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authorskachano <skachano@636b058d-ea47-450e-bf9e-a15bfbe3eedb>2015-04-27 16:23:54 +0000
committerskachano <skachano@636b058d-ea47-450e-bf9e-a15bfbe3eedb>2015-04-27 16:23:54 +0000
commita99d289c4f37766bc262baa980284fa1a9816d42 (patch)
tree0f7c456c7b06072765b25fe2dc7d7f75c36fcec1
parenteaedaf52122a397f35fb75df93f83ae9ffdceb7c (diff)
Added the file for knn landmarks (no CGAL include yet). New algorithm for landmark selection: now 10 times faster!
git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/witness@580 636b058d-ea47-450e-bf9e-a15bfbe3eedb Former-commit-id: 9de270bd67ac33fd1079de7692dd8974441db606
-rw-r--r--src/Witness_complex/example/CMakeLists.txt10
-rw-r--r--src/Witness_complex/example/witness_complex_from_file.cpp4
-rw-r--r--src/Witness_complex/example/witness_complex_from_off.cpp4
-rw-r--r--src/Witness_complex/example/witness_complex_knn_landmarks.cpp161
-rw-r--r--src/Witness_complex/include/gudhi/Witness_complex.h176
5 files changed, 303 insertions, 52 deletions
diff --git a/src/Witness_complex/example/CMakeLists.txt b/src/Witness_complex/example/CMakeLists.txt
index 14d23551..fa594de7 100644
--- a/src/Witness_complex/example/CMakeLists.txt
+++ b/src/Witness_complex/example/CMakeLists.txt
@@ -14,9 +14,9 @@ project(GUDHIWitnessComplex)
add_executable ( simple_witness_complex simple_witness_complex.cpp )
add_test(simple_witness_complex ${CMAKE_CURRENT_BINARY_DIR}/simple_witness_complex)
- #add_executable( witness_complex_from_file witness_complex_from_file.cpp )
+ add_executable( witness_complex_from_file witness_complex_from_file.cpp )
#target_link_libraries(witness_complex_from_file ${EIGEN3_LIBRARIES} ${CGAL_LIBRARY})
- #add_test( witness_complex_from_bunny &{CMAKE_CURRENT_BINARY_DIR}/witness_complex_from_file ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100)
+ add_test( witness_complex_from_bunny &{CMAKE_CURRENT_BINARY_DIR}/witness_complex_from_file ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100)
add_executable( witness_complex_from_off witness_complex_from_off.cpp )
@@ -35,7 +35,7 @@ if(GMP_FOUND AND CGAL_FOUND)
INCLUDE_DIRECTORIES(${EIGEN3_INCLUDE_DIRS})
INCLUDE_DIRECTORIES(${GMP_INCLUDE_DIR})
INCLUDE_DIRECTORIES(${CGAL_INCLUDE_DIRS})
- add_executable (witness_complex_from_file witness_complex_from_file.cpp )
- target_link_libraries(witness_complex_from_file ${GMP_LIBRARIES} ${EIGEN3_LIBRARIES} ${CGAL_LIBRARY})
- add_test(witness_complex_from_file ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_from_file ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100)
+ add_executable (witness_complex_knn_landmarks witness_complex_knn_landmarks.cpp )
+ target_link_libraries(witness_complex_knn_landmarks ${EIGEN3_LIBRARIES} ${CGAL_LIBRARY})
+ add_test(witness_complex_knn_landmarks ${CMAKE_CURRENT_BINARY_DIR}/witness_complex_knn_landmarks ${CMAKE_SOURCE_DIR}/data/points/bunny_5000 100)
endif()
diff --git a/src/Witness_complex/example/witness_complex_from_file.cpp b/src/Witness_complex/example/witness_complex_from_file.cpp
index cf09899b..b842574b 100644
--- a/src/Witness_complex/example/witness_complex_from_file.cpp
+++ b/src/Witness_complex/example/witness_complex_from_file.cpp
@@ -109,9 +109,11 @@ int main (int argc, char * const argv[])
witnessComplex.setNbL(nbL);
// witnessComplex.witness_complex_from_points(point_vector);
std::vector<std::vector< int > > WL;
+ std::set<int> L;
start = clock();
//witnessComplex.landmark_choice_by_furthest_points(point_vector, point_vector.size(), WL);
- witnessComplex.landmark_choice_by_random_points(point_vector, point_vector.size(), WL);
+ witnessComplex.landmark_choice_by_random_points(point_vector, point_vector.size(), L);
+ witnessComplex.nearest_landmarks(point_vector,L,WL);
end = clock();
std::cout << "Landmark choice took "
<< (double)(end-start)/CLOCKS_PER_SEC << " s. \n";
diff --git a/src/Witness_complex/example/witness_complex_from_off.cpp b/src/Witness_complex/example/witness_complex_from_off.cpp
index 04d4e601..948f09a8 100644
--- a/src/Witness_complex/example/witness_complex_from_off.cpp
+++ b/src/Witness_complex/example/witness_complex_from_off.cpp
@@ -148,9 +148,11 @@ int main (int argc, char * const argv[])
witnessComplex.setNbL(nbL);
// witnessComplex.witness_complex_from_points(point_vector);
std::vector<std::vector< int > > WL;
+ std::set<int> L;
start = clock();
//witnessComplex.landmark_choice_by_furthest_points(point_vector, point_vector.size(), WL);
- witnessComplex.landmark_choice_by_random_points(point_vector, point_vector.size(), WL);
+ witnessComplex.landmark_choice_by_random_points(point_vector, point_vector.size(), L);
+ witnessComplex.nearest_landmarks(point_vector,L,WL);
end = clock();
std::cout << "Landmark choice took "
<< (double)(end-start)/CLOCKS_PER_SEC << " s. \n";
diff --git a/src/Witness_complex/example/witness_complex_knn_landmarks.cpp b/src/Witness_complex/example/witness_complex_knn_landmarks.cpp
new file mode 100644
index 00000000..2003f218
--- /dev/null
+++ b/src/Witness_complex/example/witness_complex_knn_landmarks.cpp
@@ -0,0 +1,161 @@
+/* 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 <http://www.gnu.org/licenses/>.
+ */
+
+#include <iostream>
+#include <fstream>
+#include <ctime>
+
+#include <sys/types.h>
+#include <sys/stat.h>
+//#include <stdlib.h>
+
+//#include "gudhi/graph_simplicial_complex.h"
+#include "gudhi/Witness_complex.h"
+#include "gudhi/reader_utils.h"
+//#include <boost/filesystem.hpp>
+
+//#include <CGAL/Delaunay_triangulation.h>
+//#include <CGAL/Epick_d.h>
+#include <CGAL/K_neighbor_search.h>
+
+using namespace Gudhi;
+//using namespace boost::filesystem;
+
+typedef std::vector< Vertex_handle > typeVectorVertex;
+typedef std::vector< std::vector <double> > Point_Vector;
+//typedef std::pair<typeVectorVertex, Filtration_value> typeSimplex;
+//typedef std::pair< Simplex_tree<>::Simplex_handle, bool > typePairSimplexBool;
+
+
+/**
+ * \brief Customized version of read_points
+ * which takes into account a possible nbP first line
+ *
+ */
+inline void
+read_points_cust ( std::string file_name , std::vector< std::vector< double > > & points)
+{
+ std::ifstream in_file (file_name.c_str(),std::ios::in);
+ if(!in_file.is_open())
+ {
+ std::cerr << "Unable to open file " << file_name << std::endl;
+ return;
+ }
+ std::string line;
+ double x;
+ while( getline ( in_file , line ) )
+ {
+ std::vector< double > point;
+ std::istringstream iss( line );
+ while(iss >> x) { point.push_back(x); }
+ if (point.size() != 1)
+ points.push_back(point);
+ }
+ in_file.close();
+}
+
+void write_wl( std::string file_name, std::vector< std::vector <int> > & WL)
+{
+ std::ofstream ofs (file_name, std::ofstream::out);
+ for (auto w : WL)
+ {
+ for (auto l: w)
+ ofs << l << " ";
+ ofs << "\n";
+ }
+ ofs.close();
+}
+
+int main (int argc, char * const argv[])
+{
+ if (argc != 3)
+ {
+ std::cerr << "Usage: " << argv[0]
+ << " path_to_point_file nbL \n";
+ return 0;
+ }
+ /*
+ boost::filesystem::path p;
+
+ for (; argc > 2; --argc, ++argv)
+ p /= argv[1];
+ */
+ std::string file_name = argv[1];
+ int nbL = atoi(argv[2]);
+
+ clock_t start, end;
+ //Construct the Simplex Tree
+ Witness_complex<> witnessComplex;
+
+ std::cout << "Let the carnage begin!\n";
+ Point_Vector point_vector;
+ read_points_cust(file_name, point_vector);
+ //std::cout << "Successfully read the points\n";
+ witnessComplex.setNbL(nbL);
+ // witnessComplex.witness_complex_from_points(point_vector);
+ std::vector<std::vector< int > > WL;
+ std::set<int> L;
+ int nbP = point_vector.size();
+ start = clock();
+ //witnessComplex.landmark_choice_by_furthest_points(point_vector, point_vector.size(), WL);
+ witnessComplex.landmark_choice_by_random_points(point_vector, nbP, L);
+ witnessComplex.nearest_landmarks(point_vector,L,WL);
+ end = clock();
+ std::cout << "Landmark choice took "
+ << (double)(end-start)/CLOCKS_PER_SEC << " s. \n";
+ // Write the WL matrix in a file
+ mkdir("output", S_IRWXU);
+ const size_t last_slash_idx = file_name.find_last_of("/");
+ if (std::string::npos != last_slash_idx)
+ {
+ file_name.erase(0, last_slash_idx + 1);
+ }
+ std::string out_file = "output/"+file_name+"_"+argv[2]+".wl";
+ //write_wl(out_file,WL);
+ start = clock();
+ witnessComplex.witness_complex(WL);
+ //
+ end = clock();
+ std::cout << "Howdy world! The process took "
+ << (double)(end-start)/CLOCKS_PER_SEC << " s. \n";
+ /*
+ char buffer[100];
+ int i = sprintf(buffer,"%s_%s_result.txt",argv[1],argv[2]);
+ if (i >= 0)
+ {
+ std::string out_file = (std::string)buffer;
+ std::ofstream ofs (out_file, std::ofstream::out);
+ witnessComplex.st_to_file(ofs);
+ ofs.close();
+ }
+ */
+
+ out_file = "output/"+file_name+"_"+argv[2]+".stree";
+ std::ofstream ofs (out_file, std::ofstream::out);
+ witnessComplex.st_to_file(ofs);
+ ofs.close();
+
+ out_file = "output/"+file_name+"_"+argv[2]+".badlinks";
+ std::ofstream ofs2(out_file, std::ofstream::out);
+ witnessComplex.write_bad_links(ofs2);
+ ofs2.close();
+}
diff --git a/src/Witness_complex/include/gudhi/Witness_complex.h b/src/Witness_complex/include/gudhi/Witness_complex.h
index 3c030c45..2ccaa416 100644
--- a/src/Witness_complex/include/gudhi/Witness_complex.h
+++ b/src/Witness_complex/include/gudhi/Witness_complex.h
@@ -32,7 +32,8 @@
#include "gudhi/Simplex_tree.h"
#include <vector>
#include <list>
-#include <unordered_set>
+#include <set>
+#include <queue>
#include <limits>
#include <math.h>
#include <ctime>
@@ -40,9 +41,9 @@
// Needed for nearest neighbours
//#include <CGAL/Delaunay_triangulation.h>
-#include <CGAL/Epick_d.h>
-#include <CGAL/K_neighbor_search.h>
-#include <CGAL/Search_traits_d.h>
+//#include <CGAL/Epick_d.h>
+//#include <CGAL/K_neighbor_search.h>
+//#include <CGAL/Search_traits_d.h>
// Needed for the adjacency graph in bad link search
#include <boost/graph/graph_traits.hpp>
@@ -233,12 +234,12 @@ namespace Gudhi {
* FURTHEST_POINT_STRATEGY and RANDOM_POINT_STRATEGY and
* density must be set to the right value for DENSITY_STRATEGY
*/
- void witness_complex_from_points(Point_Vector point_vector)
- {
- std::vector<std::vector< int > > WL;
- landmark_choice_by_random_points(point_vector, point_vector.size(), WL);
- witness_complex(WL);
- }
+ // void witness_complex_from_points(Point_Vector point_vector)
+ // {
+ // std::vector<std::vector< int > > WL;
+ // landmark_choice_by_random_points(point_vector, point_vector.size(), WL);
+ // witness_complex(WL);
+ // }
private:
@@ -468,75 +469,160 @@ private:
*
*/
- template <typename KNearestNeighbours>
- void landmark_choice_by_random_points(Point_Vector &W, int nbP, KNearestNeighbours &WL)
+ // template <typename KNearestNeighbours>
+ // void landmark_choice_by_random_points(Point_Vector &W, int nbP, KNearestNeighbours &WL)
+ // {
+ // std::cout << "Enter landmark_choice_by_random_points "<< std::endl;
+ // //std::cout << "W="; print_vvector(W);
+ // std::unordered_set< int > chosen_landmarks; // landmark set
+
+ // Point_Vector wit_land_dist(nbP,std::vector<double>()); // distance matrix witness x landmarks
+
+ // WL = KNearestNeighbours(nbP,std::vector<int>());
+ // int current_number_of_landmarks=0; // counter for landmarks
+
+ // srand(24660);
+ // int chosen_landmark = rand()%nbP;
+ // double curr_dist;
+
+ // //int j;
+ // //int temp_swap_int;
+ // //double temp_swap_double;
+
+
+ // for (current_number_of_landmarks = 0; current_number_of_landmarks != nbL; current_number_of_landmarks++)
+ // {
+ // while (chosen_landmarks.find(chosen_landmark) != chosen_landmarks.end())
+ // {
+ // srand((int)clock());
+ // chosen_landmark = rand()% nbP;
+ // //std::cout << chosen_landmark << "\n";
+ // }
+ // chosen_landmarks.insert(chosen_landmark);
+ // //std::cout << "**********Entered loop with current number of landmarks = " << current_number_of_landmarks << std::endl;
+ // //std::cout << "WL="; print_vvector(WL);
+ // //std::cout << "WLD="; print_vvector(wit_land_dist);
+ // //std::cout << "landmarks="; print_vector(chosen_landmarks); std::cout << std::endl;
+ // for (auto v: WL)
+ // v.push_back(current_number_of_landmarks);
+ // for (int i = 0; i < nbP; ++i)
+ // {
+ // // iteration on points in W. update of distance vectors
+
+ // //std::cout << "In the loop with i=" << i << " and landmark=" << chosen_landmarks[current_number_of_landmarks] << std::endl;
+ // //std::cout << "W[i]="; print_vector(W[i]); std::cout << " W[landmark]="; print_vector(W[chosen_landmarks[current_number_of_landmarks]]); std::cout << std::endl;
+ // curr_dist = euclidean_distance(W[i],W[chosen_landmark]);
+ // //std::cout << "The problem is not in distance function\n";
+ // wit_land_dist[i].push_back(curr_dist);
+ // WL[i].push_back(current_number_of_landmarks);
+ // //std::cout << "Push't back\n";
+ // //j = current_number_of_landmarks;
+ // //std::cout << "First half complete\n";
+ // //std::cout << "result WL="; print_vvector(WL);
+ // //std::cout << "result WLD="; print_vvector(wit_land_dist);
+ // //std::cout << "End loop\n";
+ // }
+ // }
+ // for (int i = 0; i < nbP; i++)
+ // {
+ // sort(WL[i].begin(), WL[i].end(), [&](int j1, int j2){return wit_land_dist[i][j1] < wit_land_dist[i][j2];});
+ // }
+ // //std::cout << endl;
+ // }
+
+ /** \brief Landmark choice strategy by taking random vertices for landmarks.
+ *
+ */
+
+ // template <typename KNearestNeighbours>
+ void landmark_choice_by_random_points(Point_Vector &W, int nbP, std::set<int> &L)
{
std::cout << "Enter landmark_choice_by_random_points "<< std::endl;
//std::cout << "W="; print_vvector(W);
- std::unordered_set< int > chosen_landmarks; // landmark set
+ //std::unordered_set< int > chosen_landmarks; // landmark set
Point_Vector wit_land_dist(nbP,std::vector<double>()); // distance matrix witness x landmarks
- WL = KNearestNeighbours(nbP,std::vector<int>());
+ //WL = KNearestNeighbours(nbP,std::vector<int>());
int current_number_of_landmarks=0; // counter for landmarks
srand(24660);
int chosen_landmark = rand()%nbP;
- double curr_dist;
-
+ //double curr_dist;
//int j;
//int temp_swap_int;
- //double temp_swap_double;
-
-
+ //double temp_swap_double;
for (current_number_of_landmarks = 0; current_number_of_landmarks != nbL; current_number_of_landmarks++)
{
- while (chosen_landmarks.find(chosen_landmark) != chosen_landmarks.end())
+ while (L.find(chosen_landmark) != L.end())
{
srand((int)clock());
chosen_landmark = rand()% nbP;
//std::cout << chosen_landmark << "\n";
}
- chosen_landmarks.insert(chosen_landmark);
+ L.insert(chosen_landmark);
//std::cout << "**********Entered loop with current number of landmarks = " << current_number_of_landmarks << std::endl;
//std::cout << "WL="; print_vvector(WL);
//std::cout << "WLD="; print_vvector(wit_land_dist);
//std::cout << "landmarks="; print_vector(chosen_landmarks); std::cout << std::endl;
- for (auto v: WL)
- v.push_back(current_number_of_landmarks);
- for (int i = 0; i < nbP; ++i)
- {
- // iteration on points in W. update of distance vectors
+ // for (auto v: WL)
+ // v.push_back(current_number_of_landmarks);
+ // for (int i = 0; i < nbP; ++i)
+ // {
+ // // iteration on points in W. update of distance vectors
- //std::cout << "In the loop with i=" << i << " and landmark=" << chosen_landmarks[current_number_of_landmarks] << std::endl;
- //std::cout << "W[i]="; print_vector(W[i]); std::cout << " W[landmark]="; print_vector(W[chosen_landmarks[current_number_of_landmarks]]); std::cout << std::endl;
- curr_dist = euclidean_distance(W[i],W[chosen_landmark]);
- //std::cout << "The problem is not in distance function\n";
- wit_land_dist[i].push_back(curr_dist);
- WL[i].push_back(current_number_of_landmarks);
- //std::cout << "Push't back\n";
- //j = current_number_of_landmarks;
- //std::cout << "First half complete\n";
- //std::cout << "result WL="; print_vvector(WL);
- //std::cout << "result WLD="; print_vvector(wit_land_dist);
- //std::cout << "End loop\n";
- }
- }
- for (int i = 0; i < nbP; i++)
- {
- sort(WL[i].begin(), WL[i].end(), [&](int j1, int j2){return wit_land_dist[i][j1] < wit_land_dist[i][j2];});
+ // //std::cout << "In the loop with i=" << i << " and landmark=" << chosen_landmarks[current_number_of_landmarks] << std::endl;
+ // //std::cout << "W[i]="; print_vector(W[i]); std::cout << " W[landmark]="; print_vector(W[chosen_landmarks[current_number_of_landmarks]]); std::cout << std::endl;
+ // curr_dist = euclidean_distance(W[i],W[chosen_landmark]);
+ // //std::cout << "The problem is not in distance function\n";
+ // wit_land_dist[i].push_back(curr_dist);
+ // WL[i].push_back(current_number_of_landmarks);
+ // //std::cout << "Push't back\n";
+ // //j = current_number_of_landmarks;
+ // //std::cout << "First half complete\n";
+ // //std::cout << "result WL="; print_vvector(WL);
+ // //std::cout << "result WLD="; print_vvector(wit_land_dist);
+ // //std::cout << "End loop\n";
+ // }
}
+ // for (int i = 0; i < nbP; i++)
+ // {
+ // sort(WL[i].begin(), WL[i].end(), [&](int j1, int j2){return wit_land_dist[i][j1] < wit_land_dist[i][j2];});
+ // }
//std::cout << endl;
}
+
/** \brief Construct the matrix |W|x(D+1) of D+1 closest landmarks
* where W is the set of witnesses and D is the ambient dimension
*/
template <typename KNearestNeighbours>
- void nearest_landmarks(Point_Vector &W, std::unordered_set<int> &L, KNearestNeighbours &WL)
+ void nearest_landmarks(Point_Vector &W, std::set<int> &L, KNearestNeighbours &WL)
{
int D = W[0].size();
-
+ int nbP = W.size();
+ WL = KNearestNeighbours(nbP,std::vector<int>());
+ typedef std::pair<double,int> dist_i;
+ typedef bool (*comp)(dist_i,dist_i);
+ for (int W_i = 0; W_i < nbP; W_i++)
+ {
+ //std::cout << "<<<<<<<<<<<<<<" << W_i <<"\n";
+ std::priority_queue<dist_i, std::vector<dist_i>, comp> l_heap([&](dist_i j1, dist_i j2){return j1.first > j2.first;});
+ std::set<int>::iterator L_it;
+ int L_i;
+ for (L_it = L.begin(), L_i=0; L_it != L.end(); L_it++, L_i++)
+ {
+ dist_i dist = std::make_pair(euclidean_distance(W[W_i],W[*L_it]), L_i);
+ l_heap.push(dist);
+ }
+ for (int i = 0; i < D+1; i++)
+ {
+ dist_i dist = l_heap.top();
+ WL[W_i].push_back(dist.second);
+ //std::cout << dist.first << " " << dist.second << std::endl;
+ l_heap.pop();
+ }
+ }
}
/** \brief Search and output links around vertices that are not pseudomanifolds