diff options
Diffstat (limited to 'src/Collapse')
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); } |