1 files changed, 25 insertions, 4 deletions

diff --git a/src/Nerve_GIC/include/gudhi/GIC.h b/src/Nerve_GIC/include/gudhi/GIC.h
index aa6478e5..7aa95210 100644
--- a/src/Nerve_GIC/include/gudhi/GIC.h
+++ b/src/Nerve_GIC/include/gudhi/GIC.h
@@ -148,10 +148,20 @@ class Cover_complex {
     for (boost::tie(ei, ei_end) = boost::edges(G); ei != ei_end; ++ei) boost::remove_edge(*ei, G);
   }
 
+  // Thread local is not available on XCode version < V.8
+  // If not available, random engine is a class member.
+#ifndef GUDHI_CAN_USE_CXX11_THREAD_LOCAL
+  std::default_random_engine re;
+#endif  // GUDHI_CAN_USE_CXX11_THREAD_LOCAL
+
   // Find random number in [0,1].
   double GetUniform() {
+    // Thread local is not available on XCode version < V.8
+    // If available, random engine is defined for each thread.
+#ifdef GUDHI_CAN_USE_CXX11_THREAD_LOCAL
     thread_local std::default_random_engine re;
-    thread_local std::uniform_real_distribution<double> Dist(0, 1);
+#endif  // GUDHI_CAN_USE_CXX11_THREAD_LOCAL
+    std::uniform_real_distribution<double> Dist(0, 1);
     return Dist(re);
   }
 
@@ -415,7 +425,6 @@ class Cover_complex {
   double set_graph_from_automatic_rips(Distance distance, int N = 100) {
     int m = floor(n / std::exp((1 + rate_power) * std::log(std::log(n) / std::log(rate_constant))));
     m = std::min(m, n - 1);
-    std::vector<int> samples(m);
     double delta = 0;
 
     if (verbose) std::cout << n << " points in R^" << data_dimension << std::endl;
@@ -423,8 +432,12 @@ class Cover_complex {
 
     if (distances.size() == 0) compute_pairwise_distances(distance);
 
-    #ifdef GUDHI_USE_TBB
-      tbb::parallel_for(0, N, [&](int i){
+    // This cannot be parallelized if thread_local is not defined
+    // thread_local is not defined for XCode < v.8
+    #if defined(GUDHI_USE_TBB) && defined(GUDHI_CAN_USE_CXX11_THREAD_LOCAL)
+    tbb::mutex deltamutex;
+    tbb::parallel_for(0, N, [&](int i){
+        std::vector<int> samples(m);
         SampleWithoutReplacement(n, m, samples);
         double hausdorff_dist = 0;
         for (int j = 0; j < n; j++) {
@@ -432,10 +445,13 @@ class Cover_complex {
           for (int k = 1; k < m; k++) mj = std::min(mj, distances[j][samples[k]]);
           hausdorff_dist = std::max(hausdorff_dist, mj);
         }
+        deltamutex.lock();
         delta += hausdorff_dist / N;
+        deltamutex.unlock();
       });
     #else
       for (int i = 0; i < N; i++) {
+        std::vector<int> samples(m);
         SampleWithoutReplacement(n, m, samples);
         double hausdorff_dist = 0;
         for (int j = 0; j < n; j++) {
@@ -717,6 +733,7 @@ class Cover_complex {
 
     #ifdef GUDHI_USE_TBB
       if (verbose) std::cout << "Computing connected components (parallelized)..." << std::endl;
+      tbb::mutex covermutex, idmutex;
       tbb::parallel_for(0, res, [&](int i){
         // Compute connected components
         Graph G = one_skeleton.create_subgraph();
@@ -735,16 +752,20 @@ class Cover_complex {
           int identifier = ((i + component[j])*(i + component[j]) + 3 * i + component[j]) / 2;
 
           // Update covers
+          covermutex.lock();
           cover[preimages[i][j]].push_back(identifier);
           cover_back[identifier].push_back(preimages[i][j]);
           cover_fct[identifier] = i;
           cover_std[identifier] = funcstd[i];
           cover_color[identifier].second += func_color[preimages[i][j]];
           cover_color[identifier].first += 1;
+          covermutex.unlock();
         }
 
         // Maximal dimension is total number of connected components
+        idmutex.lock();
         id += max + 1;
+        idmutex.unlock();
       });
     #else
       if (verbose) std::cout << "Computing connected components..." << std::endl;