diff options
Diffstat (limited to 'src/Persistence_representations/example')
7 files changed, 451 insertions, 0 deletions
diff --git a/src/Persistence_representations/example/CMakeLists.txt b/src/Persistence_representations/example/CMakeLists.txt new file mode 100644 index 00000000..a7c6ef39 --- /dev/null +++ b/src/Persistence_representations/example/CMakeLists.txt @@ -0,0 +1,32 @@ +project(Persistence_representations_example) + +add_executable ( Persistence_representations_example_landscape_on_grid persistence_landscape_on_grid.cpp ) +add_test(NAME Persistence_representations_example_landscape_on_grid + COMMAND $<TARGET_FILE:Persistence_representations_example_landscape_on_grid>) +install(TARGETS Persistence_representations_example_landscape_on_grid DESTINATION bin) + +add_executable ( Persistence_representations_example_landscape persistence_landscape.cpp ) +add_test(NAME Persistence_representations_example_landscape + COMMAND $<TARGET_FILE:Persistence_representations_example_landscape>) +install(TARGETS Persistence_representations_example_landscape DESTINATION bin) + +add_executable ( Persistence_representations_example_intervals persistence_intervals.cpp ) +add_test(NAME Persistence_representations_example_intervals + COMMAND $<TARGET_FILE:Persistence_representations_example_intervals> + "${CMAKE_SOURCE_DIR}/data/persistence_diagram/first.pers") +install(TARGETS Persistence_representations_example_intervals DESTINATION bin) + +add_executable ( Persistence_representations_example_vectors persistence_vectors.cpp ) +add_test(NAME Persistence_representations_example_vectors + COMMAND $<TARGET_FILE:Persistence_representations_example_vectors>) +install(TARGETS Persistence_representations_example_vectors DESTINATION bin) + +add_executable ( Persistence_representations_example_heat_maps persistence_heat_maps.cpp ) +add_test(NAME Persistence_representations_example_heat_maps + COMMAND $<TARGET_FILE:Persistence_representations_example_heat_maps>) +install(TARGETS Persistence_representations_example_heat_maps DESTINATION bin) + +add_executable ( Sliced_Wasserstein sliced_wasserstein.cpp ) +add_test(NAME Sliced_Wasserstein + COMMAND $<TARGET_FILE:Sliced_Wasserstein>) +install(TARGETS Sliced_Wasserstein DESTINATION bin) diff --git a/src/Persistence_representations/example/persistence_heat_maps.cpp b/src/Persistence_representations/example/persistence_heat_maps.cpp new file mode 100644 index 00000000..1bf3a637 --- /dev/null +++ b/src/Persistence_representations/example/persistence_heat_maps.cpp @@ -0,0 +1,89 @@ +/* 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): Pawel Dlotko and Mathieu Carriere + * + * Copyright (C) 2019 Inria + * + * Modifications: + * - 2018/04 MC: Add persistence heat maps computation + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <gudhi/Persistence_heat_maps.h> +#include <gudhi/common_persistence_representations.h> + +#include <iostream> +#include <vector> +#include <utility> +#include <functional> +#include <cmath> + +std::function<double(std::pair<double, double>, std::pair<double, double>)> Gaussian_function(double sigma) { + return [=](std::pair<double, double> p, std::pair<double, double> q) { + return std::exp(-((p.first - q.first) * (p.first - q.first) + (p.second - q.second) * (p.second - q.second)) / + (sigma)); + }; +} + +using constant_scaling_function = Gudhi::Persistence_representations::constant_scaling_function; +using Persistence_heat_maps = Gudhi::Persistence_representations::Persistence_heat_maps<constant_scaling_function>; + +int main(int argc, char** argv) { + // create two simple vectors with birth--death pairs: + + std::vector<std::pair<double, double> > persistence1; + std::vector<std::pair<double, double> > persistence2; + + persistence1.push_back(std::make_pair(1, 2)); + persistence1.push_back(std::make_pair(6, 8)); + persistence1.push_back(std::make_pair(0, 4)); + persistence1.push_back(std::make_pair(3, 8)); + + persistence2.push_back(std::make_pair(2, 9)); + persistence2.push_back(std::make_pair(1, 6)); + persistence2.push_back(std::make_pair(3, 5)); + persistence2.push_back(std::make_pair(6, 10)); + + // over here we define a function we sill put on a top on every birth--death pair in the persistence interval. It can + // be anything. Over here we will use standard Gaussian + std::vector<std::vector<double> > filter = Gudhi::Persistence_representations::create_Gaussian_filter(5, 1); + + // creating two heat maps. + Persistence_heat_maps hm1(persistence1, filter, false, 20, 0, 11); + Persistence_heat_maps hm2(persistence2, filter, false, 20, 0, 11); + + std::vector<Persistence_heat_maps*> vector_of_maps; + vector_of_maps.push_back(&hm1); + vector_of_maps.push_back(&hm2); + + // compute median/mean of a vector of heat maps: + Persistence_heat_maps mean; + mean.compute_mean(vector_of_maps); + Persistence_heat_maps median; + median.compute_median(vector_of_maps); + + // to compute L^1 distance between hm1 and hm2: + std::cout << "The L^1 distance is : " << hm1.distance(hm2, 1) << std::endl; + + // to average of hm1 and hm2: + std::vector<Persistence_heat_maps*> to_average; + to_average.push_back(&hm1); + to_average.push_back(&hm2); + Persistence_heat_maps av; + av.compute_average(to_average); + + // to compute scalar product of hm1 and hm2: + std::cout << "Scalar product is : " << hm1.compute_scalar_product(hm2) << std::endl; + + Persistence_heat_maps hm1k(persistence1, Gaussian_function(1.0)); + Persistence_heat_maps hm2k(persistence2, Gaussian_function(1.0)); + Persistence_heat_maps hm1i(persistence1, Gaussian_function(1.0), 20, 20, 0, 11, 0, 11); + Persistence_heat_maps hm2i(persistence2, Gaussian_function(1.0), 20, 20, 0, 11, 0, 11); + std::cout << "Scalar product computed with exact 2D kernel on grid is : " << hm1i.compute_scalar_product(hm2i) + << std::endl; + std::cout << "Scalar product computed with exact 2D kernel is : " << hm1k.compute_scalar_product(hm2k) << std::endl; + + return 0; +} diff --git a/src/Persistence_representations/example/persistence_intervals.cpp b/src/Persistence_representations/example/persistence_intervals.cpp new file mode 100644 index 00000000..c908581c --- /dev/null +++ b/src/Persistence_representations/example/persistence_intervals.cpp @@ -0,0 +1,77 @@ +/* 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): Pawel Dlotko + * + * Copyright (C) 2016 Inria + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <gudhi/Persistence_intervals.h> + +#include <iostream> +#include <utility> +#include <vector> + +using Persistence_intervals = Gudhi::Persistence_representations::Persistence_intervals; + +int main(int argc, char** argv) { + if (argc != 2) { + std::cout << "To run this program, please provide the name of a file with persistence diagram \n"; + return 1; + } + + Persistence_intervals p(argv[1]); + std::pair<double, double> min_max_ = p.get_x_range(); + std::cout << "Birth-death range : " << min_max_.first << " " << min_max_.second << std::endl; + + std::vector<double> dominant_ten_intervals_length = p.length_of_dominant_intervals(10); + std::cout << "Length of ten dominant intervals : " << std::endl; + for (size_t i = 0; i != dominant_ten_intervals_length.size(); ++i) { + std::cout << dominant_ten_intervals_length[i] << std::endl; + } + + std::vector<std::pair<double, double> > ten_dominant_intervals = p.dominant_intervals(10); + std::cout << "Here are the dominant intervals : " << std::endl; + for (size_t i = 0; i != ten_dominant_intervals.size(); ++i) { + std::cout << "( " << ten_dominant_intervals[i].first << "," << ten_dominant_intervals[i].second << std::endl; + } + + std::vector<size_t> histogram = p.histogram_of_lengths(10); + std::cout << "Here is the histogram of barcode's length : " << std::endl; + for (size_t i = 0; i != histogram.size(); ++i) { + std::cout << histogram[i] << " "; + } + std::cout << std::endl; + + std::vector<size_t> cumulative_histogram = p.cumulative_histogram_of_lengths(10); + std::cout << "Cumulative histogram : " << std::endl; + for (size_t i = 0; i != cumulative_histogram.size(); ++i) { + std::cout << cumulative_histogram[i] << " "; + } + std::cout << std::endl; + + std::vector<double> char_funct_diag = p.characteristic_function_of_diagram(min_max_.first, min_max_.second); + std::cout << "Characteristic function of diagram : " << std::endl; + for (size_t i = 0; i != char_funct_diag.size(); ++i) { + std::cout << char_funct_diag[i] << " "; + } + std::cout << std::endl; + + std::vector<double> cumul_char_funct_diag = + p.cumulative_characteristic_function_of_diagram(min_max_.first, min_max_.second); + std::cout << "Cumulative characteristic function of diagram : " << std::endl; + for (size_t i = 0; i != cumul_char_funct_diag.size(); ++i) { + std::cout << cumul_char_funct_diag[i] << " "; + } + std::cout << std::endl; + + std::cout << "Persistence Betti numbers \n"; + std::vector<std::pair<double, size_t> > pbns = p.compute_persistent_betti_numbers(); + for (size_t i = 0; i != pbns.size(); ++i) { + std::cout << pbns[i].first << " " << pbns[i].second << std::endl; + } + + return 0; +} diff --git a/src/Persistence_representations/example/persistence_landscape.cpp b/src/Persistence_representations/example/persistence_landscape.cpp new file mode 100644 index 00000000..ff18d105 --- /dev/null +++ b/src/Persistence_representations/example/persistence_landscape.cpp @@ -0,0 +1,74 @@ +/* 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): Pawel Dlotko + * + * Copyright (C) 2016 Inria + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <gudhi/Persistence_landscape.h> + +#include <iostream> +#include <vector> +#include <utility> + +using Persistence_landscape = Gudhi::Persistence_representations::Persistence_landscape; + +int main(int argc, char** argv) { + // create two simple vectors with birth--death pairs: + + std::vector<std::pair<double, double> > persistence1; + std::vector<std::pair<double, double> > persistence2; + + persistence1.push_back(std::make_pair(1, 2)); + persistence1.push_back(std::make_pair(6, 8)); + persistence1.push_back(std::make_pair(0, 4)); + persistence1.push_back(std::make_pair(3, 8)); + + persistence2.push_back(std::make_pair(2, 9)); + persistence2.push_back(std::make_pair(1, 6)); + persistence2.push_back(std::make_pair(3, 5)); + persistence2.push_back(std::make_pair(6, 10)); + + // create two persistence landscapes based on persistence1 and persistence2: + Persistence_landscape l1(persistence1); + Persistence_landscape l2(persistence2); + + // This is how to compute integral of landscapes: + std::cout << "Integral of the first landscape : " << l1.compute_integral_of_landscape() << std::endl; + std::cout << "Integral of the second landscape : " << l2.compute_integral_of_landscape() << std::endl; + + // And here how to write landscapes to stream: + std::cout << "l1 : " << l1 << std::endl; + std::cout << "l2 : " << l2 << std::endl; + + // Arithmetic operations on landscapes: + Persistence_landscape sum = l1 + l2; + std::cout << "sum : " << sum << std::endl; + + // here are the maxima of the functions: + std::cout << "Maximum of l1 : " << l1.compute_maximum() << std::endl; + std::cout << "Maximum of l2 : " << l2.compute_maximum() << std::endl; + + // here are the norms of landscapes: + std::cout << "L^1 Norm of l1 : " << l1.compute_norm_of_landscape(1.) << std::endl; + std::cout << "L^1 Norm of l2 : " << l2.compute_norm_of_landscape(1.) << std::endl; + + // here is the average of landscapes: + Persistence_landscape average; + average.compute_average({&l1, &l2}); + std::cout << "average : " << average << std::endl; + + // here is the distance of landscapes: + std::cout << "Distance : " << l1.distance(l2) << std::endl; + + // here is the scalar product of landscapes: + std::cout << "Scalar product : " << l1.compute_scalar_product(l2) << std::endl; + + // here is how to create a file which is suitable for visualization via gnuplot: + average.plot("average_landscape"); + + return 0; +} diff --git a/src/Persistence_representations/example/persistence_landscape_on_grid.cpp b/src/Persistence_representations/example/persistence_landscape_on_grid.cpp new file mode 100644 index 00000000..16a58e1d --- /dev/null +++ b/src/Persistence_representations/example/persistence_landscape_on_grid.cpp @@ -0,0 +1,70 @@ +/* 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): Pawel Dlotko + * + * Copyright (C) 2016 Inria + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <gudhi/Persistence_landscape_on_grid.h> + +#include <iostream> +#include <utility> +#include <vector> + +using Persistence_landscape_on_grid = Gudhi::Persistence_representations::Persistence_landscape_on_grid; + +int main(int argc, char** argv) { + // create two simple vectors with birth--death pairs: + + std::vector<std::pair<double, double> > persistence1; + std::vector<std::pair<double, double> > persistence2; + + persistence1.push_back(std::make_pair(1, 2)); + persistence1.push_back(std::make_pair(6, 8)); + persistence1.push_back(std::make_pair(0, 4)); + persistence1.push_back(std::make_pair(3, 8)); + + persistence2.push_back(std::make_pair(2, 9)); + persistence2.push_back(std::make_pair(1, 6)); + persistence2.push_back(std::make_pair(3, 5)); + persistence2.push_back(std::make_pair(6, 10)); + + // create two persistence landscapes based on persistence1 and persistence2: + Persistence_landscape_on_grid l1(persistence1, 0, 11, 20); + Persistence_landscape_on_grid l2(persistence2, 0, 11, 20); + + // This is how to compute integral of landscapes: + std::cout << "Integral of the first landscape : " << l1.compute_integral_of_landscape() << std::endl; + std::cout << "Integral of the second landscape : " << l2.compute_integral_of_landscape() << std::endl; + + // And here how to write landscapes to stream: + std::cout << "l1 : " << l1 << std::endl; + std::cout << "l2 : " << l2 << std::endl; + + // here are the maxima of the functions: + std::cout << "Maximum of l1 : " << l1.compute_maximum() << std::endl; + std::cout << "Maximum of l2 : " << l2.compute_maximum() << std::endl; + + // here are the norms of landscapes: + std::cout << "L^1 Norm of l1 : " << l1.compute_norm_of_landscape(1.) << std::endl; + std::cout << "L^1 Norm of l2 : " << l2.compute_norm_of_landscape(1.) << std::endl; + + // here is the average of landscapes: + Persistence_landscape_on_grid average; + average.compute_average({&l1, &l2}); + std::cout << "average : " << average << std::endl; + + // here is the distance of landscapes: + std::cout << "Distance : " << l1.distance(l2) << std::endl; + + // here is the scalar product of landscapes: + std::cout << "Scalar product : " << l1.compute_scalar_product(l2) << std::endl; + + // here is how to create a file which is suitable for visualization via gnuplot: + average.plot("average_landscape"); + + return 0; +} diff --git a/src/Persistence_representations/example/persistence_vectors.cpp b/src/Persistence_representations/example/persistence_vectors.cpp new file mode 100644 index 00000000..b27e52d2 --- /dev/null +++ b/src/Persistence_representations/example/persistence_vectors.cpp @@ -0,0 +1,62 @@ +/* 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): Pawel Dlotko + * + * Copyright (C) 2016 Inria + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <gudhi/Persistence_vectors.h> + +#include <iostream> +#include <vector> +#include <cmath> +#include <iomanip> +#include <limits> +#include <utility> + +using Vector_distances_in_diagram = + Gudhi::Persistence_representations::Vector_distances_in_diagram<Gudhi::Euclidean_distance>; + +int main(int argc, char** argv) { + // create two simple vectors with birth--death pairs: + + std::vector<std::pair<double, double> > persistence1; + std::vector<std::pair<double, double> > persistence2; + + persistence1.push_back(std::make_pair(1, 2)); + persistence1.push_back(std::make_pair(6, 8)); + persistence1.push_back(std::make_pair(0, 4)); + persistence1.push_back(std::make_pair(3, 8)); + + persistence2.push_back(std::make_pair(2, 9)); + persistence2.push_back(std::make_pair(1, 6)); + persistence2.push_back(std::make_pair(3, 5)); + persistence2.push_back(std::make_pair(6, 10)); + + // create two persistence vectors based on persistence1 and persistence2: + Vector_distances_in_diagram v1(persistence1, std::numeric_limits<size_t>::max()); + Vector_distances_in_diagram v2(persistence2, std::numeric_limits<size_t>::max()); + + // writing to a stream: + std::cout << "v1 : " << v1 << std::endl; + std::cout << "v2 : " << v2 << std::endl; + + // averages: + Vector_distances_in_diagram average; + average.compute_average({&v1, &v2}); + std::cout << "Average : " << average << std::endl; + + // computations of distances: + std::cout << "l^1 distance : " << v1.distance(v2) << std::endl; + + // computations of scalar product: + std::cout << "Scalar product of l1 and l2 : " << v1.compute_scalar_product(v2) << std::endl; + + // create a file with a gnuplot script: + v1.plot("plot_of_vector_representation"); + + return 0; +} diff --git a/src/Persistence_representations/example/sliced_wasserstein.cpp b/src/Persistence_representations/example/sliced_wasserstein.cpp new file mode 100644 index 00000000..d5414d00 --- /dev/null +++ b/src/Persistence_representations/example/sliced_wasserstein.cpp @@ -0,0 +1,47 @@ +/* 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): Mathieu Carriere + * + * Copyright (C) 2018 INRIA (France) + * + * Modification(s): + * - YYYY/MM Author: Description of the modification + */ + +#include <gudhi/Sliced_Wasserstein.h> + +#include <iostream> +#include <vector> +#include <utility> + +using Persistence_diagram = Gudhi::Persistence_representations::Persistence_diagram; +using SW = Gudhi::Persistence_representations::Sliced_Wasserstein; + +int main(int argc, char** argv) { + + Persistence_diagram persistence1, persistence2; + + persistence1.push_back(std::make_pair(1, 2)); + persistence1.push_back(std::make_pair(6, 8)); + persistence1.push_back(std::make_pair(0, 4)); + persistence1.push_back(std::make_pair(3, 8)); + + persistence2.push_back(std::make_pair(2, 9)); + persistence2.push_back(std::make_pair(1, 6)); + persistence2.push_back(std::make_pair(3, 5)); + persistence2.push_back(std::make_pair(6, 10)); + + + SW sw1(persistence1, 1, 100); + SW sw2(persistence2, 1, 100); + + SW swex1(persistence1, 1, -1); + SW swex2(persistence2, 1, -1); + + std::cout << "Approx SW kernel: " << sw1.compute_scalar_product(sw2) << std::endl; + std::cout << "Exact SW kernel: " << swex1.compute_scalar_product(swex2) << std::endl; + std::cout << "Distance induced by approx SW kernel: " << sw1.distance(sw2) << std::endl; + std::cout << "Distance induced by exact SW kernel: " << swex1.distance(swex2) << std::endl; + + return 0; +} |