Merge pull request #624 from albert-github/feature/bug_spell

Spelling corrections

4 files changed, 4 insertions, 4 deletions

diff --git a/src/Collapse/example/edge_collapse_conserve_persistence.cpp b/src/Collapse/example/edge_collapse_conserve_persistence.cpp
index b2c55e7a..19960597 100644
--- a/src/Collapse/example/edge_collapse_conserve_persistence.cpp
+++ b/src/Collapse/example/edge_collapse_conserve_persistence.cpp
@@ -103,7 +103,7 @@ int main(int argc, char* argv[]) {
                                                                                  Gudhi::Euclidean_distance());
 
   if (num_edges(proximity_graph) <= 0) {
-    std::cerr << "Total number of egdes are zero." << std::endl;
+    std::cerr << "Total number of edges is zero." << std::endl;
     exit(-1);
   }
 
diff --git a/src/Collapse/include/gudhi/Flag_complex_edge_collapser.h b/src/Collapse/include/gudhi/Flag_complex_edge_collapser.h
index c823901f..d0b3fe4a 100644
--- a/src/Collapse/include/gudhi/Flag_complex_edge_collapser.h
+++ b/src/Collapse/include/gudhi/Flag_complex_edge_collapser.h
@@ -53,7 +53,7 @@ struct Flag_complex_edge_collapser {
 #ifdef GUDHI_COLLAPSE_USE_DENSE_ARRAY
   // Minimal matrix interface
   // Using this matrix generally helps performance, but the memory use may be excessive for a very sparse graph
-  // (and in extreme cases the constant initialization of the matrix may start to dominate the runnning time).
+  // (and in extreme cases the constant initialization of the matrix may start to dominate the running time).
   // Are there cases where the matrix is too big but a hash table would help?
   std::vector<Filtration_value> neighbors_data;
   void init_neighbors_dense(){
diff --git a/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp b/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp
index 11ee5871..38efb9e6 100644
--- a/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp
+++ b/src/Collapse/utilities/distance_matrix_edge_collapse_rips_persistence.cpp
@@ -45,7 +45,7 @@ int main(int argc, char* argv[]) {
                   min_persistence);
 
   Distance_matrix distances = Gudhi::read_lower_triangular_matrix_from_csv_file<Filtration_value>(csv_matrix_file);
-  std::cout << "Read the distance matrix succesfully, of size: " << distances.size() << std::endl;
+  std::cout << "Read the distance matrix successfully, of size: " << distances.size() << std::endl;
 
   Proximity_graph proximity_graph = Gudhi::compute_proximity_graph<Simplex_tree>(boost::irange((size_t)0,
                                                                                                distances.size()),
diff --git a/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp b/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp
index 0eea742c..d8f42ab6 100644
--- a/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp
+++ b/src/Collapse/utilities/point_cloud_edge_collapse_rips_persistence.cpp
@@ -77,7 +77,7 @@ int main(int argc, char* argv[]) {
                                                                                  Gudhi::Euclidean_distance());
 
   if (num_edges(proximity_graph) <= 0) {
-    std::cerr << "Total number of egdes are zero." << std::endl;
+    std::cerr << "Total number of edges is zero." << std::endl;
     exit(-1);
   }