Example to compute persistence of a Rips filtration "in parallel". On a machine

with a gazillion cores, it gains a factor >2 at the expense of some memory. At
this point, construction of the Rips graph and expansion are not negligible
anymore and could use some parallelism.


git-svn-id: svn+ssh://scm.gforge.inria.fr/svnroot/gudhi/branches/tbb@875 636b058d-ea47-450e-bf9e-a15bfbe3eedb

Former-commit-id: 53d6a74338f1346bd7d1ca018ec15dd1ee8287e8

1 files changed, 7 insertions, 7 deletions

diff --git a/src/Hasse_complex/include/gudhi/Hasse_complex.h b/src/Hasse_complex/include/gudhi/Hasse_complex.h
index af9ae5e9..38887264 100644
--- a/src/Hasse_complex/include/gudhi/Hasse_complex.h
+++ b/src/Hasse_complex/include/gudhi/Hasse_complex.h
@@ -44,8 +44,7 @@ struct Hasse_simplex {
   template< class Complex_ds >
   Hasse_simplex(Complex_ds & cpx
                 , typename Complex_ds::Simplex_handle sh)
-      : key_(cpx.key(sh))
-      , filtration_(cpx.filtration(sh))
+      : filtration_(cpx.filtration(sh))
       , boundary_() {
     boundary_.reserve(cpx.dimension(sh) + 1);
     for (auto b_sh : cpx.boundary_simplex_range(sh)) {
@@ -55,7 +54,7 @@ struct Hasse_simplex {
 
   Hasse_simplex(typename HasseCpx::Simplex_key key
                 , typename HasseCpx::Filtration_value fil
-                , std::vector<typename HasseCpx::Simplex_handle> boundary)
+                , std::vector<typename HasseCpx::Simplex_handle> const& boundary)
       : key_(key)
       , filtration_(fil)
       , boundary_(boundary) { }
@@ -197,11 +196,12 @@ class Hasse_complex {
   }
 
   void initialize_filtration() {
+    // Setting the keys is done by pcoh, Simplex_tree doesn't do it either.
+#if 0
     Simplex_key key = 0;
-    for (auto & h_simp : complex_) {
-      h_simp.key_ = key;
-      ++key;
-    }
+    for (auto & h_simp : complex_)
+      h_simp.key_ = key++;
+#endif
   }
 
   std::vector< Hasse_simp, Gudhi::no_init_allocator<Hasse_simp> > complex_;