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/*
* Copyright (C) 2014 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.
*/
package org.kelar.inputmethod.latin.utils;
import android.util.Log;
import org.kelar.inputmethod.annotations.UsedForTesting;
import org.kelar.inputmethod.latin.NgramContext;
import org.kelar.inputmethod.latin.common.StringUtils;
import org.kelar.inputmethod.latin.define.DecoderSpecificConstants;
import org.kelar.inputmethod.latin.settings.SpacingAndPunctuations;
import java.util.ArrayList;
import java.util.List;
import java.util.Locale;
// Note: this class is used as a parameter type of a native method. You should be careful when you
// rename this class or field name. See BinaryDictionary#addMultipleDictionaryEntriesNative().
public final class WordInputEventForPersonalization {
private static final String TAG = WordInputEventForPersonalization.class.getSimpleName();
private static final boolean DEBUG_TOKEN = false;
public final int[] mTargetWord;
public final int mPrevWordsCount;
public final int[][] mPrevWordArray =
new int[DecoderSpecificConstants.MAX_PREV_WORD_COUNT_FOR_N_GRAM][];
public final boolean[] mIsPrevWordBeginningOfSentenceArray =
new boolean[DecoderSpecificConstants.MAX_PREV_WORD_COUNT_FOR_N_GRAM];
// Time stamp in seconds.
public final int mTimestamp;
@UsedForTesting
public WordInputEventForPersonalization(final CharSequence targetWord,
final NgramContext ngramContext, final int timestamp) {
mTargetWord = StringUtils.toCodePointArray(targetWord);
mPrevWordsCount = ngramContext.getPrevWordCount();
ngramContext.outputToArray(mPrevWordArray, mIsPrevWordBeginningOfSentenceArray);
mTimestamp = timestamp;
}
// Process a list of words and return a list of {@link WordInputEventForPersonalization}
// objects.
public static ArrayList<WordInputEventForPersonalization> createInputEventFrom(
final List<String> tokens, final int timestamp,
final SpacingAndPunctuations spacingAndPunctuations, final Locale locale) {
final ArrayList<WordInputEventForPersonalization> inputEvents = new ArrayList<>();
final int N = tokens.size();
NgramContext ngramContext = NgramContext.EMPTY_PREV_WORDS_INFO;
for (int i = 0; i < N; ++i) {
final String tempWord = tokens.get(i);
if (StringUtils.isEmptyStringOrWhiteSpaces(tempWord)) {
// just skip this token
if (DEBUG_TOKEN) {
Log.d(TAG, "--- isEmptyStringOrWhiteSpaces: \"" + tempWord + "\"");
}
continue;
}
if (!DictionaryInfoUtils.looksValidForDictionaryInsertion(
tempWord, spacingAndPunctuations)) {
if (DEBUG_TOKEN) {
Log.d(TAG, "--- not looksValidForDictionaryInsertion: \""
+ tempWord + "\"");
}
// Sentence terminator found. Split.
// TODO: Detect whether the context is beginning-of-sentence.
ngramContext = NgramContext.EMPTY_PREV_WORDS_INFO;
continue;
}
if (DEBUG_TOKEN) {
Log.d(TAG, "--- word: \"" + tempWord + "\"");
}
final WordInputEventForPersonalization inputEvent =
detectWhetherVaildWordOrNotAndGetInputEvent(
ngramContext, tempWord, timestamp, locale);
if (inputEvent == null) {
continue;
}
inputEvents.add(inputEvent);
ngramContext = ngramContext.getNextNgramContext(new NgramContext.WordInfo(tempWord));
}
return inputEvents;
}
private static WordInputEventForPersonalization detectWhetherVaildWordOrNotAndGetInputEvent(
final NgramContext ngramContext, final String targetWord, final int timestamp,
final Locale locale) {
if (locale == null) {
return null;
}
return new WordInputEventForPersonalization(targetWord, ngramContext, timestamp);
}
}
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