comments

Author: gsylvand

include/hmat/hmat.h

@@ -202,7 +202,7 @@ HMAT_API hmat_clustering_algorithm_t* hmat_create_clustering_max_dof(const hmat_
  * delegate to an other algorithm.
  * @param algo the delegate algorithm
  * @param ratio ratio between the number of DOF in a cluster and
- * a span size so a DOF is concidered as large
+ * a span size so a DOF is considered as large
  */
 HMAT_API hmat_clustering_algorithm_t* hmat_create_clustering_span(
         const hmat_clustering_algorithm_t* algo, double ratio);

src/clustering.hpp

@@ -198,7 +198,7 @@ class SpanClusteringAlgorithm: public AxisAlignClusteringAlgorithm {
     double ratio_;
 public:
     /** @param ratio ratio between the number of DOF in a cluster and
-     * a span size so a DOF is concidered as large */
+     * a span size so a DOF is considered as large */
     SpanClusteringAlgorithm(const ClusteringAlgorithm &algo, double ratio);
     std::string str() const;
     ClusteringAlgorithm* clone() const;

src/compression.cpp

@@ -294,6 +294,7 @@ void acaFull(ScalarArray<T> & m, ScalarArray<T>* & tmpA, ScalarArray<T>* & tmpB,
 
       // performs the rank 1 operation m := m - va_nu*vb_nu^T
       // in order to nullify m->get(i_nu, j_nu) (the previous maximum value)
+      // as well as the whole row i_nu and column j_nu
       m.rankOneUpdate(-1, va_nu, vb_nu);
 
       // Update the estimate norm

src/scalar_array.cpp

@@ -1328,7 +1328,7 @@ template<typename T> int ScalarArray<T>::modifiedGramSchmidt(ScalarArray<T> *res
       pivmax = norm2_update[pivot];
       relative_epsilon = prec * prec;
     }
-    if (j<initialPivot) {
+    if (j<initialPivot) { // is it possible ?
       pivot = j;
       pivmax = 1.;
     }
@@ -1363,7 +1363,7 @@ template<typename T> int ScalarArray<T>::modifiedGramSchmidt(ScalarArray<T> *res
 
       // Remove the qj-component from vectors bk (k=j+1,...,n-1)
       if (j<cols-1) {
-        int firstcol=std::max(j+1, initialPivot) ;
+        int firstcol=std::max(j+1, initialPivot) ; // should always be j+1, no ?
         ScalarArray<T> bK(*this, 0, rows, firstcol, cols-firstcol); // All the columns of 'this' after column 'firstcol'
         ScalarArray<T> aj_bK(r, j, 1, firstcol, cols-firstcol); // In 'r': row 'j', all the columns after column 'firstcol'
         // Compute in 1 operation all the scalar products between aj and a_firstcol, ..., a_n

src/scalar_array.hpp

@@ -562,7 +562,7 @@ template<typename T> class ScalarArray {
     Vector(T* _m, int _rows):ScalarArray<T>(_m, _rows, 1){}
     Vector(int _rows):ScalarArray<T>(_rows, 1){}
     Vector(int _rows, bool zeroinit):ScalarArray<T>(_rows , 1 , zeroinit){}
-    /** \brief Create Vector with column 'col' of existing ScalarArray
+    /** \brief Create Vector with column '_col' of existing ScalarArray
      */
     Vector(const ScalarArray<T> &d, int _col):ScalarArray<T>(d, 0, d.rows, _col, 1){}
     //~Vector(){}