interface(Bitmap_cubical_complex_base_interface * st) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] betti_numbers() - vector[int] persistent_betti_numbers(double from_value, double to_value) - - -# CubicalComplex python interface -cdef class CubicalComplex: - """The CubicalComplex is an example of a structured complex useful in - computational mathematics (specially rigorous numerics) and image - analysis. - """ - cdef Bitmap_cubical_complex_base_interface * thisptr - - cdef Cubical_complex_persistence_interface * pcohptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, dimensions=None, top_dimensional_cells=None, - perseus_file=''): - """CubicalComplex constructor from dimensions and - top_dimensional_cells or from a perseus file style name. - - :param dimensions: A list of number of top dimensional cells. - :type dimensions: list of int - :param top_dimensional_cells: A list of top dimensional cells. - :type top_dimensional_cells: list of double - - Or - - :param perseus_file: A perseus file style name. - :type perseus_file: string - """ - - # The real cython constructor - def __cinit__(self, dimensions=None, top_dimensional_cells=None, - perseus_file=''): - if ((dimensions is not None) or (top_dimensional_cells is not None) and - (perseus_file is not '')): - print("CubicalComplex can be constructed from dimensions and " - "top_dimensional_cells or from a perseus file style name.") - else: - if dimensions is not None: - if top_dimensional_cells is not None: - self.thisptr = new Bitmap_cubical_complex_base_interface(dimensions, top_dimensional_cells) - else: - if perseus_file is not '': - if os.path.isfile(perseus_file): - self.thisptr = new Bitmap_cubical_complex_base_interface(perseus_file) - else: - print("file " + perseus_file + " not found.") - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - if self.pcohptr != NULL: - del self.pcohptr - - def __is_defined(self): - """Returns true if CubicalComplex pointer is not NULL. - """ - return self.thisptr != NULL - - def __is_persistence_defined(self): - """Returns true if Persistence pointer is not NULL. - """ - return self.pcohptr != NULL - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def persistence(self, homology_coeff_field=11, min_persistence=0): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :returns: list of pairs(dimension, pair(birth, death)) -- the - persistence of the simplicial complex. - """ - if self.pcohptr != NULL: - del self.pcohptr - if self.thisptr != NULL: - self.pcohptr = new Cubical_complex_persistence_interface(self.thisptr) - cdef vector[pair[int, pair[double, double]]] persistence_result - if self.pcohptr != NULL: - persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) - return persistence_result - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - cdef vector[int] bn_result - if self.pcohptr != NULL: - bn_result = self.pcohptr.betti_numbers() - return bn_result - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - cdef vector[int] pbn_result - if self.pcohptr != NULL: - pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) - return pbn_result diff --git a/src/cython/src/cython/mini_simplex_tree.pyx b/src/cython/src/cython/mini_simplex_tree.pyx deleted file mode 100644 index 3ba7e853..00000000 --- a/src/cython/src/cython/mini_simplex_tree.pyx +++ /dev/null @@ -1,352 +0,0 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": - cdef cppclass Simplex_tree_options_mini: - pass - - cdef cppclass Simplex_tree_interface_mini "Gudhi::Simplex_tree_interface": - Simplex_tree() - double filtration() - double simplex_filtration(vector[int] simplex) - void set_filtration(double filtration) - void initialize_filtration() - int num_vertices() - int num_simplices() - void set_dimension(int dimension) - int dimension() - bint find_simplex(vector[int] simplex) - bint insert_simplex_and_subfaces(vector[int] simplex, - double filtration) - vector[pair[vector[int], double]] get_filtered_tree() - vector[pair[vector[int], double]] get_skeleton_tree(int dimension) - vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) - vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, - int dimension) - void remove_maximal_simplex(vector[int] simplex) - -cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": - cdef cppclass Mini_simplex_tree_persistence_interface "Gudhi::Persistent_cohomology_interface>": - Mini_simplex_tree_persistence_interface(Simplex_tree_interface_mini * st) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] betti_numbers() - vector[int] persistent_betti_numbers(double from_value, double to_value) - -# MiniSimplexTree python interface -cdef class MiniSimplexTree: - """The simplex tree is an efficient and flexible data structure for - representing general (filtered) simplicial complexes. The data structure - is described in Jean-Daniel Boissonnat and Clément Maria. The Simplex - Tree: An Efficient Data Structure for General Simplicial Complexes. - Algorithmica, pages 1–22, 2014. - - This class is a non-filtered, with keys, and non contiguous vertices - version of the simplex tree. - """ - cdef Simplex_tree_interface_mini * thisptr - - cdef Mini_simplex_tree_persistence_interface * pcohptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, points=[], max_alpha_square=float('inf')): - """MiniSimplexTree constructor. - """ - - # The real cython constructor - def __cinit__(self): - self.thisptr = new Simplex_tree_interface_mini() - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - if self.pcohptr != NULL: - del self.pcohptr - - def __is_defined(self): - """Returns true if MiniSimplexTree pointer is not NULL. - """ - return self.thisptr != NULL - - def __is_persistence_defined(self): - """Returns true if Persistence pointer is not NULL. - """ - return self.pcohptr != NULL - - def get_filtration(self): - """This function returns the main simplicial complex filtration value. - - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.filtration() - - def filtration(self, simplex): - """This function returns the simplicial complex filtration value for a - given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.simplex_filtration(simplex) - - def set_filtration(self, filtration): - """This function sets the main simplicial complex filtration value. - - :param filtration: The filtration value. - :type filtration: float. - """ - self.thisptr.set_filtration( filtration) - - def initialize_filtration(self): - """This function initializes and sorts the simplicial complex - filtration vector. - - .. note:: - - This function must be launched before persistence, betti_numbers, - persistent_betti_numbers or get_filtered_tree after inserting or - removing simplices. - """ - self.thisptr.initialize_filtration() - - def num_vertices(self): - """This function returns the number of vertices of the simplicial - complex. - - :returns: int -- the simplicial complex number of vertices. - """ - return self.thisptr.num_vertices() - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def set_dimension(self, dimension): - """This function sets the dimension of the simplicial complex. - - :param dimension: The new dimension value. - :type dimension: int. - """ - self.thisptr.set_dimension(dimension) - - def find(self, simplex): - """This function returns if the N-simplex was found in the simplicial - complex or not. - - :param simplex: The N-simplex to find, represented by a list of vertex. - :type simplex: list of int. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.find_simplex(complex) - - def insert(self, simplex, filtration=0.0): - """This function inserts the given N-simplex with the given filtration - value (default value is '0.0'). - - :param simplex: The N-simplex to insert, represented by a list of - vertex. - :type simplex: list of int. - :param filtration: The filtration value of the simplex. - :type filtration: float. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.insert_simplex_and_subfaces(complex, - filtration) - - def get_filtered_tree(self): - """This function returns the tree sorted by increasing filtration - values. - - :returns: list of tuples(simplex, filtration) -- the tree sorted by - increasing filtration values. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_filtered_tree() - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_skeleton_tree(self, dimension): - """This function returns the tree skeleton of a maximum given - dimension. - - :param dimension: The skeleton dimension value. - :type dimension: int. - :returns: list of tuples(simplex, filtration) -- the skeleton tree - of a maximum dimension. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_skeleton_tree(dimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_star_tree(self, simplex): - """This function returns the star tree of a given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: list of tuples(simplex, filtration) -- the star tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_star_tree(complex) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_coface_tree(self, simplex, codimension): - """This function returns the coface tree of a given N-simplex with a - given codimension. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :param codimension: The codimension. If codimension = 0, all cofaces - are returned (equivalent of get_star_tree function) - :type codimension: int. - :returns: list of tuples(simplex, filtration) -- the coface tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_coface_tree(complex, codimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def remove_maximal_simplex(self, simplex): - """This function removes a given maximal N-simplex from the simplicial - complex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - """ - self.thisptr.remove_maximal_simplex(simplex) - - def persistence(self, homology_coeff_field=11): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :returns: list of pairs(dimension, pair(birth, death)) -- the - persistence of the simplicial complex. - """ - if self.pcohptr != NULL: - del self.pcohptr - self.pcohptr = new Mini_simplex_tree_persistence_interface(self.thisptr) - cdef vector[pair[int, pair[double, double]]] persistence_result - if self.pcohptr != NULL: - persistence_result = self.pcohptr.get_persistence(homology_coeff_field, 0) - return persistence_result - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - cdef vector[int] bn_result - if self.pcohptr != NULL: - bn_result = self.pcohptr.betti_numbers() - else: - print("betti_numbers function requires persistence function" - " to be launched first.") - return bn_result - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - cdef vector[int] pbn_result - if self.pcohptr != NULL: - pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) - else: - print("persistent_betti_numbers function requires persistence function" - " to be launched first.") - return pbn_result diff --git a/src/cython/src/cython/periodic_cubical_complex.pyx b/src/cython/src/cython/periodic_cubical_complex.pyx deleted file mode 100644 index d56eb5b1..00000000 --- a/src/cython/src/cython/periodic_cubical_complex.pyx +++ /dev/null @@ -1,181 +0,0 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair -from libcpp.string cimport string -import os - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -cdef extern from "Cubical_complex_interface.h" namespace "Gudhi": - cdef cppclass Periodic_cubical_complex_base_interface "Gudhi::Cubical_complex::Cubical_complex_interface>": - Periodic_cubical_complex_base_interface(vector[unsigned] dimensions, vector[double] top_dimensional_cells) - Periodic_cubical_complex_base_interface(string perseus_file) - int num_simplices() - int dimension() - -cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": - cdef cppclass Periodic_cubical_complex_persistence_interface "Gudhi::Persistent_cohomology_interface>>": - Periodic_cubical_complex_persistence_interface(Periodic_cubical_complex_base_interface * st) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] betti_numbers() - vector[int] persistent_betti_numbers(double from_value, double to_value) - - -# PeriodicCubicalComplex python interface -cdef class PeriodicCubicalComplex: - """The PeriodicCubicalComplex is an example of a structured complex useful - in computational mathematics (specially rigorous numerics) and image - analysis. - """ - cdef Periodic_cubical_complex_base_interface * thisptr - - cdef Periodic_cubical_complex_persistence_interface * pcohptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, dimensions=None, top_dimensional_cells=None, - perseus_file=''): - """PeriodicCubicalComplex constructor from dimensions and - top_dimensional_cells or from a perseus file style name. - - :param dimensions: A list of number of top dimensional cells. - :type dimensions: list of int - :param top_dimensional_cells: A list of top dimensional cells. - :type top_dimensional_cells: list of double - - Or - - :param perseus_file: A perseus file style name. - :type perseus_file: string - """ - - # The real cython constructor - def __cinit__(self, dimensions=None, top_dimensional_cells=None, - perseus_file=''): - if ((dimensions is not None) or (top_dimensional_cells is not None) and - (perseus_file is not '')): - print("PeriodicCubicalComplex can be constructed from dimensions" - " and top_dimensional_cells or from a perseus file style " - "name.") - else: - if dimensions is not None: - if top_dimensional_cells is not None: - self.thisptr = new Periodic_cubical_complex_base_interface(dimensions, top_dimensional_cells) - else: - if perseus_file is not '': - if os.path.isfile(perseus_file): - self.thisptr = new Periodic_cubical_complex_base_interface(perseus_file) - else: - print("file " + perseus_file + " not found.") - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - if self.pcohptr != NULL: - del self.pcohptr - - def __is_defined(self): - """Returns true if PeriodicCubicalComplex pointer is not NULL. - """ - return self.thisptr != NULL - - def __is_persistence_defined(self): - """Returns true if Persistence pointer is not NULL. - """ - return self.pcohptr != NULL - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def persistence(self, homology_coeff_field=11, min_persistence=0): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :returns: list of pairs(dimension, pair(birth, death)) -- the - persistence of the simplicial complex. - """ - if self.pcohptr != NULL: - del self.pcohptr - if self.thisptr != NULL: - self.pcohptr = new Periodic_cubical_complex_persistence_interface(self.thisptr) - cdef vector[pair[int, pair[double, double]]] persistence_result - if self.pcohptr != NULL: - persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) - return persistence_result - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - cdef vector[int] bn_result - if self.pcohptr != NULL: - bn_result = self.pcohptr.betti_numbers() - return bn_result - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - cdef vector[int] pbn_result - if self.pcohptr != NULL: - pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) - return pbn_result diff --git a/src/cython/src/cython/persistence_graphical_tools.py b/src/cython/src/cython/persistence_graphical_tools.py deleted file mode 100755 index 247e119e..00000000 --- a/src/cython/src/cython/persistence_graphical_tools.py +++ /dev/null @@ -1,155 +0,0 @@ -import matplotlib.pyplot as plt -import numpy as np - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -def __min_birth_max_death(persistence): - """This function returns (min_birth, max_death) from the persistence. - - :param persistence: The persistence to plot. - :type persistence: list of tuples(dimension, tuple(birth, death)). - :returns: (float, float) -- (min_birth, max_death). - """ - # Look for minimum birth date and maximum death date for plot optimisation - max_death = 0 - min_birth = persistence[0][1][0] - for interval in reversed(persistence): - if float(interval[1][1]) != float('inf'): - if float(interval[1][1]) > max_death: - max_death = float(interval[1][1]) - if float(interval[1][0]) > max_death: - max_death = float(interval[1][0]) - if float(interval[1][0]) < min_birth: - min_birth = float(interval[1][0]) - return (min_birth, max_death) - -""" -Only 13 colors for the palette -""" -palette = ['#ff0000', '#00ff00', '#0000ff', '#00ffff', '#ff00ff', '#ffff00', - '#000000', '#880000', '#008800', '#000088', '#888800', '#880088', - '#008888'] - -def show_palette_values(alpha=0.6): - """This function shows palette color values in function of the dimension. - - :param alpha: alpha value in [0.0, 1.0] for horizontal bars (default is - 0.6). - :type alpha: float. - :returns: plot -- An horizontal bar plot of dimensions color. - """ - colors = [] - for color in palette: - colors.append(color) - - y_pos = np.arange(len(palette)) - - plt.barh(y_pos, y_pos + 1, align='center', alpha=alpha, color=colors) - plt.ylabel('Dimension') - plt.title('Dimension palette values') - - plt.show() - -def barcode_persistence(persistence, alpha=0.6): - """This function plots the persistence bar code. - - :param persistence: The persistence to plot. - :type persistence: list of tuples(dimension, tuple(birth, death)). - :param alpha: alpha value in [0.0, 1.0] for horizontal bars (default is - 0.6). - :type alpha: float. - :returns: plot -- An horizontal bar plot of persistence. - """ - (min_birth, max_death) = __min_birth_max_death(persistence) - ind = 0 - delta = ((max_death - min_birth) / 10.0) - # Replace infinity values with max_death + delta for bar code to be more - # readable - infinity = max_death + delta - axis_start = min_birth - delta - # Draw horizontal bars in loop - for interval in reversed(persistence): - if float(interval[1][1]) != float('inf'): - # Finite death case - plt.barh(ind, (interval[1][1] - interval[1][0]), height=0.8, - left = interval[1][0], alpha=alpha, - color = palette[interval[0]]) - else: - # Infinite death case for diagram to be nicer - plt.barh(ind, (infinity - interval[1][0]), height=0.8, - left = interval[1][0], alpha=alpha, - color = palette[interval[0]]) - ind = ind + 1 - - plt.title('Persistence barcode') - # Ends plot on infinity value and starts a little bit before min_birth - plt.axis([axis_start, infinity, 0, ind]) - plt.show() - -def diagram_persistence(persistence, alpha=0.6): - """This function plots the persistence diagram. - - :param persistence: The persistence to plot. - :type persistence: list of tuples(dimension, tuple(birth, death)). - :param alpha: alpha value in [0.0, 1.0] for points and horizontal infinity - line (default is 0.6). - :type alpha: float. - :returns: plot -- An diagram plot of persistence. - """ - (min_birth, max_death) = __min_birth_max_death(persistence) - ind = 0 - delta = ((max_death - min_birth) / 10.0) - # Replace infinity values with max_death + delta for diagram to be more - # readable - infinity = max_death + delta - axis_start = min_birth - delta - - # line display of equation : birth = death - x = np.linspace(axis_start, infinity, 1000) - # infinity line and text - plt.plot(x, x, color='k', linewidth=1.0) - plt.plot(x, [infinity] * len(x), linewidth=1.0, color='k', alpha=alpha) - plt.text(axis_start, infinity, r'$\infty$', color='k', alpha=alpha) - - # Draw points in loop - for interval in reversed(persistence): - if float(interval[1][1]) != float('inf'): - # Finite death case - plt.scatter(interval[1][0], interval[1][1], alpha=alpha, - color = palette[interval[0]]) - else: - # Infinite death case for diagram to be nicer - plt.scatter(interval[1][0], infinity, alpha=alpha, - color = palette[interval[0]]) - ind = ind + 1 - - plt.title('Persistence diagram') - plt.xlabel('Birth') - plt.ylabel('Death') - # Ends plot on infinity value and starts a little bit before min_birth - plt.axis([axis_start, infinity, axis_start, infinity + delta]) - plt.show() diff --git a/src/cython/src/cython/rips_complex.pyx b/src/cython/src/cython/rips_complex.pyx deleted file mode 100644 index ee4c34b0..00000000 --- a/src/cython/src/cython/rips_complex.pyx +++ /dev/null @@ -1,369 +0,0 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": - cdef cppclass Simplex_tree_options_full_featured: - pass - - cdef cppclass Rips_complex_interface "Gudhi::Simplex_tree_interface": - Simplex_tree() - double filtration() - double simplex_filtration(vector[int] simplex) - void set_filtration(double filtration) - void initialize_filtration() - int num_vertices() - int num_simplices() - void set_dimension(int dimension) - int dimension() - bint find_simplex(vector[int] simplex) - bint insert_simplex_and_subfaces(vector[int] simplex, - double filtration) - vector[pair[vector[int], double]] get_filtered_tree() - vector[pair[vector[int], double]] get_skeleton_tree(int dimension) - vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) - vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, - int dimension) - void remove_maximal_simplex(vector[int] simplex) - void graph_expansion(vector[vector[double]] points, int max_dimension, - double max_edge_length) - -cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": - cdef cppclass Rips_complex_persistence_interface "Gudhi::Persistent_cohomology_interface>": - Rips_complex_persistence_interface(Rips_complex_interface * st) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] betti_numbers() - vector[int] persistent_betti_numbers(double from_value, double to_value) - -# RipsComplex python interface -cdef class RipsComplex: - """RipsComplex is a simplicial complex constructed from a list of points. - - Each point Pn is inserted as a vertex in the simplicial complex with a - null filtration value. - - A N-simplex represented by the list of vertices Vi, ..., Vj is inserted in - the simplicial complex if all the points Pi, ..., Pj corresponding to the - vertices are within a distance less or equal to a given maximum edge length - value, and if N (dimension of the N-simplex) is less or equal to a given - maximum dimension. - """ - cdef Rips_complex_interface * thisptr - - cdef Rips_complex_persistence_interface * pcohptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, points=[], max_dimension=3, - max_edge_length=float('inf')): - """RipsComplex constructor. - - :param points: A list of points in d-Dimension. - :type points: list of list of double - :param max_dimension: Maximum dimension of the complex to be expanded. - :type max_dimension: int - :param max_edge_length: Maximum edge length value (rips radius). - :type max_edge_length: double - """ - - # The real cython constructor - def __cinit__(self, points=[], max_dimension=3, - max_edge_length=float('inf')): - self.thisptr = new Rips_complex_interface() - # Constructor from graph expansion - if points is not None: - self.thisptr.graph_expansion(points, max_dimension, - max_edge_length) - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - if self.pcohptr != NULL: - del self.pcohptr - - def __is_defined(self): - """Returns true if RipsComplex pointer is not NULL. - """ - return self.thisptr != NULL - - def __is_persistence_defined(self): - """Returns true if Persistence pointer is not NULL. - """ - return self.pcohptr != NULL - - def get_filtration(self): - """This function returns the main simplicial complex filtration value. - - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.filtration() - - def filtration(self, simplex): - """This function returns the simplicial complex filtration value for a - given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.simplex_filtration(simplex) - - def set_filtration(self, filtration): - """This function sets the main simplicial complex filtration value. - - :param filtration: The filtration value. - :type filtration: float. - """ - self.thisptr.set_filtration( filtration) - - def initialize_filtration(self): - """This function initializes and sorts the simplicial complex - filtration vector. - - .. note:: - - This function must be launched before persistence, betti_numbers, - persistent_betti_numbers or get_filtered_tree after inserting or - removing simplices. - """ - self.thisptr.initialize_filtration() - - def num_vertices(self): - """This function returns the number of vertices of the simplicial - complex. - - :returns: int -- the simplicial complex number of vertices. - """ - return self.thisptr.num_vertices() - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def set_dimension(self, dimension): - """This function sets the dimension of the simplicial complex. - - :param dimension: The new dimension value. - :type dimension: int. - """ - self.thisptr.set_dimension(dimension) - - def find(self, simplex): - """This function returns if the N-simplex was found in the simplicial - complex or not. - - :param simplex: The N-simplex to find, represented by a list of vertex. - :type simplex: list of int. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.find_simplex(complex) - - def insert(self, simplex, filtration=0.0): - """This function inserts the given N-simplex with the given filtration - value (default value is '0.0'). - - :param simplex: The N-simplex to insert, represented by a list of - vertex. - :type simplex: list of int. - :param filtration: The filtration value of the simplex. - :type filtration: float. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.insert_simplex_and_subfaces(complex, - filtration) - - def get_filtered_tree(self): - """This function returns the tree sorted by increasing filtration - values. - - :returns: list of tuples(simplex, filtration) -- the tree sorted by - increasing filtration values. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_filtered_tree() - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_skeleton_tree(self, dimension): - """This function returns the tree skeleton of a maximum given - dimension. - - :param dimension: The skeleton dimension value. - :type dimension: int. - :returns: list of tuples(simplex, filtration) -- the skeleton tree - of a maximum dimension. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_skeleton_tree(dimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_star_tree(self, simplex): - """This function returns the star tree of a given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: list of tuples(simplex, filtration) -- the star tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_star_tree(complex) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_coface_tree(self, simplex, codimension): - """This function returns the coface tree of a given N-simplex with a - given codimension. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :param codimension: The codimension. If codimension = 0, all cofaces - are returned (equivalent of get_star_tree function) - :type codimension: int. - :returns: list of tuples(simplex, filtration) -- the coface tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_coface_tree(complex, codimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def remove_maximal_simplex(self, simplex): - """This function removes a given maximal N-simplex from the simplicial - complex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - """ - self.thisptr.remove_maximal_simplex(simplex) - - def persistence(self, homology_coeff_field=11, min_persistence=0): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :note: list of pairs(dimension, pair(birth, death)) -- the - persistence of the simplicial complex. - """ - if self.pcohptr != NULL: - del self.pcohptr - self.pcohptr = new Rips_complex_persistence_interface(self.thisptr) - cdef vector[pair[int, pair[double, double]]] persistence_result - if self.pcohptr != NULL: - persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) - return persistence_result - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - cdef vector[int] bn_result - if self.pcohptr != NULL: - bn_result = self.pcohptr.betti_numbers() - else: - print("betti_numbers function requires persistence function" - " to be launched first.") - return bn_result - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - cdef vector[int] pbn_result - if self.pcohptr != NULL: - pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) - else: - print("persistent_betti_numbers function requires persistence function" - " to be launched first.") - return pbn_result diff --git a/src/cython/src/cython/simplex_tree.pyx b/src/cython/src/cython/simplex_tree.pyx deleted file mode 100644 index bf91e812..00000000 --- a/src/cython/src/cython/simplex_tree.pyx +++ /dev/null @@ -1,352 +0,0 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -cdef extern from "Simplex_tree_interface.h" namespace "Gudhi": - cdef cppclass Simplex_tree_options_full_featured: - pass - - cdef cppclass Simplex_tree_interface_full_featured "Gudhi::Simplex_tree_interface": - Simplex_tree() - double filtration() - double simplex_filtration(vector[int] simplex) - void set_filtration(double filtration) - void initialize_filtration() - int num_vertices() - int num_simplices() - void set_dimension(int dimension) - int dimension() - bint find_simplex(vector[int] simplex) - bint insert_simplex_and_subfaces(vector[int] simplex, - double filtration) - vector[pair[vector[int], double]] get_filtered_tree() - vector[pair[vector[int], double]] get_skeleton_tree(int dimension) - vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) - vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, - int dimension) - void remove_maximal_simplex(vector[int] simplex) - -cdef extern from "Persistent_cohomology_interface.h" namespace "Gudhi": - cdef cppclass Simplex_tree_persistence_interface "Gudhi::Persistent_cohomology_interface>": - Simplex_tree_persistence_interface(Simplex_tree_interface_full_featured * st) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] betti_numbers() - vector[int] persistent_betti_numbers(double from_value, double to_value) - -# SimplexTree python interface -cdef class SimplexTree: - """The simplex tree is an efficient and flexible data structure for - representing general (filtered) simplicial complexes. The data structure - is described in Jean-Daniel Boissonnat and Clément Maria. The Simplex - Tree: An Efficient Data Structure for General Simplicial Complexes. - Algorithmica, pages 1–22, 2014. - - This class is a filtered, with keys, and non contiguous vertices version - of the simplex tree. - """ - cdef Simplex_tree_interface_full_featured * thisptr - - cdef Simplex_tree_persistence_interface * pcohptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, points=[], max_alpha_square=float('inf')): - """SimplexTree constructor. - """ - - # The real cython constructor - def __cinit__(self): - self.thisptr = new Simplex_tree_interface_full_featured() - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - if self.pcohptr != NULL: - del self.pcohptr - - def __is_defined(self): - """Returns true if SimplexTree pointer is not NULL. - """ - return self.thisptr != NULL - - def __is_persistence_defined(self): - """Returns true if Persistence pointer is not NULL. - """ - return self.pcohptr != NULL - - def get_filtration(self): - """This function returns the main simplicial complex filtration value. - - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.filtration() - - def filtration(self, simplex): - """This function returns the simplicial complex filtration value for a - given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.simplex_filtration(simplex) - - def set_filtration(self, filtration): - """This function sets the main simplicial complex filtration value. - - :param filtration: The filtration value. - :type filtration: float. - """ - self.thisptr.set_filtration( filtration) - - def initialize_filtration(self): - """This function initializes and sorts the simplicial complex - filtration vector. - - .. note:: - - This function must be launched before persistence, betti_numbers, - persistent_betti_numbers or get_filtered_tree after inserting or - removing simplices. - """ - self.thisptr.initialize_filtration() - - def num_vertices(self): - """This function returns the number of vertices of the simplicial - complex. - - :returns: int -- the simplicial complex number of vertices. - """ - return self.thisptr.num_vertices() - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def set_dimension(self, dimension): - """This function sets the dimension of the simplicial complex. - - :param dimension: The new dimension value. - :type dimension: int. - """ - self.thisptr.set_dimension(dimension) - - def find(self, simplex): - """This function returns if the N-simplex was found in the simplicial - complex or not. - - :param simplex: The N-simplex to find, represented by a list of vertex. - :type simplex: list of int. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.find_simplex(complex) - - def insert(self, simplex, filtration=0.0): - """This function inserts the given N-simplex with the given filtration - value (default value is '0.0'). - - :param simplex: The N-simplex to insert, represented by a list of - vertex. - :type simplex: list of int. - :param filtration: The filtration value of the simplex. - :type filtration: float. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.insert_simplex_and_subfaces(complex, - filtration) - - def get_filtered_tree(self): - """This function returns the tree sorted by increasing filtration - values. - - :returns: list of tuples(simplex, filtration) -- the tree sorted by - increasing filtration values. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_filtered_tree() - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_skeleton_tree(self, dimension): - """This function returns the tree skeleton of a maximum given - dimension. - - :param dimension: The skeleton dimension value. - :type dimension: int. - :returns: list of tuples(simplex, filtration) -- the skeleton tree - of a maximum dimension. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_skeleton_tree(dimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_star_tree(self, simplex): - """This function returns the star tree of a given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: list of tuples(simplex, filtration) -- the star tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_star_tree(complex) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_coface_tree(self, simplex, codimension): - """This function returns the coface tree of a given N-simplex with a - given codimension. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :param codimension: The codimension. If codimension = 0, all cofaces - are returned (equivalent of get_star_tree function) - :type codimension: int. - :returns: list of tuples(simplex, filtration) -- the coface tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_coface_tree(complex, codimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def remove_maximal_simplex(self, simplex): - """This function removes a given maximal N-simplex from the simplicial - complex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - """ - self.thisptr.remove_maximal_simplex(simplex) - - def persistence(self, homology_coeff_field=11, min_persistence=0): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :note: list of pairs(dimension, pair(birth, death)) -- the - persistence of the simplicial complex. - """ - if self.pcohptr != NULL: - del self.pcohptr - self.pcohptr = new Simplex_tree_persistence_interface(self.thisptr) - cdef vector[pair[int, pair[double, double]]] persistence_result - if self.pcohptr != NULL: - persistence_result = self.pcohptr.get_persistence(homology_coeff_field, min_persistence) - return persistence_result - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - cdef vector[int] bn_result - if self.pcohptr != NULL: - bn_result = self.pcohptr.betti_numbers() - else: - print("betti_numbers function requires persistence function" - " to be launched first.") - return bn_result - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - cdef vector[int] pbn_result - if self.pcohptr != NULL: - pbn_result = self.pcohptr.persistent_betti_numbers(from_value, to_value) - else: - print("persistent_betti_numbers function requires persistence function" - " to be launched first.") - return pbn_result diff --git a/src/cython/src/cython/witness_complex.pyx b/src/cython/src/cython/witness_complex.pyx deleted file mode 100644 index 835244cf..00000000 --- a/src/cython/src/cython/witness_complex.pyx +++ /dev/null @@ -1,322 +0,0 @@ -from cython cimport numeric -from libcpp.vector cimport vector -from libcpp.utility cimport pair - -"""This file is part of the Gudhi Library. The Gudhi library - (Geometric Understanding in Higher Dimensions) is a generic C++ - library for computational topology. - - Author(s): Vincent Rouvreau - - Copyright (C) 2016 INRIA - - This program is free software: you can redistribute it and/or modify - it under the terms of the GNU General Public License as published by - the Free Software Foundation, either version 3 of the License, or - (at your option) any later version. - - This program is distributed in the hope that it will be useful, - but WITHOUT ANY WARRANTY; without even the implied warranty of - MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - GNU General Public License for more details. - - You should have received a copy of the GNU General Public License - along with this program. If not, see . -""" - -__author__ = "Vincent Rouvreau" -__copyright__ = "Copyright (C) 2016 INRIA" -__license__ = "GPL v3" - -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[double]] points, int number_of_landmarks) - double filtration() - double simplex_filtration(vector[int] simplex) - void set_filtration(double filtration) - void initialize_filtration() - int num_vertices() - int num_simplices() - void set_dimension(int dimension) - int dimension() - bint find_simplex(vector[int] simplex) - bint insert_simplex_and_subfaces(vector[int] simplex, - double filtration) - vector[pair[vector[int], double]] get_filtered_tree() - vector[pair[vector[int], double]] get_skeleton_tree(int dimension) - vector[pair[vector[int], double]] get_star_tree(vector[int] simplex) - vector[pair[vector[int], double]] get_coface_tree(vector[int] simplex, - int dimension) - void remove_maximal_simplex(vector[int] simplex) - vector[double] get_point(int vertex) - vector[pair[int, pair[double, double]]] get_persistence(int homology_coeff_field, double min_persistence) - vector[int] get_betti_numbers() - vector[int] get_persistent_betti_numbers(double from_value, double to_value) - -# WitnessComplex python interface -cdef class WitnessComplex: - """WitnessComplex is a simplicial complex constructed from ... - - """ - - cdef Witness_complex_interface * thisptr - - # Fake constructor that does nothing but documenting the constructor - def __init__(self, points=[], number_of_landmarks=5): - """WitnessComplex constructor. - - :param points: A list of points in d-Dimension. - :type points: list of list of double - :param number_of_landmarks: Number of landmarks to build the - WitnessComplex. - :type number_of_landmarks: int - """ - - # The real cython constructor - def __cinit__(self, points=None, number_of_landmarks=5): - if points is not None: - self.thisptr = new Witness_complex_interface(points, - number_of_landmarks) - - def __dealloc__(self): - if self.thisptr != NULL: - del self.thisptr - - def __is_defined(self): - """Returns true if AlphaComplex pointer is not NULL. - """ - return self.thisptr != NULL - - def get_filtration(self): - """This function returns the main simplicial complex filtration value. - - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.filtration() - - def filtration(self, simplex): - """This function returns the simplicial complex filtration value for a - given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: float -- the simplicial complex filtration value. - """ - return self.thisptr.simplex_filtration(simplex) - - def set_filtration(self, filtration): - """This function sets the main simplicial complex filtration value. - - :param filtration: The filtration value. - :type filtration: float. - """ - self.thisptr.set_filtration( filtration) - - def initialize_filtration(self): - """This function initializes and sorts the simplicial complex - filtration vector. - - .. note:: - - This function must be launched before persistence, betti_numbers, - persistent_betti_numbers or get_filtered_tree after inserting or - removing simplices. - """ - self.thisptr.initialize_filtration() - - def num_vertices(self): - """This function returns the number of vertices of the simplicial - complex. - - :returns: int -- the simplicial complex number of vertices. - """ - return self.thisptr.num_vertices() - - def num_simplices(self): - """This function returns the number of simplices of the simplicial - complex. - - :returns: int -- the simplicial complex number of simplices. - """ - return self.thisptr.num_simplices() - - def dimension(self): - """This function returns the dimension of the simplicial complex. - - :returns: int -- the simplicial complex dimension. - """ - return self.thisptr.dimension() - - def set_dimension(self, dimension): - """This function sets the dimension of the simplicial complex. - - :param dimension: The new dimension value. - :type dimension: int. - """ - self.thisptr.set_dimension(dimension) - - def find(self, simplex): - """This function returns if the N-simplex was found in the simplicial - complex or not. - - :param simplex: The N-simplex to find, represented by a list of vertex. - :type simplex: list of int. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.find_simplex(complex) - - def insert(self, simplex, filtration=0.0): - """This function inserts the given N-simplex with the given filtration - value (default value is '0.0'). - - :param simplex: The N-simplex to insert, represented by a list of - vertex. - :type simplex: list of int. - :param filtration: The filtration value of the simplex. - :type filtration: float. - :returns: bool -- true if the simplex was found, false otherwise. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - return self.thisptr.insert_simplex_and_subfaces(complex, - filtration) - - def get_filtered_tree(self): - """This function returns the tree sorted by increasing filtration - values. - - :returns: list of tuples(simplex, filtration) -- the tree sorted by - increasing filtration values. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_filtered_tree() - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_skeleton_tree(self, dimension): - """This function returns the tree skeleton of a maximum given - dimension. - - :param dimension: The skeleton dimension value. - :type dimension: int. - :returns: list of tuples(simplex, filtration) -- the skeleton tree - of a maximum dimension. - """ - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_skeleton_tree(dimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_star_tree(self, simplex): - """This function returns the star tree of a given N-simplex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :returns: list of tuples(simplex, filtration) -- the star tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_star_tree(complex) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def get_coface_tree(self, simplex, codimension): - """This function returns the coface tree of a given N-simplex with a - given codimension. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - :param codimension: The codimension. If codimension = 0, all cofaces - are returned (equivalent of get_star_tree function) - :type codimension: int. - :returns: list of tuples(simplex, filtration) -- the coface tree of a - simplex. - """ - cdef vector[int] complex - for i in simplex: - complex.push_back(i) - cdef vector[pair[vector[int], double]] coface_tree \ - = self.thisptr.get_coface_tree(complex, codimension) - ct = [] - for filtered_complex in coface_tree: - v = [] - for vertex in filtered_complex.first: - v.append(vertex) - ct.append((v, filtered_complex.second)) - return ct - - def remove_maximal_simplex(self, simplex): - """This function removes a given maximal N-simplex from the simplicial - complex. - - :param simplex: The N-simplex, represented by a list of vertex. - :type simplex: list of int. - """ - self.thisptr.remove_maximal_simplex(simplex) - - def persistence(self, homology_coeff_field=11, min_persistence=0): - """This function returns the persistence of the simplicial complex. - - :param homology_coeff_field: The homology coefficient field. Must be a - prime number - :type homology_coeff_field: int. - :param min_persistence: The minimum persistence value to take into - account (strictly greater than min_persistence). Default value is - 0.0. - Sets min_persistence to -1.0 to see all values. - :type min_persistence: float. - :note: list of pairs(dimension, pair(birth, death)) -- the - persistence of the simplicial complex. - """ - return self.thisptr.get_persistence(homology_coeff_field, min_persistence) - - def betti_numbers(self): - """This function returns the Betti numbers of the simplicial complex. - - :returns: list of int -- The Betti numbers ([B0, B1, ..., Bn]). - - :note: betti_numbers function requires persistence function to be - launched first. - """ - return self.thisptr.get_betti_numbers() - - def persistent_betti_numbers(self, from_value, to_value): - """This function returns the persistent Betti numbers of the - simplicial complex. - - :param from_value: The persistence birth limit to be added in the - numbers (persistent birth <= from_value). - :type from_value: float. - :param to_value: The persistence death limit to be added in the - numbers (persistent death > to_value). - :type to_value: float. - - :returns: list of int -- The persistent Betti numbers ([B0, B1, ..., - Bn]). - - :note: persistent_betti_numbers function requires persistence - function to be launched first. - """ - return self.thisptr.get_persistent_betti_numbers(from_value, to_value) diff --git a/src/cython/src/doc/Makefile b/src/cython/src/doc/Makefile deleted file mode 100644 index fc353a37..00000000 --- a/src/cython/src/doc/Makefile +++ /dev/null @@ -1,177 +0,0 @@ -# Makefile for Sphinx documentation -# - -# You can set these variables from the command line. -SPHINXOPTS = -SPHINXBUILD = sphinx-build -PAPER = -BUILDDIR = _build - -# User-friendly check for sphinx-build -ifeq ($(shell which $(SPHINXBUILD) >/dev/null 2>&1; echo $$?), 1) -$(error The '$(SPHINXBUILD)' command was not found. Make sure you have Sphinx installed, then set the SPHINXBUILD environment variable to point to the full path of the '$(SPHINXBUILD)' executable. Alternatively you can add the directory with the executable to your PATH. 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The pseudo-XML files are in $(BUILDDIR)/pseudoxml." diff --git a/src/cython/src/doc/alpha_complex_ref.rst b/src/cython/src/doc/alpha_complex_ref.rst deleted file mode 100644 index 6a122b09..00000000 --- a/src/cython/src/doc/alpha_complex_ref.rst +++ /dev/null @@ -1,10 +0,0 @@ -============================== -Alpha complex reference manual -============================== - -.. autoclass:: gudhi.AlphaComplex - :members: - :undoc-members: - :show-inheritance: - - .. automethod:: gudhi.AlphaComplex.__init__ diff --git a/src/cython/src/doc/alpha_complex_sum.rst b/src/cython/src/doc/alpha_complex_sum.rst deleted file mode 100644 index b608050e..00000000 --- a/src/cython/src/doc/alpha_complex_sum.rst +++ /dev/null @@ -1,21 +0,0 @@ -===================================== ===================================== ===================================== -:Author: Vincent Rouvreau :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+-------------------------------------------+----------------------------------------------------------------------+ -| .. image:: | Alpha_complex is a simplicial complex constructed from the finite | -| img/alpha_complex_representation.png | cells of a Delaunay Triangulation. | -| | | -| | 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. | -| | | -| | This package requires having CGAL version 4.7 or higher (4.8.1 is | -| | advised for better perfomances). | -+-------------------------------------------+----------------------------------------------------------------------+ -| :doc:`alpha_complex_user` | :doc:`alpha_complex_ref` | -+-------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/src/doc/alpha_complex_user.rst b/src/cython/src/doc/alpha_complex_user.rst deleted file mode 100644 index b6b6e550..00000000 --- a/src/cython/src/doc/alpha_complex_user.rst +++ /dev/null @@ -1,192 +0,0 @@ -========================= -Alpha complex user manual -========================= -Definition ----------- - -.. include:: alpha_complex_sum.rst - -Alpha_complex is constructing a :doc:`Simplex_tree ` using -`Delaunay Triangulation `_ -:cite:`cgal:hdj-t-15b` from `CGAL `_ (the Computational Geometry Algorithms Library -:cite:`cgal:eb-15b`). - -Remarks -^^^^^^^ -When Alpha_complex is constructed with an infinite value of :math:`\alpha`, the complex is a Delaunay complex. - -Example from points -------------------- - -This example builds the Delaunay triangulation from the given points, and initializes the alpha complex with it: - -.. testcode:: - - import gudhi - alpha_complex = gudhi.AlphaComplex(points=[[1, 1], [7, 0], [4, 6], [9, 6], [0, 14], [2, 19], [9, 17]], - max_alpha_square=60.0) - result_str = 'Alpha complex is of dimension ' + repr(alpha_complex.dimension()) + ' - ' + \ - repr(alpha_complex.num_simplices()) + ' simplices - ' + \ - repr(alpha_complex.num_vertices()) + ' vertices.' - print(result_str) - for fitered_value in alpha_complex.get_filtered_tree(): - print(fitered_value) - -The output is: - -.. testoutput:: - - Alpha complex is of dimension 2 - 25 simplices - 7 vertices. - ([0], 0.0) - ([1], 0.0) - ([2], 0.0) - ([3], 0.0) - ([4], 0.0) - ([5], 0.0) - ([6], 0.0) - ([2, 3], 6.25) - ([4, 5], 7.25) - ([0, 2], 8.5) - ([0, 1], 9.25) - ([1, 3], 10.0) - ([1, 2], 11.25) - ([1, 2, 3], 12.5) - ([0, 1, 2], 12.995867768595042) - ([5, 6], 13.25) - ([2, 4], 20.0) - ([4, 6], 22.736686390532547) - ([4, 5, 6], 22.736686390532547) - ([3, 6], 30.25) - ([2, 6], 36.5) - ([2, 3, 6], 36.5) - ([2, 4, 6], 37.24489795918368) - ([0, 4], 59.710743801652896) - ([0, 2, 4], 59.710743801652896) - - -Algorithm ---------- - -Data structure -^^^^^^^^^^^^^^ - -In order to build the alpha complex, first, a Simplex tree is built from the cells of a Delaunay Triangulation. -(The filtration value is set to NaN, which stands for unknown value): - -.. image:: - img/alpha_complex_doc.png - :align: center - :alt: Simplex tree structure construction example - -Filtration value computation algorithm -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - - **for** i : dimension :math:`\rightarrow` 0 **do** - **for all** :math:`\sigma` of dimension i - **if** filtration(:math:`\sigma`) is NaN **then** - filtration(:math:`\sigma`) = :math:`\alpha^2(\sigma)` - **end if** - - *//propagate alpha filtration value* - - **for all** :math:`\tau` face of :math:`\sigma` - **if** filtration(:math:`\tau`) is not NaN **then** - filtration(:math:`\tau`) = filtration(:math:`\sigma`) - **end if** - **end for** - **end for** - **end for** - - make_filtration_non_decreasing() - - prune_above_filtration() - -Dimension 2 -^^^^^^^^^^^ - -From the example above, it means the algorithm looks into each triangle ([0,1,2], [0,2,4], [1,2,3], ...), -computes the filtration value of the triangle, and then propagates the filtration value as described -here: - -.. image:: - img/alpha_complex_doc_420.png - :align: center - :alt: Filtration value propagation example - -Dimension 1 -^^^^^^^^^^^ - -Then, the algorithm looks into each edge ([0,1], [0,2], [1,2], ...), -computes the filtration value of the edge (in this case, propagation will have no effect). - -Dimension 0 -^^^^^^^^^^^ - -Finally, the algorithm looks into each vertex ([0], [1], [2], [3], [4], [5] and [6]) and -sets the filtration value (0 in case of a vertex - propagation will have no effect). - -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). -We fix that up by calling `Simplex_tree::make_filtration_non_decreasing()` (cf. -`C++ version `_). - -Prune above given filtration value -^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ - -The simplex tree is pruned from the given maximum alpha squared value (cf. `Simplex_tree::prune_above_filtration()` -int he `C++ version `_). -In the following example, the value is given by the user as argument of the program. - - -Example from OFF file -^^^^^^^^^^^^^^^^^^^^^ - -This example builds the Delaunay triangulation from the points given by an OFF file, and initializes the alpha complex -with it. - - -Then, it is asked to display information about the alpha complex: - -.. testcode:: - - import gudhi - alpha_complex = gudhi.AlphaComplex(off_file='alphacomplexdoc.off', - max_alpha_square=59.0) - result_str = 'Alpha complex is of dimension ' + repr(alpha_complex.dimension()) + ' - ' + \ - repr(alpha_complex.num_simplices()) + ' simplices - ' + \ - repr(alpha_complex.num_vertices()) + ' vertices.' - print(result_str) - for fitered_value in alpha_complex.get_filtered_tree(): - print(fitered_value) - -the program output is: - -.. testoutput:: - - Alpha complex is of dimension 2 - 23 simplices - 7 vertices. - ([0], 0.0) - ([1], 0.0) - ([2], 0.0) - ([3], 0.0) - ([4], 0.0) - ([5], 0.0) - ([6], 0.0) - ([2, 3], 6.25) - ([4, 5], 7.25) - ([0, 2], 8.5) - ([0, 1], 9.25) - ([1, 3], 10.0) - ([1, 2], 11.25) - ([1, 2, 3], 12.5) - ([0, 1, 2], 12.995867768595042) - ([5, 6], 13.25) - ([2, 4], 20.0) - ([4, 6], 22.736686390532547) - ([4, 5, 6], 22.736686390532547) - ([3, 6], 30.25) - ([2, 6], 36.5) - ([2, 3, 6], 36.5) - ([2, 4, 6], 37.24489795918368) diff --git a/src/cython/src/doc/biblio.rst b/src/cython/src/doc/biblio.rst deleted file mode 100644 index b8e733ed..00000000 --- a/src/cython/src/doc/biblio.rst +++ /dev/null @@ -1,7 +0,0 @@ -============ -Bibliography -============ - -.. bibliography:: bibliography.bib - :filter: docnames - :style: unsrt diff --git a/src/cython/src/doc/cgal_citation.rst b/src/cython/src/doc/cgal_citation.rst deleted file mode 100644 index bbc4ef9e..00000000 --- a/src/cython/src/doc/cgal_citation.rst +++ /dev/null @@ -1,8 +0,0 @@ -============== -CGAL citations -============== - -.. - bibliography:: how_to_cite_cgal.bib - :filter: docnames - :style: unsrt diff --git a/src/cython/src/doc/conf.py b/src/cython/src/doc/conf.py deleted file mode 100755 index bc138025..00000000 --- a/src/cython/src/doc/conf.py +++ /dev/null @@ -1,271 +0,0 @@ -# -*- coding: utf-8 -*- -# -# GUDHI documentation build configuration file, created by -# sphinx-quickstart on Thu Jun 30 09:55:51 2016. -# -# This file is execfile()d with the current directory set to its -# containing dir. -# -# Note that not all possible configuration values are present in this -# autogenerated file. -# -# All configuration values have a default; values that are commented out -# serve to show the default. - -import sys -import os - -# If extensions (or modules to document with autodoc) are in another directory, -# add these directories to sys.path here. If the directory is relative to the -# documentation root, use os.path.abspath to make it absolute, like shown here. -#sys.path.insert(0, os.path.abspath('.')) - -# Path to Gudhi.so from source path -sys.path.insert(0, os.path.abspath('../..')) - -# -- General configuration ------------------------------------------------ - -# If your documentation needs a minimal Sphinx version, state it here. -#needs_sphinx = '1.0' - -# Add any Sphinx extension module names here, as strings. They can be -# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom -# ones. -extensions = [ - 'sphinx.ext.autodoc', - 'sphinx.ext.doctest', - 'sphinx.ext.todo', - 'sphinx.ext.coverage', - 'sphinx.ext.mathjax', - 'sphinx.ext.ifconfig', - 'sphinx.ext.viewcode', - 'sphinxcontrib.bibtex', -] - -todo_include_todos = True -# Add any paths that contain templates here, relative to this directory. -templates_path = ['_templates'] - -# The suffix of source filenames. -source_suffix = '.rst' - -# The encoding of source files. -#source_encoding = 'utf-8-sig' - -# The master toctree document. -master_doc = 'index' - -# General information about the project. -project = u'GUDHI' -copyright = u'2016, Vincent Rouvreau' - -# The version info for the project you're documenting, acts as replacement for -# |version| and |release|, also used in various other places throughout the -# built documents. -# -# The short X.Y version. -version = '1.3.1' -# The full version, including alpha/beta/rc tags. -release = '1.3.1' - -# The language for content autogenerated by Sphinx. Refer to documentation -# for a list of supported languages. -#language = None - -# There are two options for replacing |today|: either, you set today to some -# non-false value, then it is used: -#today = '' -# Else, today_fmt is used as the format for a strftime call. -#today_fmt = '%B %d, %Y' - -# List of patterns, relative to source directory, that match files and -# directories to ignore when looking for source files. -exclude_patterns = ['_build'] - -# The reST default role (used for this markup: `text`) to use for all -# documents. -#default_role = None - -# If true, '()' will be appended to :func: etc. cross-reference text. -#add_function_parentheses = True - -# If true, the current module name will be prepended to all description -# unit titles (such as .. function::). -#add_module_names = True - -# If true, sectionauthor and moduleauthor directives will be shown in the -# output. They are ignored by default. -#show_authors = False - -# The name of the Pygments (syntax highlighting) style to use. -pygments_style = 'sphinx' - -# A list of ignored prefixes for module index sorting. -#modindex_common_prefix = [] - -# If true, keep warnings as "system message" paragraphs in the built documents. -#keep_warnings = False - - -# -- Options for HTML output ---------------------------------------------- - -# The theme to use for HTML and HTML Help pages. See the documentation for -# a list of builtin themes. -html_theme = 'default' - -# Theme options are theme-specific and customize the look and feel of a theme -# further. For a list of options available for each theme, see the -# documentation. -#html_theme_options = {} - -# Add any paths that contain custom themes here, relative to this directory. -#html_theme_path = [] - -# The name for this set of Sphinx documents. If None, it defaults to -# " v documentation". -#html_title = None - -# A shorter title for the navigation bar. Default is the same as html_title. -#html_short_title = None - -# The name of an image file (relative to this directory) to place at the top -# of the sidebar. -#html_logo = None - -# The name of an image file (within the static path) to use as favicon of the -# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 -# pixels large. -#html_favicon = None - -# Add any paths that contain custom static files (such as style sheets) here, -# relative to this directory. They are copied after the builtin static files, -# so a file named "default.css" will overwrite the builtin "default.css". -html_static_path = ['_static'] - -# Add any extra paths that contain custom files (such as robots.txt or -# .htaccess) here, relative to this directory. These files are copied -# directly to the root of the documentation. -#html_extra_path = [] - -# If not '', a 'Last updated on:' timestamp is inserted at every page bottom, -# using the given strftime format. -#html_last_updated_fmt = '%b %d, %Y' - -# If true, SmartyPants will be used to convert quotes and dashes to -# typographically correct entities. -#html_use_smartypants = True - -# Custom sidebar templates, maps document names to template names. -#html_sidebars = {} - -# Additional templates that should be rendered to pages, maps page names to -# template names. -#html_additional_pages = {} - -# If false, no module index is generated. -#html_domain_indices = True - -# If false, no index is generated. -#html_use_index = True - -# If true, the index is split into individual pages for each letter. -#html_split_index = False - -# If true, links to the reST sources are added to the pages. -#html_show_sourcelink = True - -# If true, "Created using Sphinx" is shown in the HTML footer. Default is True. -#html_show_sphinx = True - -# If true, "(C) Copyright ..." is shown in the HTML footer. Default is True. -#html_show_copyright = True - -# If true, an OpenSearch description file will be output, and all pages will -# contain a tag referring to it. The value of this option must be the -# base URL from which the finished HTML is served. -#html_use_opensearch = '' - -# This is the file name suffix for HTML files (e.g. ".xhtml"). -#html_file_suffix = None - -# Output file base name for HTML help builder. -htmlhelp_basename = 'GUDHIdoc' - - -# -- Options for LaTeX output --------------------------------------------- - -latex_elements = { -# The paper size ('letterpaper' or 'a4paper'). -#'papersize': 'letterpaper', - -# The font size ('10pt', '11pt' or '12pt'). -#'pointsize': '10pt', - -# Additional stuff for the LaTeX preamble. -#'preamble': '', -} - -# Grouping the document tree into LaTeX files. List of tuples -# (source start file, target name, title, -# author, documentclass [howto, manual, or own class]). -latex_documents = [ - ('index', 'GUDHI.tex', u'GUDHI Documentation', - u'Vincent Rouvreau', 'manual'), -] - -# The name of an image file (relative to this directory) to place at the top of -# the title page. -#latex_logo = None - -# For "manual" documents, if this is true, then toplevel headings are parts, -# not chapters. -#latex_use_parts = False - -# If true, show page references after internal links. -#latex_show_pagerefs = False - -# If true, show URL addresses after external links. -#latex_show_urls = False - -# Documents to append as an appendix to all manuals. -#latex_appendices = [] - -# If false, no module index is generated. -#latex_domain_indices = True - - -# -- Options for manual page output --------------------------------------- - -# One entry per manual page. List of tuples -# (source start file, name, description, authors, manual section). -man_pages = [ - ('index', 'gudhi', u'GUDHI Documentation', - [u'Vincent Rouvreau'], 1) -] - -# If true, show URL addresses after external links. -#man_show_urls = False - - -# -- Options for Texinfo output ------------------------------------------- - -# Grouping the document tree into Texinfo files. List of tuples -# (source start file, target name, title, author, -# dir menu entry, description, category) -texinfo_documents = [ - ('index', 'GUDHI', u'GUDHI Documentation', - u'Vincent Rouvreau', 'GUDHI', 'One line description of project.', - 'Miscellaneous'), -] - -# Documents to append as an appendix to all manuals. -#texinfo_appendices = [] - -# If false, no module index is generated. -#texinfo_domain_indices = True - -# How to display URL addresses: 'footnote', 'no', or 'inline'. -#texinfo_show_urls = 'footnote' - -# If true, do not generate a @detailmenu in the "Top" node's menu. -#texinfo_no_detailmenu = False diff --git a/src/cython/src/doc/cubical_complex_ref.rst b/src/cython/src/doc/cubical_complex_ref.rst deleted file mode 100644 index 84aa4223..00000000 --- a/src/cython/src/doc/cubical_complex_ref.rst +++ /dev/null @@ -1,9 +0,0 @@ -Cubical complex reference manual -################################ - -.. autoclass:: gudhi.CubicalComplex - :members: - :undoc-members: - :show-inheritance: - - .. automethod:: gudhi.CubicalComplex.__init__ diff --git a/src/cython/src/doc/cubical_complex_sum.rst b/src/cython/src/doc/cubical_complex_sum.rst deleted file mode 100644 index 4008a1fd..00000000 --- a/src/cython/src/doc/cubical_complex_sum.rst +++ /dev/null @@ -1,12 +0,0 @@ -===================================== ===================================== ===================================== -:Author: Pawel Dlotko :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+---------------------------------------------+----------------------------------------------------------------------+ -| .. image:: | The cubical complex is an example of a structured complex useful in | -| img/Cubical_complex_representation.png | computational mathematics (specially rigorous numerics) and image | -| | analysis. | -+---------------------------------------------+----------------------------------------------------------------------+ -| :doc:`cubical_complex_user` | * :doc:`cubical_complex_ref` | -| | * :doc:`periodic_cubical_complex_ref` | -+---------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/src/doc/cubical_complex_user.rst b/src/cython/src/doc/cubical_complex_user.rst deleted file mode 100644 index 2cd85c0a..00000000 --- a/src/cython/src/doc/cubical_complex_user.rst +++ /dev/null @@ -1,150 +0,0 @@ -=========================== -Cubical complex user manual -=========================== -Definition ----------- - -===================================== ===================================== ===================================== -:Author: Pawel Dlotko :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+---------------------------------------------+----------------------------------------------------------------------+ -| :doc:`cubical_complex_user` | * :doc:`cubical_complex_ref` | -| | * :doc:`periodic_cubical_complex_ref` | -+---------------------------------------------+----------------------------------------------------------------------+ - -The cubical complex is an example of a structured complex useful in computational mathematics (specially rigorous -numerics) and image analysis. - -An *elementary interval* is an interval of a form :math:`[n,n+1]`, or :math:`[n,n]`, for :math:`n \in \mathcal{Z}`. -The first one is called *non-degenerate*, while the second one is a *degenerate* interval. A -*boundary of a elementary interval* is a chain :math:`\partial [n,n+1] = [n+1,n+1]-[n,n]` in case of -non-degenerated elementary interval and :math:`\partial [n,n] = 0` in case of degenerate elementary interval. An -*elementary cube* :math:`C` is a product of elementary intervals, :math:`C=I_1 \times \ldots \times I_n`. -*Embedding dimension* of a cube is n, the number of elementary intervals (degenerate or not) in the product. -A *dimension of a cube* :math:`C=I_1 \times ... \times I_n` is the number of non degenerate elementary -intervals in the product. A *boundary of a cube* :math:`C=I_1 \times \ldots \times I_n` is a chain obtained -in the following way: - -.. math:: - - \partial C = (\partial I_1 \times \ldots \times I_n) + (I_1 \times \partial I_2 \times \ldots \times I_n) + - \ldots + (I_1 \times I_2 \times \ldots \times \partial I_n). - -A *cubical complex* :math:`\mathcal{K}` is a collection of cubes closed under operation of taking boundary -(i.e. boundary of every cube from the collection is in the collection). A cube :math:`C` in cubical complex -:math:`\mathcal{K}` is *maximal* if it is not in a boundary of any other cube in :math:`\mathcal{K}`. A -*support* of a cube :math:`C` is the set in :math:`\mathbb{R}^n` occupied by :math:`C` (:math:`n` is the embedding -dimension of :math:`C`). - -Cubes may be equipped with a filtration values in which case we have filtered cubical complex. All the cubical -complexes considered in this implementation are filtered cubical complexes (although, the range of a filtration may -be a set of two elements). - -For further details and theory of cubical complexes, please consult :cite:`kaczynski2004computational` as well as the -following paper :cite:`peikert2012topological`. - -Data structure. ---------------- - -The implementation of Cubical complex provides a representation of complexes that occupy a rectangular region in -:math:`\mathbb{R}^n`. This extra assumption allows for a memory efficient way of storing cubical complexes in a form -of so called bitmaps. Let -:math:`R = [b_1,e_1] \times \ldots \times [b_n,e_n]`, for :math:`b_1,...b_n,e_1,...,e_n \in \mathbb{Z}`, -:math:`b_i \leq d_i` be the considered rectangular region and let :math:`\mathcal{K}` be a filtered -cubical complex having the rectangle :math:`R` as its support. Note that the structure of the coordinate system gives -a way a lexicographical ordering of cells of :math:`\mathcal{K}`. This ordering is a base of the presented -bitmap-based implementation. In this implementation, the whole cubical complex is stored as a vector of the values -of filtration. This, together with dimension of :math:`\mathcal{K}` and the sizes of :math:`\mathcal{K}` in all -directions, allows to determine, dimension, neighborhood, boundary and coboundary of every cube -:math:`C \in \mathcal{K}`. - -.. image:: - img/Cubical_complex_representation.png - :align: center - :alt: Cubical complex. - -Note that the cubical complex in the figure above is, in a natural way, a product of one dimensional cubical -complexes in :math:`\mathbb{R}`. The number of all cubes in each direction is equal :math:`2n+1`, where :math:`n` is -the number of maximal cubes in the considered direction. Let us consider a cube at the position :math:`k` in the -bitmap. -Knowing the sizes of the bitmap, by a series of modulo operation, we can determine which elementary intervals are -present in the product that gives the cube :math:`C`. In a similar way, we can compute boundary and the coboundary of -each cube. Further details can be found in the literature. - -Input Format. -------------- - -In the current implantation, filtration is given at the maximal cubes, and it is then extended by the lower star -filtration to all cubes. There are a number of constructors that can be used to construct cubical complex by users -who want to use the code directly. They can be found in the :doc:`cubical_complex_ref`. -Currently one input from a text file is used. It uses a format used already in -`Perseus software `_ by Vidit Nanda. -Below we are providing a description of the format. The first line contains a number d begin the dimension of the -bitmap (2 in the example below). Next d lines are the numbers of top dimensional cubes in each dimensions (3 and 3 -in the example below). Next, in lexicographical order, the filtration of top dimensional cubes is given (1 4 6 8 -20 4 7 6 5 in the example below). - -.. image:: - img/exampleBitmap.png - :align: center - :alt: Example of a input data. - -The input file for the following complex is: - -.. literalinclude:: cubicalcomplexdoc.txt - -.. centered:: cubicalcomplexdoc.txt - -.. testcode:: - - import gudhi - cubical_complex = gudhi.CubicalComplex(perseus_file='cubicalcomplexdoc.txt') - result_str = 'Cubical complex is of dimension ' + repr(cubical_complex.dimension()) + ' - ' + \ - repr(cubical_complex.num_simplices()) + ' simplices.' - print(result_str) - -the program output is: - -.. testoutput:: - - Cubical complex is of dimension 2 - 49 simplices. - -Periodic boundary conditions. ------------------------------ - -Often one would like to impose periodic boundary conditions to the cubical complex (cf. -:doc:`periodic_cubical_complex_ref`). -Let :math:`I_1\times ... \times I_n` be a box that is decomposed with a cubical complex :math:`\mathcal{K}`. -Imposing periodic boundary conditions in the direction i, means that the left and the right side of a complex -:math:`\mathcal{K}` are considered the same. In particular, if for a bitmap :math:`\mathcal{K}` periodic boundary -conditions are imposed in all directions, then complex :math:`\mathcal{K}` became n-dimensional torus. One can use -various constructors from the file Bitmap_cubical_complex_periodic_boundary_conditions_base.h to construct cubical -complex with periodic boundary conditions. One can also use Perseus style input files. To indicate periodic boundary -conditions in a given direction, then number of top dimensional cells in this direction have to be multiplied by -1. -For instance: - -.. literalinclude:: periodiccubicalcomplexdoc.txt - -.. centered:: periodiccubicalcomplexdoc.txt - -Indicate that we have imposed periodic boundary conditions in the direction x, but not in the direction y. - -.. testcode:: - - import gudhi - periodic_cc = gudhi.PeriodicCubicalComplex(perseus_file='periodiccubicalcomplexdoc.txt') - result_str = 'Periodic cubical complex is of dimension ' + repr(periodic_cc.dimension()) + ' - ' + \ - repr(periodic_cc.num_simplices()) + ' simplices.' - print(result_str) - -the program output is: - -.. testoutput:: - - Periodic cubical complex is of dimension 2 - 42 simplices. - -Examples. ---------- - -End user programs are available in cython/example/ folder. diff --git a/src/cython/src/doc/index.rst b/src/cython/src/doc/index.rst deleted file mode 100644 index 5245d69d..00000000 --- a/src/cython/src/doc/index.rst +++ /dev/null @@ -1,63 +0,0 @@ -.. GUDHI documentation master file, created by - sphinx-quickstart on Thu Jun 30 09:55:51 2016. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. - -GUDHI's documentation -##################### - -.. image:: img/Gudhi_banner.png - :align: center - -Introduction -************ - -The Gudhi library (Geometry Understanding in Higher Dimensions) is a generic -open source C++ library for Computational Topology and Topological Data -Analysis (`TDA `_). -The GUDHI library intends to help the development of new algorithmic solutions -in TDA and their transfer to applications. It provides robust, efficient, -flexible and easy to use implementations of state-of-the-art algorithms and -data structures. - -The current release of the GUDHI library includes: - -* Data structures to represent, construct and manipulate simplicial complexes. -* Algorithms to compute persistent homology and multi-field persistent homology. -* Simplication of simplicial complexes by edge contraction. - -All data-structures are generic and several of their aspects can be -parameterized via template classes. We refer to :cite:`gudhilibrary_ICMS14` -for a detailed description of the design of the library. - -Data structures -*************** - -Alpha complex -============= - -.. include:: alpha_complex_sum.rst - -Cubical complex -=============== - -.. include:: cubical_complex_sum.rst - -Simplex tree -============ - -.. include:: simplex_tree_sum.rst - -Witness complex -=============== - -.. include:: witness_complex_sum.rst - - -Toolbox -******* - -Persistence cohomology -====================== - -.. include:: persistent_cohomology_sum.rst diff --git a/src/cython/src/doc/make.bat b/src/cython/src/doc/make.bat deleted file mode 100644 index 656c0105..00000000 --- a/src/cython/src/doc/make.bat +++ /dev/null @@ -1,242 +0,0 @@ -@ECHO OFF - -REM Command file for Sphinx documentation - -if "%SPHINXBUILD%" == "" ( - set SPHINXBUILD=sphinx-build -) -set BUILDDIR=_build -set ALLSPHINXOPTS=-d %BUILDDIR%/doctrees %SPHINXOPTS% . -set I18NSPHINXOPTS=%SPHINXOPTS% . -if NOT "%PAPER%" == "" ( - set ALLSPHINXOPTS=-D latex_paper_size=%PAPER% %ALLSPHINXOPTS% - set I18NSPHINXOPTS=-D latex_paper_size=%PAPER% %I18NSPHINXOPTS% -) - -if "%1" == "" goto help - -if "%1" == "help" ( - :help - echo.Please use `make ^` where ^ is one of - echo. html to make standalone HTML files - echo. dirhtml to make HTML files named index.html in directories - echo. singlehtml to make a single large HTML file - echo. pickle to make pickle files - echo. json to make JSON files - echo. htmlhelp to make HTML files and a HTML help project - echo. qthelp to make HTML files and a qthelp project - echo. devhelp to make HTML files and a Devhelp project - echo. epub to make an epub - echo. latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter - echo. text to make text files - echo. man to make manual pages - echo. texinfo to make Texinfo files - echo. gettext to make PO message catalogs - echo. changes to make an overview over all changed/added/deprecated items - echo. xml to make Docutils-native XML files - echo. pseudoxml to make pseudoxml-XML files for display purposes - echo. linkcheck to check all external links for integrity - echo. doctest to run all doctests embedded in the documentation if enabled - goto end -) - -if "%1" == "clean" ( - for /d %%i in (%BUILDDIR%\*) do rmdir /q /s %%i - del /q /s %BUILDDIR%\* - goto end -) - - -%SPHINXBUILD% 2> nul -if errorlevel 9009 ( - echo. - echo.The 'sphinx-build' command was not found. 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The XML files are in %BUILDDIR%/xml. - goto end -) - -if "%1" == "pseudoxml" ( - %SPHINXBUILD% -b pseudoxml %ALLSPHINXOPTS% %BUILDDIR%/pseudoxml - if errorlevel 1 exit /b 1 - echo. - echo.Build finished. The pseudo-XML files are in %BUILDDIR%/pseudoxml. - goto end -) - -:end diff --git a/src/cython/src/doc/periodic_cubical_complex_ref.rst b/src/cython/src/doc/periodic_cubical_complex_ref.rst deleted file mode 100644 index c6190a1b..00000000 --- a/src/cython/src/doc/periodic_cubical_complex_ref.rst +++ /dev/null @@ -1,9 +0,0 @@ -Periodic cubical complex reference manual -######################################### - -.. autoclass:: gudhi.PeriodicCubicalComplex - :members: - :undoc-members: - :show-inheritance: - - .. automethod:: gudhi.PeriodicCubicalComplex.__init__ diff --git a/src/cython/src/doc/persistent_cohomology_sum.rst b/src/cython/src/doc/persistent_cohomology_sum.rst deleted file mode 100644 index 081399a5..00000000 --- a/src/cython/src/doc/persistent_cohomology_sum.rst +++ /dev/null @@ -1,28 +0,0 @@ -===================================== ===================================== ===================================== -:Author: Clément Maria :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+---------------------------------------------+----------------------------------------------------------------------+ -| .. image:: | The theory of homology consists in attaching to a topological space | -| img/3DTorus_poch.png | a sequence of (homology) groups, capturing global topological | -| | features like connected components, holes, cavities, etc. Persistent | -| | homology studies the evolution -- birth, life and death -- of these | -| | features when the topological space is changing. Consequently, the | -| | theory is essentially composed of three elements: topological spaces,| -| | their homology groups and an evolution scheme. | -| | | -| | Computation of persistent cohomology using the algorithm of | -| | :cite:`DBLP:journals/dcg/SilvaMV11` and | -| | :cite:`DBLP:journals/corr/abs-1208-5018` and the Compressed | -| | Annotation Matrix implementation of | -| | :cite:`DBLP:conf/esa/BoissonnatDM13`. | -| | | -+---------------------------------------------+----------------------------------------------------------------------+ -| :doc:`persistent_cohomology_user` | Please refer to each data structure that contains persistence | -| | feature for reference: | -| | | -| | * :doc:`alpha_complex_ref` | -| | * :doc:`cubical_complex_ref` | -| | * :doc:`simplex_tree_ref` | -| | * :doc:`witness_complex_ref` | -+---------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/src/doc/persistent_cohomology_user.rst b/src/cython/src/doc/persistent_cohomology_user.rst deleted file mode 100644 index 33b19ce2..00000000 --- a/src/cython/src/doc/persistent_cohomology_user.rst +++ /dev/null @@ -1,104 +0,0 @@ -================================= -Persistent cohomology user manual -================================= -Definition ----------- -===================================== ===================================== ===================================== -:Author: Clément Maria :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+---------------------------------------------+----------------------------------------------------------------------+ -| :doc:`persistent_cohomology_user` | Please refer to each data structure that contains persistence | -| | feature for reference: | -| | | -| | * :doc:`alpha_complex_ref` | -| | * :doc:`cubical_complex_ref` | -| | * :doc:`simplex_tree_ref` | -| | * :doc:`witness_complex_ref` | -+---------------------------------------------+----------------------------------------------------------------------+ - - -Computation of persistent cohomology using the algorithm of :cite:`DBLP:journals/dcg/SilvaMV11` and -:cite:`DBLP:journals/corr/abs-1208-5018` and the Compressed Annotation Matrix implementation of -:cite:`DBLP:conf/esa/BoissonnatDM13`. - -The theory of homology consists in attaching to a topological space a sequence of (homology) groups, capturing global -topological features like connected components, holes, cavities, etc. Persistent homology studies the evolution -- -birth, life and death -- of these features when the topological space is changing. Consequently, the theory is -essentially composed of three elements: - -* topological spaces -* their homology groups -* an evolution scheme. - -Topological Spaces ------------------- - -Topological spaces are represented by simplicial complexes. -Let :math:`V = \{1, \cdots ,|V|\}` be a set of *vertices*. -A *simplex* :math:`\sigma` is a subset of vertices :math:`\sigma \subseteq V`. -A *simplicial complex* :math:`\mathbf{K}` on :math:`V` is a collection of simplices :math:`\{\sigma\}`, -:math:`\sigma \subseteq V`, such that :math:`\tau \subseteq \sigma \in \mathbf{K} \Rightarrow \tau \in \mathbf{K}`. -The dimension :math:`n=|\sigma|-1` of :math:`\sigma` is its number of elements minus 1. -A *filtration* of a simplicial complex is a function :math:`f:\mathbf{K} \rightarrow \mathbb{R}` satisfying -:math:`f(\tau)\leq f(\sigma)` whenever :math:`\tau \subseteq \sigma`. - -Homology --------- - -For a ring :math:`\mathcal{R}`, the group of *n-chains*, denoted :math:`\mathbf{C}_n(\mathbf{K},\mathcal{R})`, of -:math:`\mathbf{K}` is the group of formal sums of n-simplices with :math:`\mathcal{R}` coefficients. The -*boundary operator* is a linear operator -:math:`\partial_n: \mathbf{C}_n(\mathbf{K},\mathcal{R}) \rightarrow \mathbf{C}_{n-1}(\mathbf{K},\mathcal{R})` -such that :math:`\partial_n \sigma = \partial_n [v_0, \cdots , v_n] = \sum_{i=0}^n (-1)^{i}[v_0,\cdots ,\widehat{v_i}, \cdots,v_n]`, -where :math:`\widehat{v_i}` means :math:`v_i` is omitted from the list. The chain groups form a sequence: - -.. math:: - - \cdots \ \ \mathbf{C}_n(\mathbf{K},\mathcal{R}) \xrightarrow{\ \partial_n\ } - \mathbf{C}_{n-1}(\mathbf{K},\mathcal{R}) \xrightarrow{\partial_{n-1}} \cdots \xrightarrow{\ \partial_2 \ } - \mathbf{C}_1(\mathbf{K},\mathcal{R}) \xrightarrow{\ \partial_1 \ } \mathbf{C}_0(\mathbf{K},\mathcal{R}) - -of finitely many groups :math:`\mathbf{C}_n(\mathbf{K},\mathcal{R})` and homomorphisms :math:`\partial_n`, indexed by -the dimension :math:`n \geq 0`. The boundary operators satisfy the property :math:`\partial_n \circ \partial_{n+1}=0` -for every :math:`n > 0` and we define the homology groups: - -.. math:: - - \mathbf{H}_n(\mathbf{K},\mathcal{R}) = \ker \partial_n / \mathrm{im} \ \partial_{n+1} - -We refer to :cite:`Munkres-elementsalgtop1984` for an introduction to homology -theory and to :cite:`DBLP:books/daglib/0025666` for an introduction to persistent homology. - -Indexing Scheme ---------------- - -"Changing" a simplicial complex consists in applying a simplicial map. An *indexing scheme* is a directed graph -together with a traversal order, such that two consecutive nodes in the graph are connected by an arrow (either forward -or backward). -The nodes represent simplicial complexes and the directed edges simplicial maps. - -From the computational point of view, there are two types of indexing schemes of interest in persistent homology: - -* linear ones - :math:`\bullet \longrightarrow \bullet \longrightarrow \cdots \longrightarrow \bullet \longrightarrow \bullet` - in persistent homology :cite:`DBLP:journals/dcg/ZomorodianC05`, -* zigzag ones - :math:`\bullet \longrightarrow \bullet \longleftarrow \cdots \longrightarrow \bullet \longleftarrow \bullet` - in zigzag persistent homology :cite:`DBLP:journals/focm/CarlssonS10`. - -These indexing schemes have a natural left-to-right traversal order, and we describe them with ranges and iterators. -In the current release of the Gudhi library, only the linear case is implemented. - -In the following, we consider the case where the indexing scheme is induced by a filtration. - -Ordering the simplices by increasing filtration values (breaking ties so as a simplex appears after its subsimplices of -same filtration value) provides an indexing scheme. - -Examples --------- - -We provide several example files: run these examples with -h for details on their use. - -.. todo:: - examples for persistence diff --git a/src/cython/src/doc/simplex_tree_ref.rst b/src/cython/src/doc/simplex_tree_ref.rst deleted file mode 100644 index 6d196843..00000000 --- a/src/cython/src/doc/simplex_tree_ref.rst +++ /dev/null @@ -1,10 +0,0 @@ -============================= -Simplex tree reference manual -============================= - -.. autoclass:: gudhi.SimplexTree - :members: - :undoc-members: - :show-inheritance: - - .. automethod:: gudhi.SimplexTree.__init__ diff --git a/src/cython/src/doc/simplex_tree_sum.rst b/src/cython/src/doc/simplex_tree_sum.rst deleted file mode 100644 index ffdb2cf4..00000000 --- a/src/cython/src/doc/simplex_tree_sum.rst +++ /dev/null @@ -1,13 +0,0 @@ -===================================== ===================================== ===================================== -:Author: Clément Maria :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+-------------------------------------------+----------------------------------------------------------------------+ -| .. image:: | The simplex tree is an efficient and flexible data structure for | -| img/Simplex_tree_representation.png | representing general (filtered) simplicial complexes. | -| | | -| | The data structure is described in | -| | :cite:`boissonnatmariasimplextreealgorithmica` | -+-------------------------------------------+----------------------------------------------------------------------+ -| :doc:`simplex_tree_user` | :doc:`simplex_tree_ref` | -+-------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/src/doc/simplex_tree_user.rst b/src/cython/src/doc/simplex_tree_user.rst deleted file mode 100644 index 3a00f1ac..00000000 --- a/src/cython/src/doc/simplex_tree_user.rst +++ /dev/null @@ -1,67 +0,0 @@ -======================== -Simplex tree user manual -======================== -Definition ----------- - -.. include:: simplex_tree_sum.rst - -A simplicial complex :math:`\mathbf{K}` on a set of vertices :math:`V = \{1, \cdots ,|V|\}` is a collection of -simplices :math:`\{\sigma\}`, :math:`\sigma \subseteq V` such that -:math:`\tau \subseteq \sigma \in \mathbf{K} \rightarrow \tau \in \mathbf{K}`. The dimension :math:`n=|\sigma|-1` of -:math:`\sigma` is its number of elements minus `1`. - -A filtration of a simplicial complex is a function :math:`f:\mathbf{K} \rightarrow \mathbb{R}` satisfying -:math:`f(\tau)\leq f(\sigma)` whenever :math:`\tau \subseteq \sigma`. Ordering the simplices by increasing filtration -values (breaking ties so as a simplex appears after its subsimplices of same filtration value) provides an indexing -scheme. - - -Implementation --------------- - -There are two implementation of complexes. The first on is the Simplex_tree data structure. -The simplex tree is an efficient and flexible data structure for representing general (filtered) simplicial complexes. -The data structure is described in :cite`boissonnatmariasimplextreealgorithmica`. - -The second one is the Hasse_complex. The Hasse complex is a data structure representing explicitly all co-dimension 1 -incidence relations in a complex. It is consequently faster when accessing the boundary of a simplex, but is less -compact and harder to construct from scratch. - -Example -------- - -.. testcode:: - - import gudhi - st = gudhi.SimplexTree() - if st.insert([0, 1]): - print("[0, 1] inserted") - if st.insert([0, 1, 2], filtration=4.0): - print("[0, 1, 2] inserted") - if st.find([0, 1]): - print("[0, 1] found") - print("num_vertices=", st.num_vertices()) - print("num_simplices=", st.num_simplices()) - print("skeleton_tree(2) =") - for sk_value in st.get_skeleton_tree(2): - print(sk_value) - - -The output is: - -.. testoutput:: - - [0, 1] inserted - [0, 1, 2] inserted - [0, 1] found - ('num_vertices=', 3) - ('num_simplices=', 7) - skeleton_tree(2) = - ([0, 1, 2], 4.0) - ([0, 1], 0.0) - ([0, 2], 4.0) - ([0], 0.0) - ([1, 2], 4.0) - ([1], 0.0) - ([2], 4.0) diff --git a/src/cython/src/doc/witness_complex_ref.rst b/src/cython/src/doc/witness_complex_ref.rst deleted file mode 100644 index c78760cb..00000000 --- a/src/cython/src/doc/witness_complex_ref.rst +++ /dev/null @@ -1,10 +0,0 @@ -================================ -Witness complex reference manual -================================ - -.. autoclass:: gudhi.WitnessComplex - :members: - :undoc-members: - :show-inheritance: - - .. automethod:: gudhi.WitnessComplex.__init__ diff --git a/src/cython/src/doc/witness_complex_sum.rst b/src/cython/src/doc/witness_complex_sum.rst deleted file mode 100644 index 0d65d420..00000000 --- a/src/cython/src/doc/witness_complex_sum.rst +++ /dev/null @@ -1,25 +0,0 @@ -===================================== ===================================== ===================================== -:Author: Siargey Kachanovich :Introduced in: GUDHI PYTHON 1.4.0 :Copyright: GPL v3 -===================================== ===================================== ===================================== - -+---------------------------------------------+----------------------------------------------------------------------+ -| .. image:: | Witness complex :math:`Wit(W,L)` is a simplicial complex defined on | -| img/Witness_complex_representation.png | two sets of points in :math:`\mathbb{R}^D`:Wit(W,L)` is a simplicial | -| | complex defined on two sets of points in :math:`\mathbb{R}^D`: | -| | | -| | * :math:`W` set of **witnesses** and | -| | * :math:`L \subseteq W` set of **landmarks**. | -| | | -| | The simplices are based on landmarks and a simplex belongs to the | -| | witness complex if and only if it is witnessed, that is: | -| | | -| | :math:`\sigma \subset L` is witnessed if there exists a point | -| | :math:`w \in W` such that w is closer to the vertices of | -| | :math:`\sigma` than other points in :math:`L` and all of its faces | -| | are witnessed as well. | -| | | -| | The data structure is described in | -| | :cite:`boissonnatmariasimplextreealgorithmica`. | -+---------------------------------------------+----------------------------------------------------------------------+ -| :doc:`witness_complex_user` | :doc:`witness_complex_ref` | -+---------------------------------------------+----------------------------------------------------------------------+ diff --git a/src/cython/src/doc/witness_complex_user.rst b/src/cython/src/doc/witness_complex_user.rst deleted file mode 100644 index 604c7357..00000000 --- a/src/cython/src/doc/witness_complex_user.rst +++ /dev/null @@ -1,31 +0,0 @@ -=========================== -Witness complex user manual -=========================== -Definition ----------- - -.. include:: witness_complex_sum.rst - -Implementation --------------- - -The principal class of this module is Gudhi::Witness_complex. - -In both cases, the constructor for this class takes a {witness}x{closest_landmarks} table, where each row represents a -witness and consists of landmarks sorted by distance to this witness. - -.. todo:: - This table can be constructed by two additional classes Landmark_choice_by_furthest_point and - Landmark_choice_by_random_point also included in the module. - -.. figure:: - img/bench_Cy8.png - :align: center - - Running time as function on number of landmarks. - -.. figure:: - img/bench_sphere.png - :align: center - - Running time as function on number of witnesses for |L|=300. diff --git a/src/cython/src/include/Alpha_complex_interface.h b/src/cython/src/include/Alpha_complex_interface.h deleted file mode 100644 index e2e6d100..00000000 --- a/src/cython/src/include/Alpha_complex_interface.h +++ /dev/null @@ -1,142 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Vincent Rouvreau - * - * Copyright (C) 2016 INRIA - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see . - */ - -#ifndef ALPHA_COMPLEX_INTERFACE_H -#define ALPHA_COMPLEX_INTERFACE_H - -#include -#include - -#include -#include // std::pair -#include - -namespace Gudhi { - -namespace alpha_complex { - -class Alpha_complex_interface : public Alpha_complex< CGAL::Epick_d< CGAL::Dynamic_dimension_tag > > { - using Alpha_complex = Alpha_complex< CGAL::Epick_d< CGAL::Dynamic_dimension_tag > > ; - typedef typename Alpha_complex::Simplex_handle Simplex_handle; - typedef typename std::pair Insertion_result; - using Simplex = std::vector; - using Filtered_complex = std::pair; - using Complex_tree = std::vector; - using Point_d = Alpha_complex::Point_d; - - public: - - Alpha_complex_interface(std::vector>&points, double max_alpha_square) - : Alpha_complex(points, max_alpha_square) { - } - - // bool from_file is a workaround fro cython to find the correct signature - Alpha_complex_interface(const std::string& off_file, double max_alpha_square, bool from_file) - : Alpha_complex(off_file, max_alpha_square) { - } - - bool find_simplex(const Simplex& vh) { - return (Alpha_complex::find(vh) != Alpha_complex::null_simplex()); - } - - bool insert_simplex_and_subfaces(const Simplex& complex, Filtration_value filtration = 0) { - Insertion_result result = Alpha_complex::insert_simplex_and_subfaces(complex, filtration); - return (result.second); - } - - Filtration_value simplex_filtration(const Simplex& complex) { - return Alpha_complex::filtration(Alpha_complex::find(complex)); - } - - void remove_maximal_simplex(const Simplex& complex) { - return Alpha_complex::remove_maximal_simplex(Alpha_complex::find(complex)); - } - - Complex_tree get_filtered_tree() { - Complex_tree filtered_tree; - for (auto f_simplex : Alpha_complex::filtration_simplex_range()) { - Simplex simplex; - for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - filtered_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); - } - return filtered_tree; - - } - - Complex_tree get_skeleton_tree(int dimension) { - Complex_tree skeleton_tree; - for (auto f_simplex : Alpha_complex::skeleton_simplex_range(dimension)) { - Simplex simplex; - for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - skeleton_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); - } - return skeleton_tree; - } - - Complex_tree get_star_tree(const Simplex& complex) { - Complex_tree star_tree; - for (auto f_simplex : Alpha_complex::star_simplex_range(Alpha_complex::find(complex))) { - Simplex simplex; - for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - star_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); - } - return star_tree; - } - - Complex_tree get_coface_tree(const Simplex& complex, int dimension) { - Complex_tree coface_tree; - for (auto f_simplex : Alpha_complex::cofaces_simplex_range(Alpha_complex::find(complex), dimension)) { - Simplex simplex; - for (auto vertex : Alpha_complex::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - coface_tree.push_back(std::make_pair(simplex, Alpha_complex::filtration(f_simplex))); - } - return coface_tree; - } - - std::vector get_point(int vh) { - std::vector vd; - try { - Point_d ph = Alpha_complex::get_point(vh); - for (auto coord = ph.cartesian_begin(); coord < ph.cartesian_end(); coord++) - vd.push_back(*coord); - } catch (std::out_of_range outofrange) { - // std::out_of_range is thrown in case not found. Other exceptions must be re-thrown - } - return vd; - } - -}; - -} // namespace alpha_complex - -} // namespace Gudhi - -#endif // ALPHA_COMPLEX_INTERFACE_H - diff --git a/src/cython/src/include/Cubical_complex_interface.h b/src/cython/src/include/Cubical_complex_interface.h deleted file mode 100644 index 5d17ff6b..00000000 --- a/src/cython/src/include/Cubical_complex_interface.h +++ /dev/null @@ -1,58 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Vincent Rouvreau - * - * Copyright (C) 2016 INRIA - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see . - */ - -#ifndef CUBICAL_COMPLEX_INTERFACE_H -#define CUBICAL_COMPLEX_INTERFACE_H - -#include -#include -#include - -#include -#include // std::pair -#include - -namespace Gudhi { - -namespace cubical_complex { - -template> -class Cubical_complex_interface : public Bitmap_cubical_complex { - public: - - Cubical_complex_interface(const std::vector& dimensions, - const std::vector& top_dimensional_cells) - : Bitmap_cubical_complex(dimensions, top_dimensional_cells) { - } - - Cubical_complex_interface(const std::string& perseus_file) - : Bitmap_cubical_complex(perseus_file.c_str()) { - } - -}; - -} // namespace cubical_complex - -} // namespace Gudhi - -#endif // CUBICAL_COMPLEX_INTERFACE_H - diff --git a/src/cython/src/include/Persistent_cohomology_interface.h b/src/cython/src/include/Persistent_cohomology_interface.h deleted file mode 100644 index 58421799..00000000 --- a/src/cython/src/include/Persistent_cohomology_interface.h +++ /dev/null @@ -1,90 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Vincent Rouvreau - * - * Copyright (C) 2016 INRIA - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see . - */ - -#ifndef PERSISTENT_COHOMOLOGY_INTERFACE_H -#define PERSISTENT_COHOMOLOGY_INTERFACE_H - -#include - -#include -#include // for std::pair - -namespace Gudhi { - -template -class Persistent_cohomology_interface : public -persistent_cohomology::Persistent_cohomology { - private: - /* - * Compare two intervals by dimension, then by length. - */ - struct cmp_intervals_by_dim_then_length { - - explicit cmp_intervals_by_dim_then_length(FilteredComplex * sc) - : sc_(sc) { } - - template - bool operator()(const Persistent_interval & p1, const Persistent_interval & p2) { - if (sc_->dimension(get < 0 > (p1)) == sc_->dimension(get < 0 > (p2))) - return (sc_->filtration(get < 1 > (p1)) - sc_->filtration(get < 0 > (p1)) - > sc_->filtration(get < 1 > (p2)) - sc_->filtration(get < 0 > (p2))); - else - return (sc_->dimension(get < 0 > (p1)) > sc_->dimension(get < 0 > (p2))); - } - FilteredComplex* sc_; - }; - - public: - - Persistent_cohomology_interface(FilteredComplex* stptr) - : persistent_cohomology::Persistent_cohomology(*stptr), - stptr_(stptr) { } - - std::vector>> get_persistence(int homology_coeff_field, double min_persistence) { - persistent_cohomology::Persistent_cohomology::init_coefficients(homology_coeff_field); - persistent_cohomology::Persistent_cohomology::compute_persistent_cohomology(min_persistence); - - // Custom sort and output persistence - cmp_intervals_by_dim_then_length cmp(stptr_); - auto persistent_pairs = persistent_cohomology::Persistent_cohomology::get_persistent_pairs(); - std::sort(std::begin(persistent_pairs), std::end(persistent_pairs), cmp); - - std::vector>> persistence; - for (auto pair : persistent_pairs) { - persistence.push_back(std::make_pair(stptr_->dimension(get<0>(pair)), - std::make_pair(stptr_->filtration(get<0>(pair)), - stptr_->filtration(get<1>(pair))))); - } - return persistence; - - } - - private: - // A copy - FilteredComplex* stptr_; - -}; - -} // namespace Gudhi - -#endif // PERSISTENT_COHOMOLOGY_INTERFACE_H - diff --git a/src/cython/src/include/Simplex_tree_interface.h b/src/cython/src/include/Simplex_tree_interface.h deleted file mode 100644 index 9aee630b..00000000 --- a/src/cython/src/include/Simplex_tree_interface.h +++ /dev/null @@ -1,132 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Vincent Rouvreau - * - * Copyright (C) 2016 INRIA - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see . - */ - -#ifndef SIMPLEX_TREE_INTERFACE_H -#define SIMPLEX_TREE_INTERFACE_H - -#include -#include -#include - -#include -#include // std::pair -#include - -namespace Gudhi { - -template -class Simplex_tree_interface : public Simplex_tree { - typedef typename Simplex_tree::Simplex_handle Simplex_handle; - typedef typename std::pair Insertion_result; - using Simplex = std::vector; - using Filtered_complex = std::pair; - using Complex_tree = std::vector; - - public: - - bool find_simplex(const Simplex& vh) { - return (Simplex_tree::find(vh) != Simplex_tree::null_simplex()); - } - - bool insert_simplex_and_subfaces(const Simplex& complex, Filtration_value filtration = 0) { - Insertion_result result = Simplex_tree::insert_simplex_and_subfaces(complex, filtration); - return (result.second); - } - - Filtration_value simplex_filtration(const Simplex& complex) { - return Simplex_tree::filtration(Simplex_tree::find(complex)); - } - - void remove_maximal_simplex(const Simplex& complex) { - return Simplex_tree::remove_maximal_simplex(Simplex_tree::find(complex)); - } - - Complex_tree get_filtered_tree() { - Complex_tree filtered_tree; - for (auto f_simplex : Simplex_tree::filtration_simplex_range()) { - Simplex simplex; - for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - filtered_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); - } - return filtered_tree; - - } - - Complex_tree get_skeleton_tree(int dimension) { - Complex_tree skeleton_tree; - for (auto f_simplex : Simplex_tree::skeleton_simplex_range(dimension)) { - Simplex simplex; - for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - skeleton_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); - } - return skeleton_tree; - } - - Complex_tree get_star_tree(const Simplex& complex) { - Complex_tree star_tree; - for (auto f_simplex : Simplex_tree::star_simplex_range(Simplex_tree::find(complex))) { - Simplex simplex; - for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - star_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); - } - return star_tree; - } - - Complex_tree get_coface_tree(const Simplex& complex, int dimension) { - Complex_tree coface_tree; - for (auto f_simplex : Simplex_tree::cofaces_simplex_range(Simplex_tree::find(complex), dimension)) { - Simplex simplex; - for (auto vertex : Simplex_tree::simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - coface_tree.push_back(std::make_pair(simplex, Simplex_tree::filtration(f_simplex))); - } - return coface_tree; - } - - void graph_expansion(std::vector>&points, int max_dimension, double max_edge_length) { - Graph_t prox_graph = compute_proximity_graph(points, max_edge_length, euclidean_distance>); - Simplex_tree::insert_graph(prox_graph); - Simplex_tree::expansion(max_dimension); - Simplex_tree::initialize_filtration(); - } - -}; - -struct Simplex_tree_options_mini : Simplex_tree_options_full_featured { - // Not doing persistence, so we don't need those - static const bool store_key = true; - static const bool store_filtration = false; - // I have few vertices - typedef short Vertex_handle; -}; - -} // namespace Gudhi - -#endif // SIMPLEX_TREE_INTERFACE_H - diff --git a/src/cython/src/include/Witness_complex_interface.h b/src/cython/src/include/Witness_complex_interface.h deleted file mode 100644 index bdfea91f..00000000 --- a/src/cython/src/include/Witness_complex_interface.h +++ /dev/null @@ -1,187 +0,0 @@ -/* This file is part of the Gudhi Library. The Gudhi library - * (Geometric Understanding in Higher Dimensions) is a generic C++ - * library for computational topology. - * - * Author(s): Vincent Rouvreau - * - * Copyright (C) 2016 INRIA - * - * This program is free software: you can redistribute it and/or modify - * it under the terms of the GNU General Public License as published by - * the Free Software Foundation, either version 3 of the License, or - * (at your option) any later version. - * - * This program is distributed in the hope that it will be useful, - * but WITHOUT ANY WARRANTY; without even the implied warranty of - * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the - * GNU General Public License for more details. - * - * You should have received a copy of the GNU General Public License - * along with this program. If not, see . - */ - -#ifndef WITNESS_COMPLEX_INTERFACE_H -#define WITNESS_COMPLEX_INTERFACE_H - -#include -#include -#include - -#include "Persistent_cohomology_interface.h" - -#include -#include // std::pair -#include - -namespace Gudhi { - -namespace witness_complex { - -class Witness_complex_interface { - typedef typename Simplex_tree<>::Simplex_handle Simplex_handle; - typedef typename std::pair Insertion_result; - using Simplex = std::vector; - using Filtered_complex = std::pair; - using Complex_tree = std::vector; - - public: - Witness_complex_interface(std::vector>&points, int number_of_landmarks) - : pcoh_(nullptr) { - std::vector > knn; - - Gudhi::witness_complex::landmark_choice_by_furthest_point(points, number_of_landmarks, knn); - Gudhi::witness_complex::witness_complex(knn, number_of_landmarks, points[0].size(), simplex_tree_); - - } - - bool find_simplex(const Simplex& vh) { - return (simplex_tree_.find(vh) != simplex_tree_.null_simplex()); - } - - bool insert_simplex_and_subfaces(const Simplex& complex, Filtration_value filtration = 0) { - Insertion_result result = simplex_tree_.insert_simplex_and_subfaces(complex, filtration); - return (result.second); - } - - Filtration_value simplex_filtration(const Simplex& complex) { - return simplex_tree_.filtration(simplex_tree_.find(complex)); - } - - void remove_maximal_simplex(const Simplex& complex) { - return simplex_tree_.remove_maximal_simplex(simplex_tree_.find(complex)); - } - - Complex_tree get_filtered_tree() { - Complex_tree filtered_tree; - for (auto f_simplex : simplex_tree_.filtration_simplex_range()) { - Simplex simplex; - for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - filtered_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); - } - return filtered_tree; - - } - - Complex_tree get_skeleton_tree(int dimension) { - Complex_tree skeleton_tree; - for (auto f_simplex : simplex_tree_.skeleton_simplex_range(dimension)) { - Simplex simplex; - for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - skeleton_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); - } - return skeleton_tree; - } - - Complex_tree get_star_tree(const Simplex& complex) { - Complex_tree star_tree; - for (auto f_simplex : simplex_tree_.star_simplex_range(simplex_tree_.find(complex))) { - Simplex simplex; - for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - star_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); - } - return star_tree; - } - - Complex_tree get_coface_tree(const Simplex& complex, int dimension) { - Complex_tree coface_tree; - for (auto f_simplex : simplex_tree_.cofaces_simplex_range(simplex_tree_.find(complex), dimension)) { - Simplex simplex; - for (auto vertex : simplex_tree_.simplex_vertex_range(f_simplex)) { - simplex.insert(simplex.begin(), vertex); - } - coface_tree.push_back(std::make_pair(simplex, simplex_tree_.filtration(f_simplex))); - } - return coface_tree; - } - - // Specific to Witness complex because no inheritance - Filtration_value filtration() const { - return simplex_tree_.filtration(); - } - - void set_filtration(Filtration_value fil) { - simplex_tree_.set_filtration(fil); - } - - void initialize_filtration() { - simplex_tree_.initialize_filtration(); - } - - size_t num_vertices() const { - return simplex_tree_.num_vertices(); - } - - size_t num_simplices() { - return simplex_tree_.num_simplices(); - } - - int dimension() const { - return simplex_tree_.dimension(); - } - - void set_dimension(int dimension) { - simplex_tree_.set_dimension(dimension); - } - - std::vector>> get_persistence(int homology_coeff_field, double min_persistence) { - if (pcoh_ != nullptr) { - delete pcoh_; - } - pcoh_ = new Persistent_cohomology_interface>(&simplex_tree_); - return pcoh_->get_persistence(homology_coeff_field, min_persistence); - } - - std::vector get_betti_numbers() const { - if (pcoh_ != nullptr) { - return pcoh_->betti_numbers(); - } - std::vector betti_numbers; - return betti_numbers; - } - - std::vector get_persistent_betti_numbers(Filtration_value from, Filtration_value to) const { - if (pcoh_ != nullptr) { - return pcoh_->persistent_betti_numbers(from, to); - } - std::vector persistent_betti_numbers; - return persistent_betti_numbers; - } - - private: - Simplex_tree<> simplex_tree_; - Persistent_cohomology_interface>* pcoh_; - -}; - -} // namespace witness_complex - -} // namespace Gudhi - -#endif // WITNESS_COMPLEX_INTERFACE_H - -- cgit v1.2.3