1 files changed, 81 insertions, 0 deletions
diff --git a/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp b/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp
new file mode 100644
index 00000000..05bacb9f
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+++ b/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp
@@ -0,0 +1,81 @@
+#include <gudhi/Rips_complex.h>
+#include <gudhi/Simplex_tree.h>
+#include <gudhi/distance_functions.h>
+
+#include <iostream>
+#include <string>
+#include <vector>
+#include <limits>  // for std::numeric_limits
+
+int main() {
+  // Type definitions
+  using Simplex_tree = Gudhi::Simplex_tree<>;
+  using Filtration_value = Simplex_tree::Filtration_value;
+  using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>;
+  using Distance_matrix = std::vector<std::vector<Filtration_value>>;
+
+  // User defined correlation matrix is:
+  // |1     0.06  0.23  0.01  0.89|
+  // |0.06  1     0.74  0.01  0.61|
+  // |0.23  0.74  1     0.72  0.03|
+  // |0.01  0.01  0.72  1     0.7 |
+  // |0.89  0.61  0.03  0.7   1   |
+
+  Distance_matrix correlations;
+  correlations.push_back({});
+  correlations.push_back({0.06});
+  correlations.push_back({0.23, 0.74});
+  correlations.push_back({0.01, 0.01, 0.72});
+  correlations.push_back({0.89, 0.61, 0.03, 0.7});
+
+  // ----------------------------------------------------------------------------
+  // Convert correlation matrix to a distance matrix:
+  // ----------------------------------------------------------------------------
+  double threshold = 0;
+  for (size_t i = 0; i != correlations.size(); ++i) {
+    for (size_t j = 0; j != correlations[i].size(); ++j) {
+      // Here we check if our data comes from corelation matrix.
+      if ((correlations[i][j] < -1) || (correlations[i][j] > 1)) {
+        std::cerr << "The input matrix is not a correlation matrix. The program will now terminate.\n";
+        throw "The input matrix is not a correlation matrix. The program will now terminate.\n";
+      }
+      correlations[i][j] = 1 - correlations[i][j];
+      // Here we make sure that we will get the treshold value equal to maximal
+      // distance in the matrix.
+      if (correlations[i][j] > threshold) threshold = correlations[i][j];
+    }
+  }
+
+  //-----------------------------------------------------------------------------
+  // Now the correlation matrix is a distance matrix and can be processed further.
+  //-----------------------------------------------------------------------------
+  Distance_matrix distances = correlations;
+
+  Rips_complex rips_complex_from_points(distances, threshold);
+
+  Simplex_tree stree;
+  rips_complex_from_points.create_complex(stree, 1);
+  // ----------------------------------------------------------------------------
+  // Display information about the one skeleton Rips complex. Note that
+  // the filtration displayed here comes from the distance matrix computed
+  // above, which is 1 - initial correlation matrix. Only this way, we obtain
+  // a complex with filtration. If a correlation matrix is used instead, we would
+  // have a reverse filtration (i.e. filtration of boundary of each simplex S
+  // is greater or equal to the filtration of S).
+  // ----------------------------------------------------------------------------
+  std::cout << "Rips complex is of dimension " << stree.dimension() << " - " << stree.num_simplices() << " simplices - "
+            << stree.num_vertices() << " vertices." << std::endl;
+
+  std::cout << "Iterator on Rips complex simplices in the filtration order, with [filtration value]:" << std::endl;
+  for (auto f_simplex : stree.filtration_simplex_range()) {
+    std::cout << "   ( ";
+    for (auto vertex : stree.simplex_vertex_range(f_simplex)) {
+      std::cout << vertex << " ";
+    }
+    std::cout << ") -> "
+              << "[" << stree.filtration(f_simplex) << "] ";
+    std::cout << std::endl;
+  }
+
+  return 0;
+}