Added the commented choose_n_farthest_points everywhere

git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/wit_doc_corrections@2909 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 9f7a325facf798748c4c08e3815fbbd3d4075b78

1 files changed, 3 insertions, 3 deletions

diff --git a/src/Witness_complex/doc/Witness_complex_doc.h b/src/Witness_complex/doc/Witness_complex_doc.h
index fb589a74..d070ee34 100644
--- a/src/Witness_complex/doc/Witness_complex_doc.h
+++ b/src/Witness_complex/doc/Witness_complex_doc.h
@@ -60,7 +60,6 @@
    \section witnessexample1 Example 1: Constructing weak relaxed witness complex from an off file
 
    Let's start with a simple example, which reads an off point file and computes a weak witness complex.
-   In this example, instead of choosing landmarks randomly, one can also use the farthest point selection provided by Gudhi::subsampling::choose_n_farthest_points().
 
    ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.cpp}
    
@@ -91,8 +90,9 @@ int main(int argc, char * const argv[]) {
   Gudhi::Points_off_reader<Point_d> off_reader(file_name);
   point_vector = Point_vector(off_reader.get_point_cloud());
 
-  // Choose landmarks (one can also use Gudhi::subsampling::choose_n_farthest_points())
-  Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks));
+  // Choose landmarks (one can choose either of the two methods below)
+  // Gudhi::subsampling::pick_n_random_points(point_vector, nbL, std::back_inserter(landmarks));
+  Gudhi::subsampling::choose_n_farthest_points(K(), point_vector, nbL, Gudhi::subsampling::random_starting_point, std::back_inserter(landmarks));
 
   // Compute witness complex
   Witness_complex witness_complex(landmarks,