Fix readme and doc issue after merge

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/rips_complex_from_correlation_matrix@3213 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 4fd050a6f686044aa6f6dcc290025e321e0dba1b

2 files changed, 13 insertions, 179 deletions

diff --git a/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h b/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h
index 4dbe82c7..3113a22c 100644
--- a/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h
+++ b/src/Persistent_cohomology/doc/Intro_persistent_cohomology.h
@@ -162,6 +162,19 @@ persistence diagram with a family of field coefficients.
 Rips_complex/rips_distance_matrix_persistence.cpp</a> computes the Rips complex of a distance matrix and
 outputs its persistence diagram.
 
+The file should contain square or lower triangular distance matrix with semicolons as separators.
+The code do not check if it is dealing with a distance matrix. It is the user responsibility to provide a valid input.
+Please refer to data/distance_matrix/lower_triangular_distance_matrix.csv for an example of a file.
+
+\li <a href="_rips_complex_2rips_correlation_matrix_persistence_8cpp-example.html">
+Rips_complex/rips_correlation_matrix_persistence.cpp</a>
+computes the Rips complex of a correlation matrix and outputs its persistence diagram.
+
+Note that no check is performed if the matrix given as the input is a correlation matrix.
+It is the user responsibility to ensure that this is the case. The input is to be given either as a square or a lower
+triangular matrix.
+Please refer to data/correlation_matrix/lower_triangular_correlation_matrix.csv for an example of a file.
+
 \li <a href="_alpha_complex_2alpha_complex_3d_persistence_8cpp-example.html">
 Alpha_complex/alpha_complex_3d_persistence.cpp</a> computes the persistent homology with
 \f$\mathbb{Z}/2\mathbb{Z}\f$ coefficients of the alpha complex on points sampling from an OFF file.
diff --git a/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp b/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp
deleted file mode 100644
index 676ef793..00000000
--- a/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp
+++ /dev/null
@@ -1,179 +0,0 @@
-/*    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, Vincent Rouvreau
- *
- *    Copyright (C) 2016  INRIA
- *
- *    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/Rips_complex.h>
-#include <gudhi/Simplex_tree.h>
-#include <gudhi/Persistent_cohomology.h>
-#include <gudhi/reader_utils.h>
-#include <gudhi/file_writer.h>
-
-#include <boost/program_options.hpp>
-
-#include <string>
-#include <vector>
-#include <limits>  // infinity
-
-// Types definition
-using Simplex_tree = Gudhi::Simplex_tree<Gudhi::Simplex_tree_options_fast_persistence>;
-using Filtration_value = Simplex_tree::Filtration_value;
-using Rips_complex = Gudhi::rips_complex::Rips_complex<Filtration_value>;
-using Field_Zp = Gudhi::persistent_cohomology::Field_Zp;
-using Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp>;
-using Correlation_matrix = std::vector<std::vector<Filtration_value>>;
-using intervals_common = Gudhi::Persistence_interval_common< double , int >;
-
-void program_options(int argc, char* argv[], std::string& csv_matrix_file, std::string& filediag,
-                     Filtration_value& correlation_min, int& dim_max, int& p, Filtration_value& min_persistence);
-
-int main(int argc, char* argv[]) {
-  std::string csv_matrix_file;
-  std::string filediag;
-  Filtration_value correlation_min;
-  int dim_max;
-  int p;
-  Filtration_value min_persistence;
-
-  program_options(argc, argv, csv_matrix_file, filediag, correlation_min, dim_max, p, min_persistence);
-
-  Correlation_matrix correlations =
-      Gudhi::read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_matrix_file);
-
-  // Given a correlation matrix M, we compute component-wise M'[i,j] = 1-M[i,j] to get a distance matrix:
-  for (size_t i = 0; i != correlations.size(); ++i) {
-    for (size_t j = 0; j != correlations[i].size(); ++j) {
-      correlations[i][j] = 1 - correlations[i][j];
-      if (correlations[i][j] < 0) {
-        std::cerr << "The input matrix is not a correlation matrix. \n";
-        throw "The input matrix is not a correlation matrix. \n";
-      }
-    }
-  }
-
-  Filtration_value threshold;
-  //If the correlation_min, being minimal corelation is in the range [0,1],
-  //change it to 1-correlation_min
-  if ( ( correlation_min>=0 ) && ( correlation_min<=1 ) )
-  {
-	  threshold = 1-correlation_min;
-  }
-  else
-  {
-	  std::cout << "Wrong value of the treshold corelation (should be between 0 and 1). The program will now terminate.\n";
-	  return 1;
-  }
-
-  Rips_complex rips_complex_from_file(correlations, threshold);
-
-  // Construct the Rips complex in a Simplex Tree
-  Simplex_tree simplex_tree;
-
-  rips_complex_from_file.create_complex(simplex_tree, dim_max);
-  std::cout << "The complex contains " << simplex_tree.num_simplices() << " simplices \n";
-  std::cout << "   and has dimension " << simplex_tree.dimension() << " \n";
-
-  // Sort the simplices in the order of the filtration
-  simplex_tree.initialize_filtration();
-
-  // Compute the persistence diagram of the complex
-  Persistent_cohomology pcoh(simplex_tree);
-  // initializes the coefficient field for homology
-  pcoh.init_coefficients(p);
-  //compute persistence
-  pcoh.compute_persistent_cohomology(min_persistence);
-
-
-  //invert the persistence diagram
-  auto pairs = pcoh.get_persistent_pairs();
-  std::vector< intervals_common > processed_persistence_intervals;
-  processed_persistence_intervals.reserve( pairs.size() );
-  for (auto pair :pairs )
-  {
-	  double birth = 1-simplex_tree.filtration( get<0>(pair) );
-	  double death = 1-simplex_tree.filtration( get<1>(pair) );
-	  unsigned dimension = (unsigned)simplex_tree.dimension( get<0>(pair) );
-	  int field = get<2>(pair);
-	  processed_persistence_intervals.push_back(
-	  intervals_common(birth, death,dimension,field)
-	  );
-  }
-
-  //sort the processed intervals:
-  std::sort( processed_persistence_intervals.begin() , processed_persistence_intervals.end() );
-
-  //and write them to a file
-  if (filediag.empty()) {
-    write_persistence_intervals_to_stream(processed_persistence_intervals);
-  } else {
-    std::ofstream out(filediag);
-    write_persistence_intervals_to_stream(processed_persistence_intervals,out);
-    out.close();
-  }
-  return 0;
-}
-
-void program_options(int argc, char* argv[], std::string& csv_matrix_file, std::string& filediag,
-                     Filtration_value& correlation_min, int& dim_max, int& p, Filtration_value& min_persistence) {
-  namespace po = boost::program_options;
-  po::options_description hidden("Hidden options");
-  hidden.add_options()
-      ("input-file", po::value<std::string>(&csv_matrix_file),
-       "Name of file containing a corelation matrix. Can be square or lower triangular matrix. Separator is ';'.");
-  po::options_description visible("Allowed options", 100);
-  visible.add_options()
-      ("help,h", "produce help message")
-      ("output-file,o", po::value<std::string>(&filediag)->default_value(std::string()),
-       "Name of file in which the persistence diagram is written. Default print in std::cout")
-      ("min-edge-corelation,c",
-       po::value<Filtration_value>(&correlation_min)->default_value(0),
-       "Minimal corelation of an edge for the Rips complex construction.")
-      ("cpx-dimension,d", po::value<int>(&dim_max)->default_value(1),
-       "Maximal dimension of the Rips complex we want to compute.")
-      ("field-charac,p", po::value<int>(&p)->default_value(11),
-       "Characteristic p of the coefficient field Z/pZ for computing homology.")
-      ("min-persistence,m", po::value<Filtration_value>(&min_persistence),
-       "Minimal lifetime of homology feature to be recorded. Default is 0. Enter a negative value to see zero length intervals");
-
-  po::positional_options_description pos;
-  pos.add("input-file", 1);
-
-  po::options_description all;
-  all.add(visible).add(hidden);
-
-  po::variables_map vm;
-  po::store(po::command_line_parser(argc, argv).options(all).positional(pos).run(), vm);
-  po::notify(vm);
-
-  if (vm.count("help") || !vm.count("input-file")) {
-    std::cout << std::endl;
-    std::cout << "Compute the persistent homology with coefficient field Z/pZ \n";
-    std::cout << "of a Rips complex defined on a corelation matrix.\n \n";
-    std::cout << "The output diagram contains one bar per line, written with the convention: \n";
-    std::cout << "   p   dim b d \n";
-    std::cout << "where dim is the dimension of the homological feature,\n";
-    std::cout << "b and d are respectively the birth and death of the feature and \n";
-    std::cout << "p is the characteristic of the field Z/pZ used for homology coefficients." << std::endl << std::endl;
-
-    std::cout << "Usage: " << argv[0] << " [options] input-file" << std::endl << std::endl;
-    std::cout << visible << std::endl;
-    std::abort();
-  }
-}