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			357 lines
		
	
	
	
		
			12 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			357 lines
		
	
	
	
		
			12 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
| /**************************************************************************/
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| /*  fuzzy_search.cpp                                                      */
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| /**************************************************************************/
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| /*                         This file is part of:                          */
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| /*                             GODOT ENGINE                               */
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| /*                        https://godotengine.org                         */
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| /**************************************************************************/
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| /* Copyright (c) 2014-present Godot Engine contributors (see AUTHORS.md). */
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| /* Copyright (c) 2007-2014 Juan Linietsky, Ariel Manzur.                  */
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| /*                                                                        */
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| /* Permission is hereby granted, free of charge, to any person obtaining  */
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| /* a copy of this software and associated documentation files (the        */
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| /* "Software"), to deal in the Software without restriction, including    */
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| /* without limitation the rights to use, copy, modify, merge, publish,    */
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| /* distribute, sublicense, and/or sell copies of the Software, and to     */
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| /* permit persons to whom the Software is furnished to do so, subject to  */
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| /* the following conditions:                                              */
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| /*                                                                        */
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| /* The above copyright notice and this permission notice shall be         */
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| /* included in all copies or substantial portions of the Software.        */
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| /*                                                                        */
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| /* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,        */
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| /* EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF     */
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| /* MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. */
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| /* IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY   */
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| /* CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,   */
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| /* TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE      */
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| /* SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.                 */
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| /**************************************************************************/
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| 
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| #include "fuzzy_search.h"
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| 
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| constexpr float cull_factor = 0.1f;
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| constexpr float cull_cutoff = 30.0f;
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| const String boundary_chars = "/\\-_.";
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| 
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| static bool _is_valid_interval(const Vector2i &p_interval) {
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| 	// Empty intervals are represented as (-1, -1).
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| 	return p_interval.x >= 0 && p_interval.y >= p_interval.x;
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| }
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| 
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| static Vector2i _extend_interval(const Vector2i &p_a, const Vector2i &p_b) {
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| 	if (!_is_valid_interval(p_a)) {
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| 		return p_b;
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| 	}
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| 	if (!_is_valid_interval(p_b)) {
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| 		return p_a;
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| 	}
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| 	return Vector2i(MIN(p_a.x, p_b.x), MAX(p_a.y, p_b.y));
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| }
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| 
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| static bool _is_word_boundary(const String &p_str, int p_index) {
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| 	if (p_index == -1 || p_index == p_str.size()) {
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| 		return true;
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| 	}
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| 	return boundary_chars.find_char(p_str[p_index]) != -1;
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| }
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| 
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| bool FuzzySearchToken::try_exact_match(FuzzyTokenMatch &p_match, const String &p_target, int p_offset) const {
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| 	p_match.token_idx = idx;
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| 	p_match.token_length = string.length();
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| 	int match_idx = p_target.find(string, p_offset);
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| 	if (match_idx == -1) {
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| 		return false;
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| 	}
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| 	p_match.add_substring(match_idx, string.length());
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| 	return true;
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| }
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| 
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| bool FuzzySearchToken::try_fuzzy_match(FuzzyTokenMatch &p_match, const String &p_target, int p_offset, int p_miss_budget) const {
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| 	p_match.token_idx = idx;
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| 	p_match.token_length = string.length();
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| 	int run_start = -1;
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| 	int run_len = 0;
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| 
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| 	// Search for the subsequence p_token in p_target starting from p_offset, recording each substring for
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| 	// later scoring and display.
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| 	for (int i = 0; i < string.length(); i++) {
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| 		int new_offset = p_target.find_char(string[i], p_offset);
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| 		if (new_offset < 0) {
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| 			p_miss_budget--;
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| 			if (p_miss_budget < 0) {
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| 				return false;
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| 			}
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| 		} else {
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| 			if (run_start == -1 || p_offset != new_offset) {
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| 				if (run_start != -1) {
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| 					p_match.add_substring(run_start, run_len);
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| 				}
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| 				run_start = new_offset;
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| 				run_len = 1;
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| 			} else {
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| 				run_len += 1;
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| 			}
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| 			p_offset = new_offset + 1;
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| 		}
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| 	}
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| 
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| 	if (run_start != -1) {
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| 		p_match.add_substring(run_start, run_len);
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| 	}
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| 
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| 	return true;
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| }
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| 
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| void FuzzyTokenMatch::add_substring(int p_substring_start, int p_substring_length) {
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| 	substrings.append(Vector2i(p_substring_start, p_substring_length));
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| 	matched_length += p_substring_length;
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| 	Vector2i substring_interval = { p_substring_start, p_substring_start + p_substring_length - 1 };
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| 	interval = _extend_interval(interval, substring_interval);
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| }
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| 
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| bool FuzzyTokenMatch::intersects(const Vector2i &p_other_interval) const {
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| 	if (!_is_valid_interval(interval) || !_is_valid_interval(p_other_interval)) {
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| 		return false;
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| 	}
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| 	return interval.y >= p_other_interval.x && interval.x <= p_other_interval.y;
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| }
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| 
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| bool FuzzySearchResult::can_add_token_match(const FuzzyTokenMatch &p_match) const {
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| 	if (p_match.get_miss_count() > miss_budget) {
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| 		return false;
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| 	}
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| 
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| 	if (p_match.intersects(match_interval)) {
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| 		if (token_matches.size() == 1) {
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| 			return false;
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| 		}
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| 		for (const FuzzyTokenMatch &existing_match : token_matches) {
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| 			if (existing_match.intersects(p_match.interval)) {
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| 				return false;
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| 			}
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| 		}
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| 	}
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| 
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| 	return true;
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| }
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| 
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| bool FuzzyTokenMatch::is_case_insensitive(const String &p_original, const String &p_adjusted) const {
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| 	for (const Vector2i &substr : substrings) {
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| 		const int end = substr.x + substr.y;
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| 		for (int i = substr.x; i < end; i++) {
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| 			if (p_original[i] != p_adjusted[i]) {
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| 				return true;
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| 			}
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| 		}
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| 	}
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| 	return false;
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| }
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| 
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| void FuzzySearchResult::score_token_match(FuzzyTokenMatch &p_match, bool p_case_insensitive) const {
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| 	// This can always be tweaked more. The intuition is that exact matches should almost always
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| 	// be prioritized over broken up matches, and other criteria more or less act as tie breakers.
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| 
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| 	p_match.score = -20 * p_match.get_miss_count() - (p_case_insensitive ? 3 : 0);
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| 
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| 	for (const Vector2i &substring : p_match.substrings) {
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| 		// Score longer substrings higher than short substrings.
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| 		int substring_score = substring.y * substring.y;
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| 		// Score matches deeper in path higher than shallower matches
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| 		if (substring.x > dir_index) {
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| 			substring_score *= 2;
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| 		}
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| 		// Score matches on a word boundary higher than matches within a word
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| 		if (_is_word_boundary(target, substring.x - 1) || _is_word_boundary(target, substring.x + substring.y)) {
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| 			substring_score += 4;
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| 		}
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| 		// Score exact query matches higher than non-compact subsequence matches
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| 		if (substring.y == p_match.token_length) {
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| 			substring_score += 100;
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| 		}
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| 		p_match.score += substring_score;
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| 	}
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| }
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| 
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| void FuzzySearchResult::maybe_apply_score_bonus() {
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| 	// This adds a small bonus to results which match tokens in the same order they appear in the query.
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| 	int *token_range_starts = (int *)alloca(sizeof(int) * token_matches.size());
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| 
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| 	for (const FuzzyTokenMatch &match : token_matches) {
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| 		token_range_starts[match.token_idx] = match.interval.x;
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| 	}
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| 
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| 	int last = token_range_starts[0];
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| 	for (int i = 1; i < token_matches.size(); i++) {
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| 		if (last > token_range_starts[i]) {
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| 			return;
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| 		}
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| 		last = token_range_starts[i];
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| 	}
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| 
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| 	score += 1;
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| }
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| 
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| void FuzzySearchResult::add_token_match(const FuzzyTokenMatch &p_match) {
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| 	score += p_match.score;
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| 	match_interval = _extend_interval(match_interval, p_match.interval);
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| 	miss_budget -= p_match.get_miss_count();
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| 	token_matches.append(p_match);
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| }
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| 
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| void remove_low_scores(Vector<FuzzySearchResult> &p_results, float p_cull_score) {
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| 	// Removes all results with score < p_cull_score in-place.
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| 	int i = 0;
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| 	int j = p_results.size() - 1;
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| 	FuzzySearchResult *results = p_results.ptrw();
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| 
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| 	while (true) {
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| 		// Advances i to an element to remove and j to an element to keep.
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| 		while (j >= i && results[j].score < p_cull_score) {
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| 			j--;
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| 		}
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| 		while (i < j && results[i].score >= p_cull_score) {
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| 			i++;
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| 		}
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| 		if (i >= j) {
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| 			break;
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| 		}
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| 		results[i++] = results[j--];
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| 	}
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| 
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| 	p_results.resize(j + 1);
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| }
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| 
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| void FuzzySearch::sort_and_filter(Vector<FuzzySearchResult> &p_results) const {
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| 	if (p_results.is_empty()) {
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| 		return;
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| 	}
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| 
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| 	float avg_score = 0;
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| 	float max_score = 0;
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| 
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| 	for (const FuzzySearchResult &result : p_results) {
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| 		avg_score += result.score;
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| 		max_score = MAX(max_score, result.score);
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| 	}
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| 
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| 	// TODO: Tune scoring and culling here to display fewer subsequence soup matches when good matches
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| 	//  are available.
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| 	avg_score /= p_results.size();
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| 	float cull_score = MIN(cull_cutoff, Math::lerp(avg_score, max_score, cull_factor));
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| 	remove_low_scores(p_results, cull_score);
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| 
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| 	struct FuzzySearchResultComparator {
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| 		bool operator()(const FuzzySearchResult &p_lhs, const FuzzySearchResult &p_rhs) const {
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| 			// Sort on (score, length, alphanumeric) to ensure consistent ordering.
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| 			if (p_lhs.score == p_rhs.score) {
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| 				if (p_lhs.target.length() == p_rhs.target.length()) {
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| 					return p_lhs.target < p_rhs.target;
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| 				}
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| 				return p_lhs.target.length() < p_rhs.target.length();
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| 			}
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| 			return p_lhs.score > p_rhs.score;
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| 		}
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| 	};
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| 
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| 	SortArray<FuzzySearchResult, FuzzySearchResultComparator> sorter;
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| 
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| 	if (p_results.size() > max_results) {
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| 		sorter.partial_sort(0, p_results.size(), max_results, p_results.ptrw());
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| 		p_results.resize(max_results);
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| 	} else {
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| 		sorter.sort(p_results.ptrw(), p_results.size());
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| 	}
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| }
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| 
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| void FuzzySearch::set_query(const String &p_query) {
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| 	set_query(p_query, !p_query.is_lowercase());
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| }
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| 
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| void FuzzySearch::set_query(const String &p_query, bool p_case_sensitive) {
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| 	tokens.clear();
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| 	case_sensitive = p_case_sensitive;
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| 
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| 	for (const String &string : p_query.split(" ", false)) {
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| 		tokens.append({
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| 				static_cast<int>(tokens.size()),
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| 				p_case_sensitive ? string : string.to_lower(),
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| 		});
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| 	}
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| 
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| 	struct TokenComparator {
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| 		bool operator()(const FuzzySearchToken &A, const FuzzySearchToken &B) const {
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| 			if (A.string.length() == B.string.length()) {
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| 				return A.idx < B.idx;
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| 			}
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| 			return A.string.length() > B.string.length();
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| 		}
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| 	};
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| 
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| 	// Prioritize matching longer tokens before shorter ones since match overlaps are not accepted.
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| 	tokens.sort_custom<TokenComparator>();
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| }
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| 
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| bool FuzzySearch::search(const String &p_target, FuzzySearchResult &p_result) const {
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| 	p_result.target = p_target;
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| 	p_result.dir_index = p_target.rfind_char('/');
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| 	p_result.miss_budget = max_misses;
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| 
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| 	String adjusted_target = case_sensitive ? p_target : p_target.to_lower();
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| 
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| 	// For each token, eagerly generate subsequences starting from index 0 and keep the best scoring one
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| 	// which does not conflict with prior token matches. This is not ensured to find the highest scoring
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| 	// combination of matches, or necessarily the highest scoring single subsequence, as it only considers
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| 	// eager subsequences for a given index, and likewise eagerly finds matches for each token in sequence.
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| 	for (const FuzzySearchToken &token : tokens) {
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| 		FuzzyTokenMatch best_match;
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| 		int offset = start_offset;
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| 
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| 		while (true) {
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| 			FuzzyTokenMatch match;
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| 			if (allow_subsequences) {
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| 				if (!token.try_fuzzy_match(match, adjusted_target, offset, p_result.miss_budget)) {
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| 					break;
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| 				}
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| 			} else {
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| 				if (!token.try_exact_match(match, adjusted_target, offset)) {
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| 					break;
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| 				}
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| 			}
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| 			if (p_result.can_add_token_match(match)) {
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| 				p_result.score_token_match(match, match.is_case_insensitive(p_target, adjusted_target));
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| 				if (best_match.token_idx == -1 || best_match.score < match.score) {
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| 					best_match = match;
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| 				}
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| 			}
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| 			if (_is_valid_interval(match.interval)) {
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| 				offset = match.interval.x + 1;
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| 			} else {
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| 				break;
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| 			}
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| 		}
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| 
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| 		if (best_match.token_idx == -1) {
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| 			return false;
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| 		}
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| 
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| 		p_result.add_token_match(best_match);
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| 	}
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| 
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| 	p_result.maybe_apply_score_bonus();
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| 	return true;
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| }
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| 
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| void FuzzySearch::search_all(const PackedStringArray &p_targets, Vector<FuzzySearchResult> &p_results) const {
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| 	p_results.clear();
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| 
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| 	for (int i = 0; i < p_targets.size(); i++) {
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| 		FuzzySearchResult result;
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| 		result.original_index = i;
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| 		if (search(p_targets[i], result)) {
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| 			p_results.append(result);
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| 		}
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| 	}
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| 
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| 	sort_and_filter(p_results);
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| }
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