a9bf212de0
For node search that means that shorter matching node names are moved further to the top, even if the entire search result is longer because it is in a deeper menu. This also more closely resembles how the search worked in Blender 3.6 where the menu path was not included in the search.
125 lines
3.9 KiB
C++
125 lines
3.9 KiB
C++
/* SPDX-FileCopyrightText: 2023 Blender Authors
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*
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* SPDX-License-Identifier: GPL-2.0-or-later */
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#pragma once
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#include "BLI_linear_allocator.hh"
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#include "BLI_map.hh"
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#include "BLI_span.hh"
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#include "BLI_string_ref.hh"
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#include "BLI_vector.hh"
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namespace blender::string_search {
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struct SearchItem {
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void *user_data;
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Span<StringRef> normalized_words;
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/**
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* When using menu-search, the search item is often split into multiple groups of words, each of
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* which corresponds to a menu entry. This id is the same for words in the same group and
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* different otherwise.
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*/
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Span<int> word_group_ids;
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/**
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* The id of the group that is highlighted in the UI. In some places, the words in this group are
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* given higher weight.
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*/
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int main_group_id;
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int main_group_length;
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int total_length;
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int weight;
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/**
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* This is a logical time stamp, i.e. the greater it is, the more recent the item was used. The
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* number is not based on an actual clock.
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*/
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int recent_time;
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};
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struct RecentCache {
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/**
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* Stores a logical time stamp for each previously chosen search item. The higher the time
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* stamp, the more recently the item has been selected.
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*/
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Map<std::string, int> logical_time_by_str;
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};
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/**
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* Non templated base class so that its methods can be implemented outside of this header.
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*/
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class StringSearchBase {
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protected:
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LinearAllocator<> allocator_;
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Vector<SearchItem> items_;
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const RecentCache *recent_cache_ = nullptr;
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protected:
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void add_impl(StringRef str, void *user_data, int weight);
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Vector<void *> query_impl(StringRef query) const;
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};
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/**
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* #StringSearch filters and sorts search items based on a string query. Every search item has data
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* of type T attached that is used to identify it.
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*
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* When querying, the a match score is computed between the query string and each item. Items that
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* don't match are filtered out, the rest is sorted by the score. Elements with the same score are
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* further sorted based on the optionally provided weight and other heuristics.
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*
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* The usage is simple. First #add all the search items and then use the #query method.
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*/
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template<typename T> class StringSearch : private StringSearchBase {
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public:
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StringSearch(const RecentCache *recent_cache = nullptr)
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{
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this->recent_cache_ = recent_cache;
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}
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/**
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* Add a new possible result to the search.
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*
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* \param weight: Can be used to customize the order when multiple items have the same match
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* score.
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*/
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void add(const StringRefNull str, T *user_data, const int weight = 0)
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{
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this->add_impl(str, (void *)user_data, weight);
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}
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/**
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* Filter and sort all previously added search items.
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* Returns an array containing the filtered user data.
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*/
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Vector<T *> query(const StringRef query) const
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{
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Vector<void *> result = this->query_impl(query);
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Vector<T *> result_typed = result.as_span().cast<T *>();
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return result_typed;
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}
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};
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/**
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* Computes the cost of transforming string a into b. The cost/distance is the minimal number of
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* operations that need to be executed. Valid operations are deletion, insertion, substitution and
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* transposition.
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*
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* This function is utf8 aware in the sense that it works at the level of individual code points
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* (1-4 bytes long) instead of on individual bytes.
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*/
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int damerau_levenshtein_distance(StringRef a, StringRef b);
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/**
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* Returns -1 when this is no reasonably good match.
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* Otherwise returns the number of errors in the match.
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*/
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int get_fuzzy_match_errors(StringRef query, StringRef full);
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/**
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* Splits a string into words and normalizes them (currently that just means converting to lower
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* case). The returned strings are allocated in the given allocator.
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*/
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void extract_normalized_words(StringRef str,
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LinearAllocator<> &allocator,
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Vector<StringRef, 64> &r_words,
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Vector<int, 64> &r_word_group_ids);
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} // namespace blender::string_search
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