From 9899ae167f281d10b1684dfcd02c6838c5bf28df Mon Sep 17 00:00:00 2001 From: Gard Spreemann Date: Fri, 2 Feb 2018 13:51:45 +0100 Subject: GUDHI 2.1.0 as released by upstream in a tarball. --- .../persistence_heat_maps.cpp | 80 ++++++++++++++++++++++ 1 file changed, 80 insertions(+) create mode 100644 example/Persistence_representations/persistence_heat_maps.cpp (limited to 'example/Persistence_representations/persistence_heat_maps.cpp') diff --git a/example/Persistence_representations/persistence_heat_maps.cpp b/example/Persistence_representations/persistence_heat_maps.cpp new file mode 100644 index 00000000..2a472ac6 --- /dev/null +++ b/example/Persistence_representations/persistence_heat_maps.cpp @@ -0,0 +1,80 @@ +/* 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): Pawel Dlotko + * + * Copyright (C) 2016 INRIA (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 . + */ + +#include + +#include +#include +#include + +using constant_scaling_function = Gudhi::Persistence_representations::constant_scaling_function; +using Persistence_heat_maps = Gudhi::Persistence_representations::Persistence_heat_maps; + +int main(int argc, char** argv) { + // create two simple vectors with birth--death pairs: + + std::vector > persistence1; + std::vector > 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 > 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 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 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; + + return 0; +} -- cgit v1.2.3