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BLI_kdtree: refactor to support different numbers of dimensions 

This moves logic into kdtree_impl.h which is included in a source
file that defines the number of dimensions - so we can easily support
different numbers of dimensions as needed
(currently 3D and 4D are supported).

Macro use isn't so nice but avoids a lot of duplicate code.
This commit is contained in:
Campbell Barton 2019-03-18 11:22:48 +11:00
parent e72dc667c4
commit 0719d5fa0c
6 changed files with 256 additions and 105 deletions
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67
source/blender/blenlib/BLI_kdtree.h
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@ -22,57 +22,22 @@
* \brief A kd-tree for nearest neighbor search.
*/
#include "BLI_compiler_attrs.h"
/* 3D version */
#define KD_DIMS 3
#define KDTREE_PREFIX_ID BLI_kdtree
#include "BLI_kdtree_impl.h"
#undef KD_DIMS
#undef KDTREE_PREFIX_ID
struct KDTree;
typedef struct KDTree KDTree;
typedef struct KDTreeNearest {
int index;
float dist;
float co[3];
} KDTreeNearest;
KDTree *BLI_kdtree_new(unsigned int maxsize);
void BLI_kdtree_free(KDTree *tree);
void BLI_kdtree_balance(KDTree *tree) ATTR_NONNULL(1);
void BLI_kdtree_insert(
KDTree *tree, int index,
const float co[3]) ATTR_NONNULL(1, 3);
int BLI_kdtree_find_nearest(
const KDTree *tree, const float co[3],
KDTreeNearest *r_nearest) ATTR_NONNULL(1, 2);
#define BLI_kdtree_find_nearest_n(tree, co, r_nearest, nearest_len_capacity) \
BLI_kdtree_find_nearest_n_with_len_squared_cb(tree, co, r_nearest, nearest_len_capacity, NULL, NULL)
#define BLI_kdtree_range_search(tree, co, r_nearest, range) \
BLI_kdtree_range_search_with_len_squared_cb(tree, co, r_nearest, range, NULL, NULL)
int BLI_kdtree_find_nearest_cb(
const KDTree *tree, const float co[3],
int (*filter_cb)(void *user_data, int index, const float co[3], float dist_sq), void *user_data,
KDTreeNearest *r_nearest);
void BLI_kdtree_range_search_cb(
const KDTree *tree, const float co[3], float range,
bool (*search_cb)(void *user_data, int index, const float co[3], float dist_sq), void *user_data);
int BLI_kdtree_calc_duplicates_fast(
const KDTree *tree, const float range, bool use_index_order,
int *doubles);
/* Versions of find/range search that take a squared distance callback to support bias. */
int BLI_kdtree_find_nearest_n_with_len_squared_cb(
const KDTree *tree, const float co[3],
KDTreeNearest *r_nearest,
const uint nearest_len_capacity,
float (*len_sq_fn)(const float co_search[3], const float co_test[3], const void *user_data),
const void *user_data) ATTR_NONNULL(1, 2, 3);
int BLI_kdtree_range_search_with_len_squared_cb(
const KDTree *tree, const float co[3],
KDTreeNearest **r_nearest,
const float range,
float (*len_sq_fn)(const float co_search[3], const float co_test[3], const void *user_data),
const void *user_data) ATTR_NONNULL(1, 2) ATTR_WARN_UNUSED_RESULT;
/* 4D version */
#define KD_DIMS 4
#define KDTREE_PREFIX_ID BLI_kdtree_4d
#define KDTree KDTree_4d
#define KDTreeNearest KDTreeNearest_4d
#include "BLI_kdtree_impl.h"
#undef KD_DIMS
#undef KDTree
#undef KDTreeNearest
#undef KDTREE_PREFIX_ID
#endif /* __BLI_KDTREE_H__ */

86
source/blender/blenlib/BLI_kdtree_impl.h Normal file
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@ -0,0 +1,86 @@
/*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
/** \file
* \ingroup bli
* \brief A kd-tree for nearest neighbor search.
*/
#include "BLI_compiler_attrs.h"
#define _CONCAT_AUX(MACRO_ARG1, MACRO_ARG2) MACRO_ARG1 ## MACRO_ARG2
#define _CONCAT(MACRO_ARG1, MACRO_ARG2) _CONCAT_AUX(MACRO_ARG1, MACRO_ARG2)
#define BLI_kdtree_nd_(id) _CONCAT(KDTREE_PREFIX_ID, _##id)
struct KDTree;
typedef struct KDTree KDTree;
typedef struct KDTreeNearest {
int index;
float dist;
float co[KD_DIMS];
} KDTreeNearest;
KDTree *BLI_kdtree_nd_(new)(unsigned int maxsize);
void BLI_kdtree_nd_(free)(KDTree *tree);
void BLI_kdtree_nd_(balance)(KDTree *tree) ATTR_NONNULL(1);
void BLI_kdtree_nd_(insert)(
KDTree *tree, int index,
const float co[KD_DIMS]) ATTR_NONNULL(1, 3);
int BLI_kdtree_nd_(find_nearest)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest *r_nearest) ATTR_NONNULL(1, 2);
int BLI_kdtree_nd_(find_nearest_n)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest *r_nearest,
const uint nearest_len_capacity) ATTR_NONNULL(1, 2, 3);
int BLI_kdtree_nd_(range_search)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest **r_nearest,
const float range) ATTR_NONNULL(1, 2) ATTR_WARN_UNUSED_RESULT;
int BLI_kdtree_nd_(find_nearest_cb)(
const KDTree *tree, const float co[KD_DIMS],
int (*filter_cb)(void *user_data, int index, const float co[KD_DIMS], float dist_sq), void *user_data,
KDTreeNearest *r_nearest);
void BLI_kdtree_nd_(range_search_cb)(
const KDTree *tree, const float co[KD_DIMS], float range,
bool (*search_cb)(void *user_data, int index, const float co[KD_DIMS], float dist_sq), void *user_data);
int BLI_kdtree_nd_(calc_duplicates_fast)(
const KDTree *tree, const float range, bool use_index_order,
int *doubles);
/* Versions of find/range search that take a squared distance callback to support bias. */
int BLI_kdtree_nd_(find_nearest_n_with_len_squared_cb)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest *r_nearest,
const uint nearest_len_capacity,
float (*len_sq_fn)(const float co_search[KD_DIMS], const float co_test[KD_DIMS], const void *user_data),
const void *user_data) ATTR_NONNULL(1, 2, 3);
int BLI_kdtree_nd_(range_search_with_len_squared_cb)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest **r_nearest,
const float range,
float (*len_sq_fn)(const float co_search[KD_DIMS], const float co_test[KD_DIMS], const void *user_data),
const void *user_data) ATTR_NONNULL(1, 2) ATTR_WARN_UNUSED_RESULT;
#undef _CONCAT_AUX
#undef _CONCAT
#undef BLI_kdtree_nd_

9
source/blender/blenlib/CMakeLists.txt
View File

@ -45,7 +45,6 @@ set(SRC
intern/BLI_heap.c
intern/BLI_heap_simple.c
intern/BLI_kdopbvh.c
intern/BLI_kdtree.c
intern/BLI_linklist.c
intern/BLI_linklist_lockfree.c
intern/BLI_memarena.c
@ -76,8 +75,9 @@ set(SRC
intern/hash_mm2a.c
intern/hash_mm3.c
intern/jitter_2d.c
intern/kdtree_3d.c
intern/kdtree_4d.c
intern/lasso_2d.c
intern/list_sort_impl.h
intern/listbase.c
intern/math_base.c
intern/math_base_inline.c
@ -124,6 +124,10 @@ set(SRC
intern/winstuff.c
intern/winstuff_dir.c
# Header as source (included in C files above).
intern/kdtree_impl.h
intern/list_sort_impl.h
BLI_alloca.h
BLI_args.h
BLI_array.h
@ -167,6 +171,7 @@ set(SRC
BLI_jitter_2d.h
BLI_kdopbvh.h
BLI_kdtree.h
BLI_kdtree_impl.h
BLI_lasso_2d.h
BLI_link_utils.h
BLI_linklist.h

25
source/blender/blenlib/intern/kdtree_3d.c Normal file
View File

@ -0,0 +1,25 @@
/*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
/** \file
* \ingroup bli
*/
#define KD_DIMS 3
#define KDTREE_PREFIX_ID BLI_kdtree
# include "kdtree_impl.h"
#undef DIMS
#undef KDTREE_PREFIX_ID

25
source/blender/blenlib/intern/kdtree_4d.c Normal file
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@ -0,0 +1,25 @@
/*
* This program is free software; you can redistribute it and/or
* modify it under the terms of the GNU General Public License
* as published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software Foundation,
* Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
*/
/** \file
* \ingroup bli
*/
#define KD_DIMS 4
#define KDTREE_PREFIX_ID BLI_kdtree_4d
#define KDTree KDTree_4d
#define KDTreeNearest KDTreeNearest_4d
#include "kdtree_impl.h"

149
source/blender/blenlib/intern/BLI_kdtree.c → source/blender/blenlib/intern/kdtree_impl.h
View File

@ -21,21 +21,25 @@
#include "MEM_guardedalloc.h"
#include "BLI_math.h"
#include "BLI_kdtree.h"
#include "BLI_kdtree_impl.h"
#include "BLI_utildefines.h"
#include "BLI_strict_flags.h"
#define _CONCAT_AUX(MACRO_ARG1, MACRO_ARG2) MACRO_ARG1 ## MACRO_ARG2
#define _CONCAT(MACRO_ARG1, MACRO_ARG2) _CONCAT_AUX(MACRO_ARG1, MACRO_ARG2)
#define BLI_kdtree_nd_(id) _CONCAT(KDTREE_PREFIX_ID, _##id)
typedef struct KDTreeNode_head {
uint left, right;
float co[3];
float co[KD_DIMS];
int index;
} KDTreeNode_head;
typedef struct KDTreeNode {
uint left, right;
float co[3];
float co[KD_DIMS];
int index;
uint d; /* range is only (0-2) */
uint d; /* range is only (0..KD_DIMS - 1) */
} KDTreeNode;
struct KDTree {
@ -57,10 +61,37 @@ struct KDTree {
/** When set we know all values are unbalanced, otherwise clear them when re-balancing: see T62210. */
#define KD_NODE_ROOT_IS_INIT ((uint)-2)
/* -------------------------------------------------------------------- */
/** \name Local Math API
* \{ */
static void copy_vn_vn(float v0[KD_DIMS], const float v1[KD_DIMS])
{
for (uint j = 0; j < KD_DIMS; j++) {
v0[j] = v1[j];
}
}
static float len_squared_vnvn(const float v0[KD_DIMS], const float v1[KD_DIMS])
{
float d = 0.0f;
for (uint j = 0; j < KD_DIMS; j++) {
d += SQUARE(v0[j] - v1[j]);
}
return d;
}
static float len_squared_vnvn_cb(const float co_kdtree[KD_DIMS], const float co_search[KD_DIMS], const void *UNUSED(user_data))
{
return len_squared_vnvn(co_kdtree, co_search);
}
/** \} */
/**
* Creates or free a kdtree
*/
KDTree *BLI_kdtree_new(uint nodes_len_capacity)
KDTree *BLI_kdtree_nd_(new)(uint nodes_len_capacity)
{
KDTree *tree;
@ -77,7 +108,7 @@ KDTree *BLI_kdtree_new(uint nodes_len_capacity)
return tree;
}
void BLI_kdtree_free(KDTree *tree)
void BLI_kdtree_nd_(free)(KDTree *tree)
{
if (tree) {
MEM_freeN(tree->nodes);
@ -88,7 +119,7 @@ void BLI_kdtree_free(KDTree *tree)
/**
* Construction: first insert points, then call balance. Normal is optional.
*/
void BLI_kdtree_insert(KDTree *tree, int index, const float co[3])
void BLI_kdtree_nd_(insert)(KDTree *tree, int index, const float co[KD_DIMS])
{
KDTreeNode *node = &tree->nodes[tree->nodes_len++];
@ -100,7 +131,7 @@ void BLI_kdtree_insert(KDTree *tree, int index, const float co[3])
* need to initialize all struct members */
node->left = node->right = KD_NODE_UNSET;
copy_v3_v3(node->co, co);
copy_vn_vn(node->co, co);
node->index = index;
node->d = 0;
@ -155,14 +186,14 @@ static uint kdtree_balance(KDTreeNode *nodes, uint nodes_len, uint axis, const u
/* set node and sort subnodes */
node = &nodes[median];
node->d = axis;
axis = (axis + 1) % 3;
axis = (axis + 1) % KD_DIMS;
node->left = kdtree_balance(nodes, median, axis, ofs);
node->right = kdtree_balance(nodes + median + 1, (nodes_len - (median + 1)), axis, (median + 1) + ofs);
return median + ofs;
}
void BLI_kdtree_balance(KDTree *tree)
void BLI_kdtree_nd_(balance)(KDTree *tree)
{
if (tree->root != KD_NODE_ROOT_IS_INIT) {
for (uint i = 0; i < tree->nodes_len; i++) {
@ -178,11 +209,6 @@ void BLI_kdtree_balance(KDTree *tree)
#endif
}
static float len_squared_v3v3_cb(const float co_kdtree[3], const float co_search[3], const void *UNUSED(user_data))
{
return len_squared_v3v3(co_kdtree, co_search);
}
static uint *realloc_nodes(uint *stack, uint *stack_len_capacity, const bool is_alloc)
{
uint *stack_new = MEM_mallocN((*stack_len_capacity + KD_NEAR_ALLOC_INC) * sizeof(uint), "KDTree.treestack");
@ -198,8 +224,8 @@ static uint *realloc_nodes(uint *stack, uint *stack_len_capacity, const bool is_
/**
* Find nearest returns index, and -1 if no node is found.
*/
int BLI_kdtree_find_nearest(
const KDTree *tree, const float co[3],
int BLI_kdtree_nd_(find_nearest)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest *r_nearest)
{
const KDTreeNode *nodes = tree->nodes;
@ -221,7 +247,7 @@ int BLI_kdtree_find_nearest(
root = &nodes[tree->root];
min_node = root;
min_dist = len_squared_v3v3(root->co, co);
min_dist = len_squared_vnvn(root->co, co);
if (co[root->d] < root->co[root->d]) {
if (root->right != KD_NODE_UNSET) {
@ -249,7 +275,7 @@ int BLI_kdtree_find_nearest(
cur_dist = -cur_dist * cur_dist;
if (-cur_dist < min_dist) {
cur_dist = len_squared_v3v3(node->co, co);
cur_dist = len_squared_vnvn(node->co, co);
if (cur_dist < min_dist) {
min_dist = cur_dist;
min_node = node;
@ -266,7 +292,7 @@ int BLI_kdtree_find_nearest(
cur_dist = cur_dist * cur_dist;
if (cur_dist < min_dist) {
cur_dist = len_squared_v3v3(node->co, co);
cur_dist = len_squared_vnvn(node->co, co);
if (cur_dist < min_dist) {
min_dist = cur_dist;
min_node = node;
@ -279,7 +305,7 @@ int BLI_kdtree_find_nearest(
stack[cur++] = node->left;
}
}
if (UNLIKELY(cur + 3 > stack_len_capacity)) {
if (UNLIKELY(cur + KD_DIMS > stack_len_capacity)) {
stack = realloc_nodes(stack, &stack_len_capacity, stack_default != stack);
}
}
@ -287,7 +313,7 @@ int BLI_kdtree_find_nearest(
if (r_nearest) {
r_nearest->index = min_node->index;
r_nearest->dist = sqrtf(min_dist);
copy_v3_v3(r_nearest->co, min_node->co);
copy_vn_vn(r_nearest->co, min_node->co);
}
if (stack != stack_default) {
@ -305,9 +331,9 @@ int BLI_kdtree_find_nearest(
* \param filter_cb: Filter find results,
* Return codes: (1: accept, 0: skip, -1: immediate exit).
*/
int BLI_kdtree_find_nearest_cb(
const KDTree *tree, const float co[3],
int (*filter_cb)(void *user_data, int index, const float co[3], float dist_sq), void *user_data,
int BLI_kdtree_nd_(find_nearest_cb)(
const KDTree *tree, const float co[KD_DIMS],
int (*filter_cb)(void *user_data, int index, const float co[KD_DIMS], float dist_sq), void *user_data,
KDTreeNearest *r_nearest)
{
const KDTreeNode *nodes = tree->nodes;
@ -330,7 +356,7 @@ int BLI_kdtree_find_nearest_cb(
#define NODE_TEST_NEAREST(node) \
{ \
const float dist_sq = len_squared_v3v3((node)->co, co); \
const float dist_sq = len_squared_vnvn((node)->co, co); \
if (dist_sq < min_dist) { \
const int result = filter_cb(user_data, (node)->index, (node)->co, dist_sq); \
if (result == 1) { \
@ -382,7 +408,7 @@ int BLI_kdtree_find_nearest_cb(
stack[cur++] = node->left;
}
}
if (UNLIKELY(cur + 3 > stack_len_capacity)) {
if (UNLIKELY(cur + KD_DIMS > stack_len_capacity)) {
stack = realloc_nodes(stack, &stack_len_capacity, stack_default != stack);
}
}
@ -399,7 +425,7 @@ finally:
if (r_nearest) {
r_nearest->index = min_node->index;
r_nearest->dist = sqrtf(min_dist);
copy_v3_v3(r_nearest->co, min_node->co);
copy_vn_vn(r_nearest->co, min_node->co);
}
return min_node->index;
@ -411,7 +437,7 @@ finally:
static void nearest_ordered_insert(
KDTreeNearest *nearest, uint *nearest_len, const uint nearest_len_capacity,
const int index, const float dist, const float co[3])
const int index, const float dist, const float co[KD_DIMS])
{
uint i;
@ -430,7 +456,7 @@ static void nearest_ordered_insert(
nearest[i].index = index;
nearest[i].dist = dist;
copy_v3_v3(nearest[i].co, co);
copy_vn_vn(nearest[i].co, co);
}
/**
@ -438,11 +464,11 @@ static void nearest_ordered_insert(
*
* \param r_nearest: An array of nearest, sized at least \a nearest_len_capacity.
*/
int BLI_kdtree_find_nearest_n_with_len_squared_cb(
const KDTree *tree, const float co[3],
int BLI_kdtree_nd_(find_nearest_n_with_len_squared_cb)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest r_nearest[],
const uint nearest_len_capacity,
float (*len_sq_fn)(const float co_search[3], const float co_test[3], const void *user_data),
float (*len_sq_fn)(const float co_search[KD_DIMS], const float co_test[KD_DIMS], const void *user_data),
const void *user_data)
{
const KDTreeNode *nodes = tree->nodes;
@ -461,7 +487,7 @@ int BLI_kdtree_find_nearest_n_with_len_squared_cb(
}
if (len_sq_fn == NULL) {
len_sq_fn = len_squared_v3v3_cb;
len_sq_fn = len_squared_vnvn_cb;
BLI_assert(user_data == NULL);
}
@ -530,7 +556,7 @@ int BLI_kdtree_find_nearest_n_with_len_squared_cb(
stack[cur++] = node->left;
}
}
if (UNLIKELY(cur + 3 > stack_len_capacity)) {
if (UNLIKELY(cur + KD_DIMS > stack_len_capacity)) {
stack = realloc_nodes(stack, &stack_len_capacity, stack_default != stack);
}
}
@ -546,6 +572,16 @@ int BLI_kdtree_find_nearest_n_with_len_squared_cb(
return (int)nearest_len;
}
int BLI_kdtree_nd_(find_nearest_n)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest r_nearest[],
const uint nearest_len_capacity)
{
return BLI_kdtree_nd_(find_nearest_n_with_len_squared_cb)(
tree, co, r_nearest, nearest_len_capacity,
NULL, NULL);
}
static int nearest_cmp_dist(const void *a, const void *b)
{
const KDTreeNearest *kda = a;
@ -565,7 +601,7 @@ static void nearest_add_in_range(
KDTreeNearest **r_nearest,
uint nearest_index,
uint *nearest_len_capacity,
const int index, const float dist, const float co[3])
const int index, const float dist, const float co[KD_DIMS])
{
KDTreeNearest *to;
@ -580,7 +616,7 @@ static void nearest_add_in_range(
to->index = index;
to->dist = sqrtf(dist);
copy_v3_v3(to->co, co);
copy_vn_vn(to->co, co);
}
/**
@ -588,10 +624,10 @@ static void nearest_add_in_range(
*
* \param r_nearest: Allocated array of nearest nearest_len (caller is responsible for freeing).
*/
int BLI_kdtree_range_search_with_len_squared_cb(
const KDTree *tree, const float co[3],
int BLI_kdtree_nd_(range_search_with_len_squared_cb)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest **r_nearest, const float range,
float (*len_sq_fn)(const float co_search[3], const float co_test[3], const void *user_data),
float (*len_sq_fn)(const float co_search[KD_DIMS], const float co_test[KD_DIMS], const void *user_data),
const void *user_data)
{
const KDTreeNode *nodes = tree->nodes;
@ -611,7 +647,7 @@ int BLI_kdtree_range_search_with_len_squared_cb(
}
if (len_sq_fn == NULL) {
len_sq_fn = len_squared_v3v3_cb;
len_sq_fn = len_squared_vnvn_cb;
BLI_assert(user_data == NULL);
}
@ -647,7 +683,7 @@ int BLI_kdtree_range_search_with_len_squared_cb(
}
}
if (UNLIKELY(cur + 3 > stack_len_capacity)) {
if (UNLIKELY(cur + KD_DIMS > stack_len_capacity)) {
stack = realloc_nodes(stack, &stack_len_capacity, stack_default != stack);
}
}
@ -665,6 +701,15 @@ int BLI_kdtree_range_search_with_len_squared_cb(
return (int)nearest_len;
}
int BLI_kdtree_nd_(range_search)(
const KDTree *tree, const float co[KD_DIMS],
KDTreeNearest **r_nearest, const float range)
{
return BLI_kdtree_nd_(range_search_with_len_squared_cb)(
tree, co, r_nearest, range,
NULL, NULL);
}
/**
* A version of #BLI_kdtree_range_search which runs a callback
* instead of allocating an array.
@ -673,9 +718,9 @@ int BLI_kdtree_range_search_with_len_squared_cb(
*
* \note the order of calls isn't sorted based on distance.
*/
void BLI_kdtree_range_search_cb(
const KDTree *tree, const float co[3], float range,
bool (*search_cb)(void *user_data, int index, const float co[3], float dist_sq), void *user_data)
void BLI_kdtree_nd_(range_search_cb)(
const KDTree *tree, const float co[KD_DIMS], float range,
bool (*search_cb)(void *user_data, int index, const float co[KD_DIMS], float dist_sq), void *user_data)
{
const KDTreeNode *nodes = tree->nodes;
@ -710,7 +755,7 @@ void BLI_kdtree_range_search_cb(
}
}
else {
dist_sq = len_squared_v3v3(node->co, co);
dist_sq = len_squared_vnvn(node->co, co);
if (dist_sq <= range_sq) {
if (search_cb(user_data, node->index, node->co, dist_sq) == false) {
goto finally;
@ -725,7 +770,7 @@ void BLI_kdtree_range_search_cb(
}
}
if (UNLIKELY(cur + 3 > stack_len_capacity)) {
if (UNLIKELY(cur + KD_DIMS > stack_len_capacity)) {
stack = realloc_nodes(stack, &stack_len_capacity, stack_default != stack);
}
}
@ -763,7 +808,7 @@ struct DeDuplicateParams {
int *duplicates_found;
/* Per Search */
float search_co[3];
float search_co[KD_DIMS];
int search;
};
@ -782,7 +827,7 @@ static void deduplicate_recursive(const struct DeDuplicateParams *p, uint i)
}
else {
if ((p->search != node->index) && (p->duplicates[node->index] == -1)) {
if (len_squared_v3v3(node->co, p->search_co) <= p->range_sq) {
if (len_squared_vnvn(node->co, p->search_co) <= p->range_sq) {
p->duplicates[node->index] = (int)p->search;
*p->duplicates_found += 1;
}
@ -814,7 +859,7 @@ static void deduplicate_recursive(const struct DeDuplicateParams *p, uint i)
*
* \note Merging is always a single step (target indices wont be marked for merging).
*/
int BLI_kdtree_calc_duplicates_fast(
int BLI_kdtree_nd_(calc_duplicates_fast)(
const KDTree *tree, const float range, bool use_index_order,
int *duplicates)
{
@ -834,7 +879,7 @@ int BLI_kdtree_calc_duplicates_fast(
const int index = (int)i;
if (ELEM(duplicates[index], -1, index)) {
p.search = index;
copy_v3_v3(p.search_co, tree->nodes[node_index].co);
copy_vn_vn(p.search_co, tree->nodes[node_index].co);
int found_prev = found;
deduplicate_recursive(&p, tree->root);
if (found != found_prev) {
@ -851,7 +896,7 @@ int BLI_kdtree_calc_duplicates_fast(
const int index = p.nodes[node_index].index;
if (ELEM(duplicates[index], -1, index)) {
p.search = index;
copy_v3_v3(p.search_co, tree->nodes[node_index].co);
copy_vn_vn(p.search_co, tree->nodes[node_index].co);
int found_prev = found;
deduplicate_recursive(&p, tree->root);
if (found != found_prev) {