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Changed kdtree_impl functions to pass by reference (when applicable)

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This commit is contained in:
jwaters6
2008-05-23 19:57:54 +00:00
parent a2e5f9041c
commit c46a49b7dd
3 changed files with 35 additions and 61 deletions
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fastlib2/fastlib/tree/bounds.h
-27
View File
@@ -198,33 +198,6 @@ class DHrectBound {
}
/**
* Calcualtes minimum bound-to-bound squared distance, with
* an offset between their respective coordinate systems.
*/
double MinDistanceSq(const DHrectBound& other, const Vector& offset) const {
double sum = 0;
const DRange *a = this->bounds_;
const DRange *b = other.bounds_;
index_t mdim = dim_;
DEBUG_SAME_SIZE(dim_, other.dim_);
//Add Debug for offset vector
for (index_t d = 0; d < mdim; d++) {
double v1 = b[d].lo + offset[d] - a[d].hi;
double v2 = a[d].lo - offset[d] - b[d].lo;
double v = (v1 + fabs(v1)) + (v2 + fabs(v2));
sum += math::Pow<t_pow, 1>(v);
}
return math::Pow<2, t_pow>(sum) / 4;
}
/**
* Calculates maximum bound-to-point squared distance.
*/
fastlib2/fastlib/tree/kdtree.h
+3 -3
View File
@@ -48,7 +48,7 @@ namespace tree {
template<typename TKdTree, typename T>
TKdTree *MakeKdTreeMidpointSelective(GenMatrix<T>& matrix,
Vector* split_dimensions,
const Vector& split_dimensions,
index_t leaf_size,
ArrayList<index_t> *old_from_new = NULL,
ArrayList<index_t> *new_from_old = NULL) {
@@ -68,7 +68,7 @@ namespace tree {
}
node->Init(0, matrix.n_cols());
node->bound().Init(split_dimensions->length());
node->bound().Init(split_dimensions.length());
tree_kdtree_private::SelectFindBoundFromMatrix(matrix, split_dimensions,
0, matrix.n_cols(), &node->bound());
@@ -95,7 +95,7 @@ namespace tree {
split_dimensions[i] = i;
}
TKdTree *result;
result = MakeKdTreeMidpointSelective<TKdTree>(matrix, &split_dimensions,
result = MakeKdTreeMidpointSelective<TKdTree>(matrix, split_dimensions,
leaf_size, old_from_new, new_from_old);
return result;
}
fastlib2/fastlib/tree/kdtree_impl.h
+32 -31
View File
@@ -2,28 +2,29 @@
namespace tree_kdtree_private {
template<typename T>
void MakeBoundVector(GenVector<T>* point, GenVector<T>* bound_dimensions,
GenVector<T>* bound_vector){
void MakeBoundVector(const GenVector<T>& point,
const Vector& bound_dimensions, GenVector<T>* bound_vector){
int i;
for (i = 0; i < bound_dimensions->length(); i++){
(*bound_vector)[i] = (*point)[(int)(*bound_dimensions)[i]];
for (i = 0; i < bound_dimensions.length(); i++){
(*bound_vector)[i] = point[(int)bound_dimensions[i]];
}
}
template<typename TBound, typename T>
void SelectFindBoundFromMatrix(const GenMatrix<T>& matrix,
Vector* split_dimensions, index_t first, index_t count, TBound *bounds){
const Vector& split_dimensions, index_t first, index_t count,
TBound *bounds){
index_t end = first + count;
for (index_t i = first; i < end; i++) {
GenVector<T> col;
matrix.MakeColumnVector(i, &col);
if (split_dimensions->length() == matrix.n_rows()){
if (split_dimensions.length() == matrix.n_rows()){
*bounds |= col;
} else {
GenVector<T> sub_col;
sub_col.Init(split_dimensions->length());
MakeBoundVector(&col, split_dimensions, &sub_col);
sub_col.Init(split_dimensions.length());
MakeBoundVector(col, split_dimensions, &sub_col);
*bounds |= sub_col;
}
}
@@ -38,7 +39,7 @@ namespace tree_kdtree_private {
for (i = 0; i < matrix.n_rows(); i++){
split_dimensions[i] = i;
}
SelectFindBoundFromMatrix(matrix, &split_dimensions, first, count, bounds);
SelectFindBoundFromMatrix(matrix, split_dimensions, first, count, bounds);
}
template<typename TBound>
@@ -59,11 +60,11 @@ namespace tree_kdtree_private {
}
template<typename TBound, typename T>
index_t SelectMatrixPartition(GenMatrix<T>& matrix, Vector* split_dimensions,
index_t dim, double splitvalue,
index_t first, index_t count,
TBound* left_bound, TBound* right_bound,
index_t *old_from_new) {
index_t SelectMatrixPartition(GenMatrix<T>& matrix,
const Vector& split_dimensions, index_t dim, double splitvalue,
index_t first, index_t count, TBound* left_bound, TBound* right_bound,
index_t *old_from_new) {
index_t left = first;
index_t right = first + count - 1;
@@ -76,11 +77,11 @@ namespace tree_kdtree_private {
while (matrix.get(dim, left) < splitvalue && likely(left <= right)) {
GenVector<T> left_vector;
matrix.MakeColumnVector(left, &left_vector);
if (split_dimensions->length() == matrix.n_rows()){
if (split_dimensions.length() == matrix.n_rows()){
*left_bound |= left_vector;
} else {
GenVector<T> sub_left_vector;
MakeBoundVector(&left_vector, split_dimensions, &sub_left_vector);
MakeBoundVector(left_vector, split_dimensions, &sub_left_vector);
*left_bound |= sub_left_vector;
}
left++;
@@ -89,11 +90,11 @@ namespace tree_kdtree_private {
while (matrix.get(dim, right) >= splitvalue && likely(left <= right)) {
GenVector<T> right_vector;
matrix.MakeColumnVector(right, &right_vector);
if (split_dimensions->length() == matrix.n_rows()){
if (split_dimensions.length() == matrix.n_rows()){
*right_bound |= right_vector;
} else {
GenVector<T> sub_right_vector;
MakeBoundVector(&right_vector, split_dimensions, &sub_right_vector);
MakeBoundVector(right_vector, split_dimensions, &sub_right_vector);
*right_bound |= sub_right_vector;
}
right--;
@@ -112,19 +113,19 @@ namespace tree_kdtree_private {
left_vector.SwapValues(&right_vector);
if (split_dimensions->length() == matrix.n_rows()){
if (split_dimensions.length() == matrix.n_rows()){
*left_bound |= left_vector;
} else {
GenVector<T> sub_left_vector;
MakeBoundVector(&left_vector, split_dimensions, &sub_left_vector);
MakeBoundVector(left_vector, split_dimensions, &sub_left_vector);
*left_bound |= sub_left_vector;
}
if (split_dimensions->length() == matrix.n_rows()){
if (split_dimensions.length() == matrix.n_rows()){
*right_bound |= right_vector;
} else {
GenVector<T> sub_right_vector;
MakeBoundVector(&right_vector, split_dimensions, &sub_right_vector);
MakeBoundVector(right_vector, split_dimensions, &sub_right_vector);
*right_bound |= sub_right_vector;
}
@@ -159,15 +160,15 @@ namespace tree_kdtree_private {
for (i = 0; i < matrix.n_rows(); i++){
split_dimensions[i] = i;
}
SelectSplitKdTreeMidpoint(matrix, &split_dimensions, node,
SelectSplitKdTreeMidpoint(matrix, split_dimensions, node,
leaf_size, old_from_new);
}
template<typename TKdTree, typename T>
void SelectSplitKdTreeMidpoint(GenMatrix<T>& matrix,
Vector* split_dimensions,
TKdTree *node, index_t leaf_size, index_t *old_from_new) {
void SelectSplitKdTreeMidpoint(GenMatrix<T>& matrix,
const Vector& split_dimensions, TKdTree *node, index_t leaf_size,
index_t *old_from_new) {
TKdTree *left = NULL;
TKdTree *right = NULL;
@@ -179,7 +180,7 @@ namespace tree_kdtree_private {
index_t split_dim = BIG_BAD_NUMBER;
double max_width = -1;
for (index_t d = 0; d < split_dimensions->length(); d++) {
for (index_t d = 0; d < split_dimensions.length(); d++) {
double w = node->bound().get(d).width();
if (w > max_width) {
@@ -195,20 +196,20 @@ namespace tree_kdtree_private {
// same. We have to give up.
} else {
left = new TKdTree();
left->bound().Init(split_dimensions->length());
left->bound().Init(split_dimensions.length());
right = new TKdTree();
right->bound().Init(split_dimensions->length());
right->bound().Init(split_dimensions.length());
index_t split_col = SelectMatrixPartition(matrix, split_dimensions,
(int)(*split_dimensions)[split_dim], split_val,
(int)split_dimensions[split_dim], split_val,
node->begin(), node->count(),
&left->bound(), &right->bound(),
old_from_new);
VERBOSE_MSG(3.0,"split (%d,[%d],%d) dim %d on %f (between %f, %f)",
node->begin(), split_col,
node->begin() + node->count(), (int)(*split_dimensions)[split_dim],
node->begin() + node->count(), (int)split_dimensions[split_dim],
split_val,
node->bound().get(split_dim).lo,
node->bound().get(split_dim).hi);