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-rw-r--r--src/Bottleneck_distance/benchmark/CMakeLists.txt8
-rw-r--r--src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp50
-rw-r--r--src/Bottleneck_distance/concept/Persistence_diagram.h38
-rw-r--r--src/Bottleneck_distance/doc/COPYRIGHT12
-rw-r--r--src/Bottleneck_distance/doc/Intro_bottleneck_distance.h81
-rw-r--r--src/Bottleneck_distance/doc/bottleneck_distance_example.ipe287
-rw-r--r--src/Bottleneck_distance/doc/bottleneck_distance_example.pngbin0 -> 19485 bytes
-rw-r--r--src/Bottleneck_distance/doc/perturb_pd.pngbin0 -> 20864 bytes
-rw-r--r--src/Bottleneck_distance/example/CMakeLists.txt25
-rw-r--r--src/Bottleneck_distance/example/README19
-rw-r--r--src/Bottleneck_distance/example/alpha_rips_persistence_bottleneck_distance.cpp178
-rw-r--r--src/Bottleneck_distance/example/bottleneck_basic_example.cpp28
-rw-r--r--src/Bottleneck_distance/include/gudhi/Bottleneck.h124
-rw-r--r--src/Bottleneck_distance/include/gudhi/Graph_matching.h162
-rw-r--r--src/Bottleneck_distance/include/gudhi/Internal_point.h79
-rw-r--r--src/Bottleneck_distance/include/gudhi/Neighbors_finder.h182
-rw-r--r--src/Bottleneck_distance/include/gudhi/Persistence_graph.h176
-rw-r--r--src/Bottleneck_distance/test/CMakeLists.txt14
-rw-r--r--src/Bottleneck_distance/test/README12
-rw-r--r--src/Bottleneck_distance/test/bottleneck_unit_test.cpp155
-rw-r--r--src/Bottleneck_distance/utilities/CMakeLists.txt15
-rw-r--r--src/Bottleneck_distance/utilities/bottleneck_distance.cpp38
-rw-r--r--src/Bottleneck_distance/utilities/bottleneckdistance.md26
23 files changed, 1709 insertions, 0 deletions
diff --git a/src/Bottleneck_distance/benchmark/CMakeLists.txt b/src/Bottleneck_distance/benchmark/CMakeLists.txt
new file mode 100644
index 00000000..77cb013d
--- /dev/null
+++ b/src/Bottleneck_distance/benchmark/CMakeLists.txt
@@ -0,0 +1,8 @@
+project(Bottleneck_distance_benchmark)
+
+if (NOT CGAL_VERSION VERSION_LESS 4.11.0)
+ add_executable ( bottleneck_chrono bottleneck_chrono.cpp )
+ if (TBB_FOUND)
+ target_link_libraries(bottleneck_chrono ${TBB_LIBRARIES})
+ endif(TBB_FOUND)
+endif(NOT CGAL_VERSION VERSION_LESS 4.11.0)
diff --git a/src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp b/src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp
new file mode 100644
index 00000000..576d510b
--- /dev/null
+++ b/src/Bottleneck_distance/benchmark/bottleneck_chrono.cpp
@@ -0,0 +1,50 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#include <gudhi/Bottleneck.h>
+#include <chrono>
+#include <fstream>
+#include <random>
+
+using namespace Gudhi::persistence_diagram;
+
+
+double upper_bound = 400.; // any real > 0
+
+int main() {
+ std::ofstream result_file;
+ result_file.open("results.csv", std::ios::out);
+
+ for (int n = 1000; n <= 10000; n += 1000) {
+ std::uniform_real_distribution<double> unif1(0., upper_bound);
+ std::uniform_real_distribution<double> unif2(upper_bound / 1000., upper_bound / 100.);
+ std::default_random_engine re;
+ std::vector< std::pair<double, double> > v1, v2;
+ for (int i = 0; i < n; i++) {
+ double a = unif1(re);
+ double b = unif1(re);
+ double x = unif2(re);
+ double y = unif2(re);
+ v1.emplace_back(std::min(a, b), std::max(a, b));
+ v2.emplace_back(std::min(a, b) + std::min(x, y), std::max(a, b) + std::max(x, y));
+ if (i % 5 == 0)
+ v1.emplace_back(std::min(a, b), std::min(a, b) + x);
+ if (i % 3 == 0)
+ v2.emplace_back(std::max(a, b), std::max(a, b) + y);
+ }
+ std::chrono::steady_clock::time_point start = std::chrono::steady_clock::now();
+ double b = bottleneck_distance(v1, v2);
+ std::chrono::steady_clock::time_point end = std::chrono::steady_clock::now();
+ typedef std::chrono::duration<int, std::milli> millisecs_t;
+ millisecs_t duration(std::chrono::duration_cast<millisecs_t>(end - start));
+ result_file << n << ";" << duration.count() << ";" << b << std::endl;
+ }
+ result_file.close();
+}
diff --git a/src/Bottleneck_distance/concept/Persistence_diagram.h b/src/Bottleneck_distance/concept/Persistence_diagram.h
new file mode 100644
index 00000000..8c8761cb
--- /dev/null
+++ b/src/Bottleneck_distance/concept/Persistence_diagram.h
@@ -0,0 +1,38 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: François Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#ifndef CONCEPT_BOTTLENECK_DISTANCE_PERSISTENCE_DIAGRAM_H_
+#define CONCEPT_BOTTLENECK_DISTANCE_PERSISTENCE_DIAGRAM_H_
+
+namespace Gudhi {
+
+namespace persistence_diagram {
+
+/** \brief Concept of point in a persistence diagram. std::get<0>(point) must return the birth of the corresponding component and std::get<1>(point) its death.
+ * Both should be convertible to `double`.
+ * A valid implementation of this concept is std::pair<double,double>.
+ * Death should be larger than birth, death can be std::numeric_limits<double>::infinity() for components which stay alive.
+ *
+ * \ingroup bottleneck_distance
+ */
+struct DiagramPoint{};
+
+/** \brief Concept of persistence diagram. It is a range of `DiagramPoint`.
+ * std::begin(diagram) and std::end(diagram) must return corresponding iterators.
+ *
+ * \ingroup bottleneck_distance
+ */
+struct PersistenceDiagram{};
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // CONCEPT_BOTTLENECK_DISTANCE_PERSISTENCE_DIAGRAM_H_
diff --git a/src/Bottleneck_distance/doc/COPYRIGHT b/src/Bottleneck_distance/doc/COPYRIGHT
new file mode 100644
index 00000000..61f17f6d
--- /dev/null
+++ b/src/Bottleneck_distance/doc/COPYRIGHT
@@ -0,0 +1,12 @@
+The files of this directory are part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+
+Author(s): Vincent Rouvreau
+
+Copyright (C) 2015 Inria
+
+This gives everyone the freedoms to use openFrameworks in any context:
+commercial or non-commercial, public or private, open or closed source.
+
+You should have received a copy of the MIT License along with this program.
+If not, see https://opensource.org/licenses/MIT. \ No newline at end of file
diff --git a/src/Bottleneck_distance/doc/Intro_bottleneck_distance.h b/src/Bottleneck_distance/doc/Intro_bottleneck_distance.h
new file mode 100644
index 00000000..bbc952e1
--- /dev/null
+++ b/src/Bottleneck_distance/doc/Intro_bottleneck_distance.h
@@ -0,0 +1,81 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: François Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ * - 2019/06 Vincent Rouvreau : Fix #11 - Distance computation shall be better documented.
+ */
+
+#ifndef DOC_BOTTLENECK_DISTANCE_INTRO_BOTTLENECK_DISTANCE_H_
+#define DOC_BOTTLENECK_DISTANCE_INTRO_BOTTLENECK_DISTANCE_H_
+
+// needs namespace for Doxygen to link on classes
+namespace Gudhi {
+// needs namespace for Doxygen to link on classes
+namespace persistence_diagram {
+
+/** \defgroup bottleneck_distance Bottleneck distance
+ *
+ * \author Fran&ccedil;ois Godi
+ * @{
+ *
+ * \section bottleneckdefinition Definition
+ *
+ * The bottleneck distance measures the similarity between two persistence diagrams. It is the shortest distance b for
+ * which there exists a perfect matching between the points of the two diagrams (completed with all the points on the
+ * diagonal in order to ignore cardinality mismatchs) such that any couple of matched points are at distance at most b,
+ * where the distance between points is the sup norm in \f$\mathbb{R}^2\f$ (not the Euclidean distance).
+ *
+ * \image html perturb_pd.png On this picture, the red edges represent the matching. The bottleneck distance is the length of the longest edge.
+ *
+ * This implementation is based on ideas from "Geometry Helps in Bottleneck Matching and Related Problems"
+ * \cite DBLP:journals/algorithmica/EfratIK01. Another relevant publication, although it was not used is
+ * "Geometry Helps to Compare Persistence Diagrams" \cite Kerber:2017:GHC:3047249.3064175.
+ *
+ * \section bottleneckdistanceprecision Distance computation
+ *
+ * The following example explains how the distance is computed:
+ *
+ * \code{.cpp}
+#include <gudhi/Bottleneck.h>
+
+#include <iostream>
+#include <vector>
+#include <utility> // for pair
+
+int main() {
+ std::vector< std::pair<double, double> > diag1, diag2;
+ diag1.emplace_back(0., 0.);
+ diag2.emplace_back(0., 13.);
+
+ double b = Gudhi::persistence_diagram::bottleneck_distance(diag1, diag2);
+ std::cout << "Bottleneck distance = " << b << std::endl;
+}
+ * \endcode
+ *
+ * \code Bottleneck distance = 6.5
+ * \endcode
+ *
+ * \image html bottleneck_distance_example.png The point (0, 13) is at distance 6.5 from the diagonal and more specifically from the point (6.5, 6.5)
+ *
+ * \section bottleneckbasicexample Basic example
+ *
+ * This other example computes the bottleneck distance from 2 persistence diagrams:
+ * \include Bottleneck_distance/bottleneck_basic_example.cpp
+ *
+ * \code
+ Bottleneck distance = 0.75
+ Approx bottleneck distance = 0.808176
+ * \endcode
+
+ */
+/** @} */ // end defgroup bottleneck_distance
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // DOC_BOTTLENECK_DISTANCE_INTRO_BOTTLENECK_DISTANCE_H_
diff --git a/src/Bottleneck_distance/doc/bottleneck_distance_example.ipe b/src/Bottleneck_distance/doc/bottleneck_distance_example.ipe
new file mode 100644
index 00000000..2033ea56
--- /dev/null
+++ b/src/Bottleneck_distance/doc/bottleneck_distance_example.ipe
@@ -0,0 +1,287 @@
+<?xml version="1.0"?>
+<!DOCTYPE ipe SYSTEM "ipe.dtd">
+<ipe version="70206" creator="Ipe 7.2.7">
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+distance is 6.5</text>
+</page>
+</ipe>
diff --git a/src/Bottleneck_distance/doc/bottleneck_distance_example.png b/src/Bottleneck_distance/doc/bottleneck_distance_example.png
new file mode 100644
index 00000000..1d3b91aa
--- /dev/null
+++ b/src/Bottleneck_distance/doc/bottleneck_distance_example.png
Binary files differ
diff --git a/src/Bottleneck_distance/doc/perturb_pd.png b/src/Bottleneck_distance/doc/perturb_pd.png
new file mode 100644
index 00000000..be638de0
--- /dev/null
+++ b/src/Bottleneck_distance/doc/perturb_pd.png
Binary files differ
diff --git a/src/Bottleneck_distance/example/CMakeLists.txt b/src/Bottleneck_distance/example/CMakeLists.txt
new file mode 100644
index 00000000..3d65963a
--- /dev/null
+++ b/src/Bottleneck_distance/example/CMakeLists.txt
@@ -0,0 +1,25 @@
+project(Bottleneck_distance_examples)
+
+if (NOT CGAL_VERSION VERSION_LESS 4.11.0)
+ add_executable (bottleneck_basic_example bottleneck_basic_example.cpp)
+
+ if (TBB_FOUND)
+ target_link_libraries(bottleneck_basic_example ${TBB_LIBRARIES})
+ endif(TBB_FOUND)
+
+ add_test(NAME Bottleneck_distance_example_basic COMMAND $<TARGET_FILE:bottleneck_basic_example>)
+
+endif (NOT CGAL_VERSION VERSION_LESS 4.11.0)
+
+if (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0)
+ add_executable (alpha_rips_persistence_bottleneck_distance alpha_rips_persistence_bottleneck_distance.cpp)
+ target_link_libraries(alpha_rips_persistence_bottleneck_distance ${Boost_PROGRAM_OPTIONS_LIBRARY})
+
+ if (TBB_FOUND)
+ target_link_libraries(alpha_rips_persistence_bottleneck_distance ${TBB_LIBRARIES})
+ endif(TBB_FOUND)
+
+ add_test(NAME Bottleneck_distance_example_alpha_rips_persistence_bottleneck
+ COMMAND $<TARGET_FILE:alpha_rips_persistence_bottleneck_distance>
+ "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.15" "-m" "0.12" "-d" "3" "-p" "3")
+endif (NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0)
diff --git a/src/Bottleneck_distance/example/README b/src/Bottleneck_distance/example/README
new file mode 100644
index 00000000..01bcd74a
--- /dev/null
+++ b/src/Bottleneck_distance/example/README
@@ -0,0 +1,19 @@
+# Bottleneck_distance #
+
+## `alpha_rips_persistence_bottleneck_distance` ##
+This program computes the persistent homology with coefficient field Z/pZ of a Rips complex defined on a set of input points. 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.
+
+Usage:
+`alpha_rips_persistence_bottleneck_distance [options] <OFF input file>`
+
+Allowed options:
+
+* `-h [ --help ]` Produce help message
+* `-r [ --max-edge-length ]` (default = inf) Maximal length of an edge for the Rips complex construction.`
+* `-d [ --cpx-dimension ]` (default = 1) Maximal dimension of the Rips 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.
diff --git a/src/Bottleneck_distance/example/alpha_rips_persistence_bottleneck_distance.cpp b/src/Bottleneck_distance/example/alpha_rips_persistence_bottleneck_distance.cpp
new file mode 100644
index 00000000..6c0dc9bf
--- /dev/null
+++ b/src/Bottleneck_distance/example/alpha_rips_persistence_bottleneck_distance.cpp
@@ -0,0 +1,178 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author(s): Vincent Rouvreau
+ *
+ * Copyright (C) 2017 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#include <gudhi/Alpha_complex.h>
+#include <gudhi/Rips_complex.h>
+#include <gudhi/distance_functions.h>
+#include <gudhi/Simplex_tree.h>
+#include <gudhi/Persistent_cohomology.h>
+#include <gudhi/Points_off_io.h>
+#include <gudhi/Bottleneck.h>
+
+#include <CGAL/Epick_d.h>
+
+#include <boost/program_options.hpp>
+
+#include <string>
+#include <vector>
+#include <limits> // infinity
+#include <utility> // for pair
+#include <algorithm> // for transform
+
+
+// Types definition
+using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>;
+using Filtration_value = Simplex_tree::Filtration_value;
+using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>;
+using Field_Zp = Gudhi::persistent_cohomology::Field_Zp;
+using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp >;
+using Kernel = CGAL::Epick_d< CGAL::Dynamic_dimension_tag >;
+using Point_d = Kernel::Point_d;
+using Points_off_reader = Gudhi::Points_off_reader<Point_d>;
+
+void program_options(int argc, char * argv[]
+ , std::string & off_file_points
+ , Filtration_value & threshold
+ , int & dim_max
+ , int & p
+ , Filtration_value & min_persistence);
+
+static inline std::pair<double, double> compute_root_square(std::pair<double, double> input) {
+ return std::make_pair(std::sqrt(input.first), std::sqrt(input.second));
+}
+
+int main(int argc, char * argv[]) {
+ std::string off_file_points;
+ Filtration_value threshold;
+ int dim_max;
+ int p;
+ Filtration_value min_persistence;
+
+ program_options(argc, argv, off_file_points, threshold, dim_max, p, min_persistence);
+
+ Points_off_reader off_reader(off_file_points);
+
+ // --------------------------------------------
+ // Rips persistence
+ // --------------------------------------------
+ Rips_complex rips_complex(off_reader.get_point_cloud(), threshold, Gudhi::Euclidean_distance());
+
+ // Construct the Rips complex in a Simplex Tree
+ Simplex_tree rips_stree;
+
+ rips_complex.create_complex(rips_stree, dim_max);
+ std::cout << "The Rips complex contains " << rips_stree.num_simplices() << " simplices and has dimension "
+ << rips_stree.dimension() << " \n";
+
+ // Sort the simplices in the order of the filtration
+ rips_stree.initialize_filtration();
+
+ // Compute the persistence diagram of the complex
+ Persistent_cohomology rips_pcoh(rips_stree);
+ // initializes the coefficient field for homology
+ rips_pcoh.init_coefficients(p);
+ rips_pcoh.compute_persistent_cohomology(min_persistence);
+
+ // rips_pcoh.output_diagram();
+
+ // --------------------------------------------
+ // Alpha persistence
+ // --------------------------------------------
+ Gudhi::alpha_complex::Alpha_complex<Kernel> alpha_complex(off_reader.get_point_cloud());
+
+ Simplex_tree alpha_stree;
+ alpha_complex.create_complex(alpha_stree, threshold * threshold);
+ std::cout << "The Alpha complex contains " << alpha_stree.num_simplices() << " simplices and has dimension "
+ << alpha_stree.dimension() << " \n";
+
+ // Sort the simplices in the order of the filtration
+ alpha_stree.initialize_filtration();
+
+ // Compute the persistence diagram of the complex
+ Persistent_cohomology alpha_pcoh(alpha_stree);
+ // initializes the coefficient field for homology
+ alpha_pcoh.init_coefficients(p);
+ alpha_pcoh.compute_persistent_cohomology(min_persistence * min_persistence);
+
+ // alpha_pcoh.output_diagram();
+
+ // --------------------------------------------
+ // Bottleneck distance between both persistence
+ // --------------------------------------------
+ double max_b_distance {};
+ for (int dim = 0; dim < dim_max; dim ++) {
+ std::vector< std::pair< Filtration_value , Filtration_value > > rips_intervals;
+ std::vector< std::pair< Filtration_value , Filtration_value > > alpha_intervals;
+ rips_intervals = rips_pcoh.intervals_in_dimension(dim);
+ alpha_intervals = alpha_pcoh.intervals_in_dimension(dim);
+ std::transform(alpha_intervals.begin(), alpha_intervals.end(), alpha_intervals.begin(), compute_root_square);
+
+ double bottleneck_distance = Gudhi::persistence_diagram::bottleneck_distance(rips_intervals, alpha_intervals);
+ std::cout << "In dimension " << dim << ", bottleneck distance = " << bottleneck_distance << std::endl;
+ if (bottleneck_distance > max_b_distance)
+ max_b_distance = bottleneck_distance;
+ }
+ std::cout << "================================================================================" << std::endl;
+ std::cout << "Bottleneck distance is " << max_b_distance << std::endl;
+
+ return 0;
+}
+
+void program_options(int argc, char * argv[]
+ , std::string & off_file_points
+ , 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<std::string>(&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-edge-length,r",
+ po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()),
+ "Maximal length of an edge for the Rips complex construction.")
+ ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1),
+ "Maximal dimension of the Rips complex we want to compute.")
+ ("field-charac,p", po::value<int>(&p)->default_value(11),
+ "Characteristic p of the coefficient field Z/pZ for computing homology.")
+ ("min-persistence,m", po::value<Filtration_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 Rips 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;
+ exit(-1);
+ }
+}
diff --git a/src/Bottleneck_distance/example/bottleneck_basic_example.cpp b/src/Bottleneck_distance/example/bottleneck_basic_example.cpp
new file mode 100644
index 00000000..61778a55
--- /dev/null
+++ b/src/Bottleneck_distance/example/bottleneck_basic_example.cpp
@@ -0,0 +1,28 @@
+#include <gudhi/Bottleneck.h>
+
+#include <iostream>
+#include <vector>
+#include <utility> // for pair
+#include <limits> // for numeric_limits
+
+int main() {
+ std::vector< std::pair<double, double> > v1, v2;
+
+ v1.emplace_back(2.7, 3.7);
+ v1.emplace_back(9.6, 14.);
+ v1.emplace_back(34.2, 34.974);
+ v1.emplace_back(3., std::numeric_limits<double>::infinity());
+
+ v2.emplace_back(2.8, 4.45);
+ v2.emplace_back(9.5, 14.1);
+ v2.emplace_back(3.2, std::numeric_limits<double>::infinity());
+
+
+ double b = Gudhi::persistence_diagram::bottleneck_distance(v1, v2);
+
+ std::cout << "Bottleneck distance = " << b << std::endl;
+
+ b = Gudhi::persistence_diagram::bottleneck_distance(v1, v2, 0.1);
+
+ std::cout << "Approx bottleneck distance = " << b << std::endl;
+}
diff --git a/src/Bottleneck_distance/include/gudhi/Bottleneck.h b/src/Bottleneck_distance/include/gudhi/Bottleneck.h
new file mode 100644
index 00000000..82ba9f68
--- /dev/null
+++ b/src/Bottleneck_distance/include/gudhi/Bottleneck.h
@@ -0,0 +1,124 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - 2019/06 Vincent Rouvreau : Fix doxygen warning.
+ * - 2019/08 Vincent Rouvreau: Fix issue #10 for CGAL
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#ifndef BOTTLENECK_H_
+#define BOTTLENECK_H_
+
+#include <gudhi/Graph_matching.h>
+
+#include <CGAL/version.h> // for CGAL_VERSION_NR
+
+#include <vector>
+#include <algorithm> // for max
+#include <limits> // for numeric_limits
+
+#include <cmath>
+#include <cfloat> // FLT_EVAL_METHOD
+
+// Make compilation fail - required for external projects - https://github.com/GUDHI/gudhi-devel/issues/10
+#if CGAL_VERSION_NR < 1041101000
+# error Alpha_complex_3d is only available for CGAL >= 4.11
+#endif
+
+namespace Gudhi {
+
+namespace persistence_diagram {
+
+inline double bottleneck_distance_approx(Persistence_graph& g, double e) {
+ double b_lower_bound = 0.;
+ double b_upper_bound = g.diameter_bound();
+ const double alpha = std::pow(g.size(), 1. / 5.);
+ Graph_matching m(g);
+ Graph_matching biggest_unperfect(g);
+ while (b_upper_bound - b_lower_bound > 2 * e) {
+ double step = b_lower_bound + (b_upper_bound - b_lower_bound) / alpha;
+#if !defined FLT_EVAL_METHOD || FLT_EVAL_METHOD < 0 || FLT_EVAL_METHOD > 1
+ // On platforms where double computation is done with excess precision,
+ // we force it to its true precision so the following test is reliable.
+ volatile double drop_excess_precision = step;
+ step = drop_excess_precision;
+ // Alternative: step = CGAL::IA_force_to_double(step);
+#endif
+ if (step <= b_lower_bound || step >= b_upper_bound) // Avoid precision problem
+ break;
+ m.set_r(step);
+ while (m.multi_augment()) {} // compute a maximum matching (in the graph corresponding to the current r)
+ if (m.perfect()) {
+ m = biggest_unperfect;
+ b_upper_bound = step;
+ } else {
+ biggest_unperfect = m;
+ b_lower_bound = step;
+ }
+ }
+ return (b_lower_bound + b_upper_bound) / 2.;
+}
+
+inline double bottleneck_distance_exact(Persistence_graph& g) {
+ std::vector<double> sd = g.sorted_distances();
+ long lower_bound_i = 0;
+ long upper_bound_i = sd.size() - 1;
+ const double alpha = std::pow(g.size(), 1. / 5.);
+ Graph_matching m(g);
+ Graph_matching biggest_unperfect(g);
+ while (lower_bound_i != upper_bound_i) {
+ long step = lower_bound_i + static_cast<long> ((upper_bound_i - lower_bound_i - 1) / alpha);
+ m.set_r(sd.at(step));
+ while (m.multi_augment()) {} // compute a maximum matching (in the graph corresponding to the current r)
+ if (m.perfect()) {
+ m = biggest_unperfect;
+ upper_bound_i = step;
+ } else {
+ biggest_unperfect = m;
+ lower_bound_i = step + 1;
+ }
+ }
+ return sd.at(lower_bound_i);
+}
+
+/** \brief Function to compute the Bottleneck distance between two persistence diagrams.
+ *
+ * \tparam Persistence_diagram1,Persistence_diagram2
+ * models of the concept `PersistenceDiagram`.
+ *
+ * \param[in] diag1 The first persistence diagram.
+ * \param[in] diag2 The second persistence diagram.
+ *
+ * \param[in] e
+ * \parblock
+ * If `e` is 0, this uses an expensive algorithm to compute the exact distance.
+ *
+ * If `e` is not 0, it asks for an additive `e`-approximation, and currently
+ * also allows a small multiplicative error (the last 2 or 3 bits of the
+ * mantissa may be wrong). This version of the algorithm takes advantage of the
+ * limited precision of `double` and is usually a lot faster to compute,
+ * whatever the value of `e`.
+ *
+ * Thus, by default, `e` is the smallest positive double.
+ * \endparblock
+ *
+ * \ingroup bottleneck_distance
+ */
+template<typename Persistence_diagram1, typename Persistence_diagram2>
+double bottleneck_distance(const Persistence_diagram1 &diag1, const Persistence_diagram2 &diag2,
+ double e = (std::numeric_limits<double>::min)()) {
+ Persistence_graph g(diag1, diag2, e);
+ if (g.bottleneck_alive() == std::numeric_limits<double>::infinity())
+ return std::numeric_limits<double>::infinity();
+ return (std::max)(g.bottleneck_alive(), e == 0. ? bottleneck_distance_exact(g) : bottleneck_distance_approx(g, e));
+}
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // BOTTLENECK_H_
diff --git a/src/Bottleneck_distance/include/gudhi/Graph_matching.h b/src/Bottleneck_distance/include/gudhi/Graph_matching.h
new file mode 100644
index 00000000..7b7623ce
--- /dev/null
+++ b/src/Bottleneck_distance/include/gudhi/Graph_matching.h
@@ -0,0 +1,162 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#ifndef GRAPH_MATCHING_H_
+#define GRAPH_MATCHING_H_
+
+#include <gudhi/Neighbors_finder.h>
+
+#include <vector>
+#include <unordered_set>
+#include <algorithm>
+
+namespace Gudhi {
+
+namespace persistence_diagram {
+
+/** \internal \brief Structure representing a graph matching. The graph is a Persistence_diagrams_graph.
+ *
+ * \ingroup bottleneck_distance
+ */
+class Graph_matching {
+ public:
+ /** \internal \brief Constructor constructing an empty matching. */
+ explicit Graph_matching(Persistence_graph &g);
+ /** \internal \brief Is the matching perfect ? */
+ bool perfect() const;
+ /** \internal \brief Augments the matching with a maximal set of edge-disjoint shortest augmenting paths. */
+ bool multi_augment();
+ /** \internal \brief Sets the maximum length of the edges allowed to be added in the matching, 0 initially. */
+ void set_r(double r);
+
+ private:
+ Persistence_graph* gp;
+ double r;
+ /** \internal \brief Given a point from V, provides its matched point in U, null_point_index() if there isn't. */
+ std::vector<int> v_to_u;
+ /** \internal \brief All the unmatched points in U. */
+ std::unordered_set<int> unmatched_in_u;
+
+ /** \internal \brief Provides a Layered_neighbors_finder dividing the graph in layers. Basically a BFS. */
+ Layered_neighbors_finder layering() const;
+ /** \internal \brief Augments the matching with a simple path no longer than max_depth. Basically a DFS. */
+ bool augment(Layered_neighbors_finder & layered_nf, int u_start_index, int max_depth);
+ /** \internal \brief Update the matching with the simple augmenting path given as parameter. */
+ void update(std::vector<int> & path);
+};
+
+inline Graph_matching::Graph_matching(Persistence_graph& g)
+ : gp(&g), r(0.), v_to_u(g.size(), null_point_index()), unmatched_in_u(g.size()) {
+ for (int u_point_index = 0; u_point_index < g.size(); ++u_point_index)
+ unmatched_in_u.insert(u_point_index);
+}
+
+inline bool Graph_matching::perfect() const {
+ return unmatched_in_u.empty();
+}
+
+inline bool Graph_matching::multi_augment() {
+ if (perfect())
+ return false;
+ Layered_neighbors_finder layered_nf(layering());
+ int max_depth = layered_nf.vlayers_number()*2 - 1;
+ double rn = sqrt(gp->size());
+ // verification of a necessary criterion in order to shortcut if possible
+ if (max_depth < 0 || (unmatched_in_u.size() > rn && max_depth >= rn))
+ return false;
+ bool successful = false;
+ std::vector<int> tries(unmatched_in_u.cbegin(), unmatched_in_u.cend());
+ for (auto it = tries.cbegin(); it != tries.cend(); it++)
+ // 'augment' has side-effects which have to be always executed, don't change order
+ successful = augment(layered_nf, *it, max_depth) || successful;
+ return successful;
+}
+
+inline void Graph_matching::set_r(double r) {
+ this->r = r;
+}
+
+inline bool Graph_matching::augment(Layered_neighbors_finder & layered_nf, int u_start_index, int max_depth) {
+ // V vertices have at most one successor, thus when we backtrack from U we can directly pop_back 2 vertices.
+ std::vector<int> path;
+ path.emplace_back(u_start_index);
+ do {
+ if (static_cast<int> (path.size()) > max_depth) {
+ path.pop_back();
+ path.pop_back();
+ }
+ if (path.empty())
+ return false;
+ path.emplace_back(layered_nf.pull_near(path.back(), static_cast<int> (path.size()) / 2));
+ while (path.back() == null_point_index()) {
+ path.pop_back();
+ path.pop_back();
+ if (path.empty())
+ return false;
+ path.pop_back();
+ path.emplace_back(layered_nf.pull_near(path.back(), path.size() / 2));
+ }
+ path.emplace_back(v_to_u.at(path.back()));
+ } while (path.back() != null_point_index());
+ // if v_to_u.at(path.back()) has no successor, path.back() is an exposed vertex
+ path.pop_back();
+ update(path);
+ return true;
+}
+
+inline Layered_neighbors_finder Graph_matching::layering() const {
+ std::vector<int> u_vertices(unmatched_in_u.cbegin(), unmatched_in_u.cend());
+ std::vector<int> v_vertices;
+ Neighbors_finder nf(*gp, r);
+ for (int v_point_index = 0; v_point_index < gp->size(); ++v_point_index)
+ nf.add(v_point_index);
+ Layered_neighbors_finder layered_nf(*gp, r);
+ for (int layer = 0; !u_vertices.empty(); layer++) {
+ // one layer is one step in the BFS
+ for (auto it1 = u_vertices.cbegin(); it1 != u_vertices.cend(); ++it1) {
+ std::vector<int> u_succ(nf.pull_all_near(*it1));
+ for (auto it2 = u_succ.begin(); it2 != u_succ.end(); ++it2) {
+ layered_nf.add(*it2, layer);
+ v_vertices.emplace_back(*it2);
+ }
+ }
+ // When the above for finishes, we have progress of one half-step (from U to V) in the BFS
+ u_vertices.clear();
+ bool end = false;
+ for (auto it = v_vertices.cbegin(); it != v_vertices.cend(); it++)
+ if (v_to_u.at(*it) == null_point_index())
+ // we stop when a nearest exposed V vertex (from U exposed vertices) has been found
+ end = true;
+ else
+ u_vertices.emplace_back(v_to_u.at(*it));
+ // When the above for finishes, we have progress of one half-step (from V to U) in the BFS
+ if (end)
+ return layered_nf;
+ v_vertices.clear();
+ }
+ return layered_nf;
+}
+
+inline void Graph_matching::update(std::vector<int>& path) {
+ // Must return 1.
+ unmatched_in_u.erase(path.front());
+ for (auto it = path.cbegin(); it != path.cend(); ++it) {
+ // Be careful, the iterator is incremented twice each time
+ int tmp = *it;
+ v_to_u[*(++it)] = tmp;
+ }
+}
+
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // GRAPH_MATCHING_H_
diff --git a/src/Bottleneck_distance/include/gudhi/Internal_point.h b/src/Bottleneck_distance/include/gudhi/Internal_point.h
new file mode 100644
index 00000000..f829943e
--- /dev/null
+++ b/src/Bottleneck_distance/include/gudhi/Internal_point.h
@@ -0,0 +1,79 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#ifndef INTERNAL_POINT_H_
+#define INTERNAL_POINT_H_
+
+namespace Gudhi {
+
+namespace persistence_diagram {
+
+/** \internal \brief Returns the used index for encoding none of the points */
+int null_point_index();
+
+/** \internal \typedef \brief Internal_point is the internal points representation, indexes used outside. */
+struct Internal_point {
+ double vec[2];
+ int point_index;
+
+ Internal_point() { }
+
+ Internal_point(double x, double y, int p_i) {
+ vec[0] = x;
+ vec[1] = y;
+ point_index = p_i;
+ }
+
+ double x() const {
+ return vec[ 0 ];
+ }
+
+ double y() const {
+ return vec[ 1 ];
+ }
+
+ double& x() {
+ return vec[ 0 ];
+ }
+
+ double& y() {
+ return vec[ 1 ];
+ }
+
+ bool operator==(const Internal_point& p) const {
+ return point_index == p.point_index;
+ }
+
+ bool operator!=(const Internal_point& p) const {
+ return !(*this == p);
+ }
+};
+
+inline int null_point_index() {
+ return -1;
+}
+
+struct Construct_coord_iterator {
+ typedef const double* result_type;
+
+ const double* operator()(const Internal_point& p) const {
+ return p.vec;
+ }
+
+ const double* operator()(const Internal_point& p, int) const {
+ return p.vec + 2;
+ }
+};
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // INTERNAL_POINT_H_
diff --git a/src/Bottleneck_distance/include/gudhi/Neighbors_finder.h b/src/Bottleneck_distance/include/gudhi/Neighbors_finder.h
new file mode 100644
index 00000000..c65e6082
--- /dev/null
+++ b/src/Bottleneck_distance/include/gudhi/Neighbors_finder.h
@@ -0,0 +1,182 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#ifndef NEIGHBORS_FINDER_H_
+#define NEIGHBORS_FINDER_H_
+
+// Inclusion order is important for CGAL patch
+#include <CGAL/Kd_tree.h>
+#include <CGAL/Search_traits.h>
+
+#include <gudhi/Persistence_graph.h>
+#include <gudhi/Internal_point.h>
+
+#include <unordered_set>
+#include <vector>
+#include <algorithm> // for std::max
+#include <cmath> // for std::abs
+
+namespace Gudhi {
+
+namespace persistence_diagram {
+
+/** \internal \brief Variant of CGAL::Fuzzy_iso_box to ensure that the box ic closed. It isn't clear how necessary that is.
+ */
+struct Square_query {
+ typedef CGAL::Dimension_tag<2> D;
+ typedef Internal_point Point_d;
+ typedef double FT;
+ bool contains(Point_d p) const {
+ return (std::max)(std::abs(p.x()-c.x()), std::abs(p.y()-c.y())) <= size;
+ }
+ bool inner_range_intersects(CGAL::Kd_tree_rectangle<FT, D> const&r) const {
+ return
+ r.max_coord(0) >= c.x() - size &&
+ r.min_coord(0) <= c.x() + size &&
+ r.max_coord(1) >= c.y() - size &&
+ r.min_coord(1) <= c.y() + size;
+ }
+ bool outer_range_contains(CGAL::Kd_tree_rectangle<FT, D> const&r) const {
+ return
+ r.min_coord(0) >= c.x() - size &&
+ r.max_coord(0) <= c.x() + size &&
+ r.min_coord(1) >= c.y() - size &&
+ r.max_coord(1) <= c.y() + size;
+ }
+ Point_d c;
+ FT size;
+};
+
+/** \internal \brief data structure used to find any point (including projections) in V near to a query point from U
+ * (which can be a projection).
+ *
+ * V points have to be added manually using their index and before the first pull. A neighbor pulled is automatically
+ * removed.
+ *
+ * \ingroup bottleneck_distance
+ */
+class Neighbors_finder {
+ typedef CGAL::Dimension_tag<2> D;
+ typedef CGAL::Search_traits<double, Internal_point, const double*, Construct_coord_iterator, D> Traits;
+ typedef CGAL::Kd_tree<Traits> Kd_tree;
+
+ public:
+ /** \internal \brief Constructor taking the near distance definition as parameter. */
+ Neighbors_finder(const Persistence_graph& g, double r);
+ /** \internal \brief A point added will be possibly pulled. */
+ void add(int v_point_index);
+ /** \internal \brief Returns and remove a V point near to the U point given as parameter, null_point_index() if
+ * there isn't such a point. */
+ int pull_near(int u_point_index);
+ /** \internal \brief Returns and remove all the V points near to the U point given as parameter. */
+ std::vector<int> pull_all_near(int u_point_index);
+
+ private:
+ const Persistence_graph& g;
+ const double r;
+ Kd_tree kd_t;
+ std::unordered_set<int> projections_f;
+};
+
+/** \internal \brief data structure used to find any point (including projections) in V near to a query point from U
+ * (which can be a projection) in a layered graph layer given as parmeter.
+ *
+ * V points have to be added manually using their index and before the first pull. A neighbor pulled is automatically
+ * removed.
+ *
+ * \ingroup bottleneck_distance
+ */
+class Layered_neighbors_finder {
+ public:
+ /** \internal \brief Constructor taking the near distance definition as parameter. */
+ Layered_neighbors_finder(const Persistence_graph& g, double r);
+ /** \internal \brief A point added will be possibly pulled. */
+ void add(int v_point_index, int vlayer);
+ /** \internal \brief Returns and remove a V point near to the U point given as parameter, null_point_index() if
+ * there isn't such a point. */
+ int pull_near(int u_point_index, int vlayer);
+ /** \internal \brief Returns the number of layers. */
+ int vlayers_number() const;
+
+ private:
+ const Persistence_graph& g;
+ const double r;
+ std::vector<std::unique_ptr<Neighbors_finder>> neighbors_finder;
+};
+
+inline Neighbors_finder::Neighbors_finder(const Persistence_graph& g, double r) :
+ g(g), r(r), kd_t(), projections_f() { }
+
+inline void Neighbors_finder::add(int v_point_index) {
+ if (g.on_the_v_diagonal(v_point_index))
+ projections_f.emplace(v_point_index);
+ else
+ kd_t.insert(g.get_v_point(v_point_index));
+}
+
+inline int Neighbors_finder::pull_near(int u_point_index) {
+ int tmp;
+ int c = g.corresponding_point_in_v(u_point_index);
+ if (g.on_the_u_diagonal(u_point_index) && !projections_f.empty()) {
+ // Any pair of projection is at distance 0
+ tmp = *projections_f.cbegin();
+ projections_f.erase(tmp);
+ } else if (projections_f.count(c) && (g.distance(u_point_index, c) <= r)) {
+ // Is the query point near to its projection ?
+ tmp = c;
+ projections_f.erase(tmp);
+ } else {
+ // Is the query point near to a V point in the plane ?
+ Internal_point u_point = g.get_u_point(u_point_index);
+ auto neighbor = kd_t.search_any_point(Square_query{u_point, r});
+ if (!neighbor)
+ return null_point_index();
+ tmp = neighbor->point_index;
+ auto point = g.get_v_point(tmp);
+ int idx = point.point_index;
+ kd_t.remove(point, [idx](Internal_point const&p){return p.point_index == idx;});
+ }
+ return tmp;
+}
+
+inline std::vector<int> Neighbors_finder::pull_all_near(int u_point_index) {
+ std::vector<int> all_pull;
+ int last_pull = pull_near(u_point_index);
+ while (last_pull != null_point_index()) {
+ all_pull.emplace_back(last_pull);
+ last_pull = pull_near(u_point_index);
+ }
+ return all_pull;
+}
+
+inline Layered_neighbors_finder::Layered_neighbors_finder(const Persistence_graph& g, double r) :
+ g(g), r(r), neighbors_finder() { }
+
+inline void Layered_neighbors_finder::add(int v_point_index, int vlayer) {
+ for (int l = neighbors_finder.size(); l <= vlayer; l++)
+ neighbors_finder.emplace_back(std::unique_ptr<Neighbors_finder>(new Neighbors_finder(g, r)));
+ neighbors_finder.at(vlayer)->add(v_point_index);
+}
+
+inline int Layered_neighbors_finder::pull_near(int u_point_index, int vlayer) {
+ if (static_cast<int> (neighbors_finder.size()) <= vlayer)
+ return null_point_index();
+ return neighbors_finder.at(vlayer)->pull_near(u_point_index);
+}
+
+inline int Layered_neighbors_finder::vlayers_number() const {
+ return static_cast<int> (neighbors_finder.size());
+}
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // NEIGHBORS_FINDER_H_
diff --git a/src/Bottleneck_distance/include/gudhi/Persistence_graph.h b/src/Bottleneck_distance/include/gudhi/Persistence_graph.h
new file mode 100644
index 00000000..f791e37c
--- /dev/null
+++ b/src/Bottleneck_distance/include/gudhi/Persistence_graph.h
@@ -0,0 +1,176 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#ifndef PERSISTENCE_GRAPH_H_
+#define PERSISTENCE_GRAPH_H_
+
+#include <gudhi/Internal_point.h>
+
+#ifdef GUDHI_USE_TBB
+#include <tbb/parallel_sort.h>
+#endif
+
+#include <vector>
+#include <algorithm>
+#include <limits> // for numeric_limits
+
+namespace Gudhi {
+
+namespace persistence_diagram {
+
+/** \internal \brief Structure representing an euclidean bipartite graph containing
+ * the points from the two persistence diagrams (including the projections).
+ *
+ * \ingroup bottleneck_distance
+ */
+class Persistence_graph {
+ public:
+ /** \internal \brief Constructor taking 2 PersistenceDiagrams (concept) as parameters. */
+ template<typename Persistence_diagram1, typename Persistence_diagram2>
+ Persistence_graph(const Persistence_diagram1& diag1, const Persistence_diagram2& diag2, double e);
+ /** \internal \brief Is the given point from U the projection of a point in V ? */
+ bool on_the_u_diagonal(int u_point_index) const;
+ /** \internal \brief Is the given point from V the projection of a point in U ? */
+ bool on_the_v_diagonal(int v_point_index) const;
+ /** \internal \brief Given a point from V, returns the corresponding (projection or projector) point in U. */
+ int corresponding_point_in_u(int v_point_index) const;
+ /** \internal \brief Given a point from U, returns the corresponding (projection or projector) point in V. */
+ int corresponding_point_in_v(int u_point_index) const;
+ /** \internal \brief Given a point from U and a point from V, returns the distance between those points. */
+ double distance(int u_point_index, int v_point_index) const;
+ /** \internal \brief Returns size = |U| = |V|. */
+ int size() const;
+ /** \internal \brief Is there as many infinite points (alive components) in both diagrams ? */
+ double bottleneck_alive() const;
+ /** \internal \brief Returns the O(n^2) sorted distances between the points. */
+ std::vector<double> sorted_distances() const;
+ /** \internal \brief Returns an upper bound for the diameter of the convex hull of all non infinite points */
+ double diameter_bound() const;
+ /** \internal \brief Returns the corresponding internal point */
+ Internal_point get_u_point(int u_point_index) const;
+ /** \internal \brief Returns the corresponding internal point */
+ Internal_point get_v_point(int v_point_index) const;
+
+ private:
+ std::vector<Internal_point> u;
+ std::vector<Internal_point> v;
+ double b_alive;
+};
+
+template<typename Persistence_diagram1, typename Persistence_diagram2>
+Persistence_graph::Persistence_graph(const Persistence_diagram1 &diag1,
+ const Persistence_diagram2 &diag2, double e)
+ : u(), v(), b_alive(0.) {
+ std::vector<double> u_alive;
+ std::vector<double> v_alive;
+ for (auto it = std::begin(diag1); it != std::end(diag1); ++it) {
+ if (std::get<1>(*it) == std::numeric_limits<double>::infinity())
+ u_alive.push_back(std::get<0>(*it));
+ else if (std::get<1>(*it) - std::get<0>(*it) > e)
+ u.push_back(Internal_point(std::get<0>(*it), std::get<1>(*it), u.size()));
+ }
+ for (auto it = std::begin(diag2); it != std::end(diag2); ++it) {
+ if (std::get<1>(*it) == std::numeric_limits<double>::infinity())
+ v_alive.push_back(std::get<0>(*it));
+ else if (std::get<1>(*it) - std::get<0>(*it) > e)
+ v.push_back(Internal_point(std::get<0>(*it), std::get<1>(*it), v.size()));
+ }
+ if (u.size() < v.size())
+ swap(u, v);
+ std::sort(u_alive.begin(), u_alive.end());
+ std::sort(v_alive.begin(), v_alive.end());
+ if (u_alive.size() != v_alive.size()) {
+ b_alive = std::numeric_limits<double>::infinity();
+ } else {
+ for (auto it_u = u_alive.cbegin(), it_v = v_alive.cbegin(); it_u != u_alive.cend(); ++it_u, ++it_v)
+ b_alive = (std::max)(b_alive, std::fabs(*it_u - *it_v));
+ }
+}
+
+inline bool Persistence_graph::on_the_u_diagonal(int u_point_index) const {
+ return u_point_index >= static_cast<int> (u.size());
+}
+
+inline bool Persistence_graph::on_the_v_diagonal(int v_point_index) const {
+ return v_point_index >= static_cast<int> (v.size());
+}
+
+inline int Persistence_graph::corresponding_point_in_u(int v_point_index) const {
+ return on_the_v_diagonal(v_point_index) ?
+ v_point_index - static_cast<int> (v.size()) : v_point_index + static_cast<int> (u.size());
+}
+
+inline int Persistence_graph::corresponding_point_in_v(int u_point_index) const {
+ return on_the_u_diagonal(u_point_index) ?
+ u_point_index - static_cast<int> (u.size()) : u_point_index + static_cast<int> (v.size());
+}
+
+inline double Persistence_graph::distance(int u_point_index, int v_point_index) const {
+ if (on_the_u_diagonal(u_point_index) && on_the_v_diagonal(v_point_index))
+ return 0.;
+ Internal_point p_u = get_u_point(u_point_index);
+ Internal_point p_v = get_v_point(v_point_index);
+ return (std::max)(std::fabs(p_u.x() - p_v.x()), std::fabs(p_u.y() - p_v.y()));
+}
+
+inline int Persistence_graph::size() const {
+ return static_cast<int> (u.size() + v.size());
+}
+
+inline double Persistence_graph::bottleneck_alive() const {
+ return b_alive;
+}
+
+inline std::vector<double> Persistence_graph::sorted_distances() const {
+ std::vector<double> distances;
+ distances.push_back(0.); // for empty diagrams
+ for (int u_point_index = 0; u_point_index < size(); ++u_point_index) {
+ distances.push_back(distance(u_point_index, corresponding_point_in_v(u_point_index)));
+ for (int v_point_index = 0; v_point_index < size(); ++v_point_index)
+ distances.push_back(distance(u_point_index, v_point_index));
+ }
+#ifdef GUDHI_USE_TBB
+ tbb::parallel_sort(distances.begin(), distances.end());
+#else
+ std::sort(distances.begin(), distances.end());
+#endif
+ return distances;
+}
+
+inline Internal_point Persistence_graph::get_u_point(int u_point_index) const {
+ if (!on_the_u_diagonal(u_point_index))
+ return u.at(u_point_index);
+ Internal_point projector = v.at(corresponding_point_in_v(u_point_index));
+ double m = (projector.x() + projector.y()) / 2.;
+ return Internal_point(m, m, u_point_index);
+}
+
+inline Internal_point Persistence_graph::get_v_point(int v_point_index) const {
+ if (!on_the_v_diagonal(v_point_index))
+ return v.at(v_point_index);
+ Internal_point projector = u.at(corresponding_point_in_u(v_point_index));
+ double m = (projector.x() + projector.y()) / 2.;
+ return Internal_point(m, m, v_point_index);
+}
+
+inline double Persistence_graph::diameter_bound() const {
+ double max = 0.;
+ for (auto it = u.cbegin(); it != u.cend(); it++)
+ max = (std::max)(max, it->y());
+ for (auto it = v.cbegin(); it != v.cend(); it++)
+ max = (std::max)(max, it->y());
+ return max;
+}
+
+} // namespace persistence_diagram
+
+} // namespace Gudhi
+
+#endif // PERSISTENCE_GRAPH_H_
diff --git a/src/Bottleneck_distance/test/CMakeLists.txt b/src/Bottleneck_distance/test/CMakeLists.txt
new file mode 100644
index 00000000..ec2d045f
--- /dev/null
+++ b/src/Bottleneck_distance/test/CMakeLists.txt
@@ -0,0 +1,14 @@
+project(Bottleneck_distance_tests)
+
+if (NOT CGAL_VERSION VERSION_LESS 4.11.0)
+ include(GUDHI_test_coverage)
+
+ add_executable ( Bottleneck_distance_test_unit bottleneck_unit_test.cpp )
+ target_link_libraries(Bottleneck_distance_test_unit ${Boost_UNIT_TEST_FRAMEWORK_LIBRARY})
+ if (TBB_FOUND)
+ target_link_libraries(Bottleneck_distance_test_unit ${TBB_LIBRARIES})
+ endif(TBB_FOUND)
+
+ gudhi_add_coverage_test(Bottleneck_distance_test_unit)
+
+endif (NOT CGAL_VERSION VERSION_LESS 4.11.0)
diff --git a/src/Bottleneck_distance/test/README b/src/Bottleneck_distance/test/README
new file mode 100644
index 00000000..00bd9a91
--- /dev/null
+++ b/src/Bottleneck_distance/test/README
@@ -0,0 +1,12 @@
+To compile:
+***********
+
+cmake .
+make
+
+To launch with details:
+***********************
+
+./Bottleneck_distance_unit_test --report_level=detailed --log_level=all
+
+ ==> echo $? returns 0 in case of success (non-zero otherwise)
diff --git a/src/Bottleneck_distance/test/bottleneck_unit_test.cpp b/src/Bottleneck_distance/test/bottleneck_unit_test.cpp
new file mode 100644
index 00000000..3fc6fc7b
--- /dev/null
+++ b/src/Bottleneck_distance/test/bottleneck_unit_test.cpp
@@ -0,0 +1,155 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Author: Francois Godi
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+
+#define BOOST_TEST_DYN_LINK
+#define BOOST_TEST_MODULE "bottleneck distance"
+#include <boost/test/unit_test.hpp>
+
+#include <random>
+#include <gudhi/Bottleneck.h>
+
+using namespace Gudhi::persistence_diagram;
+
+int n1 = 81; // a natural number >0
+int n2 = 180; // a natural number >0
+double upper_bound = 406.43; // any real >0
+
+
+std::uniform_real_distribution<double> unif(0., upper_bound);
+std::default_random_engine re;
+std::vector< std::pair<double, double> > v1, v2;
+
+BOOST_AUTO_TEST_CASE(persistence_graph) {
+ // Random construction
+ for (int i = 0; i < n1; i++) {
+ double a = unif(re);
+ double b = unif(re);
+ v1.emplace_back(std::min(a, b), std::max(a, b));
+ }
+ for (int i = 0; i < n2; i++) {
+ double a = unif(re);
+ double b = unif(re);
+ v2.emplace_back(std::min(a, b), std::max(a, b));
+ }
+ Persistence_graph g(v1, v2, 0.);
+ std::vector<double> d(g.sorted_distances());
+ //
+ BOOST_CHECK(!g.on_the_u_diagonal(n1 - 1));
+ BOOST_CHECK(!g.on_the_u_diagonal(n1));
+ BOOST_CHECK(!g.on_the_u_diagonal(n2 - 1));
+ BOOST_CHECK(g.on_the_u_diagonal(n2));
+ BOOST_CHECK(!g.on_the_v_diagonal(n1 - 1));
+ BOOST_CHECK(g.on_the_v_diagonal(n1));
+ BOOST_CHECK(g.on_the_v_diagonal(n2 - 1));
+ BOOST_CHECK(g.on_the_v_diagonal(n2));
+ //
+ BOOST_CHECK(g.corresponding_point_in_u(0) == n2);
+ BOOST_CHECK(g.corresponding_point_in_u(n1) == 0);
+ BOOST_CHECK(g.corresponding_point_in_v(0) == n1);
+ BOOST_CHECK(g.corresponding_point_in_v(n2) == 0);
+ //
+ BOOST_CHECK(g.size() == (n1 + n2));
+ //
+ BOOST_CHECK((int) d.size() == (n1 + n2)*(n1 + n2) + n1 + n2 + 1);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, 0)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n1 - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n2 - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, n2)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(0, (n1 + n2) - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, 0)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n1 - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n2 - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, n2)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance(n1, (n1 + n2) - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, 0)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n1 - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n2 - 1)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, n2)) > 0);
+ BOOST_CHECK(std::count(d.begin(), d.end(), g.distance((n1 + n2) - 1, (n1 + n2) - 1)) > 0);
+}
+
+BOOST_AUTO_TEST_CASE(neighbors_finder) {
+ Persistence_graph g(v1, v2, 0.);
+ Neighbors_finder nf(g, 1.);
+ for (int v_point_index = 1; v_point_index < ((n2 + n1)*9 / 10); v_point_index += 2)
+ nf.add(v_point_index);
+ //
+ int v_point_index_1 = nf.pull_near(n2 / 2);
+ BOOST_CHECK((v_point_index_1 == -1) || (g.distance(n2 / 2, v_point_index_1) <= 1.));
+ std::vector<int> l = nf.pull_all_near(n2 / 2);
+ bool v = true;
+ for (auto it = l.cbegin(); it != l.cend(); ++it)
+ v = v && (g.distance(n2 / 2, *it) > 1.);
+ BOOST_CHECK(v);
+ int v_point_index_2 = nf.pull_near(n2 / 2);
+ BOOST_CHECK(v_point_index_2 == -1);
+}
+
+BOOST_AUTO_TEST_CASE(layered_neighbors_finder) {
+ Persistence_graph g(v1, v2, 0.);
+ Layered_neighbors_finder lnf(g, 1.);
+ for (int v_point_index = 1; v_point_index < ((n2 + n1)*9 / 10); v_point_index += 2)
+ lnf.add(v_point_index, v_point_index % 7);
+ //
+ int v_point_index_1 = lnf.pull_near(n2 / 2, 6);
+ BOOST_CHECK((v_point_index_1 == -1) || (g.distance(n2 / 2, v_point_index_1) <= 1.));
+ int v_point_index_2 = lnf.pull_near(n2 / 2, 6);
+ BOOST_CHECK(v_point_index_2 == -1);
+ v_point_index_1 = lnf.pull_near(n2 / 2, 0);
+ BOOST_CHECK((v_point_index_1 == -1) || (g.distance(n2 / 2, v_point_index_1) <= 1.));
+ v_point_index_2 = lnf.pull_near(n2 / 2, 0);
+ BOOST_CHECK(v_point_index_2 == -1);
+}
+
+BOOST_AUTO_TEST_CASE(graph_matching) {
+ Persistence_graph g(v1, v2, 0.);
+ Graph_matching m1(g);
+ m1.set_r(0.);
+ int e = 0;
+ while (m1.multi_augment())
+ ++e;
+ BOOST_CHECK(e > 0);
+ BOOST_CHECK(e <= 2 * sqrt(2 * (n1 + n2)));
+ Graph_matching m2 = m1;
+ BOOST_CHECK(!m2.multi_augment());
+ m2.set_r(upper_bound);
+ e = 0;
+ while (m2.multi_augment())
+ ++e;
+ BOOST_CHECK(e <= 2 * sqrt(2 * (n1 + n2)));
+ BOOST_CHECK(m2.perfect());
+ BOOST_CHECK(!m1.perfect());
+}
+
+BOOST_AUTO_TEST_CASE(global) {
+ std::uniform_real_distribution<double> unif1(0., upper_bound);
+ std::uniform_real_distribution<double> unif2(upper_bound / 10000., upper_bound / 100.);
+ std::default_random_engine re;
+ std::vector< std::pair<double, double> > v1, v2;
+ for (int i = 0; i < n1; i++) {
+ double a = unif1(re);
+ double b = unif1(re);
+ double x = unif2(re);
+ double y = unif2(re);
+ v1.emplace_back(std::min(a, b), std::max(a, b));
+ v2.emplace_back(std::min(a, b) + std::min(x, y), std::max(a, b) + std::max(x, y));
+ if (i % 5 == 0)
+ v1.emplace_back(std::min(a, b), std::min(a, b) + x);
+ if (i % 3 == 0)
+ v2.emplace_back(std::max(a, b), std::max(a, b) + y);
+ }
+ BOOST_CHECK(bottleneck_distance(v1, v2, 0.) <= upper_bound / 100.);
+ BOOST_CHECK(bottleneck_distance(v1, v2, upper_bound / 10000.) <= upper_bound / 100. + upper_bound / 10000.);
+ BOOST_CHECK(std::abs(bottleneck_distance(v1, v2, 0.) - bottleneck_distance(v1, v2, upper_bound / 10000.)) <= upper_bound / 10000.);
+}
diff --git a/src/Bottleneck_distance/utilities/CMakeLists.txt b/src/Bottleneck_distance/utilities/CMakeLists.txt
new file mode 100644
index 00000000..86d74cf5
--- /dev/null
+++ b/src/Bottleneck_distance/utilities/CMakeLists.txt
@@ -0,0 +1,15 @@
+project(Bottleneck_distance_utilities)
+
+if(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0)
+ add_executable (bottleneck_distance bottleneck_distance.cpp)
+ if (TBB_FOUND)
+ target_link_libraries(bottleneck_distance ${TBB_LIBRARIES})
+ endif(TBB_FOUND)
+
+ add_test(NAME Bottleneck_distance_utilities_Bottleneck_read_file
+ COMMAND $<TARGET_FILE:bottleneck_distance>
+ "${CMAKE_SOURCE_DIR}/data/persistence_diagram/first.pers" "${CMAKE_SOURCE_DIR}/data/persistence_diagram/second.pers")
+
+ install(TARGETS bottleneck_distance DESTINATION bin)
+
+endif(NOT CGAL_WITH_EIGEN3_VERSION VERSION_LESS 4.11.0)
diff --git a/src/Bottleneck_distance/utilities/bottleneck_distance.cpp b/src/Bottleneck_distance/utilities/bottleneck_distance.cpp
new file mode 100644
index 00000000..d88a8a0b
--- /dev/null
+++ b/src/Bottleneck_distance/utilities/bottleneck_distance.cpp
@@ -0,0 +1,38 @@
+/* This file is part of the Gudhi Library - https://gudhi.inria.fr/ - which is released under MIT.
+ * See file LICENSE or go to https://gudhi.inria.fr/licensing/ for full license details.
+ * Authors: Francois Godi, small modifications by Pawel Dlotko
+ *
+ * Copyright (C) 2015 Inria
+ *
+ * Modification(s):
+ * - YYYY/MM Author: Description of the modification
+ */
+
+#include <gudhi/Bottleneck.h>
+#include <gudhi/reader_utils.h>
+#include <iostream>
+#include <vector>
+#include <utility> // for pair
+#include <string>
+#include <limits> // for numeric_limits
+
+int main(int argc, char** argv) {
+ if (argc < 3) {
+ std::cout << "To run this program please provide as an input two files with persistence diagrams. Each file" <<
+ " should contain a birth-death pair per line. Third, optional parameter is an error bound on the bottleneck" <<
+ " distance (set by default to the smallest positive double value). If you set the error bound to 0, be" <<
+ " aware this version is exact but expensive. The program will now terminate \n";
+ return -1;
+ }
+ std::vector<std::pair<double, double>> diag1 = Gudhi::read_persistence_intervals_in_dimension(argv[1]);
+ std::vector<std::pair<double, double>> diag2 = Gudhi::read_persistence_intervals_in_dimension(argv[2]);
+
+ double tolerance = std::numeric_limits<double>::min();
+ if (argc == 4) {
+ tolerance = atof(argv[3]);
+ }
+ double b = Gudhi::persistence_diagram::bottleneck_distance(diag1, diag2, tolerance);
+ std::cout << "The distance between the diagrams is : " << b << ". The tolerance is : " << tolerance << std::endl;
+
+ return 0;
+}
diff --git a/src/Bottleneck_distance/utilities/bottleneckdistance.md b/src/Bottleneck_distance/utilities/bottleneckdistance.md
new file mode 100644
index 00000000..a81426cf
--- /dev/null
+++ b/src/Bottleneck_distance/utilities/bottleneckdistance.md
@@ -0,0 +1,26 @@
+---
+layout: page
+title: "Bottleneck distance"
+meta_title: "Bottleneck distance"
+teaser: ""
+permalink: /bottleneckdistance/
+---
+{::comment}
+Leave the lines above as it is required by the web site generator 'Jekyll'
+{:/comment}
+
+
+## bottleneck_read_file_example ##
+
+This program computes the Bottleneck distance between two persistence diagram files.
+
+**Usage**
+
+```
+ bottleneck_read_file_example <file_1.pers> <file_2.pers> [<tolerance>]
+```
+
+where
+
+* `<file_1.pers>` and `<file_2.pers>` must be in the format described [here]({{ site.officialurl }}/doc/latest/fileformats.html#FileFormatsPers).
+* `<tolerance>` is an error bound on the bottleneck distance (set by default to the smallest positive double value).