From 3c65ebebc4bfc32ec1b436c3d99a1f97a94b60d7 Mon Sep 17 00:00:00 2001 From: skachano Date: Mon, 20 Jun 2016 13:24:52 +0000 Subject: Renamed the two landmarking functions git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/subsampling_and_spatialsearching@1314 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 5025e0aff02306d61fa809eac10b7db27947b120 --- src/Subsampling/test/landmarking.cpp | 8 +- .../example/witness_complex_from_file.cpp | 4 +- .../example/witness_complex_sphere.cpp | 4 +- .../gudhi/Landmark_choice_by_furthest_point.h | 105 --------------------- .../gudhi/Landmark_choice_by_random_point.h | 96 ------------------- .../test/witness_complex_points.cpp | 5 +- 6 files changed, 10 insertions(+), 212 deletions(-) delete mode 100644 src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h delete mode 100644 src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h (limited to 'src') diff --git a/src/Subsampling/test/landmarking.cpp b/src/Subsampling/test/landmarking.cpp index 3131c798..a2c85349 100644 --- a/src/Subsampling/test/landmarking.cpp +++ b/src/Subsampling/test/landmarking.cpp @@ -2,8 +2,8 @@ // # define TBB_USE_THREADING_TOOL // #endif -#include -#include +#include +#include #include #include @@ -35,13 +35,13 @@ int main() { std::vector landmarks; - Gudhi::landmark_choice_by_random_point(vect, 5, std::back_inserter(landmarks)); + Gudhi::pick_random_points(vect, 5, std::back_inserter(landmarks)); std::cout << "landmark vector contains: "; for (auto l: landmarks) std::cout << l << "\n"; landmarks.clear(); K k; - Gudhi::landmark_choice_by_farthest_point(k, vect, 16, std::back_inserter(landmarks)); + Gudhi::choose_by_farthest_point(k, vect, 16, std::back_inserter(landmarks)); } diff --git a/src/Witness_complex/example/witness_complex_from_file.cpp b/src/Witness_complex/example/witness_complex_from_file.cpp index fbc3cf1d..17b63dcf 100644 --- a/src/Witness_complex/example/witness_complex_from_file.cpp +++ b/src/Witness_complex/example/witness_complex_from_file.cpp @@ -26,7 +26,7 @@ #include #include #include -#include +#include #include #include @@ -87,7 +87,7 @@ int main(int argc, char * const argv[]) { // Choose landmarks start = clock(); std::vector > knn; - Gudhi::landmark_choice_by_random_point(point_vector, 100, std::back_inserter(landmarks)); + Gudhi::pick_random_points(point_vector, 100, std::back_inserter(landmarks)); Gudhi::witness_complex::construct_closest_landmark_table(point_vector, landmarks, knn); end = clock(); std::cout << "Landmark choice for " << nbL << " landmarks took " diff --git a/src/Witness_complex/example/witness_complex_sphere.cpp b/src/Witness_complex/example/witness_complex_sphere.cpp index 9cf2f119..495a5895 100644 --- a/src/Witness_complex/example/witness_complex_sphere.cpp +++ b/src/Witness_complex/example/witness_complex_sphere.cpp @@ -28,7 +28,7 @@ #include #include #include -#include +#include #include #include @@ -76,7 +76,7 @@ int main(int argc, char * const argv[]) { // Choose landmarks start = clock(); std::vector > knn; - Gudhi::landmark_choice_by_random_point(point_vector, 100, std::back_inserter(landmarks)); + Gudhi::pick_random_points(point_vector, 100, std::back_inserter(landmarks)); Gudhi::witness_complex::construct_closest_landmark_table(point_vector, landmarks, knn); // Compute witness complex diff --git a/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h b/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h deleted file mode 100644 index df93155b..00000000 --- a/src/Witness_complex/include/gudhi/Landmark_choice_by_furthest_point.h +++ /dev/null @@ -1,105 +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): Siargey Kachanovich - * - * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) - * - * 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 LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ -#define LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ - -#include - -#include // for numeric_limits<> -#include -#include // for sort -#include - -namespace Gudhi { - -namespace witness_complex { - - typedef std::vector typeVectorVertex; - - /** - * \ingroup witness_complex - * \brief Landmark choice strategy by iteratively adding the furthest witness from the - * current landmark set as the new landmark. - * \details It chooses nbL landmarks from a random access range `points` and - * writes {witness}*{closest landmarks} matrix in `knn`. - * - * The type KNearestNeighbors can be seen as - * Witness_range>, where - * Witness_range and Closest_landmark_range are random access ranges - * - */ - - template - void landmark_choice_by_furthest_point(Point_random_access_range const &points, - int nbL, - KNearestNeighbours &knn) { - int nb_points = boost::size(points); - assert(nb_points >= nbL); - // distance matrix witness x landmarks - std::vector> wit_land_dist(nb_points, std::vector()); - // landmark list - typeVectorVertex chosen_landmarks; - - knn = KNearestNeighbours(nb_points, std::vector()); - int current_number_of_landmarks = 0; // counter for landmarks - double curr_max_dist = 0; // used for defining the furhest point from L - const double infty = std::numeric_limits::infinity(); // infinity (see next entry) - std::vector< double > dist_to_L(nb_points, infty); // vector of current distances to L from points - - // TODO(SK) Consider using rand_r(...) instead of rand(...) for improved thread safety - // or better yet std::uniform_int_distribution - int rand_int = rand() % nb_points; - int curr_max_w = rand_int; // For testing purposes a pseudo-random number is used here - - for (current_number_of_landmarks = 0; current_number_of_landmarks != nbL; current_number_of_landmarks++) { - // curr_max_w at this point is the next landmark - chosen_landmarks.push_back(curr_max_w); - unsigned i = 0; - for (auto& p : points) { - double curr_dist = euclidean_distance(p, *(std::begin(points) + chosen_landmarks[current_number_of_landmarks])); - wit_land_dist[i].push_back(curr_dist); - knn[i].push_back(current_number_of_landmarks); - if (curr_dist < dist_to_L[i]) - dist_to_L[i] = curr_dist; - ++i; - } - curr_max_dist = 0; - for (i = 0; i < dist_to_L.size(); i++) - if (dist_to_L[i] > curr_max_dist) { - curr_max_dist = dist_to_L[i]; - curr_max_w = i; - } - } - for (int i = 0; i < nb_points; ++i) - std::sort(std::begin(knn[i]), - std::end(knn[i]), - [&wit_land_dist, i](int a, int b) { - return wit_land_dist[i][a] < wit_land_dist[i][b]; }); - } - -} // namespace witness_complex - -} // namespace Gudhi - -#endif // LANDMARK_CHOICE_BY_FURTHEST_POINT_H_ diff --git a/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h b/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h deleted file mode 100644 index ebf6aad1..00000000 --- a/src/Witness_complex/include/gudhi/Landmark_choice_by_random_point.h +++ /dev/null @@ -1,96 +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): Siargey Kachanovich - * - * Copyright (C) 2015 INRIA Sophia Antipolis-Méditerranée (France) - * - * 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 LANDMARK_CHOICE_BY_RANDOM_POINT_H_ -#define LANDMARK_CHOICE_BY_RANDOM_POINT_H_ - -#include - -#include // for priority_queue<> -#include // for pair<> -#include -#include -#include - -namespace Gudhi { - -namespace witness_complex { - - /** - * \ingroup witness_complex - * \brief Landmark choice strategy by taking random vertices for landmarks. - * \details It chooses nbL distinct landmarks from a random access range `points` - * and outputs a matrix {witness}*{closest landmarks} in knn. - * - * The type KNearestNeighbors can be seen as - * Witness_range>, where - * Witness_range and Closest_landmark_range are random access ranges and - * Vertex_handle is the label type of a vertex in a simplicial complex. - * Closest_landmark_range needs to have push_back operation. - */ - - template - void landmark_choice_by_random_point(Point_random_access_range const &points, - int nbL, - KNearestNeighbours &knn) { - int nbP = boost::size(points); - assert(nbP >= nbL); - std::set landmarks; - int current_number_of_landmarks = 0; // counter for landmarks - - // TODO(SK) Consider using rand_r(...) instead of rand(...) for improved thread safety - int chosen_landmark = rand() % nbP; - for (current_number_of_landmarks = 0; current_number_of_landmarks != nbL; current_number_of_landmarks++) { - while (landmarks.find(chosen_landmark) != landmarks.end()) - chosen_landmark = rand() % nbP; - landmarks.insert(chosen_landmark); - } - - int dim = boost::size(*std::begin(points)); - typedef std::pair dist_i; - typedef bool (*comp)(dist_i, dist_i); - knn = KNearestNeighbours(nbP); - for (int points_i = 0; points_i < nbP; points_i++) { - std::priority_queue, comp> l_heap([](dist_i j1, dist_i j2) { - return j1.first > j2.first; - }); - std::set::iterator landmarks_it; - int landmarks_i = 0; - for (landmarks_it = landmarks.begin(), landmarks_i = 0; landmarks_it != landmarks.end(); - ++landmarks_it, landmarks_i++) { - dist_i dist = std::make_pair(euclidean_distance(points[points_i], points[*landmarks_it]), landmarks_i); - l_heap.push(dist); - } - for (int i = 0; i < dim + 1; i++) { - dist_i dist = l_heap.top(); - knn[points_i].push_back(dist.second); - l_heap.pop(); - } - } - } - -} // namespace witness_complex - -} // namespace Gudhi - -#endif // LANDMARK_CHOICE_BY_RANDOM_POINT_H_ diff --git a/src/Witness_complex/test/witness_complex_points.cpp b/src/Witness_complex/test/witness_complex_points.cpp index c0006142..596152f4 100644 --- a/src/Witness_complex/test/witness_complex_points.cpp +++ b/src/Witness_complex/test/witness_complex_points.cpp @@ -28,8 +28,7 @@ #include #include #include -#include -#include +#include #include #include @@ -51,7 +50,7 @@ BOOST_AUTO_TEST_CASE(witness_complex_points) { bool b_print_output = false; // First test: random choice Simplex_tree complex1; - Gudhi::landmark_choice_by_random_point(points, 100, std::back_inserter(landmarks)); + Gudhi::pick_random_points(points, 100, std::back_inserter(landmarks)); Gudhi::witness_complex::construct_closest_landmark_table(points, landmarks, knn); assert(!knn.empty()); WitnessComplex witnessComplex1(knn, 100, 3, complex1); -- cgit v1.2.3