1 files changed, 0 insertions, 81 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
deleted file mode 100644
index 05bacb9f..00000000
--- a/example/Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp
+++ /dev/null
@@ -1,81 +0,0 @@
-#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;
-}