diff options
| -rw-r--r-- | src/Nerve_GIC/include/gudhi/GIC.h | 1 | ||||
| -rw-r--r-- | src/cython/CMakeLists.txt | 1 | ||||
| -rw-r--r-- | src/cython/cython/nerve_gic.pyx | 129 | ||||
| -rw-r--r-- | src/cython/gudhi.pyx.in | 1 | ||||
| -rw-r--r-- | src/cython/include/Nerve_gic_interface.h | 46 |
5 files changed, 177 insertions, 1 deletions
diff --git a/src/Nerve_GIC/include/gudhi/GIC.h b/src/Nerve_GIC/include/gudhi/GIC.h index 40ff7a4a..dfff0337 100644 --- a/src/Nerve_GIC/include/gudhi/GIC.h +++ b/src/Nerve_GIC/include/gudhi/GIC.h @@ -1103,7 +1103,6 @@ class Cover_complex { * @param[in] N number of bootstrap iterations. * */ - template <typename SimplicialComplex> void compute_distribution(int N = 100) { if (distribution.size() >= N) { std::cout << "Already done!" << std::endl; diff --git a/src/cython/CMakeLists.txt b/src/cython/CMakeLists.txt index afca9d60..1524a1bc 100644 --- a/src/cython/CMakeLists.txt +++ b/src/cython/CMakeLists.txt @@ -85,6 +85,7 @@ if(CYTHON_FOUND) if (NOT CGAL_VERSION VERSION_LESS 4.8.1) set(GUDHI_CYTHON_BOTTLENECK_DISTANCE "include '${CMAKE_CURRENT_SOURCE_DIR}/cython/bottleneck_distance.pyx'") + set(GUDHI_CYTHON_NERVE_GIC "include '${CMAKE_CURRENT_SOURCE_DIR}/cython/nerve_gic.pyx'") endif (NOT CGAL_VERSION VERSION_LESS 4.8.1) if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.8.1) set(GUDHI_CYTHON_SUBSAMPLING "include '${CMAKE_CURRENT_SOURCE_DIR}/cython/subsampling.pyx'") diff --git a/src/cython/cython/nerve_gic.pyx b/src/cython/cython/nerve_gic.pyx new file mode 100644 index 00000000..7a6287fa --- /dev/null +++ b/src/cython/cython/nerve_gic.pyx @@ -0,0 +1,129 @@ +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) 2018 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 <http://www.gnu.org/licenses/>. +""" + +__author__ = "Vincent Rouvreau" +__copyright__ = "Copyright (C) 2018 Inria" +__license__ = "GPL v3" + +cdef extern from "Nerve_gic_interface.h" namespace "Gudhi": + cdef cppclass Nerve_gic_interface "Gudhi::cover_complex::Nerve_gic_interface": + Nerve_gic_interface() + bool read_point_cloud(string off_file_name) + double compute_confidence_level_from_distance(double distance) + double compute_distance_from_confidence_level(double alpha) + void compute_distribution(int N) + double compute_p_value() + +# CoverComplex python interface +cdef class CoverComplex: + """Cover complex data structure. + + The data structure is a simplicial complex, representing a Graph Induced + simplicial Complex (GIC) or a Nerve, and whose simplices are computed with + a cover C of a point cloud P, which often comes from the preimages of + intervals covering the image of a function f defined on P. These intervals + are parameterized by their resolution (either their length or their number) + and their gain (percentage of overlap). To compute a GIC, one also needs a + graph G built on top of P, whose cliques with vertices belonging to + different elements of C correspond to the simplices of the GIC. + """ + + cdef Nerve_gic_interface * thisptr + + # Fake constructor that does nothing but documenting the constructor + def __init__(self): + """CoverComplex constructor. + """ + + # The real cython constructor + def __cinit__(self): + self.thisptr = new Nerve_gic_interface() + + def __dealloc__(self): + if self.thisptr != NULL: + del self.thisptr + + def __is_defined(self): + """Returns true if CoverComplex pointer is not NULL. + """ + return self.thisptr != NULL + + def read_point_cloud(self, off_file): + """Reads and stores the input point cloud. + + :param off_file: Name of the input .OFF or .nOFF file. + :type off_file: string + :rtype: bool + :returns: Read file status. + """ + if os.path.isfile(off_file): + return self.thisptr.read_point_cloud(str.encode(off_file)) + else: + print("file " + off_file + " not found.") + return False + + def compute_confidence_level_from_distance(self, distance): + """Computes the confidence level of a specific bottleneck distance + threshold. + + :param distance: Bottleneck distance. + :type distance: double + :rtype: double + :returns: Confidence level. + """ + return self.thisptr.compute_confidence_level_from_distance(distance) + + def compute_distance_from_confidence_level(self, alpha): + """Computes the bottleneck distance threshold corresponding to a + specific confidence level. + + :param alpha: Confidence level. + :type alpha: double + :rtype: double + :returns: Bottleneck distance. + """ + return self.thisptr.compute_distance_from_confidence_level(alpha) + + def compute_distribution(self, N=100): + """Computes bootstrapped distances distribution. + + :param N: Loop number (default value is 100). + :type alpha: int + """ + self.thisptr.compute_distribution(N) + + def compute_p_value(self): + """Computes the p-value, i.e. the opposite of the confidence level of + the largest bottleneck distance preserving the points in the + persistence diagram of the output simplicial complex. + + :rtype: double + :returns: p-value. + """ + return self.thisptr.compute_p_value() diff --git a/src/cython/gudhi.pyx.in b/src/cython/gudhi.pyx.in index a8dd9f80..10df2946 100644 --- a/src/cython/gudhi.pyx.in +++ b/src/cython/gudhi.pyx.in @@ -41,3 +41,4 @@ include '@CMAKE_CURRENT_SOURCE_DIR@/cython/strong_witness_complex.pyx' @GUDHI_CYTHON_SUBSAMPLING@ @GUDHI_CYTHON_TANGENTIAL_COMPLEX@ @GUDHI_CYTHON_BOTTLENECK_DISTANCE@ +@GUDHI_CYTHON_NERVE_GIC@ diff --git a/src/cython/include/Nerve_gic_interface.h b/src/cython/include/Nerve_gic_interface.h new file mode 100644 index 00000000..8273d190 --- /dev/null +++ b/src/cython/include/Nerve_gic_interface.h @@ -0,0 +1,46 @@ +/* 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) 2018 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 <http://www.gnu.org/licenses/>. + */ + +#ifndef INCLUDE_NERVE_GIC_INTERFACE_H_ +#define INCLUDE_NERVE_GIC_INTERFACE_H_ + +#include <gudhi/Simplex_tree.h> +#include <gudhi/GIC.h> + +#include "Simplex_tree_interface.h" + +#include <iostream> +#include <vector> +#include <string> + +namespace Gudhi { + +namespace cover_complex { + +class Nerve_gic_interface : public Cover_complex<std::vector<double>> { +}; + +} // namespace cover_complex + +} // namespace Gudhi + +#endif // INCLUDE_NERVE_GIC_INTERFACE_H_ |