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Reduction, step 2

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Change-Id: I06e117df43d25dbaf9fc7a7366efd9355a6215ce
This commit is contained in:
Jean Chalard 2012-03-09 18:10:13 +09:00
parent f08f30176b
commit 8abd15b59f
1 changed files with 9 additions and 63 deletions
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72
java/src/com/android/inputmethod/latin/Suggest.java
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@ -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>();