Remove python rips_complex construction from files as it can lead to errors with correlation matrix

Add examples for doxygen
Cythonization of rips correlation matrix


git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/rips_complex_from_correlation_matrix@2727 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 8aae33839fa27f9d26897e625904671b2c05e0e7

14 files changed, 155 insertions, 143 deletions

diff --git a/src/Persistent_cohomology/example/CMakeLists.txt b/src/Persistent_cohomology/example/CMakeLists.txt
index 8a21d038..926cef6b 100644
--- a/src/Persistent_cohomology/example/CMakeLists.txt
+++ b/src/Persistent_cohomology/example/CMakeLists.txt
@@ -40,7 +40,7 @@ add_test(NAME Persistent_cohomology_example_from_simple_simplex_tree COMMAND $<T
 add_test(NAME Persistent_cohomology_example_from_rips_distance_matrix COMMAND $<TARGET_FILE:rips_distance_matrix_persistence>
     "${CMAKE_SOURCE_DIR}/data/distance_matrix/full_square_distance_matrix.csv" "-r" "1.0" "-d" "3" "-p" "3" "-m" "0")
 add_test(rips_distance_matrix ${CMAKE_CURRENT_BINARY_DIR}/rips_distance_matrix_persistence
-    ${CMAKE_SOURCE_DIR}/data/distance_matrix/full_correlation_matrix.csv.csv -r 1.0 -d 3 -p 3 -m 0)
+    ${CMAKE_SOURCE_DIR}/data/correlation_matrix/full_correlation_matrix.csv.csv -r 1.0 -d 3 -p 3 -m 0)
 add_test(NAME Persistent_cohomology_example_from_rips_on_tore_3D COMMAND $<TARGET_FILE:rips_persistence>
     "${CMAKE_SOURCE_DIR}/data/points/tore3D_1307.off" "-r" "0.25" "-m" "0.5" "-d" "3" "-p" "3")
 add_test(NAME Persistent_cohomology_example_from_rips_step_by_step_on_tore_3D COMMAND $<TARGET_FILE:rips_persistence_step_by_step>
diff --git a/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp b/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp
index 6f2891fe..41cf915a 100644
--- a/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp
+++ b/src/Persistent_cohomology/example/rips_correlation_matrix_persistence.cpp
@@ -1,5 +1,5 @@
-/*    This file is part of the Gudhi Library. The Gudhi library 
- *    (Geometric Understanding in Higher Dimensions) is a generic C++ 
+/*    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
@@ -31,24 +31,18 @@
 #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 Persistent_cohomology = Gudhi::persistent_cohomology::Persistent_cohomology<Simplex_tree, Field_Zp>;
 using Correlation_matrix = std::vector<std::vector<Filtration_value>>;
 
-void program_options(int argc, char * argv[]
-                     , std::string & csv_matrix_file
-                     , std::string & filediag
-                     , Filtration_value & threshold
-                     , int & dim_max
-                     , int & p
-                     , Filtration_value & min_persistence);
+void program_options(int argc, char* argv[], std::string& csv_matrix_file, std::string& filediag,
+                     Filtration_value& threshold, int& dim_max, int& p, Filtration_value& min_persistence);
 
-int main(int argc, char * argv[]) {
+int main(int argc, char* argv[]) {
   std::string csv_matrix_file;
   std::string filediag;
   Filtration_value threshold;
@@ -58,22 +52,20 @@ int main(int argc, char * argv[]) {
 
   program_options(argc, argv, csv_matrix_file, filediag, threshold, 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";
-		  }		  
-	  }
-  } 
-  
+  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";
+      }
+    }
+  }
+
   Rips_complex rips_complex_from_file(correlations, threshold);
 
   // Construct the Rips complex in a Simplex Tree
@@ -104,33 +96,28 @@ int main(int argc, char * argv[]) {
   return 0;
 }
 
-void program_options(int argc, char * argv[]
-                     , std::string & csv_matrix_file
-                     , std::string & filediag
-                     , Filtration_value & threshold
-                     , int & dim_max
-                     , int & p
-                     , Filtration_value & min_persistence) {
+void program_options(int argc, char* argv[], std::string& csv_matrix_file, std::string& filediag,
+                     Filtration_value& threshold, 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 distance matrix. Can be square or lower triangular matrix. Separator is ';'.");
+  hidden.add_options()(
+      "input-file", po::value<std::string>(&csv_matrix_file),
+      "Name of file containing a distance 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")
-      ("max-edge-length,r",
-       po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()),
-       "Maximal length 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");
+  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")(
+      "max-edge-length,r",
+      po::value<Filtration_value>(&threshold)->default_value(std::numeric_limits<Filtration_value>::infinity()),
+      "Maximal length 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);
@@ -139,8 +126,7 @@ void program_options(int argc, char * argv[]
   all.add(visible).add(hidden);
 
   po::variables_map vm;
-  po::store(po::command_line_parser(argc, argv).
-            options(all).positional(pos).run(), 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")) {
diff --git a/src/Rips_complex/example/CMakeLists.txt b/src/Rips_complex/example/CMakeLists.txt
index f58ab455..fcb1eaee 100644
--- a/src/Rips_complex/example/CMakeLists.txt
+++ b/src/Rips_complex/example/CMakeLists.txt
@@ -9,23 +9,25 @@ add_executable ( Rips_complex_example_one_skeleton_from_points example_one_skele
 # Distance matrix
 add_executable ( Rips_complex_example_one_skeleton_from_distance_matrix example_one_skeleton_rips_from_distance_matrix.cpp )
 
-add_executable ( example_one_skeleton_rips_from_correlation_matrix example_one_skeleton_rips_from_correlation_matrix.cpp )
-
-
 add_executable ( Rips_complex_example_from_csv_distance_matrix example_rips_complex_from_csv_distance_matrix_file.cpp )
 
+# Correlation matrix
+add_executable (  Rips_complex_example_one_skeleton_rips_from_correlation_matrix example_one_skeleton_rips_from_correlation_matrix.cpp )
+
 if (TBB_FOUND)
   target_link_libraries(Rips_complex_example_from_off ${TBB_LIBRARIES})
   target_link_libraries(Rips_complex_example_one_skeleton_from_points ${TBB_LIBRARIES})
   target_link_libraries(Rips_complex_example_one_skeleton_from_distance_matrix ${TBB_LIBRARIES})
-  target_link_libraries(example_one_skeleton_rips_from_correlation_matrix ${TBB_LIBRARIES})
   target_link_libraries(Rips_complex_example_from_csv_distance_matrix ${TBB_LIBRARIES})
+  target_link_libraries(Rips_complex_example_one_skeleton_rips_from_correlation_matrix ${TBB_LIBRARIES})
 endif()
 
 add_test(NAME Rips_complex_example_one_skeleton_from_points
     COMMAND $<TARGET_FILE:Rips_complex_example_one_skeleton_from_points>)
 add_test(NAME Rips_complex_example_one_skeleton_from_distance_matrix
     COMMAND $<TARGET_FILE:Rips_complex_example_one_skeleton_from_distance_matrix>)
+add_test(NAME Rips_complex_example_one_skeleton_rips_from_correlation_matrix
+    COMMAND $<TARGET_FILE:Rips_complex_example_one_skeleton_rips_from_correlation_matrix>)
 
 add_test(NAME Rips_complex_example_from_off_doc_12_1 COMMAND $<TARGET_FILE:Rips_complex_example_from_off>
     "${CMAKE_SOURCE_DIR}/data/points/alphacomplexdoc.off" "12.0" "1" "${CMAKE_CURRENT_BINARY_DIR}/ripsoffreader_result_12_1.txt")
@@ -61,3 +63,4 @@ install(TARGETS Rips_complex_example_from_off DESTINATION bin)
 install(TARGETS Rips_complex_example_one_skeleton_from_points DESTINATION bin)
 install(TARGETS Rips_complex_example_one_skeleton_from_distance_matrix DESTINATION bin)
 install(TARGETS Rips_complex_example_from_csv_distance_matrix DESTINATION bin)
+install(TARGETS Rips_complex_example_one_skeleton_rips_from_correlation_matrix DESTINATION bin)
diff --git a/src/Rips_complex/example/example_one_skeleton_rips_from_correlation_matrix.cpp b/src/Rips_complex/example/example_one_skeleton_rips_from_correlation_matrix.cpp
index 0acdfe83..ae347a00 100644
--- a/src/Rips_complex/example/example_one_skeleton_rips_from_correlation_matrix.cpp
+++ b/src/Rips_complex/example/example_one_skeleton_rips_from_correlation_matrix.cpp
@@ -21,7 +21,6 @@ int main() {
   // |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});
@@ -32,24 +31,21 @@ int main() {
   // ----------------------------------------------------------------------------
   // Convert correlation matrix to 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";
-		  }		  
-	  }
-  } 
-  
+  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";
+      }
+    }
+  }
+
   //-----------------------------------------------------------------------------
-  // Now the correlation matrix is really the distance matrix and can be processed further. 
+  // Now the correlation matrix is really the distance matrix and can be processed further.
   //-----------------------------------------------------------------------------
   Distance_matrix distances = correlations;
-  
+
   double threshold = 1.0;
   Rips_complex rips_complex_from_points(distances, threshold);
 
@@ -58,18 +54,17 @@ int main() {
   // ----------------------------------------------------------------------------
   // Display information about the one skeleton Rips complex
   // ----------------------------------------------------------------------------
-  std::cout << "Rips complex is of dimension " << stree.dimension() <<
-               " - " << stree.num_simplices() << " simplices - " <<
-               stree.num_vertices() << " vertices." << std::endl;
+  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;
+  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 << ") -> "
+              << "[" << stree.filtration(f_simplex) << "] ";
     std::cout << std::endl;
   }
 
diff --git a/src/common/doc/main_page.h b/src/common/doc/main_page.h
index 1a7994a5..91535ee6 100644
--- a/src/common/doc/main_page.h
+++ b/src/common/doc/main_page.h
@@ -456,11 +456,15 @@ make doxygen
  * @example Persistent_cohomology/persistence_from_simple_simplex_tree.cpp
  * @example Persistent_cohomology/plain_homology.cpp
  * @example Persistent_cohomology/rips_multifield_persistence.cpp
+ * @example Persistent_cohomology/rips_correlation_matrix_persistence.cpp
  * @example Persistent_cohomology/rips_distance_matrix_persistence.cpp
  * @example Persistent_cohomology/rips_persistence.cpp
  * @example Persistent_cohomology/custom_persistence_sort.cpp
  * @example Persistent_cohomology/rips_persistence_step_by_step.cpp
+ * @example Rips_complex/example_one_skeleton_rips_from_correlation_matrix.cpp
+ * @example Rips_complex/example_one_skeleton_rips_from_distance_matrix.cpp
  * @example Rips_complex/example_one_skeleton_rips_from_points.cpp
+ * @example Rips_complex/example_rips_complex_from_csv_distance_matrix_file.cpp
  * @example Rips_complex/example_rips_complex_from_off_file.cpp
  * @example Simplex_tree/mini_simplex_tree.cpp
  * @example Simplex_tree/simple_simplex_tree.cpp
diff --git a/src/cython/cython/off_reader.pyx b/src/cython/cython/off_reader.pyx
index b6e107ef..266dae2c 100644
--- a/src/cython/cython/off_reader.pyx
+++ b/src/cython/cython/off_reader.pyx
@@ -46,4 +46,5 @@ def read_off(off_file=''):
             return read_points_from_OFF_file(str.encode(off_file))
         else:
             print("file " + off_file + " not found.")
+            return []
 
diff --git a/src/cython/cython/rips_complex.pyx b/src/cython/cython/rips_complex.pyx
index ad9b0a4d..73b154b8 100644
--- a/src/cython/cython/rips_complex.pyx
+++ b/src/cython/cython/rips_complex.pyx
@@ -34,8 +34,6 @@ __license__ = "GPL v3"
 cdef extern from "Rips_complex_interface.h" namespace "Gudhi":
     cdef cppclass Rips_complex_interface "Gudhi::rips_complex::Rips_complex_interface":
         Rips_complex_interface(vector[vector[double]] values, double threshold, bool euclidean)
-        # bool from_file is a workaround for cython to find the correct signature
-        Rips_complex_interface(string file_name, double threshold, bool euclidean, bool from_file)
         void create_simplex_tree(Simplex_tree_interface_full_featured* simplex_tree, int dim_max)
 
 # RipsComplex python interface
@@ -49,7 +47,7 @@ cdef class RipsComplex:
     cdef Rips_complex_interface * thisptr
 
     # Fake constructor that does nothing but documenting the constructor
-    def __init__(self, points=None, off_file='', distance_matrix=None, csv_file='', max_edge_length=float('inf')):
+    def __init__(self, points=None, distance_matrix=None, max_edge_length=float('inf')):
         """RipsComplex constructor.
 
         :param max_edge_length: Rips value.
@@ -60,41 +58,14 @@ cdef class RipsComplex:
 
         Or
 
-        :param off_file: An OFF file style name.
-        :type off_file: string
-
-        Or
-
         :param distance_matrix: A distance matrix (full square or lower
         triangular).
         :type points: list of list of double
-
-        Or
-
-        :param csv_file: A csv file style name containing a full square or a
-        lower triangular distance matrix.
-        :type csv_file: string
         """
 
     # The real cython constructor
-    def __cinit__(self, points=None, off_file='', distance_matrix=None, csv_file='', max_edge_length=float('inf')):
-        if off_file is not '':
-            if os.path.isfile(off_file):
-                self.thisptr = new Rips_complex_interface(str.encode(off_file),
-                                                          max_edge_length,
-                                                          True,
-                                                          True)
-            else:
-                print("file " + off_file + " not found.")
-        elif csv_file is not '':
-            if os.path.isfile(csv_file):
-                self.thisptr = new Rips_complex_interface(str.encode(csv_file),
-                                                          max_edge_length,
-                                                          False,
-                                                          True)
-            else:
-                print("file " + csv_file + " not found.")
-        elif distance_matrix is not None:
+    def __cinit__(self, points=None, distance_matrix=None, max_edge_length=float('inf')):
+        if distance_matrix is not None:
             self.thisptr = new Rips_complex_interface(distance_matrix, max_edge_length, False)
         else:
             if points is None:
diff --git a/src/cython/doc/persistence_graphical_tools_user.rst b/src/cython/doc/persistence_graphical_tools_user.rst
index 9033331f..a5523d23 100644
--- a/src/cython/doc/persistence_graphical_tools_user.rst
+++ b/src/cython/doc/persistence_graphical_tools_user.rst
@@ -58,8 +58,8 @@ This function can display the persistence result as a diagram:
 
     import gudhi
     
-    rips_complex = gudhi.RipsComplex(off_file=gudhi.__root_source_dir__ + \
-        '/data/points/tore3D_1307.off', max_edge_length=0.2)
+    point_cloud = gudhi.read_off(off_file=gudhi.__root_source_dir__ + '/data/points/tore3D_1307.off')
+    rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=0.2)
     simplex_tree = rips_complex.create_simplex_tree(max_dimension=3)
     diag = simplex_tree.persistence()
     plt = gudhi.plot_persistence_diagram(diag, band_boot=0.13)
@@ -69,8 +69,8 @@ This function can display the persistence result as a diagram:
 
     import gudhi
 
-    rips_complex = gudhi.RipsComplex(off_file=gudhi.__root_source_dir__ + \
-        '/data/points/tore3D_1307.off', max_edge_length=0.2)
+    point_cloud = gudhi.read_off(off_file=gudhi.__root_source_dir__ + '/data/points/tore3D_1307.off')
+    rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=0.2)
     simplex_tree = rips_complex.create_simplex_tree(max_dimension=3)
     diag = simplex_tree.persistence()
     plt = gudhi.plot_persistence_diagram(diag, band_boot=0.13)
diff --git a/src/cython/doc/pyplots/diagram_persistence.py b/src/cython/doc/pyplots/diagram_persistence.py
index c2fbf801..ac20bf47 100755
--- a/src/cython/doc/pyplots/diagram_persistence.py
+++ b/src/cython/doc/pyplots/diagram_persistence.py
@@ -1,7 +1,8 @@
 import gudhi
 
-rips_complex = gudhi.RipsComplex(off_file=gudhi.__root_source_dir__ + \
-    '/data/points/tore3D_1307.off', max_edge_length=0.2)
+point_cloud = gudhi.read_off(off_file=gudhi.__root_source_dir__ + \
+    '/data/points/tore3D_1307.off')
+rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=0.2)
 simplex_tree = rips_complex.create_simplex_tree(max_dimension=3)
 diag = simplex_tree.persistence()
 plt = gudhi.plot_persistence_diagram(diag, band_boot=0.13)
diff --git a/src/cython/doc/rips_complex_user.rst b/src/cython/doc/rips_complex_user.rst
index 96ba9944..f0e7bf2d 100644
--- a/src/cython/doc/rips_complex_user.rst
+++ b/src/cython/doc/rips_complex_user.rst
@@ -101,8 +101,8 @@ Finally, it is asked to display information about the Rips complex.
 .. testcode::
 
     import gudhi
-    rips_complex = gudhi.RipsComplex(off_file=gudhi.__root_source_dir__ + \
-        '/data/points/alphacomplexdoc.off', max_edge_length=12.0)
+    point_cloud = gudhi.read_off(off_file=gudhi.__root_source_dir__ + '/data/points/alphacomplexdoc.off')
+    rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=12.0)
     simplex_tree = rips_complex.create_simplex_tree(max_dimension=1)
     result_str = 'Rips complex is of dimension ' + repr(simplex_tree.dimension()) + ' - ' + \
         repr(simplex_tree.num_simplices()) + ' simplices - ' + \
@@ -206,8 +206,9 @@ Finally, it is asked to display information about the Rips complex.
 .. testcode::
 
     import gudhi
-    rips_complex = gudhi.RipsComplex(csv_file=gudhi.__root_source_dir__ + \
-        '/data/distance_matrix/full_square_distance_matrix.csv', max_edge_length=12.0)
+    distance_matrix = gudhi.read_lower_triangular_matrix_from_csv_file(csv_file=gudhi.__root_source_dir__ + \
+        '/data/distance_matrix/full_square_distance_matrix.csv')
+    rips_complex = gudhi.RipsComplex(distance_matrix=distance_matrix, max_edge_length=12.0)
     simplex_tree = rips_complex.create_simplex_tree(max_dimension=1)
     result_str = 'Rips complex is of dimension ' + repr(simplex_tree.dimension()) + ' - ' + \
         repr(simplex_tree.num_simplices()) + ' simplices - ' + \
@@ -240,3 +241,67 @@ the program output is:
     [0, 3] -> 9.43
     [4, 6] -> 9.49
     [3, 6] -> 11.00
+
+Correlation matrix
+---------------
+
+Example from  a correlation matrix
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+Analogously to the case of distance matrix, Rips complexes can be also constructed based on correlation matrix.
+Given a correlation matrix M, comportment-wise 1-M is a distance matrix.
+This example builds the one skeleton graph from the given corelation matrix and threshold value.
+Then it creates a :doc:`Simplex_tree <simplex_tree_ref>` with it.
+
+Finally, it is asked to display information about the simplicial complex.
+
+.. testcode::
+
+    import gudhi
+    import numpy as np
+
+    # 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   |
+    correlation_matrix=np.array([[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.]], float)
+
+    distance_matrix = np.ones((correlation_matrix.shape),float) - correlation_matrix
+    rips_complex = gudhi.RipsComplex(distance_matrix=distance_matrix, max_edge_length=1.0)
+
+    simplex_tree = rips_complex.create_simplex_tree(max_dimension=1)
+    result_str = 'Rips complex is of dimension ' + repr(simplex_tree.dimension()) + ' - ' + \
+        repr(simplex_tree.num_simplices()) + ' simplices - ' + \
+        repr(simplex_tree.num_vertices()) + ' vertices.'
+    print(result_str)
+    fmt = '%s -> %.2f'
+    for filtered_value in simplex_tree.get_filtration():
+        print(fmt % tuple(filtered_value))
+
+When launching (Rips maximal distance between 2 points is 12.0, is expanded
+until dimension 1 - one skeleton graph in other words), the output is:
+
+.. testoutput::
+
+    Rips complex is of dimension 1 - 15 simplices - 5 vertices.
+    [0] -> 0.00
+    [1] -> 0.00
+    [2] -> 0.00
+    [3] -> 0.00
+    [4] -> 0.00
+    [0, 4] -> 0.11
+    [1, 2] -> 0.26
+    [2, 3] -> 0.28
+    [3, 4] -> 0.30
+    [1, 4] -> 0.39
+    [0, 2] -> 0.77
+    [0, 1] -> 0.94
+    [2, 4] -> 0.97
+    [0, 3] -> 0.99
+    [1, 3] -> 0.99
diff --git a/src/cython/example/alpha_rips_persistence_bottleneck_distance.py b/src/cython/example/alpha_rips_persistence_bottleneck_distance.py
index ab5fc1e9..386f8457 100755
--- a/src/cython/example/alpha_rips_persistence_bottleneck_distance.py
+++ b/src/cython/example/alpha_rips_persistence_bottleneck_distance.py
@@ -45,13 +45,14 @@ args = parser.parse_args()
 with open(args.file, 'r') as f:
     first_line = f.readline()
     if (first_line == 'OFF\n') or (first_line == 'nOFF\n'):
+        point_cloud = gudhi.read_off(off_file=args.file)
         print("#####################################################################")
         print("RipsComplex creation from points read in a OFF file")
 
         message = "RipsComplex with max_edge_length=" + repr(args.threshold)
         print(message)
 
-        rips_complex = gudhi.RipsComplex(off_file=args.file,
+        rips_complex = gudhi.RipsComplex(points=point_cloud,
                                          max_edge_length=args.threshold)
 
         rips_stree = rips_complex.create_simplex_tree(max_dimension=args.max_dimension)
@@ -67,7 +68,7 @@ with open(args.file, 'r') as f:
         message = "AlphaComplex with max_edge_length=" + repr(args.threshold)
         print(message)
 
-        alpha_complex = gudhi.AlphaComplex(off_file=args.file)
+        alpha_complex = gudhi.AlphaComplex(points=point_cloud)
         alpha_stree = alpha_complex.create_simplex_tree(max_alpha_square=(args.threshold * args.threshold))
 
         message = "Number of simplices=" + repr(alpha_stree.num_simplices())
diff --git a/src/cython/example/rips_complex_diagram_persistence_from_distance_matrix_file_example.py b/src/cython/example/rips_complex_diagram_persistence_from_distance_matrix_file_example.py
index 3baebd17..fa82a2f3 100755
--- a/src/cython/example/rips_complex_diagram_persistence_from_distance_matrix_file_example.py
+++ b/src/cython/example/rips_complex_diagram_persistence_from_distance_matrix_file_example.py
@@ -50,7 +50,8 @@ print("RipsComplex creation from distance matrix read in a csv file")
 message = "RipsComplex with max_edge_length=" + repr(args.max_edge_length)
 print(message)
 
-rips_complex = gudhi.RipsComplex(csv_file=args.file, max_edge_length=args.max_edge_length)
+distance_matrix = gudhi.read_lower_triangular_matrix_from_csv_file(csv_file=args.file)
+rips_complex = gudhi.RipsComplex(distance_matrix=distance_matrix, max_edge_length=args.max_edge_length)
 simplex_tree = rips_complex.create_simplex_tree(max_dimension=args.max_dimension)
 
 message = "Number of simplices=" + repr(simplex_tree.num_simplices())
diff --git a/src/cython/example/rips_complex_diagram_persistence_from_off_file_example.py b/src/cython/example/rips_complex_diagram_persistence_from_off_file_example.py
index 5951eedf..544b68c9 100755
--- a/src/cython/example/rips_complex_diagram_persistence_from_off_file_example.py
+++ b/src/cython/example/rips_complex_diagram_persistence_from_off_file_example.py
@@ -53,7 +53,8 @@ with open(args.file, 'r') as f:
         message = "RipsComplex with max_edge_length=" + repr(args.max_edge_length)
         print(message)
         
-        rips_complex = gudhi.RipsComplex(off_file=args.file, max_edge_length=args.max_edge_length)
+        point_cloud = gudhi.read_off(off_file=args.file)
+        rips_complex = gudhi.RipsComplex(points=point_cloud, max_edge_length=args.max_edge_length)
         simplex_tree = rips_complex.create_simplex_tree(max_dimension=args.max_dimension)
     
         message = "Number of simplices=" + repr(simplex_tree.num_simplices())
diff --git a/src/cython/include/Rips_complex_interface.h b/src/cython/include/Rips_complex_interface.h
index 02985727..f26befbc 100644
--- a/src/cython/include/Rips_complex_interface.h
+++ b/src/cython/include/Rips_complex_interface.h
@@ -25,9 +25,7 @@
 
 #include <gudhi/Simplex_tree.h>
 #include <gudhi/Rips_complex.h>
-#include <gudhi/Points_off_io.h>
 #include <gudhi/distance_functions.h>
-#include <gudhi/reader_utils.h>
 
 #include "Simplex_tree_interface.h"
 
@@ -56,21 +54,6 @@ class Rips_complex_interface {
     }
   }
 
-  Rips_complex_interface(const std::string& file_name, double threshold, bool euclidean, bool from_file = true) {
-    if (euclidean) {
-      // Rips construction where file_name is an OFF file
-      Gudhi::Points_off_reader<Point_d> off_reader(file_name);
-      rips_complex_ = new Rips_complex<Simplex_tree_interface<>::Filtration_value>(off_reader.get_point_cloud(),
-                                                                                   threshold,
-                                                                                   Gudhi::Euclidean_distance());
-    } else {
-      // Rips construction where values is a distance matrix
-      Distance_matrix distances =
-          Gudhi::read_lower_triangular_matrix_from_csv_file<Simplex_tree_interface<>::Filtration_value>(file_name);
-      rips_complex_ = new Rips_complex<Simplex_tree_interface<>::Filtration_value>(distances, threshold);
-    }
-  }
-
   ~Rips_complex_interface() {
     delete rips_complex_;
   }