Lu Fan(SonnyCalcr)
23bfdd4d51
- 符号混输不再挡读得成拼音的编码：混输本来就只认整串精确匹配，xi → ξ 也照样混入；单字母编码仍不混。 - 构建器读取 msime-dictionary 新增的 custom/symbols.txt（拼音<TAB>符号），把 dian → · 、、 shuminghao → 《》 〈〉 等标点读音写进 symbol_code，书名号、引号、括号成对给出。 - emoji 混输改用新的 query_mixed_emoji，只认整串精确等于关键词，不再按前缀带出 emoji；双拼下只查 展开后的全拼，并和符号一样只在光标位于末尾时查询。Shift+E 的 emoji 模式仍按前缀查。 - 同步更新设置页说明、出厂与开发配置注释和 README。
210 lines
8.8 KiB
C++
210 lines
8.8 KiB
C++
#include "candidate_queries.h"
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#include "data_path.h"
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#include "../contracts/assets/assets.h"
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#include "../local_modes/emoji_query.h"
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#include "../local_modes/jianpin_query.h"
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#include "../local_modes/kaomoji_query.h"
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#include "../local_modes/quick_phrase_query.h"
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#include "../local_modes/radical_query.h"
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#include <algorithm>
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#include <cctype>
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#include <iterator>
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#include <unordered_set>
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namespace metasequoia
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{
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local_modes::LocalQueryResult CandidateQueries::local(LocalInputMode mode, const std::string &preedit,
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SchemeType scheme,
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const std::function<local_modes::LocalDateTime()> &clock,
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const std::vector<WordItem> &engine_candidates)
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{
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local_modes::LocalQueryResult result;
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switch (mode)
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{
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case LocalInputMode::Radical:
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// 拆字表是会话级资源：按会话的 RuntimePaths 解析，和 other_dictionary、translations 一致。
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result.candidates =
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local_modes::query_radical(paths_.resource(assets::radical_decomposition), preedit.substr(1));
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return result;
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case LocalInputMode::DateTime: {
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const local_modes::LocalDateTime now = clock ? clock() : local_modes::current_local_date_time();
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result.candidates = local_modes::query_date_time(preedit.substr(1), &now);
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return result;
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}
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case LocalInputMode::QuickPhrase: {
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local_modes::QuickPhraseQueryResult query =
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local_modes::query_quick_phrases(preedit.substr(1), paths_.dictionary(assets::main_dictionary));
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result.candidates = std::move(query.candidates);
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result.diagnostic = std::move(query.diagnostic);
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return result;
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}
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case LocalInputMode::Emoji: {
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local_modes::LocalQueryResult query = local_modes::query_emoji(
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preedit.substr(1), scheme, paths_.resource(assets::other_dictionary), 10, shuangpin_profile_);
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result.candidates = std::move(query.candidates);
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result.diagnostic = std::move(query.diagnostic);
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return result;
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}
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case LocalInputMode::Kaomoji: {
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local_modes::LocalQueryResult query = local_modes::query_kaomoji(
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preedit.substr(1), scheme, paths_.resource(assets::other_dictionary), 10, shuangpin_profile_);
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result.candidates = std::move(query.candidates);
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result.diagnostic = std::move(query.diagnostic);
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return result;
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}
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case LocalInputMode::SuperJianpin: {
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const std::string code = preedit.substr(1);
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const int limit = code.size() == 1 ? 24 : 100;
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local_modes::LocalQueryResult query = local_modes::query_jianpin(
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code, scheme, paths_.dictionary(assets::main_dictionary), limit, shuangpin_profile_);
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result.candidates = std::move(query.candidates);
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result.diagnostic = std::move(query.diagnostic);
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return result;
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}
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case LocalInputMode::TemporaryEnglish: {
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const std::string raw = preedit.substr(1);
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result.candidates.clear();
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if (raw.empty())
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{
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return result;
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}
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result.candidates.emplace_back("", raw, 0, CandidateSource::Generated);
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std::string prefix = raw;
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std::transform(prefix.begin(), prefix.end(), prefix.begin(),
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[](unsigned char character) { return static_cast<char>(std::tolower(character)); });
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auto completions = english_dictionary().query_prefix(prefix, 1000);
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completions.erase(std::remove_if(completions.begin(), completions.end(),
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[&](const WordItem &candidate) {
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if (candidate.word.size() != raw.size())
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{
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return false;
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}
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return std::equal(candidate.word.begin(), candidate.word.end(),
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raw.begin(),
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[](unsigned char left, unsigned char right) {
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return std::tolower(left) == std::tolower(right);
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});
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}),
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completions.end());
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result.candidates.insert(result.candidates.end(), std::make_move_iterator(completions.begin()),
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std::make_move_iterator(completions.end()));
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return result;
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}
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case LocalInputMode::TemporaryJapanese:
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result.candidates = engine_candidates;
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return result;
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case LocalInputMode::None:
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result.candidates.clear();
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return result;
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}
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return result;
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}
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std::vector<WordItem> CandidateQueries::mixed(std::vector<WordItem> candidates, const std::string &prefix,
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SchemeType scheme, EnglishInputOptions english_options,
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MixedExpressiveOptions expressive_options, bool dedicated_english,
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LocalInputMode local_mode)
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{
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if ((!english_options.mixed_candidates && !expressive_options.emoji_candidates &&
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!expressive_options.kaomoji_candidates) ||
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dedicated_english || local_mode != LocalInputMode::None ||
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(scheme != SchemeType::Quanpin && scheme != SchemeType::Shuangpin))
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{
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return candidates;
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}
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if (prefix.empty())
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{
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return candidates;
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}
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std::unordered_set<std::string> seen;
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for (const auto &candidate : candidates)
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{
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seen.insert(candidate.word);
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}
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const auto collect_unique = [&](std::vector<WordItem> candidates) {
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std::vector<WordItem> unique;
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unique.reserve(candidates.size());
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for (auto &candidate : candidates)
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{
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if (seen.insert(candidate.word).second)
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{
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unique.push_back(std::move(candidate));
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}
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}
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return unique;
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};
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std::vector<WordItem> english_candidates;
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const bool lower_ascii_prefix = std::all_of(
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prefix.begin(), prefix.end(), [](unsigned char character) { return character >= 'a' && character <= 'z'; });
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if (english_options.mixed_candidates && prefix.size() >= english_options.minimum_prefix && lower_ascii_prefix)
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{
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english_candidates = collect_unique(english_dictionary().query_mixed_prefix(prefix));
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}
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std::vector<WordItem> emoji_candidates;
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if (expressive_options.emoji_candidates && prefix.size() >= 2)
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{
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emoji_candidates =
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collect_unique(local_modes::query_mixed_emoji(prefix, scheme, paths_.resource(assets::other_dictionary), 3,
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shuangpin_profile_)
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.candidates);
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}
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std::vector<WordItem> kaomoji_candidates;
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if (expressive_options.kaomoji_candidates && prefix.size() >= 2)
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{
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kaomoji_candidates = collect_unique(
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local_modes::query_kaomoji(prefix, scheme, paths_.resource(assets::other_dictionary), 3, shuangpin_profile_)
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.candidates);
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}
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std::size_t priority_slot = std::min<std::size_t>(1, candidates.size());
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const auto has_source = [&](CandidateSource source) {
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return std::any_of(candidates.begin(), candidates.end(),
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[source](const WordItem &candidate) { return candidate.source == source; });
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};
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if (has_source(CandidateSource::CloudSuggestion))
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{
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priority_slot = std::min<std::size_t>(2, candidates.size());
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}
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if (has_source(CandidateSource::AiSuggestion))
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{
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priority_slot = std::min<std::size_t>(3, candidates.size());
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}
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const auto insert_leading = [&](std::vector<WordItem> &source) {
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if (source.empty())
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{
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return;
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}
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candidates.insert(candidates.begin() + static_cast<std::ptrdiff_t>(priority_slot), std::move(source.front()));
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source.erase(source.begin());
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++priority_slot;
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};
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insert_leading(english_candidates);
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for (auto *source : {&english_candidates, &emoji_candidates, &kaomoji_candidates})
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{
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candidates.insert(candidates.end(), std::make_move_iterator(source->begin()),
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std::make_move_iterator(source->end()));
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}
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return candidates;
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}
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EnglishDictionary &CandidateQueries::english_dictionary()
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{
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if (!english_dictionary_)
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{
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english_dictionary_ =
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std::make_unique<EnglishDictionary>(path_to_utf8(paths_.dictionary(assets::english_dictionary)), false,
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path_to_utf8(paths_.resource(assets::translations)));
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}
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return *english_dictionary_;
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}
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} // namespace metasequoia
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