From 56618be4e28a6a149aaa0fef944d8fde719f7844 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Fri, 16 Feb 2018 08:04:07 +0000 Subject: Add Cech complex. Do not compile yet. git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3250 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: bef87ed8038444685b964175ea65860300917380 --- .../include/Miniball/Miniball.COPYRIGHT | 4 + src/Cech_complex/include/Miniball/Miniball.README | 23 + src/Cech_complex/include/Miniball/Miniball.hpp | 515 +++++++++++++++++++++ src/Cech_complex/include/gudhi/Cech_complex.h | 126 +++++ .../include/gudhi/Cech_complex_blocker.h | 85 ++++ 5 files changed, 753 insertions(+) create mode 100644 src/Cech_complex/include/Miniball/Miniball.COPYRIGHT create mode 100644 src/Cech_complex/include/Miniball/Miniball.README create mode 100644 src/Cech_complex/include/Miniball/Miniball.hpp create mode 100644 src/Cech_complex/include/gudhi/Cech_complex.h create mode 100644 src/Cech_complex/include/gudhi/Cech_complex_blocker.h (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/Miniball/Miniball.COPYRIGHT b/src/Cech_complex/include/Miniball/Miniball.COPYRIGHT new file mode 100644 index 00000000..dbe4c553 --- /dev/null +++ b/src/Cech_complex/include/Miniball/Miniball.COPYRIGHT @@ -0,0 +1,4 @@ +The miniball software is available under the GNU General Public License (GPLv3 - https://www.gnu.org/copyleft/gpl.html). +If your intended use is not compliant with this license, please buy a commercial license (EUR 500 - https://people.inf.ethz.ch/gaertner/subdir/software/miniball/license.html). +You need a license if the software that you develop using Miniball V3.0 is not open source. + diff --git a/src/Cech_complex/include/Miniball/Miniball.README b/src/Cech_complex/include/Miniball/Miniball.README new file mode 100644 index 00000000..86a96f08 --- /dev/null +++ b/src/Cech_complex/include/Miniball/Miniball.README @@ -0,0 +1,23 @@ +https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html + +Smallest Enclosing Balls of Points - Fast and Robust in C++. +(high-quality software for smallest enclosing balls of balls is available in the computational geometry algorithms library CGAL) + + +This is the miniball software (V3.0) for computing smallest enclosing balls of points in arbitrary dimensions. It consists of a C++ header file Miniball.hpp (around 500 lines of code) and two example programs miniball_example.cpp and miniball_example_containers.cpp that demonstrate the usage. The first example stores the coordinates of the input points in a two-dimensional array, the second example uses a list of vectors to show how generic containers can be used. + +Credits: Aditya Gupta and Alexandros Konstantinakis-Karmis have significantly contributed to this version of the software. + +Changes - https://people.inf.ethz.ch/gaertner/subdir/software/miniball/changes.txt - from previous versions. + +The theory - https://people.inf.ethz.ch/gaertner/subdir/texts/own_work/esa99_final.pdf - behind the miniball software (Proc. 7th Annual European Symposium on Algorithms (ESA), Lecture Notes in Computer Science 1643, Springer-Verlag, pp.325-338, 1999). + +Main Features: + + Very fast in low dimensions. 1 million points in 5-space are processed within 0.05 seconds on any recent machine. + + High numerical stability. Almost all input degeneracies (cospherical points, multiple points, points very close together) are routinely handled. + + Easily integrates into your code. You can freely choose the coordinate type of your points and the container to store the points. If you still need to adapt the code, the header is small and readable and contains documentation for all major methods. + + diff --git a/src/Cech_complex/include/Miniball/Miniball.hpp b/src/Cech_complex/include/Miniball/Miniball.hpp new file mode 100644 index 00000000..cb76c534 --- /dev/null +++ b/src/Cech_complex/include/Miniball/Miniball.hpp @@ -0,0 +1,515 @@ +// Copright (C) 1999-2013, Bernd Gaertner +// $Rev: 3581 $ +// +// 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 . +// +// Contact: +// -------- +// Bernd Gaertner +// Institute of Theoretical Computer Science +// ETH Zuerich +// CAB G31.1 +// CH-8092 Zuerich, Switzerland +// http://www.inf.ethz.ch/personal/gaertner + +#include +#include +#include +#include +#include + +namespace Miniball { + + // Global Functions + // ================ + template + inline NT mb_sqr (NT r) {return r*r;} + + // Functors + // ======== + + // functor to map a point iterator to the corresponding coordinate iterator; + // generic version for points whose coordinate containers have begin() + template < typename Pit_, typename Cit_ > + struct CoordAccessor { + typedef Pit_ Pit; + typedef Cit_ Cit; + inline Cit operator() (Pit it) const { return (*it).begin(); } + }; + + // partial specialization for points whose coordinate containers are arrays + template < typename Pit_, typename Cit_ > + struct CoordAccessor { + typedef Pit_ Pit; + typedef Cit_* Cit; + inline Cit operator() (Pit it) const { return *it; } + }; + + // Class Declaration + // ================= + + template + class Miniball { + private: + // types + // The iterator type to go through the input points + typedef typename CoordAccessor::Pit Pit; + // The iterator type to go through the coordinates of a single point. + typedef typename CoordAccessor::Cit Cit; + // The coordinate type + typedef typename std::iterator_traits::value_type NT; + // The iterator to go through the support points + typedef typename std::list::iterator Sit; + + // data members... + const int d; // dimension + Pit points_begin; + Pit points_end; + CoordAccessor coord_accessor; + double time; + const NT nt0; // NT(0) + + //...for the algorithms + std::list L; + Sit support_end; + int fsize; // number of forced points + int ssize; // number of support points + + // ...for the ball updates + NT* current_c; + NT current_sqr_r; + NT** c; + NT* sqr_r; + + // helper arrays + NT* q0; + NT* z; + NT* f; + NT** v; + NT** a; + + public: + // The iterator type to go through the support points + typedef typename std::list::const_iterator SupportPointIterator; + + // PRE: [begin, end) is a nonempty range + // POST: computes the smallest enclosing ball of the points in the range + // [begin, end); the functor a maps a point iterator to an iterator + // through the d coordinates of the point + Miniball (int d_, Pit begin, Pit end, CoordAccessor ca = CoordAccessor()); + + // POST: returns a pointer to the first element of an array that holds + // the d coordinates of the center of the computed ball + const NT* center () const; + + // POST: returns the squared radius of the computed ball + NT squared_radius () const; + + // POST: returns the number of support points of the computed ball; + // the support points form a minimal set with the same smallest + // enclosing ball as the input set; in particular, the support + // points are on the boundary of the computed ball, and their + // number is at most d+1 + int nr_support_points () const; + + // POST: returns an iterator to the first support point + SupportPointIterator support_points_begin () const; + + // POST: returns a past-the-end iterator for the range of support points + SupportPointIterator support_points_end () const; + + // POST: returns the maximum excess of any input point w.r.t. the computed + // ball, divided by the squared radius of the computed ball. The + // excess of a point is the difference between its squared distance + // from the center and the squared radius; Ideally, the return value + // is 0. subopt is set to the absolute value of the most negative + // coefficient in the affine combination of the support points that + // yields the center. Ideally, this is a convex combination, and there + // is no negative coefficient in which case subopt is set to 0. + NT relative_error (NT& subopt) const; + + // POST: return true if the relative error is at most tol, and the + // suboptimality is 0; the default tolerance is 10 times the + // coordinate type's machine epsilon + bool is_valid (NT tol = NT(10) * std::numeric_limits::epsilon()) const; + + // POST: returns the time in seconds taken by the constructor call for + // computing the smallest enclosing ball + double get_time() const; + + // POST: deletes dynamically allocated arrays + ~Miniball(); + + private: + void mtf_mb (Sit n); + void mtf_move_to_front (Sit j); + void pivot_mb (Pit n); + void pivot_move_to_front (Pit j); + NT excess (Pit pit) const; + void pop (); + bool push (Pit pit); + NT suboptimality () const; + void create_arrays(); + void delete_arrays(); + }; + + // Class Definition + // ================ + template + Miniball::Miniball (int d_, Pit begin, Pit end, + CoordAccessor ca) + : d (d_), + points_begin (begin), + points_end (end), + coord_accessor (ca), + time (clock()), + nt0 (NT(0)), + L(), + support_end (L.begin()), + fsize(0), + ssize(0), + current_c (NULL), + current_sqr_r (NT(-1)), + c (NULL), + sqr_r (NULL), + q0 (NULL), + z (NULL), + f (NULL), + v (NULL), + a (NULL) + { + assert (points_begin != points_end); + create_arrays(); + + // set initial center + for (int j=0; j + Miniball::~Miniball() + { + delete_arrays(); + } + + template + void Miniball::create_arrays() + { + c = new NT*[d+1]; + v = new NT*[d+1]; + a = new NT*[d+1]; + for (int i=0; i + void Miniball::delete_arrays() + { + delete[] f; + delete[] z; + delete[] q0; + delete[] sqr_r; + for (int i=0; i + const typename Miniball::NT* + Miniball::center () const + { + return current_c; + } + + template + typename Miniball::NT + Miniball::squared_radius () const + { + return current_sqr_r; + } + + template + int Miniball::nr_support_points () const + { + assert (ssize < d+2); + return ssize; + } + + template + typename Miniball::SupportPointIterator + Miniball::support_points_begin () const + { + return L.begin(); + } + + template + typename Miniball::SupportPointIterator + Miniball::support_points_end () const + { + return support_end; + } + + template + typename Miniball::NT + Miniball::relative_error (NT& subopt) const + { + NT e, max_e = nt0; + // compute maximum absolute excess of support points + for (SupportPointIterator it = support_points_begin(); + it != support_points_end(); ++it) { + e = excess (*it); + if (e < nt0) e = -e; + if (e > max_e) { + max_e = e; + } + } + // compute maximum excess of any point + for (Pit i = points_begin; i != points_end; ++i) + if ((e = excess (i)) > max_e) + max_e = e; + + subopt = suboptimality(); + assert (current_sqr_r > nt0 || max_e == nt0); + return (current_sqr_r == nt0 ? nt0 : max_e / current_sqr_r); + } + + template + bool Miniball::is_valid (NT tol) const + { + NT suboptimality; + return ( (relative_error (suboptimality) <= tol) && (suboptimality == 0) ); + } + + template + double Miniball::get_time() const + { + return time; + } + + template + void Miniball::mtf_mb (Sit n) + { + // Algorithm 1: mtf_mb (L_{n-1}, B), where L_{n-1} = [L.begin, n) + // B: the set of forced points, defining the current ball + // S: the superset of support points computed by the algorithm + // -------------------------------------------------------------- + // from B. Gaertner, Fast and Robust Smallest Enclosing Balls, ESA 1999, + // http://www.inf.ethz.ch/personal/gaertner/texts/own_work/esa99_final.pdf + + // PRE: B = S + assert (fsize == ssize); + + support_end = L.begin(); + if ((fsize) == d+1) return; + + // incremental construction + for (Sit i = L.begin(); i != n;) + { + // INV: (support_end - L.begin() == |S|-|B|) + assert (std::distance (L.begin(), support_end) == ssize - fsize); + + Sit j = i++; + if (excess(*j) > nt0) + if (push(*j)) { // B := B + p_i + mtf_mb (j); // mtf_mb (L_{i-1}, B + p_i) + pop(); // B := B - p_i + mtf_move_to_front(j); + } + } + // POST: the range [L.begin(), support_end) stores the set S\B + } + + template + void Miniball::mtf_move_to_front (Sit j) + { + if (support_end == j) + support_end++; + L.splice (L.begin(), L, j); + } + + template + void Miniball::pivot_mb (Pit n) + { + // Algorithm 2: pivot_mb (L_{n-1}), where L_{n-1} = [L.begin, n) + // -------------------------------------------------------------- + // from B. Gaertner, Fast and Robust Smallest Enclosing Balls, ESA 1999, + // http://www.inf.ethz.ch/personal/gaertner/texts/own_work/esa99_final.pdf + NT old_sqr_r; + const NT* c; + Pit pivot, k; + NT e, max_e, sqr_r; + Cit p; + do { + old_sqr_r = current_sqr_r; + sqr_r = current_sqr_r; + + pivot = points_begin; + max_e = nt0; + for (k = points_begin; k != n; ++k) { + p = coord_accessor(k); + e = -sqr_r; + c = current_c; + for (int j=0; j(*p++-*c++); + if (e > max_e) { + max_e = e; + pivot = k; + } + } + + if (max_e > nt0) { + // check if the pivot is already contained in the support set + if (std::find(L.begin(), support_end, pivot) == support_end) { + assert (fsize == 0); + if (push (pivot)) { + mtf_mb(support_end); + pop(); + pivot_move_to_front(pivot); + } + } + } + } while (old_sqr_r < current_sqr_r); + } + + template + void Miniball::pivot_move_to_front (Pit j) + { + L.push_front(j); + if (std::distance(L.begin(), support_end) == d+2) + support_end--; + } + + template + inline typename Miniball::NT + Miniball::excess (Pit pit) const + { + Cit p = coord_accessor(pit); + NT e = -current_sqr_r; + NT* c = current_c; + for (int k=0; k(*p++-*c++); + } + return e; + } + + template + void Miniball::pop () + { + --fsize; + } + + template + bool Miniball::push (Pit pit) + { + int i, j; + NT eps = mb_sqr(std::numeric_limits::epsilon()); + + Cit cit = coord_accessor(pit); + Cit p = cit; + + if (fsize==0) { + for (i=0; i(v[fsize][j]); + z[fsize]*=2; + + // reject push if z_fsize too small + if (z[fsize](*p++-c[fsize-1][i]); + f[fsize]=e/z[fsize]; + + for (i=0; i + typename Miniball::NT + Miniball::suboptimality () const + { + NT* l = new NT[d+1]; + NT min_l = nt0; + l[0] = NT(1); + for (int i=ssize-1; i>0; --i) { + l[i] = f[i]; + for (int k=ssize-1; k>i; --k) + l[i]-=a[k][i]*l[k]; + if (l[i] < min_l) min_l = l[i]; + l[0] -= l[i]; + } + if (l[0] < min_l) min_l = l[0]; + delete[] l; + if (min_l < nt0) + return -min_l; + return nt0; + } + +} // end Namespace Miniball diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h new file mode 100644 index 00000000..3a0d828a --- /dev/null +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -0,0 +1,126 @@ +/* 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 . + */ + +#ifndef CECH_COMPLEX_H_ +#define CECH_COMPLEX_H_ + +#include // for Gudhi::Proximity_graph +#include // for GUDHI_CHECK +#include // for Gudhi::cech_complex::Cech_blocker + +#include +#include +#include +#include // for std::size + +namespace Gudhi { + +namespace cech_complex { + +/** + * \class Cech_complex + * \brief Cech complex data structure. + * + * \ingroup Cech_complex + * + * \details + * The data structure is a one skeleton graph, or Rips graph, containing edges when the edge length is less or equal + * to a given threshold. Edge length is computed from a user given point cloud with a given distance function, or a + * distance matrix. + * + * \tparam Filtration_value is the type used to store the filtration values of the simplicial complex. + */ +template +class Cech_complex { + private: + using Vertex_handle = typename SimplicialComplexForCechComplex::Vertex_handle; + using Filtration_value = typename SimplicialComplexForCechComplex::Filtration_value; + using Proximity_graph = Gudhi::Proximity_graph; + + public: + /** \brief Cech_complex constructor from a list of points. + * + * @param[in] points Range of points. + * @param[in] threshold Rips value. + * @param[in] distance distance function that returns a `Filtration_value` from 2 given points. + * + * \tparam ForwardPointRange must be a range for which `std::begin` and `std::end` return input iterators on a + * point. + * + * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where + * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`. + */ + template + Cech_complex(const ForwardPointRange& points, Filtration_value threshold, Distance distance) + : threshold_(threshold), + point_cloud_(points) { + GUDHI_CHECK(std::size(points) > 0, + std::invalid_argument("Cech_complex::create_complex - point cloud is empty")); + dimension_ = points[0].size(); + cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, threshold_, distance); + } + + /** \brief Initializes the simplicial complex from the Rips graph and expands it until a given maximal + * dimension. + * + * @param[in] complex SimplicialComplexForCech to be created. + * @param[in] dim_max graph expansion for Rips until this given maximal dimension. + * @exception std::invalid_argument In debug mode, if `complex.num_vertices()` does not return 0. + * + */ + void create_complex(SimplicialComplexForCechComplex& complex, int dim_max) { + GUDHI_CHECK(complex.num_vertices() == 0, + std::invalid_argument("Cech_complex::create_complex - simplicial complex is not empty")); + + // insert the proximity graph in the simplicial complex + complex.insert_graph(cech_skeleton_graph_); + // expand the graph until dimension dim_max + complex.expansion_with_blockers(dim_max, + Cech_blocker(complex, this)); + } + + Filtration_value threshold() const { + return threshold_; + } + + std::size_t dimension() const { + return dimension_; + } + + auto point(std::size_t vertex) const -> decltype(point_cloud_.begin() + vertex) { + GUDHI_CHECK((point_cloud_.begin() + vertex) < point_cloud_.end(), + std::invalid_argument("Cech_complex::point - simplicial complex is not empty")); + return (point_cloud_.begin() + vertex); + } + + private: + Proximity_graph cech_skeleton_graph_; + Filtration_value threshold_; + ForwardPointRange point_cloud_; + std::size_t dimension_; +}; + +} // namespace cech_complex + +} // namespace Gudhi + +#endif // CECH_COMPLEX_H_ diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h new file mode 100644 index 00000000..647bf0b7 --- /dev/null +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -0,0 +1,85 @@ +/* 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 . + */ + +#ifndef CECH_COMPLEX_BLOCKER_H_ +#define CECH_COMPLEX_BLOCKER_H_ + +#include +#include + +#include + +#include +#include +#include // for std::sqrt + +namespace Gudhi { + +namespace cech_complex { + +// Just declaring Cech_complex class because used and not yet defined. +template +class Cech_complex; + +template +class Cech_blocker { + private: + using Point = std::vector; + using Point_cloud = std::vector; + using Point_iterator = Point_cloud::const_iterator; + using Coordinate_iterator = Point::const_iterator; + using Min_sphere = Miniball::Miniball>; + using Simplex_handle = typename SimplicialComplexForCech::Simplex_handle; + using Filtration_value = typename SimplicialComplexForCech::Filtration_value; + using Cech_complex = Gudhi::cech_complex::Cech_complex; + + public: + bool operator()(Simplex_handle sh) { + Point_cloud points; + for (auto vertex : simplicial_complex_.simplex_vertex_range(sh)) { + points.push_back(cc_ptr_->point(vertex)); +#ifdef DEBUG_TRACES + std::cout << "#(" << vertex << ")#"; +#endif // DEBUG_TRACES + } + Min_sphere ms(cc_ptr_->dimension(), points.begin(),points.end()); + Filtration_value radius = std::sqrt(ms.squared_radius()); +#ifdef DEBUG_TRACES + std::cout << "radius = " << radius << " - " << (radius > cc_ptr_->threshold()) << std::endl; +#endif // DEBUG_TRACES + simplicial_complex_.assign_filtration(sh, radius); + return (radius > cc_ptr_->threshold()); + } + Cech_blocker(SimplicialComplexForCech& simplicial_complex, Cech_complex* cc_ptr) + : simplicial_complex_(simplicial_complex), + cc_ptr_(cc_ptr) { + } + private: + SimplicialComplexForCech simplicial_complex_; + Cech_complex* cc_ptr_; +}; + +} // namespace cech_complex + +} // namespace Gudhi + +#endif // CECH_COMPLEX_BLOCKER_H_ -- cgit v1.2.3 From 4a91726c9500e4b7ffe469192aa1140650c3d094 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Fri, 16 Feb 2018 16:42:04 +0000 Subject: Compiles. Class documentation is done. git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3252 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: fdcfe090afddb112dee4c19c7b42432277a7f468 --- src/Cech_complex/include/gudhi/Cech_complex.h | 57 +++++++++++++--------- .../include/gudhi/Cech_complex_blocker.h | 5 +- 2 files changed, 37 insertions(+), 25 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 3a0d828a..94939105 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -29,8 +29,8 @@ #include #include -#include -#include // for std::size +#include // for std::size_t +#include // for exception management namespace Gudhi { @@ -43,18 +43,21 @@ namespace cech_complex { * \ingroup Cech_complex * * \details - * The data structure is a one skeleton graph, or Rips graph, containing edges when the edge length is less or equal - * to a given threshold. Edge length is computed from a user given point cloud with a given distance function, or a - * distance matrix. - * - * \tparam Filtration_value is the type used to store the filtration values of the simplicial complex. + * The data structure is a proximity graph, containing edges when the edge length is less or equal + * to a given threshold. Edge length is computed from a user given point cloud with a given distance function. + * + * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required + * by `Gudhi::Proximity_graph`. + * + * \tparam ForwardPointRange furnishes `.size()`, `.begin()` and `.end()` methods, and a `const_iterator` type + * definition. */ -template +template class Cech_complex { private: - using Vertex_handle = typename SimplicialComplexForCechComplex::Vertex_handle; - using Filtration_value = typename SimplicialComplexForCechComplex::Filtration_value; - using Proximity_graph = Gudhi::Proximity_graph; + using Vertex_handle = typename SimplicialComplexForProximityGraph::Vertex_handle; + using Filtration_value = typename SimplicialComplexForProximityGraph::Filtration_value; + using Proximity_graph = Gudhi::Proximity_graph; public: /** \brief Cech_complex constructor from a list of points. @@ -62,9 +65,10 @@ class Cech_complex { * @param[in] points Range of points. * @param[in] threshold Rips value. * @param[in] distance distance function that returns a `Filtration_value` from 2 given points. - * - * \tparam ForwardPointRange must be a range for which `std::begin` and `std::end` return input iterators on a - * point. + * @exception std::invalid_argument In debug mode, if `points.size()` returns a value ≤ 0. + * + * \tparam ForwardPointRange must be a range for which `.size()`, `.begin()` and `.end()` methods return input + * iterators on a point. A point must have a `.size()` method available. * * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`. @@ -73,20 +77,23 @@ class Cech_complex { Cech_complex(const ForwardPointRange& points, Filtration_value threshold, Distance distance) : threshold_(threshold), point_cloud_(points) { - GUDHI_CHECK(std::size(points) > 0, + GUDHI_CHECK(points.size() > 0, std::invalid_argument("Cech_complex::create_complex - point cloud is empty")); - dimension_ = points[0].size(); - cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, threshold_, distance); + dimension_ = points.begin()->size(); + cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, + threshold_, + distance); } - /** \brief Initializes the simplicial complex from the Rips graph and expands it until a given maximal - * dimension. + /** \brief Initializes the simplicial complex from the proximity graph and expands it until a given maximal + * dimension, using the Cech blocker oracle. * * @param[in] complex SimplicialComplexForCech to be created. - * @param[in] dim_max graph expansion for Rips until this given maximal dimension. + * @param[in] dim_max graph expansion until this given maximal dimension. * @exception std::invalid_argument In debug mode, if `complex.num_vertices()` does not return 0. * */ + template void create_complex(SimplicialComplexForCechComplex& complex, int dim_max) { GUDHI_CHECK(complex.num_vertices() == 0, std::invalid_argument("Cech_complex::create_complex - simplicial complex is not empty")); @@ -98,17 +105,23 @@ class Cech_complex { Cech_blocker(complex, this)); } + /** @return Threshold value given at construction. */ Filtration_value threshold() const { return threshold_; } + /** @return Dimension value given at construction by the first point dimension. */ std::size_t dimension() const { return dimension_; } - auto point(std::size_t vertex) const -> decltype(point_cloud_.begin() + vertex) { + /** @param[in] vertex Point position in the range. + * @return Threshold value given at construction. + * @exception std::out_of_range In debug mode, if point position in the range is out. + */ + typename ForwardPointRange::const_iterator point(std::size_t vertex) const { GUDHI_CHECK((point_cloud_.begin() + vertex) < point_cloud_.end(), - std::invalid_argument("Cech_complex::point - simplicial complex is not empty")); + std::out_of_range("Cech_complex::point - simplicial complex is not empty")); return (point_cloud_.begin() + vertex); } diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index 647bf0b7..25fab909 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -23,8 +23,7 @@ #ifndef CECH_COMPLEX_BLOCKER_H_ #define CECH_COMPLEX_BLOCKER_H_ -#include -#include +#include // Cech_blocker is using a pointer on Gudhi::cech_complex::Cech_complex #include @@ -56,7 +55,7 @@ class Cech_blocker { bool operator()(Simplex_handle sh) { Point_cloud points; for (auto vertex : simplicial_complex_.simplex_vertex_range(sh)) { - points.push_back(cc_ptr_->point(vertex)); + points.push_back(*(cc_ptr_->point(vertex))); #ifdef DEBUG_TRACES std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES -- cgit v1.2.3 From 0586a149b5bb3a4b65b63b2ab7d3ecdd9682ee1b Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Tue, 20 Feb 2018 16:03:52 +0000 Subject: tests and utils fix git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3253 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 5786a8a7e4b16750f29fac99ca61926158542cfd --- .../concept/SimplicialComplexForCech.h | 66 +++++ .../example_one_skeleton_cech_from_points.cpp | 5 +- src/Cech_complex/include/Miniball/Miniball.hpp | 5 + src/Cech_complex/include/gudhi/Cech_complex.h | 18 +- .../include/gudhi/Cech_complex_blocker.h | 23 +- src/Cech_complex/test/CMakeLists.txt | 15 ++ src/Cech_complex/test/README | 12 + src/Cech_complex/test/test_cech_complex.cpp | 274 +++++++++++++++++++++ src/Cech_complex/utilities/CMakeLists.txt | 14 ++ src/Cech_complex/utilities/cech_persistence.cpp | 136 ++++++++++ src/Cech_complex/utilities/cechcomplex.md | 33 +++ 11 files changed, 587 insertions(+), 14 deletions(-) create mode 100644 src/Cech_complex/concept/SimplicialComplexForCech.h create mode 100644 src/Cech_complex/test/CMakeLists.txt create mode 100644 src/Cech_complex/test/README create mode 100644 src/Cech_complex/test/test_cech_complex.cpp create mode 100644 src/Cech_complex/utilities/CMakeLists.txt create mode 100644 src/Cech_complex/utilities/cech_persistence.cpp create mode 100644 src/Cech_complex/utilities/cechcomplex.md (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/concept/SimplicialComplexForCech.h b/src/Cech_complex/concept/SimplicialComplexForCech.h new file mode 100644 index 00000000..1954a703 --- /dev/null +++ b/src/Cech_complex/concept/SimplicialComplexForCech.h @@ -0,0 +1,66 @@ +/* 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 . + */ + +#ifndef CONCEPT_CECH_COMPLEX_SIMPLICIAL_COMPLEX_FOR_CECH_H_ +#define CONCEPT_CECH_COMPLEX_SIMPLICIAL_COMPLEX_FOR_CECH_H_ + +namespace Gudhi { + +namespace cech_complex { + +/** \brief The concept SimplicialComplexForCech describes the requirements for a type to implement a simplicial + * complex, that can be created from a `Cech_complex`. + */ +struct SimplicialComplexForCech { + /** Handle to specify a simplex. */ + typedef unspecified Simplex_handle; + /** Handle to specify a vertex. Must be a non-negative integer. */ + typedef unspecified Vertex_handle; + /** Handle to specify the simplex filtration value. */ + typedef unspecified Filtration_value; + + /** Assigns the 'simplex' with the given 'filtration' value. */ + int assign_filtration(Simplex_handle simplex, Filtration_value filtration); + + /** \brief Returns a range over vertices of a given + * simplex. */ + Simplex_vertex_range simplex_vertex_range(Simplex_handle const & simplex); + + /** \brief Inserts a given `Gudhi::ProximityGraph` in the simplicial complex. */ + template + void insert_graph(const ProximityGraph& proximity_graph); + + /** \brief Expands the simplicial complex containing only its one skeleton until a given maximal dimension. + * expansion can be blocked by the blocker oracle. */ + template< typename Blocker > + void expansion_with_blockers(int max_dim, Blocker block_simplex); + + /** Returns the number of vertices in the simplicial complex. */ + std::size_t num_vertices(); + +}; + +} // namespace alpha_complex + +} // namespace Gudhi + +#endif // CONCEPT_ALPHA_COMPLEX_SIMPLICIAL_COMPLEX_FOR_ALPHA_H_ diff --git a/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp b/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp index 9b03616c..73679716 100644 --- a/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp +++ b/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp @@ -27,11 +27,12 @@ #include #include #include +#include #include // for std::numeric_limits int main() { // Type definitions - using Point_cloud = std::vector>; + using Point_cloud = std::vector>; using Simplex_tree = Gudhi::Simplex_tree; using Filtration_value = Simplex_tree::Filtration_value; using Cech_complex = Gudhi::cech_complex::Cech_complex; @@ -52,7 +53,7 @@ int main() { Cech_complex cech_complex_from_points(points, threshold, Gudhi::Euclidean_distance()); Simplex_tree stree; - cech_complex_from_points.create_complex(stree, 2); + cech_complex_from_points.create_complex(stree, 3); // ---------------------------------------------------------------------------- // Display information about the one skeleton Rips complex // ---------------------------------------------------------------------------- diff --git a/src/Cech_complex/include/Miniball/Miniball.hpp b/src/Cech_complex/include/Miniball/Miniball.hpp index cb76c534..a42d62a7 100644 --- a/src/Cech_complex/include/Miniball/Miniball.hpp +++ b/src/Cech_complex/include/Miniball/Miniball.hpp @@ -23,6 +23,9 @@ // CH-8092 Zuerich, Switzerland // http://www.inf.ethz.ch/personal/gaertner +#ifndef MINIBALL_HPP_ +#define MINIBALL_HPP_ + #include #include #include @@ -513,3 +516,5 @@ namespace Miniball { } } // end Namespace Miniball + +#endif // MINIBALL_HPP_ diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 94939105..e847c97f 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -28,7 +28,6 @@ #include // for Gudhi::cech_complex::Cech_blocker #include -#include #include // for std::size_t #include // for exception management @@ -40,7 +39,7 @@ namespace cech_complex { * \class Cech_complex * \brief Cech complex data structure. * - * \ingroup Cech_complex + * \ingroup cech_complex * * \details * The data structure is a proximity graph, containing edges when the edge length is less or equal @@ -65,10 +64,9 @@ class Cech_complex { * @param[in] points Range of points. * @param[in] threshold Rips value. * @param[in] distance distance function that returns a `Filtration_value` from 2 given points. - * @exception std::invalid_argument In debug mode, if `points.size()` returns a value ≤ 0. * * \tparam ForwardPointRange must be a range for which `.size()`, `.begin()` and `.end()` methods return input - * iterators on a point. A point must have a `.size()` method available. + * iterators on a point. `.begin()` and `.end()` methods are required for a point. * * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`. @@ -77,12 +75,10 @@ class Cech_complex { Cech_complex(const ForwardPointRange& points, Filtration_value threshold, Distance distance) : threshold_(threshold), point_cloud_(points) { - GUDHI_CHECK(points.size() > 0, - std::invalid_argument("Cech_complex::create_complex - point cloud is empty")); - dimension_ = points.begin()->size(); + dimension_ = points.begin()->end() - points.begin()->begin(); cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, - threshold_, - distance); + threshold_, + distance); } /** \brief Initializes the simplicial complex from the proximity graph and expands it until a given maximal @@ -116,10 +112,10 @@ class Cech_complex { } /** @param[in] vertex Point position in the range. - * @return Threshold value given at construction. + * @return A const iterator on the point. * @exception std::out_of_range In debug mode, if point position in the range is out. */ - typename ForwardPointRange::const_iterator point(std::size_t vertex) const { + typename ForwardPointRange::const_iterator point_iterator(std::size_t vertex) const { GUDHI_CHECK((point_cloud_.begin() + vertex) < point_cloud_.end(), std::out_of_range("Cech_complex::point - simplicial complex is not empty")); return (point_cloud_.begin() + vertex); diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index 25fab909..f8738be0 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -39,6 +39,20 @@ namespace cech_complex { template class Cech_complex; +/** \internal + * \class Cech_blocker + * \brief Cech complex blocker. + * + * \ingroup cech_complex + * + * \details + * Cech blocker is an oracle constructed from a Cech_complex and a simplicial complex. + * + * \tparam SimplicialComplexForProximityGraph furnishes `Simplex_handle` and `Filtration_value` type definition, + * `simplex_vertex_range(Simplex_handle sh)`and `assign_filtration(Simplex_handle sh, Filtration_value filt)` methods. + * + * \tparam ForwardPointRange is required by the pointer on Chech_complex for type definition. + */ template class Cech_blocker { private: @@ -52,10 +66,15 @@ class Cech_blocker { using Cech_complex = Gudhi::cech_complex::Cech_complex; public: + /** \internal \brief Cech complex blocker operator() - the oracle - assigns the filtration value from the simplex + * radius and returns if the simplex expansion must be blocked. + * \param[in] sh The Simplex_handle. + * \return true if the simplex radius is greater than the Cech_complex threshold*/ bool operator()(Simplex_handle sh) { Point_cloud points; for (auto vertex : simplicial_complex_.simplex_vertex_range(sh)) { - points.push_back(*(cc_ptr_->point(vertex))); + points.push_back(Point(cc_ptr_->point_iterator(vertex)->begin(), + cc_ptr_->point_iterator(vertex)->end())); #ifdef DEBUG_TRACES std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES @@ -68,6 +87,8 @@ class Cech_blocker { simplicial_complex_.assign_filtration(sh, radius); return (radius > cc_ptr_->threshold()); } + + /** \internal \brief Cech complex blocker constructor. */ Cech_blocker(SimplicialComplexForCech& simplicial_complex, Cech_complex* cc_ptr) : simplicial_complex_(simplicial_complex), cc_ptr_(cc_ptr) { diff --git a/src/Cech_complex/test/CMakeLists.txt b/src/Cech_complex/test/CMakeLists.txt new file mode 100644 index 00000000..8db51173 --- /dev/null +++ b/src/Cech_complex/test/CMakeLists.txt @@ -0,0 +1,15 @@ +cmake_minimum_required(VERSION 2.6) +project(Cech_complex_tests) + +include(GUDHI_test_coverage) + +add_executable ( Cech_complex_test_unit test_cech_complex.cpp ) +target_link_libraries(Cech_complex_test_unit ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY}) +if (TBB_FOUND) + target_link_libraries(Cech_complex_test_unit ${TBB_LIBRARIES}) +endif() + +# Do not forget to copy test files in current binary dir +file(COPY "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) + +gudhi_add_coverage_test(Cech_complex_test_unit) diff --git a/src/Cech_complex/test/README b/src/Cech_complex/test/README new file mode 100644 index 00000000..adf704f7 --- /dev/null +++ b/src/Cech_complex/test/README @@ -0,0 +1,12 @@ +To compile: +*********** + +cmake . +make + +To launch with details: +*********************** + +./Cech_complex_test_unit --report_level=detailed --log_level=all + + ==> echo $? returns 0 in case of success (non-zero otherwise) diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp new file mode 100644 index 00000000..aa42d322 --- /dev/null +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -0,0 +1,274 @@ +/* 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 . + */ + +#define BOOST_TEST_DYN_LINK +#define BOOST_TEST_MODULE "cech_complex" +#include + +#include // float comparison +#include +#include +#include +#include // std::max + +#include +// to construct Cech_complex from a OFF file of points +#include +#include +#include +#include + +#include + +// Type definitions +using Simplex_tree = Gudhi::Simplex_tree<>; +using Filtration_value = Simplex_tree::Filtration_value; +using Point = std::vector; +using Point_cloud = std::vector; +using Points_off_reader = Gudhi::Points_off_reader; +using Cech_complex = Gudhi::cech_complex::Cech_complex; + +using Point_iterator = Point_cloud::const_iterator; +using Coordinate_iterator = Point::const_iterator; +using Min_sphere = Miniball::Miniball>; + +BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { + // ---------------------------------------------------------------------------- + // + // Init of a Cech complex from a OFF file + // + // ---------------------------------------------------------------------------- + std::string off_file_name("alphacomplexdoc.off"); + double threshold = 12.0; + std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech threshold=" << + threshold << "==========" << std::endl; + + Points_off_reader off_reader(off_file_name); + Point_cloud point_cloud = off_reader.get_point_cloud(); + Cech_complex cech_complex_from_file(point_cloud, threshold, Gudhi::Euclidean_distance()); + + std::size_t i = 0; + for (; i < point_cloud.size(); i++) { + BOOST_CHECK(point_cloud[i] == *(cech_complex_from_file.point_iterator(i))); + } +#ifdef GUDHI_DEBUG + BOOST_CHECK_THROW (cech_complex_from_file.point_iterator(i+1), std::out_of_range); +#endif // GUDHI_DEBUG + + const int DIMENSION_1 = 1; + Simplex_tree st; + cech_complex_from_file.create_complex(st, DIMENSION_1); + std::cout << "st.dimension()=" << st.dimension() << std::endl; + BOOST_CHECK(st.dimension() == DIMENSION_1); + + const int NUMBER_OF_VERTICES = 7; + std::cout << "st.num_vertices()=" << st.num_vertices() << std::endl; + BOOST_CHECK(st.num_vertices() == NUMBER_OF_VERTICES); + + std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl; + BOOST_CHECK(st.num_simplices() == 18); + + // Check filtration values of vertices is 0.0 + for (auto f_simplex : st.skeleton_simplex_range(0)) { + BOOST_CHECK(st.filtration(f_simplex) == 0.0); + } + + // Check filtration values of edges + for (auto f_simplex : st.skeleton_simplex_range(DIMENSION_1)) { + if (DIMENSION_1 == st.dimension(f_simplex)) { + std::vector vp; + std::cout << "vertex = ("; + for (auto vertex : st.simplex_vertex_range(f_simplex)) { + std::cout << vertex << ","; + vp.push_back(off_reader.get_point_cloud().at(vertex)); + } + std::cout << ") - distance =" << Gudhi::Euclidean_distance()(vp.at(0), vp.at(1)) << + " - filtration =" << st.filtration(f_simplex) << std::endl; + BOOST_CHECK(vp.size() == 2); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Euclidean_distance()(vp.at(0), vp.at(1))); + } + } + + const int DIMENSION_2 = 2; + Simplex_tree st2; + cech_complex_from_file.create_complex(st2, DIMENSION_2); + std::cout << "st2.dimension()=" << st2.dimension() << std::endl; + BOOST_CHECK(st2.dimension() == DIMENSION_2); + + std::cout << "st2.num_vertices()=" << st2.num_vertices() << std::endl; + BOOST_CHECK(st2.num_vertices() == NUMBER_OF_VERTICES); + + std::cout << "st2.num_simplices()=" << st2.num_simplices() << std::endl; + BOOST_CHECK(st2.num_simplices() == 23); + + Point_cloud points012; + for (std::size_t vertex = 0; vertex <= 2; vertex++) { + points012.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), + cech_complex_from_file.point_iterator(vertex)->end())); + } + Min_sphere ms012(cech_complex_from_file.dimension(), points012.begin(),points012.end()); + + Simplex_tree::Filtration_value f012 = st2.filtration(st2.find({0, 1, 2})); + std::cout << "f012= " << f012 << " | ms012_radius= " << std::sqrt(ms012.squared_radius()) << std::endl; + + GUDHI_TEST_FLOAT_EQUALITY_CHECK(f012, std::sqrt(ms012.squared_radius())); + + Point_cloud points456; + for (std::size_t vertex = 4; vertex <= 6; vertex++) { + points456.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), + cech_complex_from_file.point_iterator(vertex)->end())); + } + Min_sphere ms456(cech_complex_from_file.dimension(), points456.begin(),points456.end()); + + Simplex_tree::Filtration_value f456 = st2.filtration(st2.find({4, 5, 6})); + std::cout << "f456= " << f456 << " | ms456_radius= " << std::sqrt(ms456.squared_radius()) << std::endl; + + GUDHI_TEST_FLOAT_EQUALITY_CHECK(f456, std::sqrt(ms456.squared_radius())); + + const int DIMENSION_3 = 3; + Simplex_tree st3; + cech_complex_from_file.create_complex(st3, DIMENSION_3); + std::cout << "st3.dimension()=" << st3.dimension() << std::endl; + BOOST_CHECK(st3.dimension() == DIMENSION_3); + + std::cout << "st3.num_vertices()=" << st3.num_vertices() << std::endl; + BOOST_CHECK(st3.num_vertices() == NUMBER_OF_VERTICES); + + std::cout << "st3.num_simplices()=" << st3.num_simplices() << std::endl; + BOOST_CHECK(st3.num_simplices() == 24); + + Point_cloud points0123; + for (std::size_t vertex = 0; vertex <= 3; vertex++) { + points0123.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), + cech_complex_from_file.point_iterator(vertex)->end())); + } + Min_sphere ms0123(cech_complex_from_file.dimension(), points0123.begin(),points0123.end()); + + Simplex_tree::Filtration_value f0123 = st3.filtration(st3.find({0, 1, 2, 3})); + std::cout << "f0123= " << f0123 << " | ms0123_radius= " << std::sqrt(ms0123.squared_radius()) << std::endl; + + GUDHI_TEST_FLOAT_EQUALITY_CHECK(f0123, std::sqrt(ms0123.squared_radius())); + + + + Point_cloud points01; + for (std::size_t vertex = 0; vertex <= 1; vertex++) { + points01.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), + cech_complex_from_file.point_iterator(vertex)->end())); + } + Min_sphere ms01(cech_complex_from_file.dimension(), points01.begin(),points01.end()); + + Simplex_tree::Filtration_value f01 = st2.filtration(st2.find({0, 1})); + std::cout << "f01= " << f01 << " | ms01_radius= " << std::sqrt(ms01.squared_radius()) << std::endl; + +} + +BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { + // ---------------------------------------------------------------------------- + // Init of a list of points + // ---------------------------------------------------------------------------- + Point_cloud points; + std::vector coords = { 0.0, 0.0, 0.0, 1.0 }; + points.push_back(Point(coords.begin(), coords.end())); + coords = { 0.0, 0.0, 1.0, 0.0 }; + points.push_back(Point(coords.begin(), coords.end())); + coords = { 0.0, 1.0, 0.0, 0.0 }; + points.push_back(Point(coords.begin(), coords.end())); + coords = { 1.0, 0.0, 0.0, 0.0 }; + points.push_back(Point(coords.begin(), coords.end())); + + // ---------------------------------------------------------------------------- + // Init of a Cech complex from the list of points + // ---------------------------------------------------------------------------- + Cech_complex cech_complex_from_points(points, 2.0, Gudhi::Euclidean_distance()); + + std::cout << "========== cech_complex_from_points ==========" << std::endl; + Simplex_tree st; + const int DIMENSION = 3; + cech_complex_from_points.create_complex(st, DIMENSION); + + // Another way to check num_simplices + std::cout << "Iterator on Cech complex simplices in the filtration order, with [filtration value]:" << std::endl; + int num_simplices = 0; + for (auto f_simplex : st.filtration_simplex_range()) { + num_simplices++; + std::cout << " ( "; + for (auto vertex : st.simplex_vertex_range(f_simplex)) { + std::cout << vertex << " "; + } + std::cout << ") -> " << "[" << st.filtration(f_simplex) << "] "; + std::cout << std::endl; + } + BOOST_CHECK(num_simplices == 15); + std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl; + BOOST_CHECK(st.num_simplices() == 15); + + std::cout << "st.dimension()=" << st.dimension() << std::endl; + BOOST_CHECK(st.dimension() == DIMENSION); + std::cout << "st.num_vertices()=" << st.num_vertices() << std::endl; + BOOST_CHECK(st.num_vertices() == 4); + + for (auto f_simplex : st.filtration_simplex_range()) { + std::cout << "dimension(" << st.dimension(f_simplex) << ") - f = " << st.filtration(f_simplex) << std::endl; + switch (st.dimension(f_simplex)) { + case 0: + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.0); + break; + case 1: + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 1.41421, .00001); + break; + case 2: + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.816497, .00001); + break; + case 3: + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.866025, .00001); + break; + default: + BOOST_CHECK(false); // Shall not happen + break; + } + } +} + +#ifdef GUDHI_DEBUG +BOOST_AUTO_TEST_CASE(Cech_create_complex_throw) { + // ---------------------------------------------------------------------------- + // + // Init of a Cech complex from a OFF file + // + // ---------------------------------------------------------------------------- + std::string off_file_name("alphacomplexdoc.off"); + double threshold = 12.0; + std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech threshold=" << + threshold << "==========" << std::endl; + + Gudhi::Points_off_reader off_reader(off_file_name); + Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); + + Simplex_tree stree; + std::vector simplex = {0, 1, 2}; + stree.insert_simplex_and_subfaces(simplex); + std::cout << "Check exception throw in debug mode" << std::endl; + // throw excpt because stree is not empty + BOOST_CHECK_THROW (cech_complex_from_file.create_complex(stree, 1), std::invalid_argument); +} +#endif diff --git a/src/Cech_complex/utilities/CMakeLists.txt b/src/Cech_complex/utilities/CMakeLists.txt new file mode 100644 index 00000000..a4f89d2c --- /dev/null +++ b/src/Cech_complex/utilities/CMakeLists.txt @@ -0,0 +1,14 @@ +cmake_minimum_required(VERSION 2.6) +project(Cech_complex_utilities) + +add_executable(cech_persistence cech_persistence.cpp) +target_link_libraries(cech_persistence ${Boost_PROGRAM_OPTIONS_LIBRARY}) + +if (TBB_FOUND) + target_link_libraries(cech_persistence ${TBB_LIBRARIES}) +endif() + +add_test(NAME Cech_complex_utility_from_rips_on_tore_3D COMMAND $ + "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.25" "-m" "0.5" "-d" "3" "-p" "3") + +install(TARGETS cech_persistence DESTINATION bin) diff --git a/src/Cech_complex/utilities/cech_persistence.cpp b/src/Cech_complex/utilities/cech_persistence.cpp new file mode 100644 index 00000000..e93596d4 --- /dev/null +++ b/src/Cech_complex/utilities/cech_persistence.cpp @@ -0,0 +1,136 @@ +/* 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): Clément Maria + * + * Copyright (C) 2014 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 . + */ + +#include +#include +#include +#include +#include + +#include + +#include +#include +#include // infinity + +// Types definition +using Simplex_tree = Gudhi::Simplex_tree; +using Filtration_value = Simplex_tree::Filtration_value; +using Point = std::vector; +using Point_cloud = std::vector; +using Points_off_reader = Gudhi::Points_off_reader; +using Cech_complex = Gudhi::cech_complex::Cech_complex; +using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; +using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology; + +void program_options(int argc, char* argv[], std::string& off_file_points, std::string& filediag, + Filtration_value& threshold, int& dim_max, int& p, Filtration_value& min_persistence); + +int main(int argc, char* argv[]) { + std::string off_file_points; + std::string filediag; + Filtration_value threshold; + int dim_max; + int p; + Filtration_value min_persistence; + + program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); + + Points_off_reader off_reader(off_file_points); + Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); + + // Construct the Cech complex in a Simplex Tree + Simplex_tree simplex_tree; + + cech_complex_from_file.create_complex(simplex_tree, dim_max); + std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n"; + std::cout << " and has dimension " << simplex_tree.dimension() << " \n"; + + // Sort the simplices in the order of the filtration + simplex_tree.initialize_filtration(); + + // Compute the persistence diagram of the complex + Persistent_cohomology pcoh(simplex_tree); + // initializes the coefficient field for homology + pcoh.init_coefficients(p); + + pcoh.compute_persistent_cohomology(min_persistence); + + // Output the diagram in filediag + if (filediag.empty()) { + pcoh.output_diagram(); + } else { + std::ofstream out(filediag); + pcoh.output_diagram(out); + out.close(); + } + + return 0; +} + +void program_options(int argc, char* argv[], std::string& off_file_points, std::string& filediag, + Filtration_value& threshold, int& dim_max, int& p, Filtration_value& min_persistence) { + namespace po = boost::program_options; + po::options_description hidden("Hidden options"); + hidden.add_options()("input-file", po::value(&off_file_points), + "Name of an OFF file containing a point set.\n"); + + po::options_description visible("Allowed options", 100); + visible.add_options()("help,h", "produce help message")( + "output-file,o", po::value(&filediag)->default_value(std::string()), + "Name of file in which the persistence diagram is written. Default print in std::cout")( + "max-edge-length,r", + po::value(&threshold)->default_value(std::numeric_limits::infinity()), + "Maximal length of an edge for the Cech complex construction.")( + "cpx-dimension,d", po::value(&dim_max)->default_value(1), + "Maximal dimension of the Cech complex we want to compute.")( + "field-charac,p", po::value(&p)->default_value(11), + "Characteristic p of the coefficient field Z/pZ for computing homology.")( + "min-persistence,m", po::value(&min_persistence), + "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length " + "intervals"); + + po::positional_options_description pos; + pos.add("input-file", 1); + + po::options_description all; + all.add(visible).add(hidden); + + po::variables_map vm; + po::store(po::command_line_parser(argc, argv).options(all).positional(pos).run(), vm); + po::notify(vm); + + if (vm.count("help") || !vm.count("input-file")) { + std::cout << std::endl; + std::cout << "Compute the persistent homology with coefficient field Z/pZ \n"; + std::cout << "of a Cech complex defined on a set of input points.\n \n"; + std::cout << "The output diagram contains one bar per line, written with the convention: \n"; + std::cout << " p dim b d \n"; + std::cout << "where dim is the dimension of the homological feature,\n"; + std::cout << "b and d are respectively the birth and death of the feature and \n"; + std::cout << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl; + + std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl; + std::cout << visible << std::endl; + std::abort(); + } +} diff --git a/src/Cech_complex/utilities/cechcomplex.md b/src/Cech_complex/utilities/cechcomplex.md new file mode 100644 index 00000000..6330727a --- /dev/null +++ b/src/Cech_complex/utilities/cechcomplex.md @@ -0,0 +1,33 @@ + + +# Cech complex # + +## cech_persistence ## +This program computes the persistent homology with coefficient field *Z/pZ* of a Cech complex defined on a set of input points, using Euclidean distance. The output diagram contains one bar per line, written with the convention: + +`p dim birth death` + +where `dim` is the dimension of the homological feature, `birth` and `death` are respectively the birth and death of the feature, and `p` is the characteristic of the field *Z/pZ* used for homology coefficients (`p` must be a prime number). + +**Usage** + +`cech_persistence [options] ` + +**Allowed options** + +* `-h [ --help ]` Produce help message +* `-o [ --output-file ]` Name of file in which the persistence diagram is written. Default print in standard output. +* `-r [ --max-edge-length ]` (default = inf) Maximal length of an edge for the Cech complex construction. +* `-d [ --cpx-dimension ]` (default = 1) Maximal dimension of the Cech complex we want to compute. +* `-p [ --field-charac ]` (default = 11) Characteristic p of the coefficient field Z/pZ for computing homology. +* `-m [ --min-persistence ]` (default = 0) Minimal lifetime of homology feature to be recorded. Enter a negative value to see zero length intervals. + +Beware: this program may use a lot of RAM and take a lot of time if `max-edge-length` is set to a large value. + +**Example 1 with Z/2Z coefficients** + +`cech_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 2` + +**Example 2 with Z/3Z coefficients** + +`cech_persistence ../../data/points/tore3D_1307.off -r 0.25 -m 0.5 -d 3 -p 3` -- cgit v1.2.3 From d57e3dfbf15f8aaa3afa097a4e3ed49cd23d26ea Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Tue, 20 Feb 2018 16:30:27 +0000 Subject: Add doc, example renamed git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3254 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 666bacd07c711b89167c87155c21fe88688e2e68 --- src/Cech_complex/doc/COPYRIGHT | 19 ++ src/Cech_complex/doc/Intro_cech_complex.h | 92 ++++++ .../doc/cech_complex_representation.ipe | 326 +++++++++++++++++++++ .../doc/cech_complex_representation.png | Bin 0 -> 15677 bytes src/Cech_complex/doc/cech_one_skeleton.ipe | 326 +++++++++++++++++++++ src/Cech_complex/doc/cech_one_skeleton.png | Bin 0 -> 47651 bytes src/Cech_complex/example/CMakeLists.txt | 6 +- .../example/cech_complex_example_from_points.cpp | 75 +++++ .../cech_complex_example_from_points_for_doc.txt | 16 + .../example_one_skeleton_cech_from_points.cpp | 75 ----- .../include/gudhi/Cech_complex_blocker.h | 8 +- 11 files changed, 861 insertions(+), 82 deletions(-) create mode 100644 src/Cech_complex/doc/COPYRIGHT create mode 100644 src/Cech_complex/doc/cech_complex_representation.ipe create mode 100644 src/Cech_complex/doc/cech_complex_representation.png create mode 100644 src/Cech_complex/doc/cech_one_skeleton.ipe create mode 100644 src/Cech_complex/doc/cech_one_skeleton.png create mode 100644 src/Cech_complex/example/cech_complex_example_from_points.cpp create mode 100644 src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt delete mode 100644 src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/doc/COPYRIGHT b/src/Cech_complex/doc/COPYRIGHT new file mode 100644 index 00000000..594b7d03 --- /dev/null +++ b/src/Cech_complex/doc/COPYRIGHT @@ -0,0 +1,19 @@ +The files of this directory are part of the Gudhi Library. The Gudhi library +(Geometric Understanding in Higher Dimensions) is a generic C++ library for +computational topology. + +Author(s): Clément Maria, Pawel Dlotko, Vincent Rouvreau + +Copyright (C) 2015 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 . diff --git a/src/Cech_complex/doc/Intro_cech_complex.h b/src/Cech_complex/doc/Intro_cech_complex.h index e69de29b..f2052763 100644 --- a/src/Cech_complex/doc/Intro_cech_complex.h +++ b/src/Cech_complex/doc/Intro_cech_complex.h @@ -0,0 +1,92 @@ +/* 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 . + */ + +#ifndef DOC_CECH_COMPLEX_INTRO_CECH_COMPLEX_H_ +#define DOC_CECH_COMPLEX_INTRO_CECH_COMPLEX_H_ + +namespace Gudhi { + +namespace cech_complex { + +/** \defgroup cech_complex Cech complex + * + * \author Clément Maria, Pawel Dlotko, Vincent Rouvreau + * + * @{ + * + * \section cechdefinition Cech complex definition + * + * Cech_complex + * (Wikipedia) is a + * proximity graph that allows to construct a + * simplicial complex + * from it. + * The input can be a point cloud with a given distance function. + * + * The filtration value of each edge is computed from a user-given distance function. + * + * All edges that have a filtration value strictly greater than a given threshold value are not inserted into + * the complex. + * + * When creating a simplicial complex from this proximity graph, Cech inserts the proximity graph into the data + * structure, and then expands the simplicial complex when required. + * + * Vertex name correspond to the index of the point in the given range (aka. the point cloud). + * + * \image html "cech_complex_representation.png" "Cech complex proximity graph representation" + * + * On this example, as edges (4,5), (4,6) and (5,6) are in the complex, simplex (4,5,6) is added with the filtration + * value set with \f$max(filtration(4,5), filtration(4,6), filtration(5,6))\f$. + * And so on for simplex (0,1,2,3). + * + * If the Cech_complex interfaces are not detailed enough for your need, please refer to + * + * cech_persistence_step_by_step.cpp example, where the graph construction over the Simplex_tree is more detailed. + * + * \section cechpointsdistance Point cloud and distance function + * + * \subsection cechpointscloudexample Example from a point cloud and a distance function + * + * This example builds the proximity graph from the given points, threshold value, and distance function. + * Then it creates a `Simplex_tree` with it. + * + * Then, it is asked to display information about the simplicial complex. + * + * \include Cech_complex/cech_complex_example_from_points.cpp + * + * When launching (Cech maximal distance between 2 points is 7.1, is expanded until dimension 2): + * + * \code $> ./Cech_complex_example_from_points + * \endcode + * + * the program output is: + * + * \include Cech_complex/cech_complex_example_from_points_for_doc.txt + * + */ +/** @} */ // end defgroup cech_complex + +} // namespace cech_complex + +} // namespace Gudhi + +#endif // DOC_CECH_COMPLEX_INTRO_CECH_COMPLEX_H_ diff --git a/src/Cech_complex/doc/cech_complex_representation.ipe b/src/Cech_complex/doc/cech_complex_representation.ipe new file mode 100644 index 00000000..7f6028f4 --- /dev/null +++ b/src/Cech_complex/doc/cech_complex_representation.ipe @@ -0,0 +1,326 @@ + + + + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h + + + + +0.6 0 0 0.6 0 0 e +0.4 0 0 0.4 0 0 e + + + + +0.6 0 0 0.6 0 0 e + + + + + +0.5 0 0 0.5 0 0 e + + +0.6 0 0 0.6 0 0 e +0.4 0 0 0.4 0 0 e + + + + + +-0.6 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541.915 l +h + + +79.8776 552.169 m +109.756 601.699 l +139.812 542.209 l +h + + +69.8453 682.419 m +159.925 712.208 l +90.12 732.039 l +h + +Rips complex +0 +1 +2 +3 +4 +5 +6 + +60 710 m +40 660 l + + +40 660 m +130 690 l + + +130 690 m +60 710 l + + +40 660 m +80 580 l + + +80 580 m +130 580 l +130 580 l + + +130 580 m +110 520 l + + +110 520 m +50 530 l +50 530 l +50 530 l + + +50 530 m +80 580 l + + +130 580 m +130 690 l + + + + + + + +150.038 609.9 m +179.929 549.727 l + + + + +158.7 593.269 m +81.4925 544.805 l + + +256.324 639.958 m +370.055 639.958 l + + +56.8567 0 0 56.8567 313.217 639.756 e + + + +Rips threshold + + diff --git a/src/Cech_complex/doc/cech_complex_representation.png b/src/Cech_complex/doc/cech_complex_representation.png new file mode 100644 index 00000000..e901d92e Binary files /dev/null and b/src/Cech_complex/doc/cech_complex_representation.png differ diff --git a/src/Cech_complex/doc/cech_one_skeleton.ipe b/src/Cech_complex/doc/cech_one_skeleton.ipe new file mode 100644 index 00000000..3a35970c --- /dev/null +++ b/src/Cech_complex/doc/cech_one_skeleton.ipe @@ -0,0 +1,326 @@ + + + + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h + + + + +0.6 0 0 0.6 0 0 e +0.4 0 0 0.4 0 0 e + + + + +0.6 0 0 0.6 0 0 e + + + + + +0.5 0 0 0.5 0 0 e + + +0.6 0 0 0.6 0 0 e +0.4 0 0 0.4 0 0 e + + + + + +-0.6 -0.6 m +0.6 -0.6 l +0.6 0.6 l +-0.6 0.6 l +h +-0.4 -0.4 m +0.4 -0.4 l +0.4 0.4 l +-0.4 0.4 l +h + + + + +-0.6 -0.6 m +0.6 -0.6 l +0.6 0.6 l +-0.6 0.6 l +h + + + + + +-0.5 -0.5 m +0.5 -0.5 l +0.5 0.5 l +-0.5 0.5 l +h + + +-0.6 -0.6 m +0.6 -0.6 l +0.6 0.6 l +-0.6 0.6 l +h +-0.4 -0.4 m +0.4 -0.4 l +0.4 0.4 l +-0.4 0.4 l +h + + + + + + +-0.43 -0.57 m +0.57 0.43 l +0.43 0.57 l +-0.57 -0.43 l +h + + +-0.43 0.57 m +0.57 -0.43 l +0.43 -0.57 l +-0.57 0.43 l +h + + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h + + + + +0 0 m +-1 0.333 l +-0.8 0 l +-1 -0.333 l +h + + + + +0 0 m +-1 0.333 l +-0.8 0 l +-1 -0.333 l +h + + + + +-1 0.333 m +0 0 l +-1 -0.333 l + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h +-1 0 m +-2 0.333 l +-2 -0.333 l +h + + + + +0 0 m +-1 0.333 l +-1 -0.333 l +h +-1 0 m +-2 0.333 l +-2 -0.333 l +h + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +109.771 601.912 m +159.595 601.797 l +140.058 541.915 l +h + + +79.8776 552.169 m +109.756 601.699 l +139.812 542.209 l +h + + +69.8453 682.419 m +159.925 712.208 l +90.12 732.039 l +h + +One skeleton graph +0 +1 +2 +3 +4 +5 +6 + +60 710 m +40 660 l + + +40 660 m +130 690 l + + +130 690 m +60 710 l + + +40 660 m +80 580 l + + +80 580 m +130 580 l +130 580 l + + +130 580 m +110 520 l + + +110 520 m +50 530 l +50 530 l +50 530 l + + +50 530 m +80 580 l + + +130 580 m +130 690 l + + + + + + + +150.038 609.9 m +179.929 549.727 l + + + + +158.7 593.269 m +81.4925 544.805 l + + +256.324 639.958 m +370.055 639.958 l + + +56.8567 0 0 56.8567 313.217 639.756 e + + + +Rips threshold + + diff --git a/src/Cech_complex/doc/cech_one_skeleton.png b/src/Cech_complex/doc/cech_one_skeleton.png new file mode 100644 index 00000000..1028770e Binary files /dev/null and b/src/Cech_complex/doc/cech_one_skeleton.png differ diff --git a/src/Cech_complex/example/CMakeLists.txt b/src/Cech_complex/example/CMakeLists.txt index 8097871f..ac32ff95 100644 --- a/src/Cech_complex/example/CMakeLists.txt +++ b/src/Cech_complex/example/CMakeLists.txt @@ -7,8 +7,8 @@ if (TBB_FOUND) target_link_libraries(Cech_complex_example_step_by_step ${TBB_LIBRARIES}) endif() -add_executable ( Cech_complex_example_one_skeleton_from_points example_one_skeleton_cech_from_points.cpp) +add_executable ( Cech_complex_example_from_points cech_complex_example_from_points.cpp) if (TBB_FOUND) - target_link_libraries(Cech_complex_example_one_skeleton_from_points ${TBB_LIBRARIES}) + target_link_libraries(Cech_complex_example_from_points ${TBB_LIBRARIES}) endif() -add_test(NAME Cech_complex_example_one_skeleton_from_points COMMAND $) +add_test(NAME Cech_complex_example_from_points COMMAND $) diff --git a/src/Cech_complex/example/cech_complex_example_from_points.cpp b/src/Cech_complex/example/cech_complex_example_from_points.cpp new file mode 100644 index 00000000..882849c3 --- /dev/null +++ b/src/Cech_complex/example/cech_complex_example_from_points.cpp @@ -0,0 +1,75 @@ +/* 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 . + */ + +#include +#include +#include + +#include +#include +#include +#include + +int main() { + // Type definitions + using Point_cloud = std::vector>; + using Simplex_tree = Gudhi::Simplex_tree; + using Filtration_value = Simplex_tree::Filtration_value; + using Cech_complex = Gudhi::cech_complex::Cech_complex; + + Point_cloud points; + points.push_back({1.0, 1.0}); + points.push_back({7.0, 0.0}); + points.push_back({4.0, 6.0}); + points.push_back({9.0, 6.0}); + points.push_back({0.0, 14.0}); + points.push_back({2.0, 19.0}); + points.push_back({9.0, 17.0}); + + // ---------------------------------------------------------------------------- + // Init of a Cech complex from points + // ---------------------------------------------------------------------------- + // 7.1 is a magic number to force one blocker, and one non-blocker + Filtration_value threshold = 7.1; + Cech_complex cech_complex_from_points(points, threshold, Gudhi::Euclidean_distance()); + + Simplex_tree stree; + cech_complex_from_points.create_complex(stree, 2); + // ---------------------------------------------------------------------------- + // Display information about the one skeleton Cech complex + // ---------------------------------------------------------------------------- + std::cout << "Cech complex is of dimension " << stree.dimension() << + " - " << stree.num_simplices() << " simplices - " << + stree.num_vertices() << " vertices." << std::endl; + + std::cout << "Iterator on Cech complex simplices in the filtration order, with [filtration value]:" << + std::endl; + for (auto f_simplex : stree.filtration_simplex_range()) { + std::cout << " ( "; + for (auto vertex : stree.simplex_vertex_range(f_simplex)) { + std::cout << vertex << " "; + } + std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; + std::cout << std::endl; + } + return 0; +} diff --git a/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt b/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt new file mode 100644 index 00000000..684e120b --- /dev/null +++ b/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt @@ -0,0 +1,16 @@ +Cech complex is of dimension 2 - 14 simplices - 7 vertices. +Iterator on Cech complex simplices in the filtration order, with [filtration value]: + ( 0 ) -> [0] + ( 1 ) -> [0] + ( 2 ) -> [0] + ( 3 ) -> [0] + ( 4 ) -> [0] + ( 5 ) -> [0] + ( 6 ) -> [0] + ( 3 2 ) -> [5] + ( 5 4 ) -> [5.38516] + ( 2 0 ) -> [5.83095] + ( 1 0 ) -> [6.08276] + ( 3 1 ) -> [6.32456] + ( 2 1 ) -> [6.7082] + ( 3 2 1 ) -> [7.07107] diff --git a/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp b/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp deleted file mode 100644 index 73679716..00000000 --- a/src/Cech_complex/example/example_one_skeleton_cech_from_points.cpp +++ /dev/null @@ -1,75 +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) 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 . - */ - -#include -#include -#include - -#include -#include -#include -#include -#include // for std::numeric_limits - -int main() { - // Type definitions - using Point_cloud = std::vector>; - using Simplex_tree = Gudhi::Simplex_tree; - using Filtration_value = Simplex_tree::Filtration_value; - using Cech_complex = Gudhi::cech_complex::Cech_complex; - - Point_cloud points; - points.push_back({1.0, 1.0}); - points.push_back({7.0, 0.0}); - points.push_back({4.0, 6.0}); - points.push_back({9.0, 6.0}); - points.push_back({0.0, 14.0}); - points.push_back({2.0, 19.0}); - points.push_back({9.0, 17.0}); - - // ---------------------------------------------------------------------------- - // Init of a Rips complex from points - // ---------------------------------------------------------------------------- - Filtration_value threshold = 12.0; - Cech_complex cech_complex_from_points(points, threshold, Gudhi::Euclidean_distance()); - - Simplex_tree stree; - cech_complex_from_points.create_complex(stree, 3); - // ---------------------------------------------------------------------------- - // Display information about the one skeleton Rips complex - // ---------------------------------------------------------------------------- - std::cout << "Cech complex is of dimension " << stree.dimension() << - " - " << stree.num_simplices() << " simplices - " << - stree.num_vertices() << " vertices." << std::endl; - - std::cout << "Iterator on Cech complex simplices in the filtration order, with [filtration value]:" << - std::endl; - for (auto f_simplex : stree.filtration_simplex_range()) { - std::cout << " ( "; - for (auto vertex : stree.simplex_vertex_range(f_simplex)) { - std::cout << vertex << " "; - } - std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; - std::cout << std::endl; - } - return 0; -} diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index f8738be0..fb52f712 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -80,12 +80,12 @@ class Cech_blocker { #endif // DEBUG_TRACES } Min_sphere ms(cc_ptr_->dimension(), points.begin(),points.end()); - Filtration_value radius = std::sqrt(ms.squared_radius()); + Filtration_value diameter = 2 * std::sqrt(ms.squared_radius()); #ifdef DEBUG_TRACES - std::cout << "radius = " << radius << " - " << (radius > cc_ptr_->threshold()) << std::endl; + std::cout << "diameter = " << diameter << " - " << (diameter > cc_ptr_->threshold()) << std::endl; #endif // DEBUG_TRACES - simplicial_complex_.assign_filtration(sh, radius); - return (radius > cc_ptr_->threshold()); + simplicial_complex_.assign_filtration(sh, diameter); + return (diameter > cc_ptr_->threshold()); } /** \internal \brief Cech complex blocker constructor. */ -- cgit v1.2.3 From 3cd1e01f0b0d4fdb46f49ec640c389374ca2fe70 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Thu, 22 Feb 2018 23:16:55 +0000 Subject: Fix Cech with radius distance Add a meta generation script for off_file_generator git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3256 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: fb13baa124ddc97c0dc61835ab0c72595d666155 --- scripts/metagen.sh | 15 ++ src/Cech_complex/benchmark/CMakeLists.txt | 12 ++ .../benchmark/cech_complex_benchmark.cpp | 153 +++++++++++++++++++++ src/Cech_complex/doc/cech_one_skeleton.png | Bin 47651 -> 12070 bytes .../example/cech_complex_example_from_points.cpp | 43 ++---- .../example/cech_complex_step_by_step.cpp | 32 ++--- src/Cech_complex/include/gudhi/Cech_complex.h | 33 ++--- .../include/gudhi/Cech_complex_blocker.h | 19 +-- src/Cech_complex/test/test_cech_complex.cpp | 38 ++--- src/Cech_complex/utilities/CMakeLists.txt | 2 +- src/Cech_complex/utilities/cech_persistence.cpp | 14 +- src/common/include/gudhi/distance_functions.h | 33 +++++ 12 files changed, 284 insertions(+), 110 deletions(-) create mode 100755 scripts/metagen.sh create mode 100644 src/Cech_complex/benchmark/CMakeLists.txt create mode 100644 src/Cech_complex/benchmark/cech_complex_benchmark.cpp (limited to 'src/Cech_complex/include') diff --git a/scripts/metagen.sh b/scripts/metagen.sh new file mode 100755 index 00000000..4483d24e --- /dev/null +++ b/scripts/metagen.sh @@ -0,0 +1,15 @@ +#!/bin/bash +sep="_" +for geom in "sphere" "klein" "torus" +do + for number in 10 100 1000 + do + for dim in {3..5} + do + echo "./off_file_from_shape_generator on $geom $geom$sep$number$sep$dim.off $number $dim" + ./off_file_from_shape_generator on $geom $geom$sep$number$sep$dim.off $number $dim + done + done +done + +#./off_file_from_shape_generator in|on sphere|cube off_file_name points_number[integer > 0] dimension[integer > 1] radius[double > 0.0 | default = 1.0] diff --git a/src/Cech_complex/benchmark/CMakeLists.txt b/src/Cech_complex/benchmark/CMakeLists.txt new file mode 100644 index 00000000..2a65865b --- /dev/null +++ b/src/Cech_complex/benchmark/CMakeLists.txt @@ -0,0 +1,12 @@ +cmake_minimum_required(VERSION 2.6) +project(Cech_complex_benchmark) + +# Do not forget to copy test files in current binary dir +#file(COPY "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) + +add_executable(cech_complex_benchmark cech_complex_benchmark.cpp) +target_link_libraries(cech_complex_benchmark ${Boost_FILESYSTEM_LIBRARY}) + +if (TBB_FOUND) + target_link_libraries(cech_complex_benchmark ${TBB_LIBRARIES}) +endif() diff --git a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp new file mode 100644 index 00000000..71c88982 --- /dev/null +++ b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp @@ -0,0 +1,153 @@ +/* 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 . + */ + +#include +#include +#include +#include +#include +#include +#include + +#include + +#include "boost/filesystem.hpp" // includes all needed Boost.Filesystem declarations + +#include +#include + + +// Types definition +using Simplex_tree = Gudhi::Simplex_tree<>; +using Filtration_value = Simplex_tree::Filtration_value; +using Point = std::vector; +using Point_cloud = std::vector; +using Points_off_reader = Gudhi::Points_off_reader; +using Proximity_graph = Gudhi::Proximity_graph; +using Rips_complex = Gudhi::rips_complex::Rips_complex; +using Cech_complex = Gudhi::cech_complex::Cech_complex; + + +class Radius_distance { + public: + // boost::range_value is not SFINAE-friendly so we cannot use it in the return type + template< typename Point > + typename std::iterator_traits::type>::value_type + operator()(const Point& p1, const Point& p2) const { + // Type def + using Point_cloud = std::vector; + using Point_iterator = typename Point_cloud::const_iterator; + using Coordinate_iterator = typename Point::const_iterator; + using Min_sphere = typename Miniball::Miniball>; + + Point_cloud point_cloud; + point_cloud.push_back(p1); + point_cloud.push_back(p2); + + GUDHI_CHECK((p1.end()-p1.begin()) != (p2.end()-p2.begin()), "inconsistent point dimensions"); + Min_sphere min_sphere(p1.end()-p1.begin(), point_cloud.begin(),point_cloud.end()); + + return std::sqrt(min_sphere.squared_radius()); + } +}; + + +int main(int argc, char * argv[]) { + std::string off_file_points = "tore3D_1307.off"; + Filtration_value threshold = 1e20; + + // Extract the points from the file filepoints + Points_off_reader off_reader(off_file_points); + + Gudhi::Clock euclidean_clock("Gudhi::Euclidean_distance"); + // Compute the proximity graph of the points + Proximity_graph euclidean_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), + threshold, + Gudhi::Euclidean_distance()); + + std::cout << euclidean_clock << std::endl; + + Gudhi::Clock radius_clock("Radius_distance"); + // Compute the proximity graph of the points + Proximity_graph radius_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), + threshold, + Radius_distance()); + std::cout << radius_clock << std::endl; + + Gudhi::Clock squared_radius_clock("Gudhi::Radius_distance()"); + // Compute the proximity graph of the points + Proximity_graph sq_radius_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), + threshold, + Gudhi::Radius_distance()); + std::cout << squared_radius_clock << std::endl; + + + boost::filesystem::path full_path(boost::filesystem::current_path()); + std::cout << "Current path is : " << full_path << std::endl; + + + std::cout << "File name;Radius;Rips time;Cech time; Ratio Rips/Cech time;Rips nb simplices;Cech nb simplices;" << std::endl; + boost::filesystem::directory_iterator end_itr; // default construction yields past-the-end + for ( boost::filesystem::directory_iterator itr( boost::filesystem::current_path() ); + itr != end_itr; + ++itr ) + { + if ( ! boost::filesystem::is_directory(itr->status()) ) + { + if ( itr->path().extension() == ".off" ) // see below + { + Points_off_reader off_reader(itr->path().string()); + + for (Filtration_value radius = 0.1; radius < 0.4; radius += 0.1) { + std::cout << itr->path().stem() << ";"; + std::cout << radius << ";"; + Gudhi::Clock rips_clock("Rips computation"); + Rips_complex rips_complex_from_points(off_reader.get_point_cloud(), radius, Gudhi::Radius_distance()); + Simplex_tree rips_stree; + rips_complex_from_points.create_complex(rips_stree, 2); + // ------------------------------------------ + // Display information about the Rips complex + // ------------------------------------------ + double rips_sec = rips_clock.num_seconds(); + std::cout << rips_sec << ";"; + + Gudhi::Clock cech_clock("Cech computation"); + Cech_complex cech_complex_from_points(off_reader.get_point_cloud(), radius); + Simplex_tree cech_stree; + cech_complex_from_points.create_complex(cech_stree, 2); + // ------------------------------------------ + // Display information about the Cech complex + // ------------------------------------------ + double cech_sec = cech_clock.num_seconds(); + std::cout << cech_sec << ";"; + std::cout << cech_sec / rips_sec << ";"; + + std::cout << rips_stree.num_simplices() << ";"; + std::cout << cech_stree.num_simplices() << ";" << std::endl; + } + } + } + } + + + return 0; +} diff --git a/src/Cech_complex/doc/cech_one_skeleton.png b/src/Cech_complex/doc/cech_one_skeleton.png index 1028770e..ffa9c329 100644 Binary files a/src/Cech_complex/doc/cech_one_skeleton.png and b/src/Cech_complex/doc/cech_one_skeleton.png differ diff --git a/src/Cech_complex/example/cech_complex_example_from_points.cpp b/src/Cech_complex/example/cech_complex_example_from_points.cpp index 882849c3..97327e69 100644 --- a/src/Cech_complex/example/cech_complex_example_from_points.cpp +++ b/src/Cech_complex/example/cech_complex_example_from_points.cpp @@ -1,25 +1,3 @@ -/* 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 . - */ - #include #include #include @@ -37,23 +15,22 @@ int main() { using Cech_complex = Gudhi::cech_complex::Cech_complex; Point_cloud points; - points.push_back({1.0, 1.0}); - points.push_back({7.0, 0.0}); - points.push_back({4.0, 6.0}); - points.push_back({9.0, 6.0}); - points.push_back({0.0, 14.0}); - points.push_back({2.0, 19.0}); - points.push_back({9.0, 17.0}); + points.push_back({0., 0.}); + points.push_back({0., 2.}); + points.push_back({std::sqrt(3.), 1.}); + points.push_back({1., 0.}); + points.push_back({1., 2.}); + points.push_back({1. - std::sqrt(3.), 1.}); // ---------------------------------------------------------------------------- // Init of a Cech complex from points // ---------------------------------------------------------------------------- - // 7.1 is a magic number to force one blocker, and one non-blocker - Filtration_value threshold = 7.1; - Cech_complex cech_complex_from_points(points, threshold, Gudhi::Euclidean_distance()); + // 5. is a magic number to force one blocker, and one non-blocker + Filtration_value max_radius = 12.; + Cech_complex cech_complex_from_points(points, max_radius); Simplex_tree stree; - cech_complex_from_points.create_complex(stree, 2); + cech_complex_from_points.create_complex(stree, -1); // ---------------------------------------------------------------------------- // Display information about the one skeleton Cech complex // ---------------------------------------------------------------------------- diff --git a/src/Cech_complex/example/cech_complex_step_by_step.cpp b/src/Cech_complex/example/cech_complex_step_by_step.cpp index e71086b6..8705a3e5 100644 --- a/src/Cech_complex/example/cech_complex_step_by_step.cpp +++ b/src/Cech_complex/example/cech_complex_step_by_step.cpp @@ -65,23 +65,22 @@ class Cech_blocker { std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES } - Min_sphere ms(dimension_, points.begin(),points.end()); - Filtration_value radius = std::sqrt(ms.squared_radius()); + Filtration_value radius = Gudhi::Radius_distance()(points); #ifdef DEBUG_TRACES - std::cout << "radius = " << radius << " - " << (radius > threshold_) << std::endl; + std::cout << "radius = " << radius << " - " << (radius > max_radius_) << std::endl; #endif // DEBUG_TRACES simplex_tree_.assign_filtration(sh, radius); - return (radius > threshold_); + return (radius > max_radius_); } - Cech_blocker(Simplex_tree& simplex_tree, Filtration_value threshold, const std::vector& point_cloud) + Cech_blocker(Simplex_tree& simplex_tree, Filtration_value max_radius, const std::vector& point_cloud) : simplex_tree_(simplex_tree), - threshold_(threshold), + max_radius_(max_radius), point_cloud_(point_cloud) { dimension_ = point_cloud_[0].size(); } private: Simplex_tree simplex_tree_; - Filtration_value threshold_; + Filtration_value max_radius_; std::vector point_cloud_; int dimension_; }; @@ -89,31 +88,31 @@ class Cech_blocker { void program_options(int argc, char * argv[] , std::string & off_file_points - , Filtration_value & threshold + , Filtration_value & max_radius , int & dim_max); int main(int argc, char * argv[]) { std::string off_file_points; - Filtration_value threshold; + Filtration_value max_radius; int dim_max; - program_options(argc, argv, off_file_points, threshold, dim_max); + program_options(argc, argv, off_file_points, max_radius, dim_max); // Extract the points from the file filepoints Points_off_reader off_reader(off_file_points); // Compute the proximity graph of the points Proximity_graph prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Gudhi::Euclidean_distance()); + max_radius, + Gudhi::Radius_distance()); // Construct the Rips complex in a Simplex Tree Simplex_tree st; // insert the proximity graph in the simplex tree st.insert_graph(prox_graph); // expand the graph until dimension dim_max - st.expansion_with_blockers(dim_max, Cech_blocker(st, threshold, off_reader.get_point_cloud())); + st.expansion_with_blockers(dim_max, Cech_blocker(st, max_radius, off_reader.get_point_cloud())); std::cout << "The complex contains " << st.num_simplices() << " simplices \n"; std::cout << " and has dimension " << st.dimension() << " \n"; @@ -123,7 +122,6 @@ int main(int argc, char * argv[]) { #if DEBUG_TRACES std::cout << "********************************************************************\n"; - // Display the Simplex_tree - Can not be done in the middle of 2 inserts std::cout << "* The complex contains " << st.num_simplices() << " simplices - dimension=" << st.dimension() << "\n"; std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n"; for (auto f_simplex : st.filtration_simplex_range()) { @@ -140,7 +138,7 @@ int main(int argc, char * argv[]) { void program_options(int argc, char * argv[] , std::string & off_file_points - , Filtration_value & threshold + , Filtration_value & max_radius , int & dim_max) { namespace po = boost::program_options; po::options_description hidden("Hidden options"); @@ -151,8 +149,8 @@ void program_options(int argc, char * argv[] po::options_description visible("Allowed options", 100); visible.add_options() ("help,h", "produce help message") - ("max-edge-length,r", - po::value(&threshold)->default_value(std::numeric_limits::infinity()), + ("max-radius,r", + po::value(&max_radius)->default_value(std::numeric_limits::infinity()), "Maximal length of an edge for the Rips complex construction.") ("cpx-dimension,d", po::value(&dim_max)->default_value(1), "Maximal dimension of the Rips complex we want to compute."); diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index e847c97f..a50ed9fa 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -23,12 +23,12 @@ #ifndef CECH_COMPLEX_H_ #define CECH_COMPLEX_H_ +#include // for Gudhi::Squared_radius #include // for Gudhi::Proximity_graph #include // for GUDHI_CHECK #include // for Gudhi::cech_complex::Cech_blocker #include -#include // for std::size_t #include // for exception management namespace Gudhi { @@ -43,7 +43,7 @@ namespace cech_complex { * * \details * The data structure is a proximity graph, containing edges when the edge length is less or equal - * to a given threshold. Edge length is computed from a user given point cloud with a given distance function. + * to a given max_radius. Edge length is computed from `Gudhi::Squared_radius` distance function. * * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required * by `Gudhi::Proximity_graph`. @@ -62,23 +62,18 @@ class Cech_complex { /** \brief Cech_complex constructor from a list of points. * * @param[in] points Range of points. - * @param[in] threshold Rips value. - * @param[in] distance distance function that returns a `Filtration_value` from 2 given points. + * @param[in] max_radius Maximal radius value. * * \tparam ForwardPointRange must be a range for which `.size()`, `.begin()` and `.end()` methods return input * iterators on a point. `.begin()` and `.end()` methods are required for a point. * - * \tparam Distance furnishes `operator()(const Point& p1, const Point& p2)`, where - * `Point` is a point from the `ForwardPointRange`, and that returns a `Filtration_value`. */ - template - Cech_complex(const ForwardPointRange& points, Filtration_value threshold, Distance distance) - : threshold_(threshold), + Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) + : max_radius_(max_radius), point_cloud_(points) { - dimension_ = points.begin()->end() - points.begin()->begin(); cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, - threshold_, - distance); + max_radius_, + Gudhi::Radius_distance()); } /** \brief Initializes the simplicial complex from the proximity graph and expands it until a given maximal @@ -101,14 +96,9 @@ class Cech_complex { Cech_blocker(complex, this)); } - /** @return Threshold value given at construction. */ - Filtration_value threshold() const { - return threshold_; - } - - /** @return Dimension value given at construction by the first point dimension. */ - std::size_t dimension() const { - return dimension_; + /** @return max_radius value given at construction. */ + Filtration_value max_radius() const { + return max_radius_; } /** @param[in] vertex Point position in the range. @@ -123,9 +113,8 @@ class Cech_complex { private: Proximity_graph cech_skeleton_graph_; - Filtration_value threshold_; + Filtration_value max_radius_; ForwardPointRange point_cloud_; - std::size_t dimension_; }; } // namespace cech_complex diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index fb52f712..d718b56e 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -23,9 +23,8 @@ #ifndef CECH_COMPLEX_BLOCKER_H_ #define CECH_COMPLEX_BLOCKER_H_ -#include // Cech_blocker is using a pointer on Gudhi::cech_complex::Cech_complex - -#include +#include // Cech_blocker is using a pointer on Gudhi::cech_complex::Cech_complex +#include // for Gudhi::Squared_radius #include #include @@ -58,9 +57,6 @@ class Cech_blocker { private: using Point = std::vector; using Point_cloud = std::vector; - using Point_iterator = Point_cloud::const_iterator; - using Coordinate_iterator = Point::const_iterator; - using Min_sphere = Miniball::Miniball>; using Simplex_handle = typename SimplicialComplexForCech::Simplex_handle; using Filtration_value = typename SimplicialComplexForCech::Filtration_value; using Cech_complex = Gudhi::cech_complex::Cech_complex; @@ -69,7 +65,7 @@ class Cech_blocker { /** \internal \brief Cech complex blocker operator() - the oracle - assigns the filtration value from the simplex * radius and returns if the simplex expansion must be blocked. * \param[in] sh The Simplex_handle. - * \return true if the simplex radius is greater than the Cech_complex threshold*/ + * \return true if the simplex radius is greater than the Cech_complex max_radius*/ bool operator()(Simplex_handle sh) { Point_cloud points; for (auto vertex : simplicial_complex_.simplex_vertex_range(sh)) { @@ -79,13 +75,12 @@ class Cech_blocker { std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES } - Min_sphere ms(cc_ptr_->dimension(), points.begin(),points.end()); - Filtration_value diameter = 2 * std::sqrt(ms.squared_radius()); + Filtration_value squared_radius = Gudhi::Radius_distance()(points); #ifdef DEBUG_TRACES - std::cout << "diameter = " << diameter << " - " << (diameter > cc_ptr_->threshold()) << std::endl; + std::cout << "squared_radius = " << squared_radius << " - " << (squared_radius > cc_ptr_->max_radius()) << std::endl; #endif // DEBUG_TRACES - simplicial_complex_.assign_filtration(sh, diameter); - return (diameter > cc_ptr_->threshold()); + simplicial_complex_.assign_filtration(sh, squared_radius); + return (squared_radius > cc_ptr_->max_radius()); } /** \internal \brief Cech complex blocker constructor. */ diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp index aa42d322..626f1d82 100644 --- a/src/Cech_complex/test/test_cech_complex.cpp +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -58,14 +58,15 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { // // ---------------------------------------------------------------------------- std::string off_file_name("alphacomplexdoc.off"); - double threshold = 12.0; - std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech threshold=" << - threshold << "==========" << std::endl; + double max_radius = 12.0; + std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech max_radius=" << + max_radius << "==========" << std::endl; Points_off_reader off_reader(off_file_name); Point_cloud point_cloud = off_reader.get_point_cloud(); - Cech_complex cech_complex_from_file(point_cloud, threshold, Gudhi::Euclidean_distance()); + Cech_complex cech_complex_from_file(point_cloud, max_radius); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(cech_complex_from_file.max_radius(), max_radius); std::size_t i = 0; for (; i < point_cloud.size(); i++) { BOOST_CHECK(point_cloud[i] == *(cech_complex_from_file.point_iterator(i))); @@ -101,10 +102,10 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { std::cout << vertex << ","; vp.push_back(off_reader.get_point_cloud().at(vertex)); } - std::cout << ") - distance =" << Gudhi::Euclidean_distance()(vp.at(0), vp.at(1)) << + std::cout << ") - distance =" << Gudhi::Radius_distance()(vp.at(0), vp.at(1)) << " - filtration =" << st.filtration(f_simplex) << std::endl; BOOST_CHECK(vp.size() == 2); - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Euclidean_distance()(vp.at(0), vp.at(1))); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Radius_distance()(vp.at(0), vp.at(1))); } } @@ -125,7 +126,8 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { points012.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), cech_complex_from_file.point_iterator(vertex)->end())); } - Min_sphere ms012(cech_complex_from_file.dimension(), points012.begin(),points012.end()); + std::size_t dimension = point_cloud[0].end() - point_cloud[0].begin(); + Min_sphere ms012(dimension, points012.begin(),points012.end()); Simplex_tree::Filtration_value f012 = st2.filtration(st2.find({0, 1, 2})); std::cout << "f012= " << f012 << " | ms012_radius= " << std::sqrt(ms012.squared_radius()) << std::endl; @@ -137,7 +139,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { points456.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), cech_complex_from_file.point_iterator(vertex)->end())); } - Min_sphere ms456(cech_complex_from_file.dimension(), points456.begin(),points456.end()); + Min_sphere ms456(dimension, points456.begin(),points456.end()); Simplex_tree::Filtration_value f456 = st2.filtration(st2.find({4, 5, 6})); std::cout << "f456= " << f456 << " | ms456_radius= " << std::sqrt(ms456.squared_radius()) << std::endl; @@ -161,7 +163,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { points0123.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), cech_complex_from_file.point_iterator(vertex)->end())); } - Min_sphere ms0123(cech_complex_from_file.dimension(), points0123.begin(),points0123.end()); + Min_sphere ms0123(dimension, points0123.begin(),points0123.end()); Simplex_tree::Filtration_value f0123 = st3.filtration(st3.find({0, 1, 2, 3})); std::cout << "f0123= " << f0123 << " | ms0123_radius= " << std::sqrt(ms0123.squared_radius()) << std::endl; @@ -175,7 +177,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { points01.push_back(Point(cech_complex_from_file.point_iterator(vertex)->begin(), cech_complex_from_file.point_iterator(vertex)->end())); } - Min_sphere ms01(cech_complex_from_file.dimension(), points01.begin(),points01.end()); + Min_sphere ms01(dimension, points01.begin(),points01.end()); Simplex_tree::Filtration_value f01 = st2.filtration(st2.find({0, 1})); std::cout << "f01= " << f01 << " | ms01_radius= " << std::sqrt(ms01.squared_radius()) << std::endl; @@ -199,7 +201,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { // ---------------------------------------------------------------------------- // Init of a Cech complex from the list of points // ---------------------------------------------------------------------------- - Cech_complex cech_complex_from_points(points, 2.0, Gudhi::Euclidean_distance()); + Cech_complex cech_complex_from_points(points, 2.0); std::cout << "========== cech_complex_from_points ==========" << std::endl; Simplex_tree st; @@ -234,13 +236,13 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.0); break; case 1: - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 1.41421, .00001); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.5); break; case 2: - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.816497, .00001); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.666667, .00001); break; case 3: - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.866025, .00001); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.75); break; default: BOOST_CHECK(false); // Shall not happen @@ -257,12 +259,12 @@ BOOST_AUTO_TEST_CASE(Cech_create_complex_throw) { // // ---------------------------------------------------------------------------- std::string off_file_name("alphacomplexdoc.off"); - double threshold = 12.0; - std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech threshold=" << - threshold << "==========" << std::endl; + double max_radius = 12.0; + std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech max_radius=" << + max_radius << "==========" << std::endl; Gudhi::Points_off_reader off_reader(off_file_name); - Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); + Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), max_radius); Simplex_tree stree; std::vector simplex = {0, 1, 2}; diff --git a/src/Cech_complex/utilities/CMakeLists.txt b/src/Cech_complex/utilities/CMakeLists.txt index a4f89d2c..30b99729 100644 --- a/src/Cech_complex/utilities/CMakeLists.txt +++ b/src/Cech_complex/utilities/CMakeLists.txt @@ -9,6 +9,6 @@ if (TBB_FOUND) endif() add_test(NAME Cech_complex_utility_from_rips_on_tore_3D COMMAND $ - "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.25" "-m" "0.5" "-d" "3" "-p" "3") + "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" "-r" "0.25" "-m" "0.5" "-d" "3" "-p" "3") install(TARGETS cech_persistence DESTINATION bin) diff --git a/src/Cech_complex/utilities/cech_persistence.cpp b/src/Cech_complex/utilities/cech_persistence.cpp index e93596d4..93a200ff 100644 --- a/src/Cech_complex/utilities/cech_persistence.cpp +++ b/src/Cech_complex/utilities/cech_persistence.cpp @@ -43,20 +43,20 @@ using Field_Zp = Gudhi::persistent_cohomology::Field_Zp; using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology; void program_options(int argc, char* argv[], std::string& off_file_points, std::string& filediag, - Filtration_value& threshold, int& dim_max, int& p, Filtration_value& min_persistence); + Filtration_value& max_radius, int& dim_max, int& p, Filtration_value& min_persistence); int main(int argc, char* argv[]) { std::string off_file_points; std::string filediag; - Filtration_value threshold; + Filtration_value max_radius; int dim_max; int p; Filtration_value min_persistence; - program_options(argc, argv, off_file_points, filediag, threshold, dim_max, p, min_persistence); + program_options(argc, argv, off_file_points, filediag, max_radius, dim_max, p, min_persistence); Points_off_reader off_reader(off_file_points); - Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); + Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), max_radius); // Construct the Cech complex in a Simplex Tree Simplex_tree simplex_tree; @@ -88,7 +88,7 @@ int main(int argc, char* argv[]) { } void program_options(int argc, char* argv[], std::string& off_file_points, std::string& filediag, - Filtration_value& threshold, int& dim_max, int& p, Filtration_value& min_persistence) { + Filtration_value& max_radius, int& dim_max, int& p, Filtration_value& min_persistence) { namespace po = boost::program_options; po::options_description hidden("Hidden options"); hidden.add_options()("input-file", po::value(&off_file_points), @@ -98,8 +98,8 @@ void program_options(int argc, char* argv[], std::string& off_file_points, std:: visible.add_options()("help,h", "produce help message")( "output-file,o", po::value(&filediag)->default_value(std::string()), "Name of file in which the persistence diagram is written. Default print in std::cout")( - "max-edge-length,r", - po::value(&threshold)->default_value(std::numeric_limits::infinity()), + "max-radius,r", + po::value(&max_radius)->default_value(std::numeric_limits::infinity()), "Maximal length of an edge for the Cech complex construction.")( "cpx-dimension,d", po::value(&dim_max)->default_value(1), "Maximal dimension of the Cech complex we want to compute.")( diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h index 3a5d1fd5..3ce51ad1 100644 --- a/src/common/include/gudhi/distance_functions.h +++ b/src/common/include/gudhi/distance_functions.h @@ -25,6 +25,8 @@ #include +#include + #include #include // for std::sqrt @@ -68,6 +70,37 @@ class Euclidean_distance { } }; +/** @brief Compute the squared radius between Points given by a range of coordinates. The points are assumed to + * have the same dimension. */ +class Radius_distance { + public: + // boost::range_value is not SFINAE-friendly so we cannot use it in the return type + template< typename Point > + typename std::iterator_traits::type>::value_type + operator()(const Point& p1, const Point& p2) const { + return Euclidean_distance()(p1, p2) / 2.; + } + // boost::range_value is not SFINAE-friendly so we cannot use it in the return type + template< typename Point_cloud, + typename Point_iterator = typename boost::range_const_iterator::type, + typename Point= typename std::iterator_traits::value_type, + typename Coordinate_iterator = typename boost::range_const_iterator::type, + typename Coordinate = typename std::iterator_traits::value_type> + Coordinate + operator()(const Point_cloud& point_cloud) const { + using Min_sphere = Miniball::Miniball>; + + //Min_sphere ms(point_cloud.begin()->end() - point_cloud.begin()->begin(), point_cloud.begin(),point_cloud.end()); + Min_sphere ms(point_cloud.end() - point_cloud.begin(), point_cloud.begin(),point_cloud.end()); +#ifdef DEBUG_TRACES + std::cout << "Radius on " << point_cloud.end() - point_cloud.begin() << " points = " + << std::sqrt(ms.squared_radius()) << std::endl; +#endif // DEBUG_TRACES + + return std::sqrt(ms.squared_radius()); + } +}; + } // namespace Gudhi #endif // DISTANCE_FUNCTIONS_H_ -- cgit v1.2.3 From b3a64294af818c977804c4b67a317782d872e2b5 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Mon, 5 Mar 2018 13:38:57 +0000 Subject: Fix doc and tests git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3262 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: c76eb981f5960938221aa2498cb87b0707391733 --- .../benchmark/cech_complex_benchmark.cpp | 10 +- src/Cech_complex/doc/Intro_cech_complex.h | 52 ++++--- .../doc/cech_complex_representation.ipe | 160 +++++++++++---------- .../doc/cech_complex_representation.png | Bin 15677 -> 54399 bytes src/Cech_complex/doc/cech_one_skeleton.ipe | 154 +++++++++----------- src/Cech_complex/doc/cech_one_skeleton.png | Bin 12070 -> 29354 bytes .../example/cech_complex_example_from_points.cpp | 22 +-- .../cech_complex_example_from_points_for_doc.txt | 45 ++++-- src/Cech_complex/include/gudhi/Cech_complex.h | 4 +- .../include/gudhi/Cech_complex_blocker.h | 11 +- src/Cech_complex/test/test_cech_complex.cpp | 12 +- src/Doxyfile | 3 +- src/common/include/gudhi/distance_functions.h | 8 +- 13 files changed, 255 insertions(+), 226 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp index 71c88982..83ef9dca 100644 --- a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp +++ b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp @@ -93,12 +93,12 @@ int main(int argc, char * argv[]) { Radius_distance()); std::cout << radius_clock << std::endl; - Gudhi::Clock squared_radius_clock("Gudhi::Radius_distance()"); + Gudhi::Clock common_radius_clock("Gudhi::Radius_distance()"); // Compute the proximity graph of the points Proximity_graph sq_radius_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), threshold, Gudhi::Radius_distance()); - std::cout << squared_radius_clock << std::endl; + std::cout << common_radius_clock << std::endl; boost::filesystem::path full_path(boost::filesystem::current_path()); @@ -116,6 +116,7 @@ int main(int argc, char * argv[]) { if ( itr->path().extension() == ".off" ) // see below { Points_off_reader off_reader(itr->path().string()); + Point p0 = off_reader.get_point_cloud()[0]; for (Filtration_value radius = 0.1; radius < 0.4; radius += 0.1) { std::cout << itr->path().stem() << ";"; @@ -123,7 +124,7 @@ int main(int argc, char * argv[]) { Gudhi::Clock rips_clock("Rips computation"); Rips_complex rips_complex_from_points(off_reader.get_point_cloud(), radius, Gudhi::Radius_distance()); Simplex_tree rips_stree; - rips_complex_from_points.create_complex(rips_stree, 2); + rips_complex_from_points.create_complex(rips_stree, p0.size() - 1); // ------------------------------------------ // Display information about the Rips complex // ------------------------------------------ @@ -133,7 +134,7 @@ int main(int argc, char * argv[]) { Gudhi::Clock cech_clock("Cech computation"); Cech_complex cech_complex_from_points(off_reader.get_point_cloud(), radius); Simplex_tree cech_stree; - cech_complex_from_points.create_complex(cech_stree, 2); + cech_complex_from_points.create_complex(cech_stree, p0.size() - 1); // ------------------------------------------ // Display information about the Cech complex // ------------------------------------------ @@ -141,6 +142,7 @@ int main(int argc, char * argv[]) { std::cout << cech_sec << ";"; std::cout << cech_sec / rips_sec << ";"; + assert(rips_stree.num_simplices() >= cech_stree.num_simplices()); std::cout << rips_stree.num_simplices() << ";"; std::cout << cech_stree.num_simplices() << ";" << std::endl; } diff --git a/src/Cech_complex/doc/Intro_cech_complex.h b/src/Cech_complex/doc/Intro_cech_complex.h index f2052763..8b6c7851 100644 --- a/src/Cech_complex/doc/Intro_cech_complex.h +++ b/src/Cech_complex/doc/Intro_cech_complex.h @@ -29,7 +29,7 @@ namespace cech_complex { /** \defgroup cech_complex Cech complex * - * \author Clément Maria, Pawel Dlotko, Vincent Rouvreau + * \author Vincent Rouvreau * * @{ * @@ -40,40 +40,54 @@ namespace cech_complex { * proximity graph that allows to construct a * simplicial complex * from it. - * The input can be a point cloud with a given distance function. + * The input shall be a point cloud in an Euclidean space. * - * The filtration value of each edge is computed from a user-given distance function. + * The filtration value of each edge of the `Gudhi::Proximity_graph` is computed from `Gudhi::Radius_distance` function. * - * All edges that have a filtration value strictly greater than a given threshold value are not inserted into - * the complex. + * All edges that have a filtration value strictly greater than a user given maximal radius value, \f$max\_radius\f$, + * are not inserted into the complex. * - * When creating a simplicial complex from this proximity graph, Cech inserts the proximity graph into the data - * structure, and then expands the simplicial complex when required. - * * Vertex name correspond to the index of the point in the given range (aka. the point cloud). * - * \image html "cech_complex_representation.png" "Cech complex proximity graph representation" - * - * On this example, as edges (4,5), (4,6) and (5,6) are in the complex, simplex (4,5,6) is added with the filtration - * value set with \f$max(filtration(4,5), filtration(4,6), filtration(5,6))\f$. - * And so on for simplex (0,1,2,3). + * \image html "cech_one_skeleton.png" "Cech complex proximity graph representation" * + * When creating a simplicial complex from this proximity graph, Cech inserts the proximity graph into the simplicial + * complex data structure, and then expands the simplicial complex when required. + * + * On this example, as edges \f$(x,y)\f$, \f$(y,z)\f$ and \f$(z,y)\f$ are in the complex, the minimal ball radius + * containing the points \f$(x,y,z)\f$ is computed. + * + * \f$(x,y,z)\f$ is inserted to the simplicial complex with the filtration value set with + * \f$mini\_ball\_radius(x,y,z))\f$ iff \f$mini\_ball\_radius(x,y,z)) \leq max\_radius\f$. + * + * And so on for higher dimensions. + * + * \image html "cech_complex_representation.png" "Cech complex expansion" + * + * The minimal ball radius computation is insured by + * + * the miniball software (V3.0) - Smallest Enclosing Balls of Points - and distributed with GUDHI. + * + * Please refer to + * + * the miniball software design description for more information about this computation. + * * If the Cech_complex interfaces are not detailed enough for your need, please refer to - * - * cech_persistence_step_by_step.cpp example, where the graph construction over the Simplex_tree is more detailed. + * + * cech_complex_step_by_step.cpp example, where the graph construction over the Simplex_tree is more detailed. * - * \section cechpointsdistance Point cloud and distance function + * \section cechpointsdistance Point cloud * - * \subsection cechpointscloudexample Example from a point cloud and a distance function + * \subsection cechpointscloudexample Example from a point cloud * - * This example builds the proximity graph from the given points, threshold value, and distance function. + * This example builds the proximity graph from the given points, and maximal radius values. * Then it creates a `Simplex_tree` with it. * * Then, it is asked to display information about the simplicial complex. * * \include Cech_complex/cech_complex_example_from_points.cpp * - * When launching (Cech maximal distance between 2 points is 7.1, is expanded until dimension 2): + * When launching (Cech maximal distance between 2 points is 1., is expanded until dimension 2): * * \code $> ./Cech_complex_example_from_points * \endcode diff --git a/src/Cech_complex/doc/cech_complex_representation.ipe b/src/Cech_complex/doc/cech_complex_representation.ipe index 7f6028f4..c64d7596 100644 --- a/src/Cech_complex/doc/cech_complex_representation.ipe +++ b/src/Cech_complex/doc/cech_complex_representation.ipe @@ -1,7 +1,7 @@ - + @@ -232,95 +232,99 @@ h - -109.771 601.912 m -159.595 601.797 l -140.058 541.915 l + +48 640 m +80 672 l +48 672 l h - -79.8776 552.169 m -109.756 601.699 l -139.812 542.209 l +Cech complex +0 +1 +2 +3 +4 +5 +6 + + + + + + + + + + + + + +32 0 0 32 304 672 e + + +304 672 m +336 672 l + +Maximal radius +7 +8 +9 + +112 576 m +144 608 l + + +144 672 m +144 608 l +200 640 l h - -69.8453 682.419 m -159.925 712.208 l -90.12 732.039 l + +48 576 m +112 576 l +80 544 l h -Rips complex -0 -1 -2 -3 -4 -5 -6 - -60 710 m -40 660 l - - -40 660 m -130 690 l - - -130 690 m -60 710 l - - -40 660 m -80 580 l - - -80 580 m -130 580 l -130 580 l - - -130 580 m -110 520 l - - -110 520 m -50 530 l -50 530 l -50 530 l + + +80 672 m +144 672 l +112 728 l +h - -50 530 m -80 580 l + + + + +48 576 m +48 640 l +32 608 l +h - -130 580 m -130 690 l + + + + + + + +32 0 0 32 80 576 e - - - - - - -150.038 609.9 m -179.929 549.727 l + +22.6274 0 0 22.6274 64 656 e - - - -158.7 593.269 m -81.4925 544.805 l + +37.1429 0 0 37.1429 112 690.857 e - -256.324 639.958 m -370.055 639.958 l + +37.1429 0 0 37.1429 162.857 640 e - -56.8567 0 0 56.8567 313.217 639.756 e + +10 + +32 0 0 32 48 608 e - - -Rips threshold + + diff --git a/src/Cech_complex/doc/cech_complex_representation.png b/src/Cech_complex/doc/cech_complex_representation.png index e901d92e..4d103a56 100644 Binary files a/src/Cech_complex/doc/cech_complex_representation.png and b/src/Cech_complex/doc/cech_complex_representation.png differ diff --git a/src/Cech_complex/doc/cech_one_skeleton.ipe b/src/Cech_complex/doc/cech_one_skeleton.ipe index 3a35970c..345e6d7b 100644 --- a/src/Cech_complex/doc/cech_one_skeleton.ipe +++ b/src/Cech_complex/doc/cech_one_skeleton.ipe @@ -1,7 +1,7 @@ - + @@ -232,95 +232,83 @@ h - -109.771 601.912 m -159.595 601.797 l -140.058 541.915 l +Proximity graph +0 +1 + +304 672 m +336 672 l + +2 +3 +4 +5 +6 + + + + + + + + + + + +32 0 0 32 304 672 e + +Maximal radius +7 +8 +9 + +112 576 m +144 608 l + + +144 672 m +144 608 l +200 640 l h - -79.8776 552.169 m -109.756 601.699 l -139.812 542.209 l + +48 640 m +80 672 l +48 672 l h - -69.8453 682.419 m -159.925 712.208 l -90.12 732.039 l + +48 576 m +112 576 l +80 544 l h -One skeleton graph -0 -1 -2 -3 -4 -5 -6 - -60 710 m -40 660 l - - -40 660 m -130 690 l - - -130 690 m -60 710 l - - -40 660 m -80 580 l - - -80 580 m -130 580 l -130 580 l - - -130 580 m -110 520 l - - -110 520 m -50 530 l -50 530 l -50 530 l - - -50 530 m -80 580 l - - -130 580 m -130 690 l - - - - - - - -150.038 609.9 m -179.929 549.727 l - - - - -158.7 593.269 m -81.4925 544.805 l - - -256.324 639.958 m -370.055 639.958 l + + +80 672 m +144 672 l +112 728 l +h - -56.8567 0 0 56.8567 313.217 639.756 e + + +48 576 m +48 640 l +32 608 l +h - - -Rips threshold + + + + + + + + + + +10 + + diff --git a/src/Cech_complex/doc/cech_one_skeleton.png b/src/Cech_complex/doc/cech_one_skeleton.png index ffa9c329..807e0936 100644 Binary files a/src/Cech_complex/doc/cech_one_skeleton.png and b/src/Cech_complex/doc/cech_one_skeleton.png differ diff --git a/src/Cech_complex/example/cech_complex_example_from_points.cpp b/src/Cech_complex/example/cech_complex_example_from_points.cpp index 97327e69..3b889d56 100644 --- a/src/Cech_complex/example/cech_complex_example_from_points.cpp +++ b/src/Cech_complex/example/cech_complex_example_from_points.cpp @@ -15,22 +15,26 @@ int main() { using Cech_complex = Gudhi::cech_complex::Cech_complex; Point_cloud points; - points.push_back({0., 0.}); - points.push_back({0., 2.}); - points.push_back({std::sqrt(3.), 1.}); - points.push_back({1., 0.}); - points.push_back({1., 2.}); - points.push_back({1. - std::sqrt(3.), 1.}); + points.push_back({1., 0.}); // 0 + points.push_back({0., 1.}); // 1 + points.push_back({2., 1.}); // 2 + points.push_back({3., 2.}); // 3 + points.push_back({0., 3.}); // 4 + points.push_back({3. + std::sqrt(3.), 3.}); // 5 + points.push_back({1., 4.}); // 6 + points.push_back({3., 4.}); // 7 + points.push_back({2., 4. + std::sqrt(3.)}); // 8 + points.push_back({0., 4.}); // 9 + points.push_back({-0.5, 2.}); // 10 // ---------------------------------------------------------------------------- // Init of a Cech complex from points // ---------------------------------------------------------------------------- - // 5. is a magic number to force one blocker, and one non-blocker - Filtration_value max_radius = 12.; + Filtration_value max_radius = 1.; Cech_complex cech_complex_from_points(points, max_radius); Simplex_tree stree; - cech_complex_from_points.create_complex(stree, -1); + cech_complex_from_points.create_complex(stree, 2); // ---------------------------------------------------------------------------- // Display information about the one skeleton Cech complex // ---------------------------------------------------------------------------- diff --git a/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt b/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt index 684e120b..be0afc76 100644 --- a/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt +++ b/src/Cech_complex/example/cech_complex_example_from_points_for_doc.txt @@ -1,16 +1,31 @@ -Cech complex is of dimension 2 - 14 simplices - 7 vertices. Iterator on Cech complex simplices in the filtration order, with [filtration value]: - ( 0 ) -> [0] - ( 1 ) -> [0] - ( 2 ) -> [0] - ( 3 ) -> [0] - ( 4 ) -> [0] - ( 5 ) -> [0] - ( 6 ) -> [0] - ( 3 2 ) -> [5] - ( 5 4 ) -> [5.38516] - ( 2 0 ) -> [5.83095] - ( 1 0 ) -> [6.08276] - ( 3 1 ) -> [6.32456] - ( 2 1 ) -> [6.7082] - ( 3 2 1 ) -> [7.07107] + ( 0 ) -> [0] + ( 1 ) -> [0] + ( 2 ) -> [0] + ( 3 ) -> [0] + ( 4 ) -> [0] + ( 5 ) -> [0] + ( 6 ) -> [0] + ( 7 ) -> [0] + ( 8 ) -> [0] + ( 9 ) -> [0] + ( 10 ) -> [0] + ( 9 4 ) -> [0.5] + ( 9 6 ) -> [0.5] + ( 10 1 ) -> [0.559017] + ( 10 4 ) -> [0.559017] + ( 1 0 ) -> [0.707107] + ( 2 0 ) -> [0.707107] + ( 3 2 ) -> [0.707107] + ( 6 4 ) -> [0.707107] + ( 9 6 4 ) -> [0.707107] + ( 2 1 ) -> [1] + ( 2 1 0 ) -> [1] + ( 4 1 ) -> [1] + ( 5 3 ) -> [1] + ( 7 3 ) -> [1] + ( 7 5 ) -> [1] + ( 7 6 ) -> [1] + ( 8 6 ) -> [1] + ( 8 7 ) -> [1] + ( 10 4 1 ) -> [1] diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index a50ed9fa..612c73c3 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -23,7 +23,7 @@ #ifndef CECH_COMPLEX_H_ #define CECH_COMPLEX_H_ -#include // for Gudhi::Squared_radius +#include // for Gudhi::Radius_distance #include // for Gudhi::Proximity_graph #include // for GUDHI_CHECK #include // for Gudhi::cech_complex::Cech_blocker @@ -43,7 +43,7 @@ namespace cech_complex { * * \details * The data structure is a proximity graph, containing edges when the edge length is less or equal - * to a given max_radius. Edge length is computed from `Gudhi::Squared_radius` distance function. + * to a given max_radius. Edge length is computed from `Gudhi::Radius_distance` distance function. * * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required * by `Gudhi::Proximity_graph`. diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index d718b56e..5ba17c51 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -24,7 +24,7 @@ #define CECH_COMPLEX_BLOCKER_H_ #include // Cech_blocker is using a pointer on Gudhi::cech_complex::Cech_complex -#include // for Gudhi::Squared_radius +#include // for Gudhi::Radius_distance #include #include @@ -75,12 +75,13 @@ class Cech_blocker { std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES } - Filtration_value squared_radius = Gudhi::Radius_distance()(points); + Filtration_value radius = Gudhi::Radius_distance()(points); #ifdef DEBUG_TRACES - std::cout << "squared_radius = " << squared_radius << " - " << (squared_radius > cc_ptr_->max_radius()) << std::endl; + if (radius > cc_ptr_->max_radius()) + std::cout << "radius > max_radius => expansion is blocked\n"; #endif // DEBUG_TRACES - simplicial_complex_.assign_filtration(sh, squared_radius); - return (squared_radius > cc_ptr_->max_radius()); + simplicial_complex_.assign_filtration(sh, radius); + return (radius > cc_ptr_->max_radius()); } /** \internal \brief Cech complex blocker constructor. */ diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp index 626f1d82..eae8778c 100644 --- a/src/Cech_complex/test/test_cech_complex.cpp +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -86,7 +86,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { BOOST_CHECK(st.num_vertices() == NUMBER_OF_VERTICES); std::cout << "st.num_simplices()=" << st.num_simplices() << std::endl; - BOOST_CHECK(st.num_simplices() == 18); + BOOST_CHECK(st.num_simplices() == 28); // Check filtration values of vertices is 0.0 for (auto f_simplex : st.skeleton_simplex_range(0)) { @@ -119,7 +119,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { BOOST_CHECK(st2.num_vertices() == NUMBER_OF_VERTICES); std::cout << "st2.num_simplices()=" << st2.num_simplices() << std::endl; - BOOST_CHECK(st2.num_simplices() == 23); + BOOST_CHECK(st2.num_simplices() == 63); Point_cloud points012; for (std::size_t vertex = 0; vertex <= 2; vertex++) { @@ -156,7 +156,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_file) { BOOST_CHECK(st3.num_vertices() == NUMBER_OF_VERTICES); std::cout << "st3.num_simplices()=" << st3.num_simplices() << std::endl; - BOOST_CHECK(st3.num_simplices() == 24); + BOOST_CHECK(st3.num_simplices() == 98); Point_cloud points0123; for (std::size_t vertex = 0; vertex <= 3; vertex++) { @@ -236,13 +236,13 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.0); break; case 1: - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.5); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.707107, .00001); break; case 2: - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.666667, .00001); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.816497, .00001); break; case 3: - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.75); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), 0.866025, .00001); break; default: BOOST_CHECK(false); // Shall not happen diff --git a/src/Doxyfile b/src/Doxyfile index f1981e2e..52de65b0 100644 --- a/src/Doxyfile +++ b/src/Doxyfile @@ -843,7 +843,8 @@ EXAMPLE_RECURSIVE = NO IMAGE_PATH = doc/Skeleton_blocker/ \ doc/Alpha_complex/ \ doc/common/ \ - doc/Contraction/ \ + doc/Cech_complex/ \ + doc/Contraction/ \ doc/Simplex_tree/ \ doc/Persistent_cohomology/ \ doc/Witness_complex/ \ diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h index 3ce51ad1..7749b98e 100644 --- a/src/common/include/gudhi/distance_functions.h +++ b/src/common/include/gudhi/distance_functions.h @@ -90,11 +90,11 @@ class Radius_distance { operator()(const Point_cloud& point_cloud) const { using Min_sphere = Miniball::Miniball>; - //Min_sphere ms(point_cloud.begin()->end() - point_cloud.begin()->begin(), point_cloud.begin(),point_cloud.end()); - Min_sphere ms(point_cloud.end() - point_cloud.begin(), point_cloud.begin(),point_cloud.end()); + Min_sphere ms(point_cloud.begin()->end() - point_cloud.begin()->begin(), point_cloud.begin(),point_cloud.end()); #ifdef DEBUG_TRACES - std::cout << "Radius on " << point_cloud.end() - point_cloud.begin() << " points = " - << std::sqrt(ms.squared_radius()) << std::endl; + std::cout << "Radius_distance = " << std::sqrt(ms.squared_radius()) << " | nb points = " + << point_cloud.end() - point_cloud.begin() << " | dimension = " + << point_cloud.begin()->end() - point_cloud.begin()->begin() << std::endl; #endif // DEBUG_TRACES return std::sqrt(ms.squared_radius()); -- cgit v1.2.3 From 0d0ca116e7fef77cc950b7e85380495661311d91 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Thu, 22 Mar 2018 08:36:00 +0000 Subject: Move Miniball in gudhi git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3302 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 736e5c33a9593e4dfb5b19ddc745ab9852d71b40 --- src/CMakeLists.txt | 1 - .../benchmark/cech_complex_benchmark.cpp | 5 +- src/Cech_complex/example/CMakeLists.txt | 2 + .../example/cech_complex_step_by_step.cpp | 4 +- .../include/Miniball/Miniball.COPYRIGHT | 4 - src/Cech_complex/include/Miniball/Miniball.README | 23 - src/Cech_complex/include/Miniball/Miniball.hpp | 520 -------------------- src/Cech_complex/include/gudhi/Miniball.COPYRIGHT | 4 + src/Cech_complex/include/gudhi/Miniball.README | 23 + src/Cech_complex/include/gudhi/Miniball.hpp | 523 +++++++++++++++++++++ src/Cech_complex/test/test_cech_complex.cpp | 5 +- src/common/include/gudhi/distance_functions.h | 2 +- 12 files changed, 559 insertions(+), 557 deletions(-) delete mode 100644 src/Cech_complex/include/Miniball/Miniball.COPYRIGHT delete mode 100644 src/Cech_complex/include/Miniball/Miniball.README delete mode 100644 src/Cech_complex/include/Miniball/Miniball.hpp create mode 100644 src/Cech_complex/include/gudhi/Miniball.COPYRIGHT create mode 100644 src/Cech_complex/include/gudhi/Miniball.README create mode 100644 src/Cech_complex/include/gudhi/Miniball.hpp (limited to 'src/Cech_complex/include') diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index ff7acafc..7cccb19f 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -105,5 +105,4 @@ install(FILES # install the include file on "make install" install(DIRECTORY include/gudhi DESTINATION include) -install(DIRECTORY include/Miniball DESTINATION include) #--------------------------------------------------------------------------------------- diff --git a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp index 83ef9dca..6ba52419 100644 --- a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp +++ b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp @@ -27,8 +27,7 @@ #include #include #include - -#include +#include #include "boost/filesystem.hpp" // includes all needed Boost.Filesystem declarations @@ -57,7 +56,7 @@ class Radius_distance { using Point_cloud = std::vector; using Point_iterator = typename Point_cloud::const_iterator; using Coordinate_iterator = typename Point::const_iterator; - using Min_sphere = typename Miniball::Miniball>; + using Min_sphere = typename Gudhi::Miniball::Miniball>; Point_cloud point_cloud; point_cloud.push_back(p1); diff --git a/src/Cech_complex/example/CMakeLists.txt b/src/Cech_complex/example/CMakeLists.txt index ac32ff95..ab391215 100644 --- a/src/Cech_complex/example/CMakeLists.txt +++ b/src/Cech_complex/example/CMakeLists.txt @@ -6,6 +6,8 @@ target_link_libraries(Cech_complex_example_step_by_step ${Boost_PROGRAM_OPTIONS_ if (TBB_FOUND) target_link_libraries(Cech_complex_example_step_by_step ${TBB_LIBRARIES}) endif() +add_test(NAME Cech_complex_utility_from_rips_on_tore_3D COMMAND $ + "${CMAKE_SOURCE_DIR}/data/points/tore3D_300.off" "-r" "0.25" "-d" "3") add_executable ( Cech_complex_example_from_points cech_complex_example_from_points.cpp) if (TBB_FOUND) diff --git a/src/Cech_complex/example/cech_complex_step_by_step.cpp b/src/Cech_complex/example/cech_complex_step_by_step.cpp index 8705a3e5..0e7c4bbd 100644 --- a/src/Cech_complex/example/cech_complex_step_by_step.cpp +++ b/src/Cech_complex/example/cech_complex_step_by_step.cpp @@ -25,7 +25,7 @@ #include #include -#include +#include #include @@ -55,7 +55,7 @@ class Cech_blocker { using Point_cloud = std::vector; using Point_iterator = Point_cloud::const_iterator; using Coordinate_iterator = Point::const_iterator; - using Min_sphere = Miniball::Miniball >; + using Min_sphere = Gudhi::Miniball::Miniball >; public: bool operator()(Simplex_handle sh) { std::vector points; diff --git a/src/Cech_complex/include/Miniball/Miniball.COPYRIGHT b/src/Cech_complex/include/Miniball/Miniball.COPYRIGHT deleted file mode 100644 index dbe4c553..00000000 --- a/src/Cech_complex/include/Miniball/Miniball.COPYRIGHT +++ /dev/null @@ -1,4 +0,0 @@ -The miniball software is available under the GNU General Public License (GPLv3 - https://www.gnu.org/copyleft/gpl.html). -If your intended use is not compliant with this license, please buy a commercial license (EUR 500 - https://people.inf.ethz.ch/gaertner/subdir/software/miniball/license.html). -You need a license if the software that you develop using Miniball V3.0 is not open source. - diff --git a/src/Cech_complex/include/Miniball/Miniball.README b/src/Cech_complex/include/Miniball/Miniball.README deleted file mode 100644 index 86a96f08..00000000 --- a/src/Cech_complex/include/Miniball/Miniball.README +++ /dev/null @@ -1,23 +0,0 @@ -https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html - -Smallest Enclosing Balls of Points - Fast and Robust in C++. -(high-quality software for smallest enclosing balls of balls is available in the computational geometry algorithms library CGAL) - - -This is the miniball software (V3.0) for computing smallest enclosing balls of points in arbitrary dimensions. It consists of a C++ header file Miniball.hpp (around 500 lines of code) and two example programs miniball_example.cpp and miniball_example_containers.cpp that demonstrate the usage. The first example stores the coordinates of the input points in a two-dimensional array, the second example uses a list of vectors to show how generic containers can be used. - -Credits: Aditya Gupta and Alexandros Konstantinakis-Karmis have significantly contributed to this version of the software. - -Changes - https://people.inf.ethz.ch/gaertner/subdir/software/miniball/changes.txt - from previous versions. - -The theory - https://people.inf.ethz.ch/gaertner/subdir/texts/own_work/esa99_final.pdf - behind the miniball software (Proc. 7th Annual European Symposium on Algorithms (ESA), Lecture Notes in Computer Science 1643, Springer-Verlag, pp.325-338, 1999). - -Main Features: - - Very fast in low dimensions. 1 million points in 5-space are processed within 0.05 seconds on any recent machine. - - High numerical stability. Almost all input degeneracies (cospherical points, multiple points, points very close together) are routinely handled. - - Easily integrates into your code. You can freely choose the coordinate type of your points and the container to store the points. If you still need to adapt the code, the header is small and readable and contains documentation for all major methods. - - diff --git a/src/Cech_complex/include/Miniball/Miniball.hpp b/src/Cech_complex/include/Miniball/Miniball.hpp deleted file mode 100644 index a42d62a7..00000000 --- a/src/Cech_complex/include/Miniball/Miniball.hpp +++ /dev/null @@ -1,520 +0,0 @@ -// Copright (C) 1999-2013, Bernd Gaertner -// $Rev: 3581 $ -// -// 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 . -// -// Contact: -// -------- -// Bernd Gaertner -// Institute of Theoretical Computer Science -// ETH Zuerich -// CAB G31.1 -// CH-8092 Zuerich, Switzerland -// http://www.inf.ethz.ch/personal/gaertner - -#ifndef MINIBALL_HPP_ -#define MINIBALL_HPP_ - -#include -#include -#include -#include -#include - -namespace Miniball { - - // Global Functions - // ================ - template - inline NT mb_sqr (NT r) {return r*r;} - - // Functors - // ======== - - // functor to map a point iterator to the corresponding coordinate iterator; - // generic version for points whose coordinate containers have begin() - template < typename Pit_, typename Cit_ > - struct CoordAccessor { - typedef Pit_ Pit; - typedef Cit_ Cit; - inline Cit operator() (Pit it) const { return (*it).begin(); } - }; - - // partial specialization for points whose coordinate containers are arrays - template < typename Pit_, typename Cit_ > - struct CoordAccessor { - typedef Pit_ Pit; - typedef Cit_* Cit; - inline Cit operator() (Pit it) const { return *it; } - }; - - // Class Declaration - // ================= - - template - class Miniball { - private: - // types - // The iterator type to go through the input points - typedef typename CoordAccessor::Pit Pit; - // The iterator type to go through the coordinates of a single point. - typedef typename CoordAccessor::Cit Cit; - // The coordinate type - typedef typename std::iterator_traits::value_type NT; - // The iterator to go through the support points - typedef typename std::list::iterator Sit; - - // data members... - const int d; // dimension - Pit points_begin; - Pit points_end; - CoordAccessor coord_accessor; - double time; - const NT nt0; // NT(0) - - //...for the algorithms - std::list L; - Sit support_end; - int fsize; // number of forced points - int ssize; // number of support points - - // ...for the ball updates - NT* current_c; - NT current_sqr_r; - NT** c; - NT* sqr_r; - - // helper arrays - NT* q0; - NT* z; - NT* f; - NT** v; - NT** a; - - public: - // The iterator type to go through the support points - typedef typename std::list::const_iterator SupportPointIterator; - - // PRE: [begin, end) is a nonempty range - // POST: computes the smallest enclosing ball of the points in the range - // [begin, end); the functor a maps a point iterator to an iterator - // through the d coordinates of the point - Miniball (int d_, Pit begin, Pit end, CoordAccessor ca = CoordAccessor()); - - // POST: returns a pointer to the first element of an array that holds - // the d coordinates of the center of the computed ball - const NT* center () const; - - // POST: returns the squared radius of the computed ball - NT squared_radius () const; - - // POST: returns the number of support points of the computed ball; - // the support points form a minimal set with the same smallest - // enclosing ball as the input set; in particular, the support - // points are on the boundary of the computed ball, and their - // number is at most d+1 - int nr_support_points () const; - - // POST: returns an iterator to the first support point - SupportPointIterator support_points_begin () const; - - // POST: returns a past-the-end iterator for the range of support points - SupportPointIterator support_points_end () const; - - // POST: returns the maximum excess of any input point w.r.t. the computed - // ball, divided by the squared radius of the computed ball. The - // excess of a point is the difference between its squared distance - // from the center and the squared radius; Ideally, the return value - // is 0. subopt is set to the absolute value of the most negative - // coefficient in the affine combination of the support points that - // yields the center. Ideally, this is a convex combination, and there - // is no negative coefficient in which case subopt is set to 0. - NT relative_error (NT& subopt) const; - - // POST: return true if the relative error is at most tol, and the - // suboptimality is 0; the default tolerance is 10 times the - // coordinate type's machine epsilon - bool is_valid (NT tol = NT(10) * std::numeric_limits::epsilon()) const; - - // POST: returns the time in seconds taken by the constructor call for - // computing the smallest enclosing ball - double get_time() const; - - // POST: deletes dynamically allocated arrays - ~Miniball(); - - private: - void mtf_mb (Sit n); - void mtf_move_to_front (Sit j); - void pivot_mb (Pit n); - void pivot_move_to_front (Pit j); - NT excess (Pit pit) const; - void pop (); - bool push (Pit pit); - NT suboptimality () const; - void create_arrays(); - void delete_arrays(); - }; - - // Class Definition - // ================ - template - Miniball::Miniball (int d_, Pit begin, Pit end, - CoordAccessor ca) - : d (d_), - points_begin (begin), - points_end (end), - coord_accessor (ca), - time (clock()), - nt0 (NT(0)), - L(), - support_end (L.begin()), - fsize(0), - ssize(0), - current_c (NULL), - current_sqr_r (NT(-1)), - c (NULL), - sqr_r (NULL), - q0 (NULL), - z (NULL), - f (NULL), - v (NULL), - a (NULL) - { - assert (points_begin != points_end); - create_arrays(); - - // set initial center - for (int j=0; j - Miniball::~Miniball() - { - delete_arrays(); - } - - template - void Miniball::create_arrays() - { - c = new NT*[d+1]; - v = new NT*[d+1]; - a = new NT*[d+1]; - for (int i=0; i - void Miniball::delete_arrays() - { - delete[] f; - delete[] z; - delete[] q0; - delete[] sqr_r; - for (int i=0; i - const typename Miniball::NT* - Miniball::center () const - { - return current_c; - } - - template - typename Miniball::NT - Miniball::squared_radius () const - { - return current_sqr_r; - } - - template - int Miniball::nr_support_points () const - { - assert (ssize < d+2); - return ssize; - } - - template - typename Miniball::SupportPointIterator - Miniball::support_points_begin () const - { - return L.begin(); - } - - template - typename Miniball::SupportPointIterator - Miniball::support_points_end () const - { - return support_end; - } - - template - typename Miniball::NT - Miniball::relative_error (NT& subopt) const - { - NT e, max_e = nt0; - // compute maximum absolute excess of support points - for (SupportPointIterator it = support_points_begin(); - it != support_points_end(); ++it) { - e = excess (*it); - if (e < nt0) e = -e; - if (e > max_e) { - max_e = e; - } - } - // compute maximum excess of any point - for (Pit i = points_begin; i != points_end; ++i) - if ((e = excess (i)) > max_e) - max_e = e; - - subopt = suboptimality(); - assert (current_sqr_r > nt0 || max_e == nt0); - return (current_sqr_r == nt0 ? nt0 : max_e / current_sqr_r); - } - - template - bool Miniball::is_valid (NT tol) const - { - NT suboptimality; - return ( (relative_error (suboptimality) <= tol) && (suboptimality == 0) ); - } - - template - double Miniball::get_time() const - { - return time; - } - - template - void Miniball::mtf_mb (Sit n) - { - // Algorithm 1: mtf_mb (L_{n-1}, B), where L_{n-1} = [L.begin, n) - // B: the set of forced points, defining the current ball - // S: the superset of support points computed by the algorithm - // -------------------------------------------------------------- - // from B. Gaertner, Fast and Robust Smallest Enclosing Balls, ESA 1999, - // http://www.inf.ethz.ch/personal/gaertner/texts/own_work/esa99_final.pdf - - // PRE: B = S - assert (fsize == ssize); - - support_end = L.begin(); - if ((fsize) == d+1) return; - - // incremental construction - for (Sit i = L.begin(); i != n;) - { - // INV: (support_end - L.begin() == |S|-|B|) - assert (std::distance (L.begin(), support_end) == ssize - fsize); - - Sit j = i++; - if (excess(*j) > nt0) - if (push(*j)) { // B := B + p_i - mtf_mb (j); // mtf_mb (L_{i-1}, B + p_i) - pop(); // B := B - p_i - mtf_move_to_front(j); - } - } - // POST: the range [L.begin(), support_end) stores the set S\B - } - - template - void Miniball::mtf_move_to_front (Sit j) - { - if (support_end == j) - support_end++; - L.splice (L.begin(), L, j); - } - - template - void Miniball::pivot_mb (Pit n) - { - // Algorithm 2: pivot_mb (L_{n-1}), where L_{n-1} = [L.begin, n) - // -------------------------------------------------------------- - // from B. Gaertner, Fast and Robust Smallest Enclosing Balls, ESA 1999, - // http://www.inf.ethz.ch/personal/gaertner/texts/own_work/esa99_final.pdf - NT old_sqr_r; - const NT* c; - Pit pivot, k; - NT e, max_e, sqr_r; - Cit p; - do { - old_sqr_r = current_sqr_r; - sqr_r = current_sqr_r; - - pivot = points_begin; - max_e = nt0; - for (k = points_begin; k != n; ++k) { - p = coord_accessor(k); - e = -sqr_r; - c = current_c; - for (int j=0; j(*p++-*c++); - if (e > max_e) { - max_e = e; - pivot = k; - } - } - - if (max_e > nt0) { - // check if the pivot is already contained in the support set - if (std::find(L.begin(), support_end, pivot) == support_end) { - assert (fsize == 0); - if (push (pivot)) { - mtf_mb(support_end); - pop(); - pivot_move_to_front(pivot); - } - } - } - } while (old_sqr_r < current_sqr_r); - } - - template - void Miniball::pivot_move_to_front (Pit j) - { - L.push_front(j); - if (std::distance(L.begin(), support_end) == d+2) - support_end--; - } - - template - inline typename Miniball::NT - Miniball::excess (Pit pit) const - { - Cit p = coord_accessor(pit); - NT e = -current_sqr_r; - NT* c = current_c; - for (int k=0; k(*p++-*c++); - } - return e; - } - - template - void Miniball::pop () - { - --fsize; - } - - template - bool Miniball::push (Pit pit) - { - int i, j; - NT eps = mb_sqr(std::numeric_limits::epsilon()); - - Cit cit = coord_accessor(pit); - Cit p = cit; - - if (fsize==0) { - for (i=0; i(v[fsize][j]); - z[fsize]*=2; - - // reject push if z_fsize too small - if (z[fsize](*p++-c[fsize-1][i]); - f[fsize]=e/z[fsize]; - - for (i=0; i - typename Miniball::NT - Miniball::suboptimality () const - { - NT* l = new NT[d+1]; - NT min_l = nt0; - l[0] = NT(1); - for (int i=ssize-1; i>0; --i) { - l[i] = f[i]; - for (int k=ssize-1; k>i; --k) - l[i]-=a[k][i]*l[k]; - if (l[i] < min_l) min_l = l[i]; - l[0] -= l[i]; - } - if (l[0] < min_l) min_l = l[0]; - delete[] l; - if (min_l < nt0) - return -min_l; - return nt0; - } - -} // end Namespace Miniball - -#endif // MINIBALL_HPP_ diff --git a/src/Cech_complex/include/gudhi/Miniball.COPYRIGHT b/src/Cech_complex/include/gudhi/Miniball.COPYRIGHT new file mode 100644 index 00000000..dbe4c553 --- /dev/null +++ b/src/Cech_complex/include/gudhi/Miniball.COPYRIGHT @@ -0,0 +1,4 @@ +The miniball software is available under the GNU General Public License (GPLv3 - https://www.gnu.org/copyleft/gpl.html). +If your intended use is not compliant with this license, please buy a commercial license (EUR 500 - https://people.inf.ethz.ch/gaertner/subdir/software/miniball/license.html). +You need a license if the software that you develop using Miniball V3.0 is not open source. + diff --git a/src/Cech_complex/include/gudhi/Miniball.README b/src/Cech_complex/include/gudhi/Miniball.README new file mode 100644 index 00000000..86a96f08 --- /dev/null +++ b/src/Cech_complex/include/gudhi/Miniball.README @@ -0,0 +1,23 @@ +https://people.inf.ethz.ch/gaertner/subdir/software/miniball.html + +Smallest Enclosing Balls of Points - Fast and Robust in C++. +(high-quality software for smallest enclosing balls of balls is available in the computational geometry algorithms library CGAL) + + +This is the miniball software (V3.0) for computing smallest enclosing balls of points in arbitrary dimensions. It consists of a C++ header file Miniball.hpp (around 500 lines of code) and two example programs miniball_example.cpp and miniball_example_containers.cpp that demonstrate the usage. The first example stores the coordinates of the input points in a two-dimensional array, the second example uses a list of vectors to show how generic containers can be used. + +Credits: Aditya Gupta and Alexandros Konstantinakis-Karmis have significantly contributed to this version of the software. + +Changes - https://people.inf.ethz.ch/gaertner/subdir/software/miniball/changes.txt - from previous versions. + +The theory - https://people.inf.ethz.ch/gaertner/subdir/texts/own_work/esa99_final.pdf - behind the miniball software (Proc. 7th Annual European Symposium on Algorithms (ESA), Lecture Notes in Computer Science 1643, Springer-Verlag, pp.325-338, 1999). + +Main Features: + + Very fast in low dimensions. 1 million points in 5-space are processed within 0.05 seconds on any recent machine. + + High numerical stability. Almost all input degeneracies (cospherical points, multiple points, points very close together) are routinely handled. + + Easily integrates into your code. You can freely choose the coordinate type of your points and the container to store the points. If you still need to adapt the code, the header is small and readable and contains documentation for all major methods. + + diff --git a/src/Cech_complex/include/gudhi/Miniball.hpp b/src/Cech_complex/include/gudhi/Miniball.hpp new file mode 100644 index 00000000..ce6cbb5b --- /dev/null +++ b/src/Cech_complex/include/gudhi/Miniball.hpp @@ -0,0 +1,523 @@ +// Copright (C) 1999-2013, Bernd Gaertner +// $Rev: 3581 $ +// +// 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 . +// +// Contact: +// -------- +// Bernd Gaertner +// Institute of Theoretical Computer Science +// ETH Zuerich +// CAB G31.1 +// CH-8092 Zuerich, Switzerland +// http://www.inf.ethz.ch/personal/gaertner + +#ifndef MINIBALL_HPP_ +#define MINIBALL_HPP_ + +#include +#include +#include +#include +#include + +namespace Gudhi { + +namespace Miniball { + + // Global Functions + // ================ + template + inline NT mb_sqr (NT r) {return r*r;} + + // Functors + // ======== + + // functor to map a point iterator to the corresponding coordinate iterator; + // generic version for points whose coordinate containers have begin() + template < typename Pit_, typename Cit_ > + struct CoordAccessor { + typedef Pit_ Pit; + typedef Cit_ Cit; + inline Cit operator() (Pit it) const { return (*it).begin(); } + }; + + // partial specialization for points whose coordinate containers are arrays + template < typename Pit_, typename Cit_ > + struct CoordAccessor { + typedef Pit_ Pit; + typedef Cit_* Cit; + inline Cit operator() (Pit it) const { return *it; } + }; + + // Class Declaration + // ================= + + template + class Miniball { + private: + // types + // The iterator type to go through the input points + typedef typename CoordAccessor::Pit Pit; + // The iterator type to go through the coordinates of a single point. + typedef typename CoordAccessor::Cit Cit; + // The coordinate type + typedef typename std::iterator_traits::value_type NT; + // The iterator to go through the support points + typedef typename std::list::iterator Sit; + + // data members... + const int d; // dimension + Pit points_begin; + Pit points_end; + CoordAccessor coord_accessor; + double time; + const NT nt0; // NT(0) + + //...for the algorithms + std::list L; + Sit support_end; + int fsize; // number of forced points + int ssize; // number of support points + + // ...for the ball updates + NT* current_c; + NT current_sqr_r; + NT** c; + NT* sqr_r; + + // helper arrays + NT* q0; + NT* z; + NT* f; + NT** v; + NT** a; + + public: + // The iterator type to go through the support points + typedef typename std::list::const_iterator SupportPointIterator; + + // PRE: [begin, end) is a nonempty range + // POST: computes the smallest enclosing ball of the points in the range + // [begin, end); the functor a maps a point iterator to an iterator + // through the d coordinates of the point + Miniball (int d_, Pit begin, Pit end, CoordAccessor ca = CoordAccessor()); + + // POST: returns a pointer to the first element of an array that holds + // the d coordinates of the center of the computed ball + const NT* center () const; + + // POST: returns the squared radius of the computed ball + NT squared_radius () const; + + // POST: returns the number of support points of the computed ball; + // the support points form a minimal set with the same smallest + // enclosing ball as the input set; in particular, the support + // points are on the boundary of the computed ball, and their + // number is at most d+1 + int nr_support_points () const; + + // POST: returns an iterator to the first support point + SupportPointIterator support_points_begin () const; + + // POST: returns a past-the-end iterator for the range of support points + SupportPointIterator support_points_end () const; + + // POST: returns the maximum excess of any input point w.r.t. the computed + // ball, divided by the squared radius of the computed ball. The + // excess of a point is the difference between its squared distance + // from the center and the squared radius; Ideally, the return value + // is 0. subopt is set to the absolute value of the most negative + // coefficient in the affine combination of the support points that + // yields the center. Ideally, this is a convex combination, and there + // is no negative coefficient in which case subopt is set to 0. + NT relative_error (NT& subopt) const; + + // POST: return true if the relative error is at most tol, and the + // suboptimality is 0; the default tolerance is 10 times the + // coordinate type's machine epsilon + bool is_valid (NT tol = NT(10) * std::numeric_limits::epsilon()) const; + + // POST: returns the time in seconds taken by the constructor call for + // computing the smallest enclosing ball + double get_time() const; + + // POST: deletes dynamically allocated arrays + ~Miniball(); + + private: + void mtf_mb (Sit n); + void mtf_move_to_front (Sit j); + void pivot_mb (Pit n); + void pivot_move_to_front (Pit j); + NT excess (Pit pit) const; + void pop (); + bool push (Pit pit); + NT suboptimality () const; + void create_arrays(); + void delete_arrays(); + }; + + // Class Definition + // ================ + template + Miniball::Miniball (int d_, Pit begin, Pit end, + CoordAccessor ca) + : d (d_), + points_begin (begin), + points_end (end), + coord_accessor (ca), + time (clock()), + nt0 (NT(0)), + L(), + support_end (L.begin()), + fsize(0), + ssize(0), + current_c (NULL), + current_sqr_r (NT(-1)), + c (NULL), + sqr_r (NULL), + q0 (NULL), + z (NULL), + f (NULL), + v (NULL), + a (NULL) + { + assert (points_begin != points_end); + create_arrays(); + + // set initial center + for (int j=0; j + Miniball::~Miniball() + { + delete_arrays(); + } + + template + void Miniball::create_arrays() + { + c = new NT*[d+1]; + v = new NT*[d+1]; + a = new NT*[d+1]; + for (int i=0; i + void Miniball::delete_arrays() + { + delete[] f; + delete[] z; + delete[] q0; + delete[] sqr_r; + for (int i=0; i + const typename Miniball::NT* + Miniball::center () const + { + return current_c; + } + + template + typename Miniball::NT + Miniball::squared_radius () const + { + return current_sqr_r; + } + + template + int Miniball::nr_support_points () const + { + assert (ssize < d+2); + return ssize; + } + + template + typename Miniball::SupportPointIterator + Miniball::support_points_begin () const + { + return L.begin(); + } + + template + typename Miniball::SupportPointIterator + Miniball::support_points_end () const + { + return support_end; + } + + template + typename Miniball::NT + Miniball::relative_error (NT& subopt) const + { + NT e, max_e = nt0; + // compute maximum absolute excess of support points + for (SupportPointIterator it = support_points_begin(); + it != support_points_end(); ++it) { + e = excess (*it); + if (e < nt0) e = -e; + if (e > max_e) { + max_e = e; + } + } + // compute maximum excess of any point + for (Pit i = points_begin; i != points_end; ++i) + if ((e = excess (i)) > max_e) + max_e = e; + + subopt = suboptimality(); + assert (current_sqr_r > nt0 || max_e == nt0); + return (current_sqr_r == nt0 ? nt0 : max_e / current_sqr_r); + } + + template + bool Miniball::is_valid (NT tol) const + { + NT suboptimality; + return ( (relative_error (suboptimality) <= tol) && (suboptimality == 0) ); + } + + template + double Miniball::get_time() const + { + return time; + } + + template + void Miniball::mtf_mb (Sit n) + { + // Algorithm 1: mtf_mb (L_{n-1}, B), where L_{n-1} = [L.begin, n) + // B: the set of forced points, defining the current ball + // S: the superset of support points computed by the algorithm + // -------------------------------------------------------------- + // from B. Gaertner, Fast and Robust Smallest Enclosing Balls, ESA 1999, + // http://www.inf.ethz.ch/personal/gaertner/texts/own_work/esa99_final.pdf + + // PRE: B = S + assert (fsize == ssize); + + support_end = L.begin(); + if ((fsize) == d+1) return; + + // incremental construction + for (Sit i = L.begin(); i != n;) + { + // INV: (support_end - L.begin() == |S|-|B|) + assert (std::distance (L.begin(), support_end) == ssize - fsize); + + Sit j = i++; + if (excess(*j) > nt0) + if (push(*j)) { // B := B + p_i + mtf_mb (j); // mtf_mb (L_{i-1}, B + p_i) + pop(); // B := B - p_i + mtf_move_to_front(j); + } + } + // POST: the range [L.begin(), support_end) stores the set S\B + } + + template + void Miniball::mtf_move_to_front (Sit j) + { + if (support_end == j) + support_end++; + L.splice (L.begin(), L, j); + } + + template + void Miniball::pivot_mb (Pit n) + { + // Algorithm 2: pivot_mb (L_{n-1}), where L_{n-1} = [L.begin, n) + // -------------------------------------------------------------- + // from B. Gaertner, Fast and Robust Smallest Enclosing Balls, ESA 1999, + // http://www.inf.ethz.ch/personal/gaertner/texts/own_work/esa99_final.pdf + NT old_sqr_r; + const NT* c; + Pit pivot, k; + NT e, max_e, sqr_r; + Cit p; + do { + old_sqr_r = current_sqr_r; + sqr_r = current_sqr_r; + + pivot = points_begin; + max_e = nt0; + for (k = points_begin; k != n; ++k) { + p = coord_accessor(k); + e = -sqr_r; + c = current_c; + for (int j=0; j(*p++-*c++); + if (e > max_e) { + max_e = e; + pivot = k; + } + } + + if (max_e > nt0) { + // check if the pivot is already contained in the support set + if (std::find(L.begin(), support_end, pivot) == support_end) { + assert (fsize == 0); + if (push (pivot)) { + mtf_mb(support_end); + pop(); + pivot_move_to_front(pivot); + } + } + } + } while (old_sqr_r < current_sqr_r); + } + + template + void Miniball::pivot_move_to_front (Pit j) + { + L.push_front(j); + if (std::distance(L.begin(), support_end) == d+2) + support_end--; + } + + template + inline typename Miniball::NT + Miniball::excess (Pit pit) const + { + Cit p = coord_accessor(pit); + NT e = -current_sqr_r; + NT* c = current_c; + for (int k=0; k(*p++-*c++); + } + return e; + } + + template + void Miniball::pop () + { + --fsize; + } + + template + bool Miniball::push (Pit pit) + { + int i, j; + NT eps = mb_sqr(std::numeric_limits::epsilon()); + + Cit cit = coord_accessor(pit); + Cit p = cit; + + if (fsize==0) { + for (i=0; i(v[fsize][j]); + z[fsize]*=2; + + // reject push if z_fsize too small + if (z[fsize](*p++-c[fsize-1][i]); + f[fsize]=e/z[fsize]; + + for (i=0; i + typename Miniball::NT + Miniball::suboptimality () const + { + NT* l = new NT[d+1]; + NT min_l = nt0; + l[0] = NT(1); + for (int i=ssize-1; i>0; --i) { + l[i] = f[i]; + for (int k=ssize-1; k>i; --k) + l[i]-=a[k][i]*l[k]; + if (l[i] < min_l) min_l = l[i]; + l[0] -= l[i]; + } + if (l[0] < min_l) min_l = l[0]; + delete[] l; + if (min_l < nt0) + return -min_l; + return nt0; + } +} // namespace Miniball + +} // namespace Gudhi + +#endif // MINIBALL_HPP_ diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp index 8cbfe431..4aa85057 100644 --- a/src/Cech_complex/test/test_cech_complex.cpp +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -36,8 +36,7 @@ #include #include #include - -#include +#include // Type definitions using Simplex_tree = Gudhi::Simplex_tree<>; @@ -49,7 +48,7 @@ using Cech_complex = Gudhi::cech_complex::Cech_complex>; +using Min_sphere = Gudhi::Miniball::Miniball>; BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { // ---------------------------------------------------------------------------- diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h index 7749b98e..93956a69 100644 --- a/src/common/include/gudhi/distance_functions.h +++ b/src/common/include/gudhi/distance_functions.h @@ -25,7 +25,7 @@ #include -#include +#include #include -- cgit v1.2.3 From 1f3716292673a56413d3501b4b98b54416d193ed Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Thu, 22 Mar 2018 10:10:08 +0000 Subject: code review : Rename Radius_distance Minimal_enclosing_ball_radius git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3304 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 204aa7a7098773b2d290e35a12a1c92449743d7d --- .../benchmark/cech_complex_benchmark.cpp | 32 ++++++++++++---------- .../example/cech_complex_step_by_step.cpp | 4 +-- src/Cech_complex/include/gudhi/Cech_complex.h | 11 ++++---- .../include/gudhi/Cech_complex_blocker.h | 4 +-- src/Cech_complex/test/test_cech_complex.cpp | 4 +-- src/common/include/gudhi/distance_functions.h | 8 +++--- 6 files changed, 34 insertions(+), 29 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp index 6ba52419..2fa255ed 100644 --- a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp +++ b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp @@ -46,7 +46,7 @@ using Rips_complex = Gudhi::rips_complex::Rips_complex; using Cech_complex = Gudhi::cech_complex::Cech_complex; -class Radius_distance { +class Minimal_enclosing_ball_radius { public: // boost::range_value is not SFINAE-friendly so we cannot use it in the return type template< typename Point > @@ -80,24 +80,26 @@ int main(int argc, char * argv[]) { Gudhi::Clock euclidean_clock("Gudhi::Euclidean_distance"); // Compute the proximity graph of the points Proximity_graph euclidean_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Gudhi::Euclidean_distance()); + threshold, + Gudhi::Euclidean_distance()); std::cout << euclidean_clock << std::endl; - Gudhi::Clock radius_clock("Radius_distance"); + Gudhi::Clock miniball_clock("Minimal_enclosing_ball_radius"); // Compute the proximity graph of the points - Proximity_graph radius_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Radius_distance()); - std::cout << radius_clock << std::endl; + Proximity_graph miniball_prox_graph = + Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), + threshold, + Minimal_enclosing_ball_radius()); + std::cout << miniball_clock << std::endl; - Gudhi::Clock common_radius_clock("Gudhi::Radius_distance()"); + Gudhi::Clock common_miniball_clock("Gudhi::Minimal_enclosing_ball_radius()"); // Compute the proximity graph of the points - Proximity_graph sq_radius_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Gudhi::Radius_distance()); - std::cout << common_radius_clock << std::endl; + Proximity_graph common_miniball_prox_graph = + Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), + threshold, + Gudhi::Minimal_enclosing_ball_radius()); + std::cout << common_miniball_clock << std::endl; boost::filesystem::path full_path(boost::filesystem::current_path()); @@ -121,7 +123,9 @@ int main(int argc, char * argv[]) { std::cout << itr->path().stem() << ";"; std::cout << radius << ";"; Gudhi::Clock rips_clock("Rips computation"); - Rips_complex rips_complex_from_points(off_reader.get_point_cloud(), radius, Gudhi::Radius_distance()); + Rips_complex rips_complex_from_points(off_reader.get_point_cloud(), + radius, + Gudhi::Minimal_enclosing_ball_radius()); Simplex_tree rips_stree; rips_complex_from_points.create_complex(rips_stree, p0.size() - 1); // ------------------------------------------ diff --git a/src/Cech_complex/example/cech_complex_step_by_step.cpp b/src/Cech_complex/example/cech_complex_step_by_step.cpp index 0e7c4bbd..760b53dc 100644 --- a/src/Cech_complex/example/cech_complex_step_by_step.cpp +++ b/src/Cech_complex/example/cech_complex_step_by_step.cpp @@ -65,7 +65,7 @@ class Cech_blocker { std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES } - Filtration_value radius = Gudhi::Radius_distance()(points); + Filtration_value radius = Gudhi::Minimal_enclosing_ball_radius()(points); #ifdef DEBUG_TRACES std::cout << "radius = " << radius << " - " << (radius > max_radius_) << std::endl; #endif // DEBUG_TRACES @@ -105,7 +105,7 @@ int main(int argc, char * argv[]) { // Compute the proximity graph of the points Proximity_graph prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), max_radius, - Gudhi::Radius_distance()); + Gudhi::Minimal_enclosing_ball_radius()); // Construct the Rips complex in a Simplex Tree Simplex_tree st; diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 612c73c3..8b1a9221 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -23,7 +23,7 @@ #ifndef CECH_COMPLEX_H_ #define CECH_COMPLEX_H_ -#include // for Gudhi::Radius_distance +#include // for Gudhi::Minimal_enclosing_ball_radius #include // for Gudhi::Proximity_graph #include // for GUDHI_CHECK #include // for Gudhi::cech_complex::Cech_blocker @@ -43,7 +43,7 @@ namespace cech_complex { * * \details * The data structure is a proximity graph, containing edges when the edge length is less or equal - * to a given max_radius. Edge length is computed from `Gudhi::Radius_distance` distance function. + * to a given max_radius. Edge length is computed from `Gudhi::Minimal_enclosing_ball_radius` distance function. * * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required * by `Gudhi::Proximity_graph`. @@ -71,9 +71,10 @@ class Cech_complex { Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) : max_radius_(max_radius), point_cloud_(points) { - cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, - max_radius_, - Gudhi::Radius_distance()); + cech_skeleton_graph_ = + Gudhi::compute_proximity_graph(point_cloud_, + max_radius_, + Gudhi::Minimal_enclosing_ball_radius()); } /** \brief Initializes the simplicial complex from the proximity graph and expands it until a given maximal diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index 5ba17c51..c082815d 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -24,7 +24,7 @@ #define CECH_COMPLEX_BLOCKER_H_ #include // Cech_blocker is using a pointer on Gudhi::cech_complex::Cech_complex -#include // for Gudhi::Radius_distance +#include // for Gudhi::Minimal_enclosing_ball_radius #include #include @@ -75,7 +75,7 @@ class Cech_blocker { std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES } - Filtration_value radius = Gudhi::Radius_distance()(points); + Filtration_value radius = Gudhi::Minimal_enclosing_ball_radius()(points); #ifdef DEBUG_TRACES if (radius > cc_ptr_->max_radius()) std::cout << "radius > max_radius => expansion is blocked\n"; diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp index 4aa85057..8658729b 100644 --- a/src/Cech_complex/test/test_cech_complex.cpp +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -111,10 +111,10 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { std::cout << vertex << ","; vp.push_back(points.at(vertex)); } - std::cout << ") - distance =" << Gudhi::Radius_distance()(vp.at(0), vp.at(1)) << + std::cout << ") - distance =" << Gudhi::Minimal_enclosing_ball_radius()(vp.at(0), vp.at(1)) << " - filtration =" << st.filtration(f_simplex) << std::endl; BOOST_CHECK(vp.size() == 2); - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Radius_distance()(vp.at(0), vp.at(1))); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Minimal_enclosing_ball_radius()(vp.at(0), vp.at(1))); } } diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h index 93956a69..429a5fa7 100644 --- a/src/common/include/gudhi/distance_functions.h +++ b/src/common/include/gudhi/distance_functions.h @@ -70,9 +70,9 @@ class Euclidean_distance { } }; -/** @brief Compute the squared radius between Points given by a range of coordinates. The points are assumed to - * have the same dimension. */ -class Radius_distance { +/** @brief Compute the radius of the minimal enclosing ball between Points given by a range of coordinates. + * The points are assumed to have the same dimension. */ +class Minimal_enclosing_ball_radius { public: // boost::range_value is not SFINAE-friendly so we cannot use it in the return type template< typename Point > @@ -92,7 +92,7 @@ class Radius_distance { Min_sphere ms(point_cloud.begin()->end() - point_cloud.begin()->begin(), point_cloud.begin(),point_cloud.end()); #ifdef DEBUG_TRACES - std::cout << "Radius_distance = " << std::sqrt(ms.squared_radius()) << " | nb points = " + std::cout << "Minimal_enclosing_ball_radius = " << std::sqrt(ms.squared_radius()) << " | nb points = " << point_cloud.end() - point_cloud.begin() << " | dimension = " << point_cloud.begin()->end() - point_cloud.begin()->begin() << std::endl; #endif // DEBUG_TRACES -- cgit v1.2.3 From b69cc713465675a9bab998cb0688eb91390978a6 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Thu, 22 Mar 2018 15:12:17 +0000 Subject: code review : use std::begin, std::end and boost::size git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3305 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: e59699bc13ae66476001ef5f648759fef68ee76a --- src/Cech_complex/include/gudhi/Cech_complex.h | 12 ++++++------ src/common/include/gudhi/distance_functions.h | 9 ++++----- 2 files changed, 10 insertions(+), 11 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 8b1a9221..bfad8b77 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -48,8 +48,8 @@ namespace cech_complex { * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required * by `Gudhi::Proximity_graph`. * - * \tparam ForwardPointRange furnishes `.size()`, `.begin()` and `.end()` methods, and a `const_iterator` type - * definition. + * \tparam ForwardPointRange must be a range for which `std::begin()` and `std::end()` methods return input + * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. */ template class Cech_complex { @@ -64,8 +64,8 @@ class Cech_complex { * @param[in] points Range of points. * @param[in] max_radius Maximal radius value. * - * \tparam ForwardPointRange must be a range for which `.size()`, `.begin()` and `.end()` methods return input - * iterators on a point. `.begin()` and `.end()` methods are required for a point. + * \tparam ForwardPointRange must be a range for which `std::begin()` and `std::end()` methods return input + * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. * */ Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) @@ -107,9 +107,9 @@ class Cech_complex { * @exception std::out_of_range In debug mode, if point position in the range is out. */ typename ForwardPointRange::const_iterator point_iterator(std::size_t vertex) const { - GUDHI_CHECK((point_cloud_.begin() + vertex) < point_cloud_.end(), + GUDHI_CHECK((std::begin(point_cloud_) + vertex) < std::end(point_cloud_), std::out_of_range("Cech_complex::point - simplicial complex is not empty")); - return (point_cloud_.begin() + vertex); + return (std::begin(point_cloud_) + vertex); } private: diff --git a/src/common/include/gudhi/distance_functions.h b/src/common/include/gudhi/distance_functions.h index 429a5fa7..20b04000 100644 --- a/src/common/include/gudhi/distance_functions.h +++ b/src/common/include/gudhi/distance_functions.h @@ -28,6 +28,7 @@ #include #include +#include #include // for std::sqrt #include // for std::decay @@ -74,13 +75,11 @@ class Euclidean_distance { * The points are assumed to have the same dimension. */ class Minimal_enclosing_ball_radius { public: - // boost::range_value is not SFINAE-friendly so we cannot use it in the return type template< typename Point > typename std::iterator_traits::type>::value_type operator()(const Point& p1, const Point& p2) const { return Euclidean_distance()(p1, p2) / 2.; } - // boost::range_value is not SFINAE-friendly so we cannot use it in the return type template< typename Point_cloud, typename Point_iterator = typename boost::range_const_iterator::type, typename Point= typename std::iterator_traits::value_type, @@ -90,11 +89,11 @@ class Minimal_enclosing_ball_radius { operator()(const Point_cloud& point_cloud) const { using Min_sphere = Miniball::Miniball>; - Min_sphere ms(point_cloud.begin()->end() - point_cloud.begin()->begin(), point_cloud.begin(),point_cloud.end()); + Min_sphere ms(boost::size(*point_cloud.begin()), point_cloud.begin(),point_cloud.end()); #ifdef DEBUG_TRACES std::cout << "Minimal_enclosing_ball_radius = " << std::sqrt(ms.squared_radius()) << " | nb points = " - << point_cloud.end() - point_cloud.begin() << " | dimension = " - << point_cloud.begin()->end() - point_cloud.begin()->begin() << std::endl; + << boost::size(point_cloud) << " | dimension = " + << boost::size(*point_cloud.begin()) << std::endl; #endif // DEBUG_TRACES return std::sqrt(ms.squared_radius()); -- cgit v1.2.3 From 90ea210d07afa9c48a19cdad0621d607b4ebd54b Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Thu, 22 Mar 2018 17:08:54 +0000 Subject: code review : no more ForwardPointRange copy. Use of a vector instead. git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3306 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: f848c18595303bfb802998746ee6fe2a308c68df --- src/Cech_complex/include/gudhi/Cech_complex.h | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index bfad8b77..7c2e31ac 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -57,6 +57,9 @@ class Cech_complex { using Vertex_handle = typename SimplicialComplexForProximityGraph::Vertex_handle; using Filtration_value = typename SimplicialComplexForProximityGraph::Filtration_value; using Proximity_graph = Gudhi::Proximity_graph; + using Point_iterator = typename boost::range_const_iterator::type; + using Point= typename std::iterator_traits::value_type; + using Point_cloud = std::vector; public: /** \brief Cech_complex constructor from a list of points. @@ -70,7 +73,7 @@ class Cech_complex { */ Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) : max_radius_(max_radius), - point_cloud_(points) { + point_cloud_(std::begin(points), std::end(points)) { cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, max_radius_, @@ -115,7 +118,7 @@ class Cech_complex { private: Proximity_graph cech_skeleton_graph_; Filtration_value max_radius_; - ForwardPointRange point_cloud_; + Point_cloud point_cloud_; }; } // namespace cech_complex -- cgit v1.2.3 From 7e3cfb3aad5ad38779e48f77dc2ba24014814dc9 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Tue, 27 Mar 2018 14:01:50 +0000 Subject: No more deep copy of the simplicial complex in the Cech Blocker, just use the pointer git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3307 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 026cd5491d8e3030fce63beabd6e77bddebb05cc --- src/Cech_complex/include/gudhi/Cech_complex.h | 2 +- src/Cech_complex/include/gudhi/Cech_complex_blocker.h | 10 +++++----- 2 files changed, 6 insertions(+), 6 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 7c2e31ac..1cae7b0b 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -97,7 +97,7 @@ class Cech_complex { complex.insert_graph(cech_skeleton_graph_); // expand the graph until dimension dim_max complex.expansion_with_blockers(dim_max, - Cech_blocker(complex, this)); + Cech_blocker(&complex, this)); } /** @return max_radius value given at construction. */ diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index c082815d..6755c826 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -68,7 +68,7 @@ class Cech_blocker { * \return true if the simplex radius is greater than the Cech_complex max_radius*/ bool operator()(Simplex_handle sh) { Point_cloud points; - for (auto vertex : simplicial_complex_.simplex_vertex_range(sh)) { + for (auto vertex : sc_ptr_->simplex_vertex_range(sh)) { points.push_back(Point(cc_ptr_->point_iterator(vertex)->begin(), cc_ptr_->point_iterator(vertex)->end())); #ifdef DEBUG_TRACES @@ -80,17 +80,17 @@ class Cech_blocker { if (radius > cc_ptr_->max_radius()) std::cout << "radius > max_radius => expansion is blocked\n"; #endif // DEBUG_TRACES - simplicial_complex_.assign_filtration(sh, radius); + sc_ptr_->assign_filtration(sh, radius); return (radius > cc_ptr_->max_radius()); } /** \internal \brief Cech complex blocker constructor. */ - Cech_blocker(SimplicialComplexForCech& simplicial_complex, Cech_complex* cc_ptr) - : simplicial_complex_(simplicial_complex), + Cech_blocker(SimplicialComplexForCech* sc_ptr, Cech_complex* cc_ptr) + : sc_ptr_(sc_ptr), cc_ptr_(cc_ptr) { } private: - SimplicialComplexForCech simplicial_complex_; + SimplicialComplexForCech* sc_ptr_; Cech_complex* cc_ptr_; }; -- cgit v1.2.3 From df00c318bacd58ee48ddea6cdf161c35f0568873 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Mon, 9 Apr 2018 08:39:02 +0000 Subject: Add Miniball file changes for Gudhi requirements inside Miniball.README git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3353 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 099bc9ed544e5a81a5dc3a8dea3ce93afbfef82b --- src/Cech_complex/include/gudhi/Miniball.README | 3 +++ 1 file changed, 3 insertions(+) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Miniball.README b/src/Cech_complex/include/gudhi/Miniball.README index 86a96f08..033d8953 100644 --- a/src/Cech_complex/include/gudhi/Miniball.README +++ b/src/Cech_complex/include/gudhi/Miniball.README @@ -21,3 +21,6 @@ Main Features: Easily integrates into your code. You can freely choose the coordinate type of your points and the container to store the points. If you still need to adapt the code, the header is small and readable and contains documentation for all major methods. +Changes done for the GUDHI version of MiniBall: + - Add include guard + - Move Miniball namespace inside a new Gudhi namespace -- cgit v1.2.3 From a80c1adb219494f909e55ea274b39355218a5138 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Mon, 9 Apr 2018 12:14:26 +0000 Subject: Code review : Rename ForwardPointIterator with InputPointRange git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3358 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 6f90e228c4c546b28b9fe610e5f59bbab047cd27 --- src/Cech_complex/include/gudhi/Cech_complex.h | 14 +++++++------- src/Cech_complex/include/gudhi/Cech_complex_blocker.h | 8 ++++---- 2 files changed, 11 insertions(+), 11 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 1cae7b0b..52f03d6b 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -48,16 +48,16 @@ namespace cech_complex { * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required * by `Gudhi::Proximity_graph`. * - * \tparam ForwardPointRange must be a range for which `std::begin()` and `std::end()` methods return input + * \tparam InputPointRange must be a range for which `std::begin()` and `std::end()` methods return input * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. */ -template +template class Cech_complex { private: using Vertex_handle = typename SimplicialComplexForProximityGraph::Vertex_handle; using Filtration_value = typename SimplicialComplexForProximityGraph::Filtration_value; using Proximity_graph = Gudhi::Proximity_graph; - using Point_iterator = typename boost::range_const_iterator::type; + using Point_iterator = typename boost::range_const_iterator::type; using Point= typename std::iterator_traits::value_type; using Point_cloud = std::vector; @@ -67,11 +67,11 @@ class Cech_complex { * @param[in] points Range of points. * @param[in] max_radius Maximal radius value. * - * \tparam ForwardPointRange must be a range for which `std::begin()` and `std::end()` methods return input + * \tparam InputPointRange must be a range for which `std::begin()` and `std::end()` methods return input * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. * */ - Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) + Cech_complex(const InputPointRange& points, Filtration_value max_radius) : max_radius_(max_radius), point_cloud_(std::begin(points), std::end(points)) { cech_skeleton_graph_ = @@ -97,7 +97,7 @@ class Cech_complex { complex.insert_graph(cech_skeleton_graph_); // expand the graph until dimension dim_max complex.expansion_with_blockers(dim_max, - Cech_blocker(&complex, this)); + Cech_blocker(&complex, this)); } /** @return max_radius value given at construction. */ @@ -109,7 +109,7 @@ class Cech_complex { * @return A const iterator on the point. * @exception std::out_of_range In debug mode, if point position in the range is out. */ - typename ForwardPointRange::const_iterator point_iterator(std::size_t vertex) const { + typename InputPointRange::const_iterator point_iterator(std::size_t vertex) const { GUDHI_CHECK((std::begin(point_cloud_) + vertex) < std::end(point_cloud_), std::out_of_range("Cech_complex::point - simplicial complex is not empty")); return (std::begin(point_cloud_) + vertex); diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index 6755c826..ab56c10d 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -35,7 +35,7 @@ namespace Gudhi { namespace cech_complex { // Just declaring Cech_complex class because used and not yet defined. -template +template class Cech_complex; /** \internal @@ -50,16 +50,16 @@ class Cech_complex; * \tparam SimplicialComplexForProximityGraph furnishes `Simplex_handle` and `Filtration_value` type definition, * `simplex_vertex_range(Simplex_handle sh)`and `assign_filtration(Simplex_handle sh, Filtration_value filt)` methods. * - * \tparam ForwardPointRange is required by the pointer on Chech_complex for type definition. + * \tparam InputPointRange is required by the pointer on Chech_complex for type definition. */ -template +template class Cech_blocker { private: using Point = std::vector; using Point_cloud = std::vector; using Simplex_handle = typename SimplicialComplexForCech::Simplex_handle; using Filtration_value = typename SimplicialComplexForCech::Filtration_value; - using Cech_complex = Gudhi::cech_complex::Cech_complex; + using Cech_complex = Gudhi::cech_complex::Cech_complex; public: /** \internal \brief Cech complex blocker operator() - the oracle - assigns the filtration value from the simplex -- cgit v1.2.3 From 51ce9b513116f5fed2b4dc109f0b52595a2cd538 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Tue, 10 Apr 2018 14:53:20 +0000 Subject: Code review : Cech_blocker was hardcoding double replace point_iterator function in a get_point const function that returns a Point InputPointRange description Cech blocker is now templated with Cech complex, which is no more included. Deep copy of the point cloud on Cech complex ctor git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3365 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 93e3cf3fe61290b88a0714b9e55ad80e01a34f36 --- .../example/cech_complex_example_from_points.cpp | 1 - src/Cech_complex/include/gudhi/Cech_complex.h | 39 ++++++++++++++-------- .../include/gudhi/Cech_complex_blocker.h | 15 +++------ src/Cech_complex/test/test_cech_complex.cpp | 26 +++++---------- 4 files changed, 38 insertions(+), 43 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/example/cech_complex_example_from_points.cpp b/src/Cech_complex/example/cech_complex_example_from_points.cpp index 3b889d56..2b36e33c 100644 --- a/src/Cech_complex/example/cech_complex_example_from_points.cpp +++ b/src/Cech_complex/example/cech_complex_example_from_points.cpp @@ -1,6 +1,5 @@ #include #include -#include #include #include diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index 52f03d6b..abad0c21 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -54,11 +54,20 @@ namespace cech_complex { template class Cech_complex { private: + // Required by compute_proximity_graph using Vertex_handle = typename SimplicialComplexForProximityGraph::Vertex_handle; using Filtration_value = typename SimplicialComplexForProximityGraph::Filtration_value; using Proximity_graph = Gudhi::Proximity_graph; - using Point_iterator = typename boost::range_const_iterator::type; - using Point= typename std::iterator_traits::value_type; + + // Retrieve Coordinate type from InputPointRange + using Point_from_range_iterator = typename boost::range_const_iterator::type; + using Point_from_range = typename std::iterator_traits::value_type; + using Coordinate_iterator = typename boost::range_const_iterator::type; + using Coordinate= typename std::iterator_traits::value_type; + + public: + // Point and Point_cloud type definition + using Point = std::vector; using Point_cloud = std::vector; public: @@ -67,13 +76,20 @@ class Cech_complex { * @param[in] points Range of points. * @param[in] max_radius Maximal radius value. * - * \tparam InputPointRange must be a range for which `std::begin()` and `std::end()` methods return input - * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. + * \tparam InputPointRange must be a range of Point. Point must be a range of copyable Cartesian coordinates. * */ Cech_complex(const InputPointRange& points, Filtration_value max_radius) - : max_radius_(max_radius), - point_cloud_(std::begin(points), std::end(points)) { + : max_radius_(max_radius) { + // Point cloud deep copy + auto points_begin_itr = std::begin(points); + auto points_end_itr = std::end(points); + + point_cloud_.reserve(points_end_itr - points_begin_itr); + for (auto point_itr = points_begin_itr; point_itr < points_end_itr; point_itr++) { + point_cloud_.push_back(Point(std::begin(*point_itr), std::end(*point_itr))); + } + cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, max_radius_, @@ -97,7 +113,7 @@ class Cech_complex { complex.insert_graph(cech_skeleton_graph_); // expand the graph until dimension dim_max complex.expansion_with_blockers(dim_max, - Cech_blocker(&complex, this)); + Cech_blocker(&complex, this)); } /** @return max_radius value given at construction. */ @@ -106,13 +122,10 @@ class Cech_complex { } /** @param[in] vertex Point position in the range. - * @return A const iterator on the point. - * @exception std::out_of_range In debug mode, if point position in the range is out. + * @return The point. */ - typename InputPointRange::const_iterator point_iterator(std::size_t vertex) const { - GUDHI_CHECK((std::begin(point_cloud_) + vertex) < std::end(point_cloud_), - std::out_of_range("Cech_complex::point - simplicial complex is not empty")); - return (std::begin(point_cloud_) + vertex); + const Point& get_point(Vertex_handle vertex) const{ + return point_cloud_[vertex]; } private: diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index ab56c10d..2ecef9cf 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -23,7 +23,6 @@ #ifndef CECH_COMPLEX_BLOCKER_H_ #define CECH_COMPLEX_BLOCKER_H_ -#include // Cech_blocker is using a pointer on Gudhi::cech_complex::Cech_complex #include // for Gudhi::Minimal_enclosing_ball_radius #include @@ -34,10 +33,6 @@ namespace Gudhi { namespace cech_complex { -// Just declaring Cech_complex class because used and not yet defined. -template -class Cech_complex; - /** \internal * \class Cech_blocker * \brief Cech complex blocker. @@ -52,14 +47,13 @@ class Cech_complex; * * \tparam InputPointRange is required by the pointer on Chech_complex for type definition. */ -template +template class Cech_blocker { private: - using Point = std::vector; - using Point_cloud = std::vector; + using Point_cloud = typename Cech_complex::Point_cloud; + using Simplex_handle = typename SimplicialComplexForCech::Simplex_handle; using Filtration_value = typename SimplicialComplexForCech::Filtration_value; - using Cech_complex = Gudhi::cech_complex::Cech_complex; public: /** \internal \brief Cech complex blocker operator() - the oracle - assigns the filtration value from the simplex @@ -69,8 +63,7 @@ class Cech_blocker { bool operator()(Simplex_handle sh) { Point_cloud points; for (auto vertex : sc_ptr_->simplex_vertex_range(sh)) { - points.push_back(Point(cc_ptr_->point_iterator(vertex)->begin(), - cc_ptr_->point_iterator(vertex)->end())); + points.push_back(cc_ptr_->get_point(vertex)); #ifdef DEBUG_TRACES std::cout << "#(" << vertex << ")#"; #endif // DEBUG_TRACES diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp index 8658729b..5ca25db4 100644 --- a/src/Cech_complex/test/test_cech_complex.cpp +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -78,11 +78,8 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(cech_complex_for_doc.max_radius(), max_radius); std::size_t i = 0; for (; i < points.size(); i++) { - BOOST_CHECK(points[i] == *(cech_complex_for_doc.point_iterator(i))); + BOOST_CHECK(points[i] == cech_complex_for_doc.get_point(i)); } -#ifdef GUDHI_DEBUG - BOOST_CHECK_THROW (cech_complex_for_doc.point_iterator(i+1), std::out_of_range); -#endif // GUDHI_DEBUG const int DIMENSION_1 = 1; Simplex_tree st; @@ -137,8 +134,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { Point_cloud points012; for (std::size_t vertex = 0; vertex <= 2; vertex++) { - points012.push_back(Point(cech_complex_for_doc.point_iterator(vertex)->begin(), - cech_complex_for_doc.point_iterator(vertex)->end())); + points012.push_back(cech_complex_for_doc.get_point(vertex)); } std::size_t dimension = points[0].end() - points[0].begin(); Min_sphere ms012(dimension, points012.begin(),points012.end()); @@ -149,12 +145,9 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(f012, std::sqrt(ms012.squared_radius())); Point_cloud points1410; - points1410.push_back(Point(cech_complex_for_doc.point_iterator(1)->begin(), - cech_complex_for_doc.point_iterator(1)->end())); - points1410.push_back(Point(cech_complex_for_doc.point_iterator(4)->begin(), - cech_complex_for_doc.point_iterator(4)->end())); - points1410.push_back(Point(cech_complex_for_doc.point_iterator(10)->begin(), - cech_complex_for_doc.point_iterator(10)->end())); + points1410.push_back(cech_complex_for_doc.get_point(1)); + points1410.push_back(cech_complex_for_doc.get_point(4)); + points1410.push_back(cech_complex_for_doc.get_point(10)); Min_sphere ms1410(dimension, points1410.begin(),points1410.end()); Simplex_tree::Filtration_value f1410 = st2.filtration(st2.find({1, 4, 10})); @@ -163,12 +156,9 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { GUDHI_TEST_FLOAT_EQUALITY_CHECK(f1410, std::sqrt(ms1410.squared_radius())); Point_cloud points469; - points469.push_back(Point(cech_complex_for_doc.point_iterator(4)->begin(), - cech_complex_for_doc.point_iterator(4)->end())); - points469.push_back(Point(cech_complex_for_doc.point_iterator(6)->begin(), - cech_complex_for_doc.point_iterator(6)->end())); - points469.push_back(Point(cech_complex_for_doc.point_iterator(9)->begin(), - cech_complex_for_doc.point_iterator(9)->end())); + points469.push_back(cech_complex_for_doc.get_point(4)); + points469.push_back(cech_complex_for_doc.get_point(6)); + points469.push_back(cech_complex_for_doc.get_point(9)); Min_sphere ms469(dimension, points469.begin(),points469.end()); Simplex_tree::Filtration_value f469 = st2.filtration(st2.find({4, 6, 9})); -- cgit v1.2.3 From f70b243734ccc904f75937b90a90db45203ba8ec Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Tue, 10 Apr 2018 15:03:41 +0000 Subject: Change tparam doc from Chech_complex_blocker git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3367 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 717baf604d7c639eabed28f4ad5639c4eac15dc1 --- src/Cech_complex/include/gudhi/Cech_complex_blocker.h | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index 2ecef9cf..697d2246 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -35,17 +35,17 @@ namespace cech_complex { /** \internal * \class Cech_blocker - * \brief Cech complex blocker. + * \brief Čech complex blocker. * * \ingroup cech_complex * * \details - * Cech blocker is an oracle constructed from a Cech_complex and a simplicial complex. + * Čech blocker is an oracle constructed from a Cech_complex and a simplicial complex. * * \tparam SimplicialComplexForProximityGraph furnishes `Simplex_handle` and `Filtration_value` type definition, * `simplex_vertex_range(Simplex_handle sh)`and `assign_filtration(Simplex_handle sh, Filtration_value filt)` methods. * - * \tparam InputPointRange is required by the pointer on Chech_complex for type definition. + * \tparam Chech_complex is required by the blocker. */ template class Cech_blocker { @@ -56,7 +56,7 @@ class Cech_blocker { using Filtration_value = typename SimplicialComplexForCech::Filtration_value; public: - /** \internal \brief Cech complex blocker operator() - the oracle - assigns the filtration value from the simplex + /** \internal \brief Čech complex blocker operator() - the oracle - assigns the filtration value from the simplex * radius and returns if the simplex expansion must be blocked. * \param[in] sh The Simplex_handle. * \return true if the simplex radius is greater than the Cech_complex max_radius*/ @@ -77,7 +77,7 @@ class Cech_blocker { return (radius > cc_ptr_->max_radius()); } - /** \internal \brief Cech complex blocker constructor. */ + /** \internal \brief Čech complex blocker constructor. */ Cech_blocker(SimplicialComplexForCech* sc_ptr, Cech_complex* cc_ptr) : sc_ptr_(sc_ptr), cc_ptr_(cc_ptr) { -- cgit v1.2.3 From 5fd7f8f63704131228a57c6292743295a25db11e Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Mon, 28 May 2018 15:31:55 +0000 Subject: Code review: ForwardPointRange instead of InputPointRange Point cloud deep copy git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3478 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 29e77a605f85552bc5b31f2907e26b7e5a9da92f --- src/Cech_complex/benchmark/CMakeLists.txt | 4 ++-- src/Cech_complex/include/gudhi/Cech_complex.h | 22 +++++++++------------- 2 files changed, 11 insertions(+), 15 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/benchmark/CMakeLists.txt b/src/Cech_complex/benchmark/CMakeLists.txt index 2a65865b..b7697764 100644 --- a/src/Cech_complex/benchmark/CMakeLists.txt +++ b/src/Cech_complex/benchmark/CMakeLists.txt @@ -2,10 +2,10 @@ cmake_minimum_required(VERSION 2.6) project(Cech_complex_benchmark) # Do not forget to copy test files in current binary dir -#file(COPY "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) +file(COPY "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/) add_executable(cech_complex_benchmark cech_complex_benchmark.cpp) -target_link_libraries(cech_complex_benchmark ${Boost_FILESYSTEM_LIBRARY}) +target_link_libraries(cech_complex_benchmark ${Boost_SYSTEM_LIBRARY} ${Boost_FILESYSTEM_LIBRARY}) if (TBB_FOUND) target_link_libraries(cech_complex_benchmark ${TBB_LIBRARIES}) diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index abad0c21..def46c79 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -48,10 +48,10 @@ namespace cech_complex { * \tparam SimplicialComplexForProximityGraph furnishes `Vertex_handle` and `Filtration_value` type definition required * by `Gudhi::Proximity_graph`. * - * \tparam InputPointRange must be a range for which `std::begin()` and `std::end()` methods return input + * \tparam ForwardPointRange must be a range for which `std::begin()` and `std::end()` methods return input * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. */ -template +template class Cech_complex { private: // Required by compute_proximity_graph @@ -59,8 +59,8 @@ class Cech_complex { using Filtration_value = typename SimplicialComplexForProximityGraph::Filtration_value; using Proximity_graph = Gudhi::Proximity_graph; - // Retrieve Coordinate type from InputPointRange - using Point_from_range_iterator = typename boost::range_const_iterator::type; + // Retrieve Coordinate type from ForwardPointRange + using Point_from_range_iterator = typename boost::range_const_iterator::type; using Point_from_range = typename std::iterator_traits::value_type; using Coordinate_iterator = typename boost::range_const_iterator::type; using Coordinate= typename std::iterator_traits::value_type; @@ -76,19 +76,15 @@ class Cech_complex { * @param[in] points Range of points. * @param[in] max_radius Maximal radius value. * - * \tparam InputPointRange must be a range of Point. Point must be a range of copyable Cartesian coordinates. + * \tparam ForwardPointRange must be a range of Point. Point must be a range of copyable Cartesian coordinates. * */ - Cech_complex(const InputPointRange& points, Filtration_value max_radius) + Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) : max_radius_(max_radius) { // Point cloud deep copy - auto points_begin_itr = std::begin(points); - auto points_end_itr = std::end(points); - - point_cloud_.reserve(points_end_itr - points_begin_itr); - for (auto point_itr = points_begin_itr; point_itr < points_end_itr; point_itr++) { - point_cloud_.push_back(Point(std::begin(*point_itr), std::end(*point_itr))); - } + point_cloud_.reserve(boost::size(points)); + for (auto&& point : points) + point_cloud_.emplace_back(std::begin(point), std::end(point)); cech_skeleton_graph_ = Gudhi::compute_proximity_graph(point_cloud_, -- cgit v1.2.3 From cfe5c6b05435cb7d8cbd1d615e0c402f4a5e1674 Mon Sep 17 00:00:00 2001 From: vrouvrea Date: Tue, 29 May 2018 19:49:30 +0000 Subject: Clang format files git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/cechcomplex_vincent@3488 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 7d1da847f4c39a191afd5d8e56fe34ee79ade495 --- .../benchmark/cech_complex_benchmark.cpp | 58 ++++++++------------ .../example/cech_complex_example_from_points.cpp | 33 ++++++------ .../example/cech_complex_step_by_step.cpp | 51 +++++++----------- src/Cech_complex/include/gudhi/Cech_complex.h | 30 ++++------- .../include/gudhi/Cech_complex_blocker.h | 9 ++-- src/Cech_complex/test/test_cech_complex.cpp | 63 +++++++++++----------- 6 files changed, 104 insertions(+), 140 deletions(-) (limited to 'src/Cech_complex/include') diff --git a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp index 2fa255ed..86314930 100644 --- a/src/Cech_complex/benchmark/cech_complex_benchmark.cpp +++ b/src/Cech_complex/benchmark/cech_complex_benchmark.cpp @@ -29,12 +29,11 @@ #include #include -#include "boost/filesystem.hpp" // includes all needed Boost.Filesystem declarations +#include "boost/filesystem.hpp" // includes all needed Boost.Filesystem declarations #include #include - // Types definition using Simplex_tree = Gudhi::Simplex_tree<>; using Filtration_value = Simplex_tree::Filtration_value; @@ -45,32 +44,31 @@ using Proximity_graph = Gudhi::Proximity_graph; using Rips_complex = Gudhi::rips_complex::Rips_complex; using Cech_complex = Gudhi::cech_complex::Cech_complex; - class Minimal_enclosing_ball_radius { public: // boost::range_value is not SFINAE-friendly so we cannot use it in the return type - template< typename Point > - typename std::iterator_traits::type>::value_type - operator()(const Point& p1, const Point& p2) const { + template + typename std::iterator_traits::type>::value_type operator()( + const Point& p1, const Point& p2) const { // Type def using Point_cloud = std::vector; using Point_iterator = typename Point_cloud::const_iterator; using Coordinate_iterator = typename Point::const_iterator; - using Min_sphere = typename Gudhi::Miniball::Miniball>; + using Min_sphere = + typename Gudhi::Miniball::Miniball>; Point_cloud point_cloud; point_cloud.push_back(p1); point_cloud.push_back(p2); - GUDHI_CHECK((p1.end()-p1.begin()) != (p2.end()-p2.begin()), "inconsistent point dimensions"); - Min_sphere min_sphere(p1.end()-p1.begin(), point_cloud.begin(),point_cloud.end()); + GUDHI_CHECK((p1.end() - p1.begin()) != (p2.end() - p2.begin()), "inconsistent point dimensions"); + Min_sphere min_sphere(p1.end() - p1.begin(), point_cloud.begin(), point_cloud.end()); return std::sqrt(min_sphere.squared_radius()); } }; - -int main(int argc, char * argv[]) { +int main(int argc, char* argv[]) { std::string off_file_points = "tore3D_1307.off"; Filtration_value threshold = 1e20; @@ -79,42 +77,32 @@ int main(int argc, char * argv[]) { Gudhi::Clock euclidean_clock("Gudhi::Euclidean_distance"); // Compute the proximity graph of the points - Proximity_graph euclidean_prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Gudhi::Euclidean_distance()); + Proximity_graph euclidean_prox_graph = Gudhi::compute_proximity_graph( + off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance()); std::cout << euclidean_clock << std::endl; Gudhi::Clock miniball_clock("Minimal_enclosing_ball_radius"); // Compute the proximity graph of the points - Proximity_graph miniball_prox_graph = - Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Minimal_enclosing_ball_radius()); + Proximity_graph miniball_prox_graph = Gudhi::compute_proximity_graph( + off_reader.get_point_cloud(), threshold, Minimal_enclosing_ball_radius()); std::cout << miniball_clock << std::endl; Gudhi::Clock common_miniball_clock("Gudhi::Minimal_enclosing_ball_radius()"); // Compute the proximity graph of the points - Proximity_graph common_miniball_prox_graph = - Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - threshold, - Gudhi::Minimal_enclosing_ball_radius()); + Proximity_graph common_miniball_prox_graph = Gudhi::compute_proximity_graph( + off_reader.get_point_cloud(), threshold, Gudhi::Minimal_enclosing_ball_radius()); std::cout << common_miniball_clock << std::endl; - boost::filesystem::path full_path(boost::filesystem::current_path()); std::cout << "Current path is : " << full_path << std::endl; - - std::cout << "File name;Radius;Rips time;Cech time; Ratio Rips/Cech time;Rips nb simplices;Cech nb simplices;" << std::endl; - boost::filesystem::directory_iterator end_itr; // default construction yields past-the-end - for ( boost::filesystem::directory_iterator itr( boost::filesystem::current_path() ); - itr != end_itr; - ++itr ) - { - if ( ! boost::filesystem::is_directory(itr->status()) ) - { - if ( itr->path().extension() == ".off" ) // see below + std::cout << "File name;Radius;Rips time;Cech time; Ratio Rips/Cech time;Rips nb simplices;Cech nb simplices;" + << std::endl; + boost::filesystem::directory_iterator end_itr; // default construction yields past-the-end + for (boost::filesystem::directory_iterator itr(boost::filesystem::current_path()); itr != end_itr; ++itr) { + if (!boost::filesystem::is_directory(itr->status())) { + if (itr->path().extension() == ".off") // see below { Points_off_reader off_reader(itr->path().string()); Point p0 = off_reader.get_point_cloud()[0]; @@ -123,8 +111,7 @@ int main(int argc, char * argv[]) { std::cout << itr->path().stem() << ";"; std::cout << radius << ";"; Gudhi::Clock rips_clock("Rips computation"); - Rips_complex rips_complex_from_points(off_reader.get_point_cloud(), - radius, + Rips_complex rips_complex_from_points(off_reader.get_point_cloud(), radius, Gudhi::Minimal_enclosing_ball_radius()); Simplex_tree rips_stree; rips_complex_from_points.create_complex(rips_stree, p0.size() - 1); @@ -153,6 +140,5 @@ int main(int argc, char * argv[]) { } } - return 0; } diff --git a/src/Cech_complex/example/cech_complex_example_from_points.cpp b/src/Cech_complex/example/cech_complex_example_from_points.cpp index 2b36e33c..3cc5a4df 100644 --- a/src/Cech_complex/example/cech_complex_example_from_points.cpp +++ b/src/Cech_complex/example/cech_complex_example_from_points.cpp @@ -14,17 +14,17 @@ int main() { using Cech_complex = Gudhi::cech_complex::Cech_complex; Point_cloud points; - points.push_back({1., 0.}); // 0 - points.push_back({0., 1.}); // 1 - points.push_back({2., 1.}); // 2 - points.push_back({3., 2.}); // 3 - points.push_back({0., 3.}); // 4 - points.push_back({3. + std::sqrt(3.), 3.}); // 5 - points.push_back({1., 4.}); // 6 - points.push_back({3., 4.}); // 7 - points.push_back({2., 4. + std::sqrt(3.)}); // 8 - points.push_back({0., 4.}); // 9 - points.push_back({-0.5, 2.}); // 10 + points.push_back({1., 0.}); // 0 + points.push_back({0., 1.}); // 1 + points.push_back({2., 1.}); // 2 + points.push_back({3., 2.}); // 3 + points.push_back({0., 3.}); // 4 + points.push_back({3. + std::sqrt(3.), 3.}); // 5 + points.push_back({1., 4.}); // 6 + points.push_back({3., 4.}); // 7 + points.push_back({2., 4. + std::sqrt(3.)}); // 8 + points.push_back({0., 4.}); // 9 + points.push_back({-0.5, 2.}); // 10 // ---------------------------------------------------------------------------- // Init of a Cech complex from points @@ -37,18 +37,17 @@ int main() { // ---------------------------------------------------------------------------- // Display information about the one skeleton Cech complex // ---------------------------------------------------------------------------- - std::cout << "Cech complex is of dimension " << stree.dimension() << - " - " << stree.num_simplices() << " simplices - " << - stree.num_vertices() << " vertices." << std::endl; + std::cout << "Cech complex is of dimension " << stree.dimension() << " - " << stree.num_simplices() << " simplices - " + << stree.num_vertices() << " vertices." << std::endl; - std::cout << "Iterator on Cech complex simplices in the filtration order, with [filtration value]:" << - std::endl; + std::cout << "Iterator on Cech complex simplices in the filtration order, with [filtration value]:" << std::endl; for (auto f_simplex : stree.filtration_simplex_range()) { std::cout << " ( "; for (auto vertex : stree.simplex_vertex_range(f_simplex)) { std::cout << vertex << " "; } - std::cout << ") -> " << "[" << stree.filtration(f_simplex) << "] "; + std::cout << ") -> " + << "[" << stree.filtration(f_simplex) << "] "; std::cout << std::endl; } return 0; diff --git a/src/Cech_complex/example/cech_complex_step_by_step.cpp b/src/Cech_complex/example/cech_complex_step_by_step.cpp index 760b53dc..d2dc8b65 100644 --- a/src/Cech_complex/example/cech_complex_step_by_step.cpp +++ b/src/Cech_complex/example/cech_complex_step_by_step.cpp @@ -31,7 +31,7 @@ #include #include -#include // infinity +#include // infinity #include // for pair #include @@ -55,7 +55,8 @@ class Cech_blocker { using Point_cloud = std::vector; using Point_iterator = Point_cloud::const_iterator; using Coordinate_iterator = Point::const_iterator; - using Min_sphere = Gudhi::Miniball::Miniball >; + using Min_sphere = Gudhi::Miniball::Miniball>; + public: bool operator()(Simplex_handle sh) { std::vector points; @@ -73,11 +74,10 @@ class Cech_blocker { return (radius > max_radius_); } Cech_blocker(Simplex_tree& simplex_tree, Filtration_value max_radius, const std::vector& point_cloud) - : simplex_tree_(simplex_tree), - max_radius_(max_radius), - point_cloud_(point_cloud) { + : simplex_tree_(simplex_tree), max_radius_(max_radius), point_cloud_(point_cloud) { dimension_ = point_cloud_[0].size(); } + private: Simplex_tree simplex_tree_; Filtration_value max_radius_; @@ -85,14 +85,9 @@ class Cech_blocker { int dimension_; }; +void program_options(int argc, char* argv[], std::string& off_file_points, Filtration_value& max_radius, int& dim_max); -void program_options(int argc, char * argv[] - , std::string & off_file_points - , Filtration_value & max_radius - , int & dim_max); - - -int main(int argc, char * argv[]) { +int main(int argc, char* argv[]) { std::string off_file_points; Filtration_value max_radius; int dim_max; @@ -103,8 +98,7 @@ int main(int argc, char * argv[]) { Points_off_reader off_reader(off_file_points); // Compute the proximity graph of the points - Proximity_graph prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), - max_radius, + Proximity_graph prox_graph = Gudhi::compute_proximity_graph(off_reader.get_point_cloud(), max_radius, Gudhi::Minimal_enclosing_ball_radius()); // Construct the Rips complex in a Simplex Tree @@ -125,7 +119,8 @@ int main(int argc, char * argv[]) { std::cout << "* The complex contains " << st.num_simplices() << " simplices - dimension=" << st.dimension() << "\n"; std::cout << "* Iterator on Simplices in the filtration, with [filtration value]:\n"; for (auto f_simplex : st.filtration_simplex_range()) { - std::cout << " " << "[" << st.filtration(f_simplex) << "] "; + std::cout << " " + << "[" << st.filtration(f_simplex) << "] "; for (auto vertex : st.simplex_vertex_range(f_simplex)) { std::cout << static_cast(vertex) << " "; } @@ -136,24 +131,19 @@ int main(int argc, char * argv[]) { return 0; } -void program_options(int argc, char * argv[] - , std::string & off_file_points - , Filtration_value & max_radius - , int & dim_max) { +void program_options(int argc, char* argv[], std::string& off_file_points, Filtration_value& max_radius, int& dim_max) { namespace po = boost::program_options; po::options_description hidden("Hidden options"); - hidden.add_options() - ("input-file", po::value(&off_file_points), - "Name of an OFF file containing a point set.\n"); + hidden.add_options()("input-file", po::value(&off_file_points), + "Name of an OFF file containing a point set.\n"); po::options_description visible("Allowed options", 100); - visible.add_options() - ("help,h", "produce help message") - ("max-radius,r", - po::value(&max_radius)->default_value(std::numeric_limits::infinity()), - "Maximal length of an edge for the Rips complex construction.") - ("cpx-dimension,d", po::value(&dim_max)->default_value(1), - "Maximal dimension of the Rips complex we want to compute."); + visible.add_options()("help,h", "produce help message")( + "max-radius,r", + po::value(&max_radius)->default_value(std::numeric_limits::infinity()), + "Maximal length of an edge for the Rips complex construction.")( + "cpx-dimension,d", po::value(&dim_max)->default_value(1), + "Maximal dimension of the Rips complex we want to compute."); po::positional_options_description pos; pos.add("input-file", 1); @@ -162,8 +152,7 @@ void program_options(int argc, char * argv[] all.add(visible).add(hidden); po::variables_map vm; - po::store(po::command_line_parser(argc, argv). - options(all).positional(pos).run(), vm); + po::store(po::command_line_parser(argc, argv).options(all).positional(pos).run(), vm); po::notify(vm); if (vm.count("help") || !vm.count("input-file")) { diff --git a/src/Cech_complex/include/gudhi/Cech_complex.h b/src/Cech_complex/include/gudhi/Cech_complex.h index def46c79..f4fb4288 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex.h +++ b/src/Cech_complex/include/gudhi/Cech_complex.h @@ -38,9 +38,9 @@ namespace cech_complex { /** * \class Cech_complex * \brief Cech complex data structure. - * + * * \ingroup cech_complex - * + * * \details * The data structure is a proximity graph, containing edges when the edge length is less or equal * to a given max_radius. Edge length is computed from `Gudhi::Minimal_enclosing_ball_radius` distance function. @@ -51,7 +51,7 @@ namespace cech_complex { * \tparam ForwardPointRange must be a range for which `std::begin()` and `std::end()` methods return input * iterators on a point. `std::begin()` and `std::end()` methods are also required for a point. */ -template +template class Cech_complex { private: // Required by compute_proximity_graph @@ -63,7 +63,7 @@ class Cech_complex { using Point_from_range_iterator = typename boost::range_const_iterator::type; using Point_from_range = typename std::iterator_traits::value_type; using Coordinate_iterator = typename boost::range_const_iterator::type; - using Coordinate= typename std::iterator_traits::value_type; + using Coordinate = typename std::iterator_traits::value_type; public: // Point and Point_cloud type definition @@ -79,17 +79,13 @@ class Cech_complex { * \tparam ForwardPointRange must be a range of Point. Point must be a range of copyable Cartesian coordinates. * */ - Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) - : max_radius_(max_radius) { + Cech_complex(const ForwardPointRange& points, Filtration_value max_radius) : max_radius_(max_radius) { // Point cloud deep copy point_cloud_.reserve(boost::size(points)); - for (auto&& point : points) - point_cloud_.emplace_back(std::begin(point), std::end(point)); + for (auto&& point : points) point_cloud_.emplace_back(std::begin(point), std::end(point)); - cech_skeleton_graph_ = - Gudhi::compute_proximity_graph(point_cloud_, - max_radius_, - Gudhi::Minimal_enclosing_ball_radius()); + cech_skeleton_graph_ = Gudhi::compute_proximity_graph( + point_cloud_, max_radius_, Gudhi::Minimal_enclosing_ball_radius()); } /** \brief Initializes the simplicial complex from the proximity graph and expands it until a given maximal @@ -100,7 +96,7 @@ class Cech_complex { * @exception std::invalid_argument In debug mode, if `complex.num_vertices()` does not return 0. * */ - template + template void create_complex(SimplicialComplexForCechComplex& complex, int dim_max) { GUDHI_CHECK(complex.num_vertices() == 0, std::invalid_argument("Cech_complex::create_complex - simplicial complex is not empty")); @@ -113,16 +109,12 @@ class Cech_complex { } /** @return max_radius value given at construction. */ - Filtration_value max_radius() const { - return max_radius_; - } + Filtration_value max_radius() const { return max_radius_; } /** @param[in] vertex Point position in the range. * @return The point. */ - const Point& get_point(Vertex_handle vertex) const{ - return point_cloud_[vertex]; - } + const Point& get_point(Vertex_handle vertex) const { return point_cloud_[vertex]; } private: Proximity_graph cech_skeleton_graph_; diff --git a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h index 697d2246..b0d347b1 100644 --- a/src/Cech_complex/include/gudhi/Cech_complex_blocker.h +++ b/src/Cech_complex/include/gudhi/Cech_complex_blocker.h @@ -70,18 +70,15 @@ class Cech_blocker { } Filtration_value radius = Gudhi::Minimal_enclosing_ball_radius()(points); #ifdef DEBUG_TRACES - if (radius > cc_ptr_->max_radius()) - std::cout << "radius > max_radius => expansion is blocked\n"; + if (radius > cc_ptr_->max_radius()) std::cout << "radius > max_radius => expansion is blocked\n"; #endif // DEBUG_TRACES sc_ptr_->assign_filtration(sh, radius); return (radius > cc_ptr_->max_radius()); } /** \internal \brief Čech complex blocker constructor. */ - Cech_blocker(SimplicialComplexForCech* sc_ptr, Cech_complex* cc_ptr) - : sc_ptr_(sc_ptr), - cc_ptr_(cc_ptr) { - } + Cech_blocker(SimplicialComplexForCech* sc_ptr, Cech_complex* cc_ptr) : sc_ptr_(sc_ptr), cc_ptr_(cc_ptr) {} + private: SimplicialComplexForCech* sc_ptr_; Cech_complex* cc_ptr_; diff --git a/src/Cech_complex/test/test_cech_complex.cpp b/src/Cech_complex/test/test_cech_complex.cpp index 5b35735b..9039169c 100644 --- a/src/Cech_complex/test/test_cech_complex.cpp +++ b/src/Cech_complex/test/test_cech_complex.cpp @@ -28,7 +28,7 @@ #include #include #include -#include // std::max +#include // std::max #include // to construct Cech_complex from a OFF file of points @@ -57,21 +57,21 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { // // ---------------------------------------------------------------------------- Point_cloud points; - points.push_back({1., 0.}); // 0 - points.push_back({0., 1.}); // 1 - points.push_back({2., 1.}); // 2 - points.push_back({3., 2.}); // 3 - points.push_back({0., 3.}); // 4 - points.push_back({3. + std::sqrt(3.), 3.}); // 5 - points.push_back({1., 4.}); // 6 - points.push_back({3., 4.}); // 7 - points.push_back({2., 4. + std::sqrt(3.)}); // 8 - points.push_back({0., 4.}); // 9 - points.push_back({-0.5, 2.}); // 10 + points.push_back({1., 0.}); // 0 + points.push_back({0., 1.}); // 1 + points.push_back({2., 1.}); // 2 + points.push_back({3., 2.}); // 3 + points.push_back({0., 3.}); // 4 + points.push_back({3. + std::sqrt(3.), 3.}); // 5 + points.push_back({1., 4.}); // 6 + points.push_back({3., 4.}); // 7 + points.push_back({2., 4. + std::sqrt(3.)}); // 8 + points.push_back({0., 4.}); // 9 + points.push_back({-0.5, 2.}); // 10 Filtration_value max_radius = 1.0; - std::cout << "========== NUMBER OF POINTS = " << points.size() << " - Cech max_radius = " << - max_radius << "==========" << std::endl; + std::cout << "========== NUMBER OF POINTS = " << points.size() << " - Cech max_radius = " << max_radius + << "==========" << std::endl; Cech_complex cech_complex_for_doc(points, max_radius); @@ -108,24 +108,25 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { std::cout << vertex << ","; vp.push_back(points.at(vertex)); } - std::cout << ") - distance =" << Gudhi::Minimal_enclosing_ball_radius()(vp.at(0), vp.at(1)) << - " - filtration =" << st.filtration(f_simplex) << std::endl; + std::cout << ") - distance =" << Gudhi::Minimal_enclosing_ball_radius()(vp.at(0), vp.at(1)) + << " - filtration =" << st.filtration(f_simplex) << std::endl; BOOST_CHECK(vp.size() == 2); - GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), Gudhi::Minimal_enclosing_ball_radius()(vp.at(0), vp.at(1))); + GUDHI_TEST_FLOAT_EQUALITY_CHECK(st.filtration(f_simplex), + Gudhi::Minimal_enclosing_ball_radius()(vp.at(0), vp.at(1))); } } const int DIMENSION_2 = 2; #ifdef GUDHI_DEBUG - BOOST_CHECK_THROW (cech_complex_for_doc.create_complex(st, DIMENSION_2), std::invalid_argument); + BOOST_CHECK_THROW(cech_complex_for_doc.create_complex(st, DIMENSION_2), std::invalid_argument); #endif Simplex_tree st2; cech_complex_for_doc.create_complex(st2, DIMENSION_2); std::cout << "st2.dimension()=" << st2.dimension() << std::endl; BOOST_CHECK(st2.dimension() == DIMENSION_2); - + std::cout << "st2.num_vertices()=" << st2.num_vertices() << std::endl; BOOST_CHECK(st2.num_vertices() == NUMBER_OF_VERTICES); @@ -137,7 +138,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { points012.push_back(cech_complex_for_doc.get_point(vertex)); } std::size_t dimension = points[0].end() - points[0].begin(); - Min_sphere ms012(dimension, points012.begin(),points012.end()); + Min_sphere ms012(dimension, points012.begin(), points012.end()); Simplex_tree::Filtration_value f012 = st2.filtration(st2.find({0, 1, 2})); std::cout << "f012= " << f012 << " | ms012_radius= " << std::sqrt(ms012.squared_radius()) << std::endl; @@ -148,7 +149,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { points1410.push_back(cech_complex_for_doc.get_point(1)); points1410.push_back(cech_complex_for_doc.get_point(4)); points1410.push_back(cech_complex_for_doc.get_point(10)); - Min_sphere ms1410(dimension, points1410.begin(),points1410.end()); + Min_sphere ms1410(dimension, points1410.begin(), points1410.end()); Simplex_tree::Filtration_value f1410 = st2.filtration(st2.find({1, 4, 10})); std::cout << "f1410= " << f1410 << " | ms1410_radius= " << std::sqrt(ms1410.squared_radius()) << std::endl; @@ -159,7 +160,7 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { points469.push_back(cech_complex_for_doc.get_point(4)); points469.push_back(cech_complex_for_doc.get_point(6)); points469.push_back(cech_complex_for_doc.get_point(9)); - Min_sphere ms469(dimension, points469.begin(),points469.end()); + Min_sphere ms469(dimension, points469.begin(), points469.end()); Simplex_tree::Filtration_value f469 = st2.filtration(st2.find({4, 6, 9})); std::cout << "f469= " << f469 << " | ms469_radius= " << std::sqrt(ms469.squared_radius()) << std::endl; @@ -168,7 +169,6 @@ BOOST_AUTO_TEST_CASE(Cech_complex_for_documentation) { BOOST_CHECK((st2.find({6, 7, 8}) == st2.null_simplex())); BOOST_CHECK((st2.find({3, 5, 7}) == st2.null_simplex())); - } BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { @@ -176,13 +176,13 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { // Init of a list of points // ---------------------------------------------------------------------------- Point_cloud points; - std::vector coords = { 0.0, 0.0, 0.0, 1.0 }; + std::vector coords = {0.0, 0.0, 0.0, 1.0}; points.push_back(Point(coords.begin(), coords.end())); - coords = { 0.0, 0.0, 1.0, 0.0 }; + coords = {0.0, 0.0, 1.0, 0.0}; points.push_back(Point(coords.begin(), coords.end())); - coords = { 0.0, 1.0, 0.0, 0.0 }; + coords = {0.0, 1.0, 0.0, 0.0}; points.push_back(Point(coords.begin(), coords.end())); - coords = { 1.0, 0.0, 0.0, 0.0 }; + coords = {1.0, 0.0, 0.0, 0.0}; points.push_back(Point(coords.begin(), coords.end())); // ---------------------------------------------------------------------------- @@ -204,7 +204,8 @@ BOOST_AUTO_TEST_CASE(Cech_complex_from_points) { for (auto vertex : st.simplex_vertex_range(f_simplex)) { std::cout << vertex << " "; } - std::cout << ") -> " << "[" << st.filtration(f_simplex) << "] "; + std::cout << ") -> " + << "[" << st.filtration(f_simplex) << "] "; std::cout << std::endl; } BOOST_CHECK(num_simplices == 15); @@ -247,8 +248,8 @@ BOOST_AUTO_TEST_CASE(Cech_create_complex_throw) { // ---------------------------------------------------------------------------- std::string off_file_name("alphacomplexdoc.off"); double max_radius = 12.0; - std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech max_radius=" << - max_radius << "==========" << std::endl; + std::cout << "========== OFF FILE NAME = " << off_file_name << " - Cech max_radius=" << max_radius + << "==========" << std::endl; Gudhi::Points_off_reader off_reader(off_file_name); Cech_complex cech_complex_from_file(off_reader.get_point_cloud(), max_radius); @@ -258,6 +259,6 @@ BOOST_AUTO_TEST_CASE(Cech_create_complex_throw) { stree.insert_simplex_and_subfaces(simplex); std::cout << "Check exception throw in debug mode" << std::endl; // throw excpt because stree is not empty - BOOST_CHECK_THROW (cech_complex_from_file.create_complex(stree, 1), std::invalid_argument); + BOOST_CHECK_THROW(cech_complex_from_file.create_complex(stree, 1), std::invalid_argument); } #endif -- cgit v1.2.3