diff --git a/java/src/com/android/inputmethod/latin/Suggest.java b/java/src/com/android/inputmethod/latin/Suggest.java index ffe96a08c..30226812d 100644 --- a/java/src/com/android/inputmethod/latin/Suggest.java +++ b/java/src/com/android/inputmethod/latin/Suggest.java @@ -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 scoreInfoList = - new ArrayList(); - 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 scoreInfoList = new ArrayList();