/* 
 *  libpinyin
 *  Library to deal with pinyin.
 *  
 *  Copyright (C) 2011 Peng Wu <alexepico@gmail.com>
 *  
 *  This program 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, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This program 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 this program.  If not, see <http://www.gnu.org/licenses/>.
 */


#ifndef K_MIXTURE_MODEL
#define K_MIXTURE_MODEL

#include <math.h>
#include "novel_types.h"
#include "flexible_ngram.h"

namespace pinyin{

typedef guint32 corpus_count_t;

/* Note: storage parameters: N, T, n_r.
 * N: the total number of documents.
 * T: the total number of instances of the word or phrase.
 * n_r: the number of documents having exactly <b>r</b> occurrences.
 *      only n_0, n_1 are used here.
 */

static inline parameter_t compute_alpha(corpus_count_t N, corpus_count_t n_0){
    parameter_t alpha = 1 - n_0 / (parameter_t) N;
    return alpha;
}

static inline parameter_t compute_gamma(corpus_count_t N,
                                        corpus_count_t n_0,
                                        corpus_count_t n_1){
    parameter_t gamma = 1 - n_1 / (parameter_t) (N - n_0);
    return gamma;
}

static inline parameter_t compute_B(corpus_count_t N,
                                    corpus_count_t T,
                                    corpus_count_t n_0,
                                    corpus_count_t n_1){
    /* Note: re-check this, to see if we can remove if statement. */
    /* Please consider B_2 is no less than 2 in paper. */
#if 1
    if ( 0 == T - n_1 && 0 == N - n_0 - n_1 )
        return 2;
#endif

    parameter_t B = (T - n_1 ) / (parameter_t) (N - n_0 - n_1);
    return B;
}

/* three parameters model */
static inline parameter_t compute_Pr_G_3(corpus_count_t k,
                                         parameter_t alpha,
                                         parameter_t gamma,
                                         parameter_t B){
    if ( k == 0 )
        return 1 - alpha;

    if ( k == 1 )
        return alpha * (1 - gamma);

    if ( k > 1 ) {
        return (alpha * gamma / (B - 1)) * pow((1 - 1 / (B - 1)) , k - 2);
    }

    abort();
}

static inline parameter_t compute_Pr_G_3_with_count(corpus_count_t k,
                                                    corpus_count_t N,
                                                    corpus_count_t T,
                                                    corpus_count_t n_0,
                                                    corpus_count_t n_1){
    parameter_t alpha = compute_alpha(N, n_0);
    parameter_t gamma = compute_gamma(N, n_0, n_1);
    parameter_t B = compute_B(N, T, n_0, n_1);

    return compute_Pr_G_3(k, alpha, gamma, B);
}

/* two parameters model */
static inline parameter_t compute_Pr_G_2(corpus_count_t k,
                                         parameter_t alpha,
                                         parameter_t B){
    parameter_t gamma = 1 - 1 / (B - 1);
    return compute_Pr_G_3(k, alpha, gamma, B);
}

static inline parameter_t compute_Pr_G_2_with_count(corpus_count_t k,
                                                    corpus_count_t N,
                                                    corpus_count_t T,
                                                    corpus_count_t n_0,
                                                    corpus_count_t n_1){
    parameter_t alpha = compute_alpha(N, n_0);
    parameter_t B = compute_B(N, T, n_0, n_1);
    return compute_Pr_G_2(k, alpha, B);
}

#define K_MIXTURE_MODEL_MAGIC_NUMBER "KMMP"

typedef struct{
    /* the total number of instances of all words. */
    guint32 m_WC;
    /* the total number of documents. */
    guint32 m_N;
    /* the total freq of uni-gram. */
    guint32 m_total_freq;
} KMixtureModelMagicHeader;

typedef struct{
    /* the total number of instances of word W1. */
    guint32 m_WC;
    /* the freq of uni-gram. see m_total_freq in magic header also. */
    guint32 m_freq;
} KMixtureModelArrayHeader;

typedef struct{
    /* the total number of all W1,W2 word pair. */
    guint32 m_WC;

    /* the total number of instances of the word or phrase.
       (two word phrase) */
    /* guint32 m_T; Please use m_WC instead.
       alias of m_WC, always the same. */

    /* n_r: the number of documents having exactly r occurrences. */
    /* guint32 m_n_0;
       Note: compute this value using the following equation.
       m_n_0 = KMixtureModelMagicHeader.m_N - m_N_n_0;
       m_N_n_0, the number of documents which contains the word or phrase.
       (two word phrase) */
    guint32 m_N_n_0;
    guint32 m_n_1;

    /* maximum instances of the word or phrase (two word phrase)
       in previous documents last seen. */
    guint32 m_Mr;
} KMixtureModelArrayItem;

typedef FlexibleBigram<KMixtureModelMagicHeader,
                       KMixtureModelArrayHeader,
                       KMixtureModelArrayItem>
KMixtureModelBigram;

typedef FlexibleSingleGram<KMixtureModelArrayHeader,
                           KMixtureModelArrayItem>
KMixtureModelSingleGram;

typedef KMixtureModelSingleGram::ArrayItemWithToken
KMixtureModelArrayItemWithToken;

};


#endif
