Cut out a private method to make things more readable
Change-Id: I791700890338e023bd86b8794dbc90379b91dc7dmain
parent
ac5e463402
commit
0d0f182959
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@ -395,30 +395,7 @@ public class Suggest implements Dictionary.WordCallback {
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final ArrayList<SuggestedWordInfo> suggestionsList;
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if (DBG) {
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// TODO: this doesn't take into account the fact that removing dupes from mSuggestions
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// may have made mScores[] and mSuggestions out of sync.
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final CharSequence autoCorrectionSuggestion = mSuggestions.get(0);
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double normalizedScore = BinaryDictionary.calcNormalizedScore(
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typedWord, autoCorrectionSuggestion.toString(), mScores[0]);
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final int suggestionsSize = mSuggestions.size();
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suggestionsList = new ArrayList<SuggestedWordInfo>(suggestionsSize);
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suggestionsList.add(new SuggestedWordInfo(autoCorrectionSuggestion, "+", false));
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// Note: i here is the index in mScores[], but the index in mSuggestions is one more
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// than i because we added the typed word to mSuggestions without touching mScores.
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for (int i = 0; i < mScores.length && i < suggestionsSize - 1; ++i) {
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final String scoreInfoString;
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if (normalizedScore > 0) {
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scoreInfoString = String.format("%d (%4.2f)", mScores[i], normalizedScore);
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normalizedScore = 0.0;
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} else {
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scoreInfoString = Integer.toString(mScores[i]);
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}
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suggestionsList.add(new SuggestedWordInfo(mSuggestions.get(i + 1),
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scoreInfoString, false));
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}
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for (int i = mScores.length; i < suggestionsSize; ++i) {
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suggestionsList.add(new SuggestedWordInfo(mSuggestions.get(i), "--", false));
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}
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suggestionsList = getSuggestionsInfoListWithDebugInfo(typedWord, mSuggestions, mScores);
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} else {
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suggestionsList = SuggestedWords.getFromCharSequenceList(mSuggestions);
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}
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@ -446,6 +423,37 @@ public class Suggest implements Dictionary.WordCallback {
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false /* isPunctuationSuggestions */);
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}
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// This assumes the scores[] array is at least as long as suggestions.size() - 1.
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private static ArrayList<SuggestedWordInfo> getSuggestionsInfoListWithDebugInfo(
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final String typedWord, final ArrayList<CharSequence> suggestions, final int[] scores) {
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// TODO: this doesn't take into account the fact that removing dupes from mSuggestions
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// may have made mScores[] and mSuggestions out of sync.
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final CharSequence autoCorrectionSuggestion = suggestions.get(0);
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double normalizedScore = BinaryDictionary.calcNormalizedScore(
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typedWord, autoCorrectionSuggestion.toString(), scores[0]);
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final int suggestionsSize = suggestions.size();
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final ArrayList<SuggestedWordInfo> suggestionsList =
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new ArrayList<SuggestedWordInfo>(suggestionsSize);
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suggestionsList.add(new SuggestedWordInfo(autoCorrectionSuggestion, "+", false));
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// Note: i here is the index in mScores[], but the index in mSuggestions is one more
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// than i because we added the typed word to mSuggestions without touching mScores.
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for (int i = 0; i < scores.length && i < suggestionsSize - 1; ++i) {
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final String scoreInfoString;
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if (normalizedScore > 0) {
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scoreInfoString = String.format("%d (%4.2f)", scores[i], normalizedScore);
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normalizedScore = 0.0;
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} else {
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scoreInfoString = Integer.toString(scores[i]);
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}
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suggestionsList.add(new SuggestedWordInfo(suggestions.get(i + 1),
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scoreInfoString, false));
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}
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for (int i = scores.length; i < suggestionsSize; ++i) {
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suggestionsList.add(new SuggestedWordInfo(suggestions.get(i), "--", false));
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}
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return suggestionsList;
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}
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@Override
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public boolean addWord(final char[] word, final int offset, final int length, int score,
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final int dicTypeId, final int dataType) {
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