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