QtInputMethod_GooglePinyin/googlepinyin/ngram.h

97 lines
2.8 KiB
C++

/*
* Copyright (C) 2009 The Android Open Source Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#ifndef PINYINIME_INCLUDE_NGRAM_H__
#define PINYINIME_INCLUDE_NGRAM_H__
#include <stdio.h>
#include <stdlib.h>
#include "./dictdef.h"
namespace ime_pinyin {
typedef unsigned char CODEBOOK_TYPE;
static const size_t kCodeBookSize = 256;
class NGram {
public:
// The maximum score of a lemma item.
static const LmaScoreType kMaxScore = 0x3fff;
// In order to reduce the storage size, the original log value is amplified by
// kScoreAmplifier, and we use LmaScoreType to store.
// After this process, an item with a lower score has a higher frequency.
static const int kLogValueAmplifier = -800;
// System words' total frequency. It is not the real total frequency, instead,
// It is only used to adjust system lemmas' scores when the user dictionary's
// total frequency changes.
// In this version, frequencies of system lemmas are fixed. We are considering
// to make them changable in next version.
static const size_t kSysDictTotalFreq = 100000000;
private:
static NGram* instance_;
bool initialized_;
uint32 idx_num_;
size_t total_freq_none_sys_;
// Score compensation for system dictionary lemmas.
// Because after user adds some user lemmas, the total frequency changes, and
// we use this value to normalize the score.
float sys_score_compensation_;
#ifdef ___BUILD_MODEL___
double *freq_codes_df_;
#endif
LmaScoreType *freq_codes_;
CODEBOOK_TYPE *lma_freq_idx_;
public:
NGram();
~NGram();
static NGram& get_instance();
bool save_ngram(FILE *fp);
bool load_ngram(FILE *fp);
// Set the total frequency of all none system dictionaries.
void set_total_freq_none_sys(size_t freq_none_sys);
float get_uni_psb(LemmaIdType lma_id);
// Convert a probability to score. Actually, the score will be limited to
// kMaxScore, but at runtime, we also need float expression to get accurate
// value of the score.
// After the conversion, a lower score indicates a higher probability of the
// item.
static float convert_psb_to_score(double psb);
#ifdef ___BUILD_MODEL___
// For constructing the unigram mode model.
bool build_unigram(LemmaEntry *lemma_arr, size_t num,
LemmaIdType next_idx_unused);
#endif
};
}
#endif // PINYINIME_INCLUDE_NGRAM_H__