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Diffstat (limited to 'src/python/gudhi/simplex_tree.pyx')
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diff --git a/src/python/gudhi/simplex_tree.pyx b/src/python/gudhi/simplex_tree.pyx new file mode 100644 index 00000000..9f490271 --- /dev/null +++ b/src/python/gudhi/simplex_tree.pyx @@ -0,0 +1,508 @@ +from libc.stdint cimport intptr_t +from numpy import array as np_array +cimport simplex_tree + +""" This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT. + See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details. + Author(s): Vincent Rouvreau + + Copyright (C) 2016 Inria + + Modification(s): + - YYYY/MM Author: Description of the modification +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2016 Inria" +__license__ = "MIT" + +# 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. + """ + # unfortunately 'cdef public Simplex_tree_interface_full_featured* thisptr' is not possible + # Use intptr_t instead to cast the pointer + cdef public intptr_t thisptr + + # Get the pointer casted as it should be + cdef Simplex_tree_interface_full_featured* get_ptr(self): + return <Simplex_tree_interface_full_featured*>(self.thisptr) + + cdef Simplex_tree_persistence_interface * pcohptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self): + """SimplexTree constructor. + """ + + # The real cython constructor + def __cinit__(self): + self.thisptr = <intptr_t>(new Simplex_tree_interface_full_featured()) + + def __dealloc__(self): + cdef Simplex_tree_interface_full_featured* ptr = self.get_ptr() + if ptr != NULL: + del ptr + if self.pcohptr != NULL: + del self.pcohptr + + def __is_defined(self): + """Returns true if SimplexTree pointer is not NULL. + """ + return self.get_ptr() != NULL + + def __is_persistence_defined(self): + """Returns true if Persistence pointer is not NULL. + """ + return self.pcohptr != NULL + + def filtration(self, simplex): + """This function returns the filtration value for a given N-simplex in + this simplicial complex, or +infinity if it is not in the complex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: The simplicial complex filtration value. + :rtype: float + """ + return self.get_ptr().simplex_filtration(simplex) + + def assign_filtration(self, simplex, filtration): + """This function assigns 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. + :param filtration: The simplicial complex filtration value. + :type filtration: float + """ + self.get_ptr().assign_simplex_filtration(simplex, filtration) + + def initialize_filtration(self): + """This function initializes and sorts the simplicial complex + filtration vector. + + .. note:: + + This function must be launched before + :func:`persistence()<gudhi.SimplexTree.persistence>`, + :func:`betti_numbers()<gudhi.SimplexTree.betti_numbers>`, + :func:`persistent_betti_numbers()<gudhi.SimplexTree.persistent_betti_numbers>`, + or :func:`get_filtration()<gudhi.SimplexTree.get_filtration>` + after :func:`inserting<gudhi.SimplexTree.insert>` or + :func:`removing<gudhi.SimplexTree.remove_maximal_simplex>` + simplices. + """ + self.get_ptr().initialize_filtration() + + def num_vertices(self): + """This function returns the number of vertices of the simplicial + complex. + + :returns: The simplicial complex number of vertices. + :rtype: int + """ + return self.get_ptr().num_vertices() + + def num_simplices(self): + """This function returns the number of simplices of the simplicial + complex. + + :returns: the simplicial complex number of simplices. + :rtype: int + """ + return self.get_ptr().num_simplices() + + def dimension(self): + """This function returns the dimension of the simplicial complex. + + :returns: the simplicial complex dimension. + :rtype: int + + .. note:: + + This function is not constant time because it can recompute + dimension if required (can be triggered by + :func:`remove_maximal_simplex()<gudhi.SimplexTree.remove_maximal_simplex>` + or + :func:`prune_above_filtration()<gudhi.SimplexTree.prune_above_filtration>` + methods). + """ + return self.get_ptr().dimension() + + def upper_bound_dimension(self): + """This function returns a valid dimension upper bound of the + simplicial complex. + + :returns: an upper bound on the dimension of the simplicial complex. + :rtype: int + """ + return self.get_ptr().upper_bound_dimension() + + def set_dimension(self, dimension): + """This function sets the dimension of the simplicial complex. + + :param dimension: The new dimension value. + :type dimension: int. + + .. note:: + + This function must be used with caution because it disables + dimension recomputation when required + (this recomputation can be triggered by + :func:`remove_maximal_simplex()<gudhi.SimplexTree.remove_maximal_simplex>` + or + :func:`prune_above_filtration()<gudhi.SimplexTree.prune_above_filtration>` + ). + """ + self.get_ptr().set_dimension(<int>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: true if the simplex was found, false otherwise. + :rtype: bool + """ + cdef vector[int] csimplex + for i in simplex: + csimplex.push_back(i) + return self.get_ptr().find_simplex(csimplex) + + def insert(self, simplex, filtration=0.0): + """This function inserts the given N-simplex and its subfaces with the + given filtration value (default value is '0.0'). If some of those + simplices are already present with a higher filtration value, their + filtration value is lowered. + + :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: true if the simplex was not yet in the complex, false + otherwise (whatever its original filtration value). + :rtype: bool + """ + cdef vector[int] csimplex + for i in simplex: + csimplex.push_back(i) + return self.get_ptr().insert_simplex_and_subfaces(csimplex, + <double>filtration) + + def get_filtration(self): + """This function returns a list of all simplices with their given + filtration values. + + :returns: The simplices sorted by increasing filtration values. + :rtype: list of tuples(simplex, filtration) + """ + cdef vector[pair[vector[int], double]] filtration \ + = self.get_ptr().get_filtration() + ct = [] + for filtered_complex in filtration: + v = [] + for vertex in filtered_complex.first: + v.append(vertex) + ct.append((v, filtered_complex.second)) + return ct + + def get_skeleton(self, dimension): + """This function returns the (simplices of the) skeleton of a maximum + given dimension. + + :param dimension: The skeleton dimension value. + :type dimension: int. + :returns: The (simplices of the) skeleton of a maximum dimension. + :rtype: list of tuples(simplex, filtration) + """ + cdef vector[pair[vector[int], double]] skeleton \ + = self.get_ptr().get_skeleton(<int>dimension) + ct = [] + for filtered_simplex in skeleton: + v = [] + for vertex in filtered_simplex.first: + v.append(vertex) + ct.append((v, filtered_simplex.second)) + return ct + + def get_star(self, simplex): + """This function returns the star of a given N-simplex. + + :param simplex: The N-simplex, represented by a list of vertex. + :type simplex: list of int. + :returns: The (simplices of the) star of a simplex. + :rtype: list of tuples(simplex, filtration) + """ + cdef vector[int] csimplex + for i in simplex: + csimplex.push_back(i) + cdef vector[pair[vector[int], double]] star \ + = self.get_ptr().get_star(csimplex) + ct = [] + for filtered_simplex in star: + v = [] + for vertex in filtered_simplex.first: + v.append(vertex) + ct.append((v, filtered_simplex.second)) + return ct + + def get_cofaces(self, simplex, codimension): + """This function returns the cofaces 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 function) + :type codimension: int. + :returns: The (simplices of the) cofaces of a simplex + :rtype: list of tuples(simplex, filtration) + """ + cdef vector[int] csimplex + for i in simplex: + csimplex.push_back(i) + cdef vector[pair[vector[int], double]] cofaces \ + = self.get_ptr().get_cofaces(csimplex, <int>codimension) + ct = [] + for filtered_simplex in cofaces: + v = [] + for vertex in filtered_simplex.first: + v.append(vertex) + ct.append((v, filtered_simplex.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. + + .. note:: + + Be aware that removing is shifting data in a flat_map + (:func:`initialize_filtration()<gudhi.SimplexTree.initialize_filtration>` to be done). + + .. note:: + + The dimension of the simplicial complex may be lower after calling + remove_maximal_simplex than it was before. However, + :func:`upper_bound_dimension()<gudhi.SimplexTree.upper_bound_dimension>` + method will return the old value, which + remains a valid upper bound. If you care, you can call + :func:`dimension()<gudhi.SimplexTree.dimension>` + to recompute the exact dimension. + """ + self.get_ptr().remove_maximal_simplex(simplex) + + def prune_above_filtration(self, filtration): + """Prune above filtration value given as parameter. + + :param filtration: Maximum threshold value. + :type filtration: float. + :returns: The filtration modification information. + :rtype: bool + + + .. note:: + + Some simplex tree functions require the filtration to be valid. + prune_above_filtration function is not launching + :func:`initialize_filtration()<gudhi.SimplexTree.initialize_filtration>` + but returns the filtration modification + information. If the complex has changed , please call + :func:`initialize_filtration()<gudhi.SimplexTree.initialize_filtration>` + to recompute it. + + .. note:: + + Note that the dimension of the simplicial complex may be lower + after calling + :func:`prune_above_filtration()<gudhi.SimplexTree.prune_above_filtration>` + than it was before. However, + :func:`upper_bound_dimension()<gudhi.SimplexTree.upper_bound_dimension>` + will return the old value, which remains a + valid upper bound. If you care, you can call + :func:`dimension()<gudhi.SimplexTree.dimension>` + method to recompute the exact dimension. + """ + return self.get_ptr().prune_above_filtration(filtration) + + def expansion(self, max_dim): + """Expands the Simplex_tree containing only its one skeleton + until dimension max_dim. + + The expanded simplicial complex until dimension :math:`d` + attached to a graph :math:`G` is the maximal simplicial complex of + dimension at most :math:`d` admitting the graph :math:`G` as + :math:`1`-skeleton. + The filtration value assigned to a simplex is the maximal filtration + value of one of its edges. + + The Simplex_tree must contain no simplex of dimension bigger than + 1 when calling the method. + + :param max_dim: The maximal dimension. + :type max_dim: int. + """ + self.get_ptr().expansion(max_dim) + + def make_filtration_non_decreasing(self): + """This function ensures that each simplex has a higher filtration + value than its faces by increasing the filtration values. + + :returns: True if any filtration value was modified, + False if the filtration was already non-decreasing. + :rtype: bool + + + .. note:: + + Some simplex tree functions require the filtration to be valid. + make_filtration_non_decreasing function is not launching + :func:`initialize_filtration()<gudhi.SimplexTree.initialize_filtration>` + but returns the filtration modification + information. If the complex has changed , please call + :func:`initialize_filtration()<gudhi.SimplexTree.initialize_filtration>` + to recompute it. + """ + return self.get_ptr().make_filtration_non_decreasing() + + def persistence(self, homology_coeff_field=11, min_persistence=0, persistence_dim_max = False): + """This function returns the persistence of the simplicial complex. + + :param homology_coeff_field: The homology coefficient field. Must be a + prime number. Default value is 11. + :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. + :param persistence_dim_max: If true, the persistent homology for the + maximal dimension in the complex is computed. If false, it is + ignored. Default is false. + :type persistence_dim_max: bool + :returns: The persistence of the simplicial complex. + :rtype: list of pairs(dimension, pair(birth, death)) + """ + if self.pcohptr != NULL: + del self.pcohptr + self.pcohptr = new Simplex_tree_persistence_interface(self.get_ptr(), persistence_dim_max) + 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: The Betti numbers ([B0, B1, ..., Bn]). + :rtype: list of int + + :note: betti_numbers function requires + :func:`persistence()<gudhi.SimplexTree.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: The persistent Betti numbers ([B0, B1, ..., Bn]). + :rtype: list of int + + :note: persistent_betti_numbers function requires + :func:`persistence()<gudhi.SimplexTree.persistence>` + function to be launched first. + """ + cdef vector[int] pbn_result + if self.pcohptr != NULL: + pbn_result = self.pcohptr.persistent_betti_numbers(<double>from_value, <double>to_value) + else: + print("persistent_betti_numbers function requires persistence function" + " to be launched first.") + return pbn_result + + def persistence_intervals_in_dimension(self, dimension): + """This function returns the persistence intervals of the simplicial + complex in a specific dimension. + + :param dimension: The specific dimension. + :type dimension: int. + :returns: The persistence intervals. + :rtype: numpy array of dimension 2 + + :note: intervals_in_dim function requires + :func:`persistence()<gudhi.SimplexTree.persistence>` + function to be launched first. + """ + cdef vector[pair[double,double]] intervals_result + if self.pcohptr != NULL: + intervals_result = self.pcohptr.intervals_in_dimension(dimension) + else: + print("intervals_in_dim function requires persistence function" + " to be launched first.") + return np_array(intervals_result) + + def persistence_pairs(self): + """This function returns a list of persistence birth and death simplices pairs. + + :returns: A list of persistence simplices intervals. + :rtype: list of pair of list of int + + :note: persistence_pairs function requires + :func:`persistence()<gudhi.SimplexTree.persistence>` + function to be launched first. + """ + cdef vector[pair[vector[int],vector[int]]] persistence_pairs_result + if self.pcohptr != NULL: + persistence_pairs_result = self.pcohptr.persistence_pairs() + else: + print("persistence_pairs function requires persistence function" + " to be launched first.") + return persistence_pairs_result + + def write_persistence_diagram(self, persistence_file=''): + """This function writes the persistence intervals of the simplicial + complex in a user given file name. + + :param persistence_file: The specific dimension. + :type persistence_file: string. + + :note: intervals_in_dim function requires + :func:`persistence()<gudhi.SimplexTree.persistence>` + function to be launched first. + """ + if self.pcohptr != NULL: + if persistence_file != '': + self.pcohptr.write_output_diagram(str.encode(persistence_file)) + else: + print("persistence_file must be specified") + else: + print("intervals_in_dim function requires persistence function" + " to be launched first.") |