// 1. Convert n to n', where n' will be its rank if the tree
// was complete
// 2. Calculate neighbours for n'
- // 3. Convert the neighbours n1', n2' and n3' to their
- // appropiate values n1, n2, n3. Note that it must be
- // checked that this neighbours reallly exist.
+ // 3. Convert the neighbors n1', n2' and n3' to their
+ // appropriate values n1, n2, n3. Note that it must be
+ // checked that these neighbors actually exist.
calculate_shifts_pos_level(mod_pos, zero, l_s, r_s, p_s);
if (l_s > splitting_point)
{
/** @brief Search for the first 0 bit (growing the weight) using
* binary search
*
- * Binary search can be used instead of a naïve loop using the
+ * Binary search can be used instead of a naive loop using the
* masks in mask array
* @param x Binary number (corresponding to a rank in the tree)
* whose first 0 bit must be calculated
considering valid nodes and gaps
* @param pos Rank in the array of nodes considering only valid nodes
* @param index Partition which the rank is most likely to
- * belong to (ie. the corresponding if there were no gaps)
+ * belong to (i. e. the corresponding if there were no gaps)
* @pre 0 <= @c pos <= number_of_distinct_elements
* @return Rank in the array of nodes considering valid nodes and gaps
* @post 0 <= @c return <= number_of_elements
/** @brief Helper comparator class: Passed as a parameter of
list_partition to check that a sequence is sorted
* @param _InputIterator Iterator to the elements to compare
- * @param _CompIsSorted Comparator to check for sortedness */
+ * @param _CompIsSorted Comparator to check for sortednesss */
template<typename _InputIterator, typename _CompIsSorted>
class is_sorted_functor
{
/** @brief Element to compare with (first parameter of comp) */
_InputIterator prev;
- /** @brief Comparator to check for sortedness */
+ /** @brief Comparator to check for sortednesss */
const _CompIsSorted comp;
/** @brief Sum up the history of the operator() of this
* Sorted is set to true
* @param first Element to compare with the first time the
* operator() is called
- * @param c Comparator to check for sortednes */
+ * @param c Comparator to check for sortedness */
is_sorted_functor(const _InputIterator first, const _CompIsSorted c)
: prev(first), comp(c), sorted(true) { }
template<typename S>
struct Opposite
{
- /** @brief Obtain the conceptual left child of a node, inversing
+ /** @brief Obtain the conceptual left child of a node, inverting
the symmetry
* @param parent Node whose child must be obtained
* @return Reference to the child node */
{ return S::right(parent);}
/** @brief Obtain the conceptual right child of a node,
- inversing the symmetry
+ inverting the symmetry
* @param parent Node whose child must be obtained
* @return Reference to the child node */
static _Rb_tree_node_base*& right(_Rb_tree_node_base* parent)
be inserted into @c t */
size_type pos_beg;
- /** @brief Positition of the first node in the array of nodes
+ /** @brief Position of the first node in the array of nodes
that won't be inserted into @c t */
size_type pos_end;
* The input sequence is preprocessed so that the bulk
* construction or insertion can be performed
* efficiently. Essentially, the sequence is checked for
- * sortedness and iterators to the middle of the structure are
+ * sortednesss and iterators to the middle of the structure are
* saved so that afterwards the sequence can be processed
* effectively in parallel. */
template<typename _InputIterator, typename StrictlyLessOrLessEqual>
* The elements are copied, according to the copy policy, in order
* to be sorted. Then the
* _M_not_sorted_bulk_insertion_construction() method is called
- * appropiately
+ * appropriately
* @param access Array of iterators of size @c num_threads +
* 1. Each position contains the first element in each subsequence
* to be added into the tree.
}
- /** @brief Allocation of an array of nodes and initilization of
+ /** @brief Allocation of an array of nodes and initialization of
their value fields from an input sequence. Done in parallel.
* @param access Array of iterators of size @c num_threads +
* 1. Each position contains the first value in the subsequence to
}
- /** @brief Allocation of an array of nodes and initilization of
+ /** @brief Allocation of an array of nodes and initialization of
* their value fields from an input sequence. Done in
* parallel. Besides, the sequence is checked for uniqueness while
* copying the elements, and if there are repetitions, gaps within
}
- /** @brief Allocation of an array of nodes and initilization of
+ /** @brief Allocation of an array of nodes and initialization of
* their value fields from an input sequence.
*
* The allocation and initialization is done in parallel. Besides,
t.tic("bulk allocation and initialization");
- // Link the tree appropiately.
+ // Link the tree appropriately.
// Dealing with repetitions (EFFICIENCY ISSUE).
ranker_gaps rank(beg_partition, rank_shift, num_threads);
nodes_initializer<ranker_gaps> nodes_init(r, n - rank_shift[num_threads], num_threads, rank);
}
}
}
- // If the execution reachs this point, there has been no
+ // If the execution reaches this point, there has been no
// exception, and so the structure can be initialized.
// Join the tree laid on the array of ptrs with the header node.
//2. Split the tree according to access in num_threads parts
//Initialize upper concat_problems
- //Allocate them dinamically because they are afterwards so erased
+ //Allocate them dynamically because they are afterwards so erased
for (int i=0; i < (2*num_threads-1); ++i)
{
conc[i] = new concat_problem ();
/** @brief Divide a tree according to the splitter elements of a
* given sequence.
*
- * The tree of the intial recursive call is divided in exactly
+ * The tree of the initial recursive call is divided in exactly
* num_threads partitions, some of which may be empty. Besides,
* some nodes may be extracted from it to afterwards concatenate
* the subtrees resulting from inserting the elements into it.
* This is done sequentially. It could be done in parallel but the
* performance is much worse.
- * @param t Root of the tree to be splitted
+ * @param t Root of the tree to be split
* @param r Array of nodes to be inserted into the tree (here only
* used to look up its elements)
* @param access Array of iterators of size @c num_threads +
* sequentially.
* @param r Array of nodes containing the nodes to added into the tree
* @param ins_problems Pointer to a queue of insertion
- * problems. The calling thread owns this queue, i.e. it is the
+ * problems. The calling thread owns this queue, i. e. it is the
* only one to push elements, but other threads could pop elements
* from it in other methods.
* @param ip Current insertion problem to be solved
is_sorted_functor<_InputIterator, _Compare> sorted(__first, base_type::_M_impl._M_key_compare);
dist = list_partition(__first, __last, access, (beg_partition+1), num_pieces, sorted, 0);
- // Calculate the rank of the begining each partition from the
+ // Calculate the rank of the beginning each partition from the
// sequence sizes (what is stored at this point in beg_partition
// array).
beg_partition[0] = 0;
/** @brief Make a full copy of the elements of a sequence
*
- * The unitialized_copy method from the stl is called in parallel
+ * The uninitialized_copy method from the STL is called in parallel
* using the access array to point to the beginning of each
* partition
* @param access Array of size @c num_threads + 1 that defines @c
* @param pos_beg_right Position of the first node in the
* resulting right partition (out)
* @param existing Number of existing elements before dividing
- * (in) and after (out). Specificically, the counter is
+ * (in) and after (out). Specifically, the counter is
* incremented by one for unique containers if the splitting key
* was already in the array of nodes.
* @param strictly_less_or_less_equal Comparator to deal
}
/** @brief Split a tree according to key in three parts: a left
- * child, a right child and an intermediate node.
+ * child, a right child and an intermediate node.
*
* Trees are concatenated once the recursive call returns. That
- * is, from bottom to top (ie. smaller to larger), so the cost
+ * is, from bottom to top (i. e. smaller to larger), so the cost
* bounds for split hold.
* @param t Root of the tree to split.
* @param key Key to split according to.
}
/** @brief Split the tree in two parts: the minimum element from a
- tree (i.e. leftmost) and the rest (right subtree)
+ tree (i. e. leftmost) and the rest (right subtree)
* @param t Root of the tree
* @param root Minimum element (out)
* @param r Right subtree: @c t - {@c root}
/** @brief Split the tree in two parts: the greatest element from
- a tree (i.e. rightmost) and the rest (left subtree)
+ a tree (i. e. rightmost) and the rest (left subtree)
* @param t Root of the tree
* @param root Maximum element (out)
* @param l Left subtree: @c t - {@c root}
* and a right subtree
*
* Trees are concatenated once the recursive call returns. That
- * is, from bottom to top (ie. smaller to larger), so the cost
+ * is, from bottom to top (i. e. smaller to larger), so the cost
* bounds for split hold.
* @param t Root of the tree to split.
* @param key Key to split according to.
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