Files
@ r23755:c8be91297a35
Branch filter:
Location: cpp/openttd-patchpack/source/src/core/kdtree.hpp - annotation
r23755:c8be91297a35
16.7 KiB
text/x-c++hdr
Update: Translations from eints
hungarian: 3 changes by Brumi
hungarian: 3 changes by Brumi
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 | r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23607:36c15679007d r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23607:36c15679007d r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23607:36c15679007d r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23607:36c15679007d r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23607:36c15679007d r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca r23434:43b436f149ca | /*
* This file is part of OpenTTD.
* OpenTTD 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, version 2.
* OpenTTD 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 OpenTTD. If not, see <http://www.gnu.org/licenses/>.
*/
/** @file kdtree.hpp K-d tree template specialised for 2-dimensional Manhattan geometry */
#ifndef KDTREE_HPP
#define KDTREE_HPP
#include "../stdafx.h"
#include <vector>
#include <algorithm>
#include <limits>
/**
* K-dimensional tree, specialised for 2-dimensional space.
* This is not intended as a primary storage of data, but as an index into existing data.
* Usually the type stored by this tree should be an index into an existing array.
*
* This implementation assumes Manhattan distances are used.
*
* Be careful when using this in game code, depending on usage pattern, the tree shape may
* end up different for different clients in multiplayer, causing iteration order to differ
* and possibly having elements returned in different order. The using code should be designed
* to produce the same result regardless of iteration order.
*
* The element type T must be less-than comparable for FindNearest to work.
*
* @tparam T Type stored in the tree, should be cheap to copy.
* @tparam TxyFunc Functor type to extract coordinate from a T value and dimension index (0 or 1).
* @tparam CoordT Type of coordinate values extracted via TxyFunc.
* @tparam DistT Type to use for representing distance values.
*/
template <typename T, typename TxyFunc, typename CoordT, typename DistT>
class Kdtree {
/** Type of a node in the tree */
struct node {
T element; ///< Element stored at node
size_t left; ///< Index of node to the left, INVALID_NODE if none
size_t right; ///< Index of node to the right, INVALID_NODE if none
node(T element) : element(element), left(INVALID_NODE), right(INVALID_NODE) { }
};
static const size_t INVALID_NODE = SIZE_MAX; ///< Index value indicating no-such-node
std::vector<node> nodes; ///< Pool of all nodes in the tree
std::vector<size_t> free_list; ///< List of dead indices in the nodes vector
size_t root; ///< Index of root node
TxyFunc xyfunc; ///< Functor to extract a coordinate from an element
size_t unbalanced; ///< Number approximating how unbalanced the tree might be
/** Create one new node in the tree, return its index in the pool */
size_t AddNode(const T &element)
{
if (this->free_list.size() == 0) {
this->nodes.emplace_back(element);
return this->nodes.size() - 1;
} else {
size_t newidx = this->free_list.back();
this->free_list.pop_back();
this->nodes[newidx] = node{ element };
return newidx;
}
}
/** Find a coordinate value to split a range of elements at */
template <typename It>
CoordT SelectSplitCoord(It begin, It end, int level)
{
It mid = begin + (end - begin) / 2;
std::nth_element(begin, mid, end, [&](T a, T b) { return this->xyfunc(a, level % 2) < this->xyfunc(b, level % 2); });
return this->xyfunc(*mid, level % 2);
}
/** Construct a subtree from elements between begin and end iterators, return index of root */
template <typename It>
size_t BuildSubtree(It begin, It end, int level)
{
ptrdiff_t count = end - begin;
if (count == 0) {
return INVALID_NODE;
} else if (count == 1) {
return this->AddNode(*begin);
} else if (count > 1) {
CoordT split_coord = SelectSplitCoord(begin, end, level);
It split = std::partition(begin, end, [&](T v) { return this->xyfunc(v, level % 2) < split_coord; });
size_t newidx = this->AddNode(*split);
this->nodes[newidx].left = this->BuildSubtree(begin, split, level + 1);
this->nodes[newidx].right = this->BuildSubtree(split + 1, end, level + 1);
return newidx;
} else {
NOT_REACHED();
}
}
/** Rebuild the tree with all existing elements, optionally adding or removing one more */
bool Rebuild(const T *include_element, const T *exclude_element)
{
size_t initial_count = this->Count();
if (initial_count < 8) return false; // arbitrary value for "not worth rebalancing"
T root_element = this->nodes[this->root].element;
std::vector<T> elements = this->FreeSubtree(this->root);
elements.push_back(root_element);
if (include_element != nullptr) {
elements.push_back(*include_element);
initial_count++;
}
if (exclude_element != nullptr) {
typename std::vector<T>::iterator removed = std::remove(elements.begin(), elements.end(), *exclude_element);
elements.erase(removed, elements.end());
initial_count--;
}
this->Build(elements.begin(), elements.end());
assert(initial_count == this->Count());
return true;
}
/** Insert one element in the tree somewhere below node_idx */
void InsertRecursive(const T &element, size_t node_idx, int level)
{
/* Dimension index of current level */
int dim = level % 2;
/* Node reference */
node &n = this->nodes[node_idx];
/* Coordinate of element splitting at this node */
CoordT nc = this->xyfunc(n.element, dim);
/* Coordinate of the new element */
CoordT ec = this->xyfunc(element, dim);
/* Which side to insert on */
size_t &next = (ec < nc) ? n.left : n.right;
if (next == INVALID_NODE) {
/* New leaf */
size_t newidx = this->AddNode(element);
/* Vector may have been reallocated at this point, n and next are invalid */
node &nn = this->nodes[node_idx];
if (ec < nc) nn.left = newidx; else nn.right = newidx;
} else {
this->InsertRecursive(element, next, level + 1);
}
}
/**
* Free all children of the given node
* @return Collection of elements that were removed from tree.
*/
std::vector<T> FreeSubtree(size_t node_idx)
{
std::vector<T> subtree_elements;
node &n = this->nodes[node_idx];
/* We'll be appending items to the free_list, get index of our first item */
size_t first_free = this->free_list.size();
/* Prepare the descent with our children */
if (n.left != INVALID_NODE) this->free_list.push_back(n.left);
if (n.right != INVALID_NODE) this->free_list.push_back(n.right);
n.left = n.right = INVALID_NODE;
/* Recursively free the nodes being collected */
for (size_t i = first_free; i < this->free_list.size(); i++) {
node &fn = this->nodes[this->free_list[i]];
subtree_elements.push_back(fn.element);
if (fn.left != INVALID_NODE) this->free_list.push_back(fn.left);
if (fn.right != INVALID_NODE) this->free_list.push_back(fn.right);
fn.left = fn.right = INVALID_NODE;
}
return subtree_elements;
}
/**
* Find and remove one element from the tree.
* @param element The element to search for
* @param node_idx Sub-tree to search in
* @param level Current depth in the tree
* @return New root node index of the sub-tree processed
*/
size_t RemoveRecursive(const T &element, size_t node_idx, int level)
{
/* Node reference */
node &n = this->nodes[node_idx];
if (n.element == element) {
/* Remove this one */
this->free_list.push_back(node_idx);
if (n.left == INVALID_NODE && n.right == INVALID_NODE) {
/* Simple case, leaf, new child node for parent is "none" */
return INVALID_NODE;
} else {
/* Complex case, rebuild the sub-tree */
std::vector<T> subtree_elements = this->FreeSubtree(node_idx);
return this->BuildSubtree(subtree_elements.begin(), subtree_elements.end(), level);;
}
} else {
/* Search in a sub-tree */
/* Dimension index of current level */
int dim = level % 2;
/* Coordinate of element splitting at this node */
CoordT nc = this->xyfunc(n.element, dim);
/* Coordinate of the element being removed */
CoordT ec = this->xyfunc(element, dim);
/* Which side to remove from */
size_t next = (ec < nc) ? n.left : n.right;
assert(next != INVALID_NODE); // node must exist somewhere and must be found before a leaf is reached
/* Descend */
size_t new_branch = this->RemoveRecursive(element, next, level + 1);
if (new_branch != next) {
/* Vector may have been reallocated at this point, n and next are invalid */
node &nn = this->nodes[node_idx];
if (ec < nc) nn.left = new_branch; else nn.right = new_branch;
}
return node_idx;
}
}
DistT ManhattanDistance(const T &element, CoordT x, CoordT y) const
{
return abs((DistT)this->xyfunc(element, 0) - (DistT)x) + abs((DistT)this->xyfunc(element, 1) - (DistT)y);
}
/** A data element and its distance to a searched-for point */
using node_distance = std::pair<T, DistT>;
/** Ordering function for node_distance objects, elements with equal distance are ordered by less-than comparison */
static node_distance SelectNearestNodeDistance(const node_distance &a, const node_distance &b)
{
if (a.second < b.second) return a;
if (b.second < a.second) return b;
if (a.first < b.first) return a;
if (b.first < a.first) return b;
NOT_REACHED(); // a.first == b.first: same element must not be inserted twice
}
/** Search a sub-tree for the element nearest to a given point */
node_distance FindNearestRecursive(CoordT xy[2], size_t node_idx, int level) const
{
/* Dimension index of current level */
int dim = level % 2;
/* Node reference */
const node &n = this->nodes[node_idx];
/* Coordinate of element splitting at this node */
CoordT c = this->xyfunc(n.element, dim);
/* This node's distance to target */
DistT thisdist = ManhattanDistance(n.element, xy[0], xy[1]);
/* Assume this node is the best choice for now */
node_distance best = std::make_pair(n.element, thisdist);
/* Next node to visit */
size_t next = (xy[dim] < c) ? n.left : n.right;
if (next != INVALID_NODE) {
/* Check if there is a better node down the tree */
best = SelectNearestNodeDistance(best, this->FindNearestRecursive(xy, next, level + 1));
}
/* Check if the distance from current best is worse than distance from target to splitting line,
* if it is we also need to check the other side of the split. */
size_t opposite = (xy[dim] >= c) ? n.left : n.right; // reverse of above
if (opposite != INVALID_NODE && best.second >= abs((int)xy[dim] - (int)c)) {
node_distance other_candidate = this->FindNearestRecursive(xy, opposite, level + 1);
best = SelectNearestNodeDistance(best, other_candidate);
}
return best;
}
template <typename Outputter>
void FindContainedRecursive(CoordT p1[2], CoordT p2[2], size_t node_idx, int level, Outputter outputter) const
{
/* Dimension index of current level */
int dim = level % 2;
/* Node reference */
const node &n = this->nodes[node_idx];
/* Coordinate of element splitting at this node */
CoordT ec = this->xyfunc(n.element, dim);
/* Opposite coordinate of element */
CoordT oc = this->xyfunc(n.element, 1 - dim);
/* Test if this element is within rectangle */
if (ec >= p1[dim] && ec < p2[dim] && oc >= p1[1 - dim] && oc < p2[1 - dim]) outputter(n.element);
/* Recurse left if part of rectangle is left of split */
if (p1[dim] < ec && n.left != INVALID_NODE) this->FindContainedRecursive(p1, p2, n.left, level + 1, outputter);
/* Recurse right if part of rectangle is right of split */
if (p2[dim] > ec && n.right != INVALID_NODE) this->FindContainedRecursive(p1, p2, n.right, level + 1, outputter);
}
/** Debugging function, counts number of occurrences of an element regardless of its correct position in the tree */
size_t CountValue(const T &element, size_t node_idx) const
{
if (node_idx == INVALID_NODE) return 0;
const node &n = this->nodes[node_idx];
return CountValue(element, n.left) + CountValue(element, n.right) + ((n.element == element) ? 1 : 0);
}
void IncrementUnbalanced(size_t amount = 1)
{
this->unbalanced += amount;
}
/** Check if the entire tree is in need of rebuilding */
bool IsUnbalanced()
{
size_t count = this->Count();
if (count < 8) return false;
return this->unbalanced > this->Count() / 4;
}
/** Verify that the invariant is true for a sub-tree, assert if not */
void CheckInvariant(size_t node_idx, int level, CoordT min_x, CoordT max_x, CoordT min_y, CoordT max_y)
{
if (node_idx == INVALID_NODE) return;
const node &n = this->nodes[node_idx];
CoordT cx = this->xyfunc(n.element, 0);
CoordT cy = this->xyfunc(n.element, 1);
assert(cx >= min_x);
assert(cx < max_x);
assert(cy >= min_y);
assert(cy < max_y);
if (level % 2 == 0) {
// split in dimension 0 = x
CheckInvariant(n.left, level + 1, min_x, cx, min_y, max_y);
CheckInvariant(n.right, level + 1, cx, max_x, min_y, max_y);
} else {
// split in dimension 1 = y
CheckInvariant(n.left, level + 1, min_x, max_x, min_y, cy);
CheckInvariant(n.right, level + 1, min_x, max_x, cy, max_y);
}
}
/** Verify the invariant for the entire tree, does nothing unless KDTREE_DEBUG is defined */
void CheckInvariant()
{
#ifdef KDTREE_DEBUG
CheckInvariant(this->root, 0, std::numeric_limits<CoordT>::min(), std::numeric_limits<CoordT>::max(), std::numeric_limits<CoordT>::min(), std::numeric_limits<CoordT>::max());
#endif
}
public:
/** Construct a new Kdtree with the given xyfunc */
Kdtree(TxyFunc xyfunc) : root(INVALID_NODE), xyfunc(xyfunc), unbalanced(0) { }
/**
* Clear and rebuild the tree from a new sequence of elements,
* @tparam It Iterator type for element sequence.
* @param begin First element in sequence.
* @param end One past last element in sequence.
*/
template <typename It>
void Build(It begin, It end)
{
this->nodes.clear();
this->free_list.clear();
this->unbalanced = 0;
if (begin == end) return;
this->nodes.reserve(end - begin);
this->root = this->BuildSubtree(begin, end, 0);
CheckInvariant();
}
/**
* Reconstruct the tree with the same elements, letting it be fully balanced.
*/
void Rebuild()
{
this->Rebuild(nullptr, nullptr);
}
/**
* Insert a single element in the tree.
* Repeatedly inserting single elements may cause the tree to become unbalanced.
* Undefined behaviour if the element already exists in the tree.
*/
void Insert(const T &element)
{
if (this->Count() == 0) {
this->root = this->AddNode(element);
} else {
if (!this->IsUnbalanced() || !this->Rebuild(&element, nullptr)) {
this->InsertRecursive(element, this->root, 0);
this->IncrementUnbalanced();
}
CheckInvariant();
}
}
/**
* Remove a single element from the tree, if it exists.
* Since elements are stored in interior nodes as well as leaf nodes, removing one may
* require a larger sub-tree to be re-built. Because of this, worst case run time is
* as bad as a full tree rebuild.
*/
void Remove(const T &element)
{
size_t count = this->Count();
if (count == 0) return;
if (!this->IsUnbalanced() || !this->Rebuild(nullptr, &element)) {
/* If the removed element is the root node, this modifies this->root */
this->root = this->RemoveRecursive(element, this->root, 0);
this->IncrementUnbalanced();
}
CheckInvariant();
}
/** Get number of elements stored in tree */
size_t Count() const
{
assert(this->free_list.size() <= this->nodes.size());
return this->nodes.size() - this->free_list.size();
}
/**
* Find the element closest to given coordinate, in Manhattan distance.
* For multiple elements with the same distance, the one comparing smaller with
* a less-than comparison is chosen.
*/
T FindNearest(CoordT x, CoordT y) const
{
assert(this->Count() > 0);
CoordT xy[2] = { x, y };
return this->FindNearestRecursive(xy, this->root, 0).first;
}
/**
* Find all items contained within the given rectangle.
* @note Start coordinates are inclusive, end coordinates are exclusive. x1<x2 && y1<y2 is a precondition.
* @param x1 Start first coordinate, points found are greater or equals to this.
* @param y1 Start second coordinate, points found are greater or equals to this.
* @param x2 End first coordinate, points found are less than this.
* @param y2 End second coordinate, points found are less than this.
* @param outputter Callback used to return values from the search.
*/
template <typename Outputter>
void FindContained(CoordT x1, CoordT y1, CoordT x2, CoordT y2, Outputter outputter) const
{
assert(x1 < x2);
assert(y1 < y2);
if (this->Count() == 0) return;
CoordT p1[2] = { x1, y1 };
CoordT p2[2] = { x2, y2 };
this->FindContainedRecursive(p1, p2, this->root, 0, outputter);
}
/**
* Find all items contained within the given rectangle.
* @note End coordinates are exclusive, x1<x2 && y1<y2 is a precondition.
*/
std::vector<T> FindContained(CoordT x1, CoordT y1, CoordT x2, CoordT y2) const
{
std::vector<T> result;
this->FindContained(x1, y1, x2, y2, [&result](T e) {result.push_back(e); });
return result;
}
};
#endif
|