summaryrefslogtreecommitdiffstats
path: root/utils/training/prune_k_mixture_model.cpp
diff options
context:
space:
mode:
authorPeng Wu <alexepico@gmail.com>2011-05-04 13:45:16 +0800
committerPeng Wu <alexepico@gmail.com>2011-05-04 13:45:16 +0800
commitd91e11a3e0e3215db7b87eb902dc7e7f9974823f (patch)
tree943912c7efd1116bf7ef134cb6d107cdb7c8985f /utils/training/prune_k_mixture_model.cpp
parentdb9ed7743d01b898b1cdc086339da1dd79047a18 (diff)
downloadlibpinyin-d91e11a3e0e3215db7b87eb902dc7e7f9974823f.tar.gz
libpinyin-d91e11a3e0e3215db7b87eb902dc7e7f9974823f.tar.xz
libpinyin-d91e11a3e0e3215db7b87eb902dc7e7f9974823f.zip
wrote prune k mixture model
Diffstat (limited to 'utils/training/prune_k_mixture_model.cpp')
-rw-r--r--utils/training/prune_k_mixture_model.cpp105
1 files changed, 105 insertions, 0 deletions
diff --git a/utils/training/prune_k_mixture_model.cpp b/utils/training/prune_k_mixture_model.cpp
index f6f0bcc..7a724a9 100644
--- a/utils/training/prune_k_mixture_model.cpp
+++ b/utils/training/prune_k_mixture_model.cpp
@@ -1,9 +1,114 @@
+/*
+ * 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 2 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, write to the Free Software
+ * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
+ */
+
+
+
+#include <errno.h>
+#include <locale.h>
#include "pinyin.h"
#include "k_mixture_model.h"
static guint32 g_prune_k = 3;
static parameter_t g_prune_poss = 0.99;
+void print_help(){
+ printf("prune_k_mixture_model <FILENAME>\n");
+}
+
+bool prune_k_mixture_model(KMixtureModelMagicHeader * magic_header,
+ KMixtureModelSingleGram * & bigram){
+ bool success;
+
+ FlexibleBigramPhraseArray array = g_array_new(FALSE, FALSE, sizeof(KMixtureModelArrayItemWithToken));
+ bigram->retrieve_all(array);
+ for ( size_t i = 0; i < array->len; ++i) {
+ KMixtureModelArrayItemWithToken * item = &g_array_index(array, KMixtureModelArrayItemWithToken, i);
+ phrase_token_t token = item->m_token;
+ parameter_t remained_poss = 1;
+ for ( size_t k = 0; k < g_prune_k; ++k){
+ remained_poss -= compute_Pr_G_3_with_count
+ (k, magic_header->m_N, item->m_item.m_WC,
+ magic_header->m_N - item->m_item.m_N_n_0,
+ item->m_item.m_n_1);
+ }
+
+ assert(remained_poss >= 0);
+ if ( remained_poss < g_prune_poss ) {
+ /* prune this word or phrase. */
+ KMixtureModelArrayItem removed_item;
+ bigram->remove_array_item(token, removed_item);
+ assert( memcmp(&removed_item, &(item->m_item),
+ sizeof(KMixtureModelArrayItem)) == 0 );
+ KMixtureModelArrayHeader header;
+ bigram->get_array_header(header);
+ guint32 removed_count = removed_item.m_WC;
+ header.m_WC -= removed_count;
+ bigram->set_array_header(header);
+ magic_header->m_WC -= removed_count;
+ }
+ }
+
+ KMixtureModelArrayHeader header;
+ bigram->get_array_header(header);
+
+ if ( 0 == header.m_WC ){
+ delete bigram;
+ bigram = NULL;
+ }
+
+ return true;
+}
+
int main(int argc, char * argv[]){
+ const char * bigram_filename = NULL;
+
+ setlocale(LC_ALL, "");
+ if ( 2 != argc ){
+ print_help();
+ exit(EINVAL);
+ } else {
+ bigram_filename = argv[1];
+ }
+
+ /* TODO: magic header signature check here. */
+ KMixtureModelBigram bigram(K_MIXTURE_MODEL_MAGIC_NUMBER);
+ bigram.attach(bigram_filename);
+
+ KMixtureModelMagicHeader magic_header;
+ bigram.get_magic_header(magic_header);
+ GArray * items = g_array_new(FALSE, FALSE, sizeof(phrase_token_t));
+ bigram.get_all_items(items);
+
+ for ( size_t i; i < items->len; ++i ){
+ phrase_token_t * token = &g_array_index(items, phrase_token_t, i);
+ KMixtureModelSingleGram * single_gram = NULL;
+ bigram.load(*token, single_gram);
+
+ prune_k_mixture_model(&magic_header, single_gram);
+
+ if ( NULL == single_gram )
+ bigram.remove(*token);
+ else bigram.store(*token, single_gram);
+ }
+
+ bigram.set_magic_header(magic_header);
return 0;
}