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Reduce number of new / delete operations for class KDTreeSearch

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Add also several TODO comments because it is not clear why expensive
FLOAT64 calculations are used instead of cheaper FLOAT32 ones.

Signed-off-by: Stefan Weil <sw@weilnetz.de>
This commit is contained in:
Stefan Weil 2017-05-19 12:15:05 +02:00 committed by Zdenko Podobný
parent acf318af77
commit 046684f4cb
1 changed files with 11 additions and 10 deletions
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21
classify/kdtree.cpp
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@ -133,21 +133,20 @@ class KDTreeSearch {
KDTREE *tree_;
FLOAT32 *query_point_;
MinK<FLOAT32, void *>* results_;
FLOAT32 *sb_min_; //< search box minimum
FLOAT32 *sb_max_; //< search box maximum
MinK<FLOAT32, void *> results_;
};
KDTreeSearch::KDTreeSearch(KDTREE* tree, FLOAT32 *query_point, int k_closest) :
tree_(tree),
query_point_(query_point) {
results_ = new MinK<FLOAT32, void *>(MAXSEARCH, k_closest);
query_point_(query_point),
results_(MAXSEARCH, k_closest) {
sb_min_ = new FLOAT32[tree->KeySize];
sb_max_ = new FLOAT32[tree->KeySize];
}
KDTreeSearch::~KDTreeSearch() {
delete results_;
delete[] sb_min_;
delete[] sb_max_;
}
@ -165,11 +164,12 @@ void KDTreeSearch::Search(int *result_count,
sb_max_[i] = tree_->KeyDesc[i].Max;
}
SearchRec(0, tree_->Root.Left);
int count = results_->elements_count();
int count = results_.elements_count();
*result_count = count;
for (int j = 0; j < count; j++) {
distances[j] = (FLOAT32) sqrt((FLOAT64)results_->elements()[j].key);
results[j] = results_->elements()[j].value;
// TODO: why FLOAT64 here?
distances[j] = (FLOAT32) sqrt((FLOAT64)results_.elements()[j].key);
results[j] = results_.elements()[j].value;
}
}
}
@ -406,9 +406,9 @@ void KDTreeSearch::SearchRec(int level, KDNODE *sub_tree) {
if (!BoxIntersectsSearch(sb_min_, sb_max_))
return;
results_->insert(DistanceSquared(tree_->KeySize, tree_->KeyDesc,
results_.insert(DistanceSquared(tree_->KeySize, tree_->KeyDesc,
query_point_, sub_tree->Key),
sub_tree->Data);
sub_tree->Data);
if (query_point_[level] < sub_tree->BranchPoint) {
if (sub_tree->Left != NULL) {
@ -480,9 +480,10 @@ FLOAT32 ComputeDistance(int k, PARAM_DESC *dim, FLOAT32 p1[], FLOAT32 p2[]) {
/// one wrap distance away from the query.
bool KDTreeSearch::BoxIntersectsSearch(FLOAT32 *lower, FLOAT32 *upper) {
FLOAT32 *query = query_point_;
// Why FLOAT64?
FLOAT64 total_distance = 0.0;
FLOAT64 radius_squared =
results_->max_insertable_key() * results_->max_insertable_key();
results_.max_insertable_key() * results_.max_insertable_key();
PARAM_DESC *dim = tree_->KeyDesc;
for (int i = tree_->KeySize; i > 0; i--, dim++, query++, lower++, upper++) {