Reduction, step 2 (8abd15b5) · Commits · e / os / android_packages_inputmethods_LatinIME

java/src/com/android/inputmethod/latin/Suggest.java

+9 −63

Original line number	Diff line number	Diff line
		@@ -273,9 +273,7 @@ public class Suggest implements Dictionary.WordCallback {
		Arrays.fill(mScores, 0);

		final String typedWord = "";
		final String consideredWord = mTrailingSingleQuotesCount > 0
		? typedWord.substring(0, typedWord.length() - mTrailingSingleQuotesCount)
		: typedWord;
		final String consideredWord = "";
		// Treating USER_TYPED as UNIGRAM suggestion for logging now.
		LatinImeLogger.onAddSuggestedWord(typedWord, Suggest.DIC_USER_TYPED,
		Dictionary.UNIGRAM);
		@@ -289,7 +287,7 @@ public class Suggest implements Dictionary.WordCallback {
		final boolean allowsToBeAutoCorrected = AutoCorrection.allowsToBeAutoCorrected(
		getUnigramDictionaries(), consideredWord, false);

		if (0 <= 1 && (correctionMode == CORRECTION_FULL_BIGRAM)) {
		if (correctionMode == CORRECTION_FULL_BIGRAM) {
		// At first character typed, search only the bigrams
		Arrays.fill(mBigramScores, 0);
		collectGarbage(mBigramSuggestions, PREF_MAX_BIGRAMS);
		@@ -302,7 +300,7 @@ public class Suggest implements Dictionary.WordCallback {
		for (final Dictionary dictionary : mBigramDictionaries.values()) {
		dictionary.getBigrams(wordComposer, prevWordForBigram, this);
		}
		if (TextUtils.isEmpty(consideredWord)) {
		if (true) {
		// Nothing entered: return all bigrams for the previous word
		int insertCount = Math.min(mBigramSuggestions.size(), mPrefMaxSuggestions);
		for (int i = 0; i < insertCount; ++i) {
		@@ -326,37 +324,14 @@ public class Suggest implements Dictionary.WordCallback {
		}
		}
		}

		} else if (0 > 1) {
		// At second character typed, search the unigrams (scores being affected by bigrams)
		for (final String key : mUnigramDictionaries.keySet()) {
		// Skip UserUnigramDictionary and WhitelistDictionary to lookup
		if (key.equals(DICT_KEY_USER_UNIGRAM) \|\| key.equals(DICT_KEY_WHITELIST))
		continue;
		final Dictionary dictionary = mUnigramDictionaries.get(key);
		if (mTrailingSingleQuotesCount > 0) {
		final WordComposer tmpWordComposer = new WordComposer(wordComposer);
		for (int i = mTrailingSingleQuotesCount - 1; i >= 0; --i) {
		tmpWordComposer.deleteLast();
		}
		dictionary.getWords(tmpWordComposer, this, proximityInfo);
		} else {
		dictionary.getWords(wordComposer, this, proximityInfo);
		}
		}
		}
		final String consideredWordString = consideredWord.toString();

		CharSequence whitelistedWord = capitalizeWord(mIsAllUpperCase, mIsFirstCharCapitalized,
		mWhiteListDictionary.getWhitelistedWord(consideredWordString));
		null);

		final boolean hasAutoCorrection;
		if (CORRECTION_FULL == correctionMode
		\|\| CORRECTION_FULL_BIGRAM == correctionMode) {
		final CharSequence autoCorrection =
		AutoCorrection.computeAutoCorrectionWord(mUnigramDictionaries, wordComposer,
		mSuggestions, mScores, consideredWord, mAutoCorrectionThreshold,
		whitelistedWord);
		final CharSequence autoCorrection = null;
		hasAutoCorrection = (null != autoCorrection);
		} else {
		hasAutoCorrection = false;
		@@ -374,37 +349,9 @@ public class Suggest implements Dictionary.WordCallback {
		}
		}

		mSuggestions.add(0, typedWord.toString());
		mSuggestions.add(0, typedWord);
		StringUtils.removeDupes(mSuggestions);

		if (DBG) {
		final CharSequence autoCorrectionSuggestion = mSuggestions.get(0);
		final int autoCorrectionSuggestionScore = mScores[0];
		double normalizedScore = BinaryDictionary.calcNormalizedScore(
		typedWord.toString(), autoCorrectionSuggestion.toString(),
		autoCorrectionSuggestionScore);
		ArrayList<SuggestedWords.SuggestedWordInfo> scoreInfoList =
		new ArrayList<SuggestedWords.SuggestedWordInfo>();
		scoreInfoList.add(new SuggestedWords.SuggestedWordInfo("+", false));
		for (int i = 0; i < mScores.length; ++i) {
		if (normalizedScore > 0) {
		final String scoreThreshold = String.format("%d (%4.2f)", mScores[i],
		normalizedScore);
		scoreInfoList.add(
		new SuggestedWords.SuggestedWordInfo(scoreThreshold, false));
		normalizedScore = 0.0;
		} else {
		final String score = Integer.toString(mScores[i]);
		scoreInfoList.add(new SuggestedWords.SuggestedWordInfo(score, false));
		}
		}
		for (int i = mScores.length; i < mSuggestions.size(); ++i) {
		scoreInfoList.add(new SuggestedWords.SuggestedWordInfo("--", false));
		}
		return new SuggestedWords.Builder().addWords(mSuggestions, scoreInfoList)
		.setAllowsToBeAutoCorrected(allowsToBeAutoCorrected)
		.setHasAutoCorrection(hasAutoCorrection);
		}
		return new SuggestedWords.Builder().addWords(mSuggestions, null)
		.setAllowsToBeAutoCorrected(allowsToBeAutoCorrected)
		.setHasAutoCorrection(hasAutoCorrection);
		@@ -494,10 +441,9 @@ public class Suggest implements Dictionary.WordCallback {
		}
		}
		}
		final String consideredWordString = consideredWord.toString();

		CharSequence whitelistedWord = capitalizeWord(mIsAllUpperCase, mIsFirstCharCapitalized,
		mWhiteListDictionary.getWhitelistedWord(consideredWordString));
		mWhiteListDictionary.getWhitelistedWord(consideredWord));

		final boolean hasAutoCorrection;
		if (CORRECTION_FULL == correctionMode
		@@ -523,14 +469,14 @@ public class Suggest implements Dictionary.WordCallback {
		}
		}

		mSuggestions.add(0, typedWord.toString());
		mSuggestions.add(0, typedWord);
		StringUtils.removeDupes(mSuggestions);

		if (DBG) {
		final CharSequence autoCorrectionSuggestion = mSuggestions.get(0);
		final int autoCorrectionSuggestionScore = mScores[0];
		double normalizedScore = BinaryDictionary.calcNormalizedScore(
		typedWord.toString(), autoCorrectionSuggestion.toString(),
		typedWord, autoCorrectionSuggestion.toString(),
		autoCorrectionSuggestionScore);
		ArrayList<SuggestedWords.SuggestedWordInfo> scoreInfoList =
		new ArrayList<SuggestedWords.SuggestedWordInfo>();