1 files changed, 82 insertions, 0 deletions
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..5e3be880
--- /dev/null
+++ b/src/Persistence_representations/example/persistence_heat_maps.cpp
@@ -0,0 +1,82 @@
+/*    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 <http://www.gnu.org/licenses/>.
+ */
+
+#include <gudhi/reader_utils.h>
+#include <gudhi/Persistence_heat_maps.h>
+
+#include <iostream>
+#include <vector>
+
+using namespace Gudhi;
+using namespace Gudhi::Persistence_representations;
+
+double epsilon = 0.0000005;
+
+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 = create_Gaussian_filter(5, 1);
+
+  // creating two heat maps.
+  Persistence_heat_maps<constant_scaling_function> hm1(persistence1, filter, false, 20, 0, 11);
+  Persistence_heat_maps<constant_scaling_function> hm2(persistence2, filter, false, 20, 0, 11);
+
+  std::vector<Persistence_heat_maps<constant_scaling_function>*> 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<constant_scaling_function> mean;
+  mean.compute_mean(vector_of_maps);
+  Persistence_heat_maps<constant_scaling_function> 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<constant_scaling_function>*> to_average;
+  to_average.push_back(&hm1);
+  to_average.push_back(&hm2);
+  Persistence_heat_maps<constant_scaling_function> 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;
+}