/*
* Copyright (C) 2008 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 com.s16.inputmethod.skeyboard;
import java.nio.ByteBuffer;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import android.content.Context;
import android.text.AutoText;
import android.text.TextUtils;
import android.util.Log;
import android.view.View;
/**
* This class loads a dictionary and provides a list of suggestions for a given sequence of
* characters. This includes corrections and completions.
* @hide pending API Council Approval
*/
public class Suggest implements Dictionary.WordCallback {
public static final int APPROX_MAX_WORD_LENGTH = 32;
public static final int CORRECTION_NONE = 0;
public static final int CORRECTION_BASIC = 1;
public static final int CORRECTION_FULL = 2;
public static final int CORRECTION_FULL_BIGRAM = 3;
/**
* Words that appear in both bigram and unigram data gets multiplier ranging from
* BIGRAM_MULTIPLIER_MIN to BIGRAM_MULTIPLIER_MAX depending on the frequency score from
* bigram data.
*/
public static final double BIGRAM_MULTIPLIER_MIN = 1.2;
public static final double BIGRAM_MULTIPLIER_MAX = 1.5;
/**
* Maximum possible bigram frequency. Will depend on how many bits are being used in data
* structure. Maximum bigram freqeuncy will get the BIGRAM_MULTIPLIER_MAX as the multiplier.
*/
public static final int MAXIMUM_BIGRAM_FREQUENCY = 127;
public static final int DIC_USER_TYPED = 0;
public static final int DIC_MAIN = 1;
public static final int DIC_USER = 2;
public static final int DIC_AUTO = 3;
public static final int DIC_CONTACTS = 4;
// If you add a type of dictionary, increment DIC_TYPE_LAST_ID
public static final int DIC_TYPE_LAST_ID = 4;
static final int LARGE_DICTIONARY_THRESHOLD = 200 * 1000;
private BinaryDictionary mMainDict;
private Dictionary mUserDictionary;
private Dictionary mAutoDictionary;
private Dictionary mContactsDictionary;
private Dictionary mUserBigramDictionary;
private int mPrefMaxSuggestions = 12;
private static final int PREF_MAX_BIGRAMS = 60;
private boolean mAutoTextEnabled;
private int[] mPriorities = new int[mPrefMaxSuggestions];
private int[] mBigramPriorities = new int[PREF_MAX_BIGRAMS];
// Handle predictive correction for only the first 1280 characters for performance reasons
// If we support scripts that need latin characters beyond that, we should probably use some
// kind of a sparse array or language specific list with a mapping lookup table.
// 1280 is the size of the BASE_CHARS array in ExpandableDictionary, which is a basic set of
// latin characters.
private int[] mNextLettersFrequencies = new int[1280];
private ArrayList<CharSequence> mSuggestions = new ArrayList<CharSequence>();
ArrayList<CharSequence> mBigramSuggestions = new ArrayList<CharSequence>();
private ArrayList<CharSequence> mStringPool = new ArrayList<CharSequence>();
private boolean mHaveCorrection;
private CharSequence mOriginalWord;
private String mLowerOriginalWord;
// TODO: Remove these member variables by passing more context to addWord() callback method
private boolean mIsFirstCharCapitalized;
private boolean mIsAllUpperCase;
private int mCorrectionMode = CORRECTION_BASIC;
public Suggest(Context context, int[] dictionaryResId) {
mMainDict = new BinaryDictionary(context, dictionaryResId, DIC_MAIN);
initPool();
}
public Suggest(Context context, ByteBuffer byteBuffer) {
mMainDict = new BinaryDictionary(context, byteBuffer, DIC_MAIN);
initPool();
}
private void initPool() {
for (int i = 0; i < mPrefMaxSuggestions; i++) {
StringBuilder sb = new StringBuilder(getApproxMaxWordLength());
mStringPool.add(sb);
}
}
public void setAutoTextEnabled(boolean enabled) {
mAutoTextEnabled = enabled;
}
public int getCorrectionMode() {
return mCorrectionMode;
}
public void setCorrectionMode(int mode) {
mCorrectionMode = mode;
}
public boolean hasMainDictionary() {
//return mMainDict.getSize() > LARGE_DICTIONARY_THRESHOLD;
return true;
}
public int getApproxMaxWordLength() {
return APPROX_MAX_WORD_LENGTH;
}
/**
* Sets an optional user dictionary resource to be loaded. The user dictionary is consulted
* before the main dictionary, if set.
*/
public void setUserDictionary(Dictionary userDictionary) {
mUserDictionary = userDictionary;
}
/**
* Sets an optional contacts dictionary resource to be loaded.
*/
public void setContactsDictionary(Dictionary userDictionary) {
mContactsDictionary = userDictionary;
}
public void setAutoDictionary(Dictionary autoDictionary) {
mAutoDictionary = autoDictionary;
}
public void setUserBigramDictionary(Dictionary userBigramDictionary) {
mUserBigramDictionary = userBigramDictionary;
}
/**
* Number of suggestions to generate from the input key sequence. This has
* to be a number between 1 and 100 (inclusive).
* @param maxSuggestions
* @throws IllegalArgumentException if the number is out of range
*/
public void setMaxSuggestions(int maxSuggestions) {
if (maxSuggestions < 1 || maxSuggestions > 100) {
throw new IllegalArgumentException("maxSuggestions must be between 1 and 100");
}
mPrefMaxSuggestions = maxSuggestions;
mPriorities = new int[mPrefMaxSuggestions];
mBigramPriorities = new int[PREF_MAX_BIGRAMS];
collectGarbage(mSuggestions, mPrefMaxSuggestions);
while (mStringPool.size() < mPrefMaxSuggestions) {
StringBuilder sb = new StringBuilder(getApproxMaxWordLength());
mStringPool.add(sb);
}
}
private boolean haveSufficientCommonality(String original, CharSequence suggestion) {
final int originalLength = original.length();
final int suggestionLength = suggestion.length();
final int minLength = Math.min(originalLength, suggestionLength);
if (minLength <= 2) return true;
int matching = 0;
int lessMatching = 0; // Count matches if we skip one character
int i;
for (i = 0; i < minLength; i++) {
final char origChar = ExpandableDictionary.toLowerCase(original.charAt(i));
if (origChar == ExpandableDictionary.toLowerCase(suggestion.charAt(i))) {
matching++;
lessMatching++;
} else if (i + 1 < suggestionLength
&& origChar == ExpandableDictionary.toLowerCase(suggestion.charAt(i + 1))) {
lessMatching++;
}
}
matching = Math.max(matching, lessMatching);
if (minLength <= 4) {
return matching >= 2;
} else {
return matching > minLength / 2;
}
}
/**
* Returns a list of words that match the list of character codes passed in.
* This list will be overwritten the next time this function is called.
* @param view a view for retrieving the context for AutoText
* @param wordComposer contains what is currently being typed
* @param prevWordForBigram previous word (used only for bigram)
* @return list of suggestions.
*/
public List<CharSequence> getSuggestions(View view, WordComposer wordComposer,
boolean includeTypedWordIfValid, CharSequence prevWordForBigram) {
IMELogger.onStartSuggestion(prevWordForBigram);
mHaveCorrection = false;
mIsFirstCharCapitalized = wordComposer.isFirstCharCapitalized();
mIsAllUpperCase = wordComposer.isAllUpperCase();
collectGarbage(mSuggestions, mPrefMaxSuggestions);
Arrays.fill(mPriorities, 0);
Arrays.fill(mNextLettersFrequencies, 0);
// Save a lowercase version of the original word
mOriginalWord = wordComposer.getTypedWord();
if (mOriginalWord != null) {
final String mOriginalWordString = mOriginalWord.toString();
mOriginalWord = mOriginalWordString;
mLowerOriginalWord = mOriginalWordString.toLowerCase();
// Treating USER_TYPED as UNIGRAM suggestion for logging now.
IMELogger.onAddSuggestedWord(mOriginalWordString, Suggest.DIC_USER_TYPED,
Dictionary.DataType.UNIGRAM);
} else {
mLowerOriginalWord = "";
}
if (wordComposer.size() == 1 && (mCorrectionMode == CORRECTION_FULL_BIGRAM
|| mCorrectionMode == CORRECTION_BASIC)) {
// At first character typed, search only the bigrams
Arrays.fill(mBigramPriorities, 0);
collectGarbage(mBigramSuggestions, PREF_MAX_BIGRAMS);
if (!TextUtils.isEmpty(prevWordForBigram)) {
CharSequence lowerPrevWord = prevWordForBigram.toString().toLowerCase();
if (mMainDict.isValidWord(lowerPrevWord)) {
prevWordForBigram = lowerPrevWord;
}
if (mUserBigramDictionary != null) {
mUserBigramDictionary.getBigrams(wordComposer, prevWordForBigram, this,
mNextLettersFrequencies);
}
if (mContactsDictionary != null) {
mContactsDictionary.getBigrams(wordComposer, prevWordForBigram, this,
mNextLettersFrequencies);
}
if (mMainDict != null) {
mMainDict.getBigrams(wordComposer, prevWordForBigram, this,
mNextLettersFrequencies);
}
char currentChar = wordComposer.getTypedWord().charAt(0);
char currentCharUpper = Character.toUpperCase(currentChar);
int count = 0;
int bigramSuggestionSize = mBigramSuggestions.size();
for (int i = 0; i < bigramSuggestionSize; i++) {
if (mBigramSuggestions.get(i).charAt(0) == currentChar
|| mBigramSuggestions.get(i).charAt(0) == currentCharUpper) {
int poolSize = mStringPool.size();
StringBuilder sb = poolSize > 0 ?
(StringBuilder) mStringPool.remove(poolSize - 1)
: new StringBuilder(getApproxMaxWordLength());
sb.setLength(0);
sb.append(mBigramSuggestions.get(i));
mSuggestions.add(count++, sb);
if (count > mPrefMaxSuggestions) break;
}
}
}
} else if (wordComposer.size() > 1) {
// At second character typed, search the unigrams (scores being affected by bigrams)
if (mUserDictionary != null || mContactsDictionary != null) {
if (mUserDictionary != null) {
mUserDictionary.getWords(wordComposer, this, mNextLettersFrequencies);
}
if (mContactsDictionary != null) {
mContactsDictionary.getWords(wordComposer, this, mNextLettersFrequencies);
}
if (mSuggestions.size() > 0 && isValidWord(mOriginalWord)
&& (mCorrectionMode == CORRECTION_FULL
|| mCorrectionMode == CORRECTION_FULL_BIGRAM)) {
mHaveCorrection = true;
}
}
mMainDict.getWords(wordComposer, this, mNextLettersFrequencies);
if ((mCorrectionMode == CORRECTION_FULL || mCorrectionMode == CORRECTION_FULL_BIGRAM)
&& mSuggestions.size() > 0) {
mHaveCorrection = true;
}
}
if (mOriginalWord != null) {
mSuggestions.add(0, mOriginalWord.toString());
}
// Check if the first suggestion has a minimum number of characters in common
if (wordComposer.size() > 1 && mSuggestions.size() > 1
&& (mCorrectionMode == CORRECTION_FULL
|| mCorrectionMode == CORRECTION_FULL_BIGRAM)) {
if (!haveSufficientCommonality(mLowerOriginalWord, mSuggestions.get(1))) {
mHaveCorrection = false;
}
}
if (mAutoTextEnabled) {
int i = 0;
int max = 6;
// Don't autotext the suggestions from the dictionaries
if (mCorrectionMode == CORRECTION_BASIC) max = 1;
while (i < mSuggestions.size() && i < max) {
String suggestedWord = mSuggestions.get(i).toString().toLowerCase();
CharSequence autoText =
AutoText.get(suggestedWord, 0, suggestedWord.length(), view);
// Is there an AutoText correction?
boolean canAdd = autoText != null;
// Is that correction already the current prediction (or original word)?
canAdd &= !TextUtils.equals(autoText, mSuggestions.get(i));
// Is that correction already the next predicted word?
if (canAdd && i + 1 < mSuggestions.size() && mCorrectionMode != CORRECTION_BASIC) {
canAdd &= !TextUtils.equals(autoText, mSuggestions.get(i + 1));
}
if (canAdd) {
mHaveCorrection = true;
mSuggestions.add(i + 1, autoText);
i++;
}
i++;
}
}
removeDupes();
return mSuggestions;
}
public int[] getNextLettersFrequencies() {
return mNextLettersFrequencies;
}
private void removeDupes() {
final ArrayList<CharSequence> suggestions = mSuggestions;
if (suggestions.size() < 2) return;
int i = 1;
// Don't cache suggestions.size(), since we may be removing items
while (i < suggestions.size()) {
final CharSequence cur = suggestions.get(i);
// Compare each candidate with each previous candidate
for (int j = 0; j < i; j++) {
CharSequence previous = suggestions.get(j);
if (TextUtils.equals(cur, previous)) {
removeFromSuggestions(i);
i--;
break;
}
}
i++;
}
}
private void removeFromSuggestions(int index) {
CharSequence garbage = mSuggestions.remove(index);
if (garbage != null && garbage instanceof StringBuilder) {
mStringPool.add(garbage);
}
}
public boolean hasMinimalCorrection() {
return mHaveCorrection;
}
private boolean compareCaseInsensitive(final String mLowerOriginalWord,
final char[] word, final int offset, final int length) {
final int originalLength = mLowerOriginalWord.length();
if (originalLength == length && Character.isUpperCase(word[offset])) {
for (int i = 0; i < originalLength; i++) {
if (mLowerOriginalWord.charAt(i) != Character.toLowerCase(word[offset+i])) {
return false;
}
}
return true;
}
return false;
}
public boolean addWord(final char[] word, final int offset, final int length, int freq,
final int dicTypeId, final Dictionary.DataType dataType) {
Dictionary.DataType dataTypeForLog = dataType;
ArrayList<CharSequence> suggestions;
int[] priorities;
int prefMaxSuggestions;
if(dataType == Dictionary.DataType.BIGRAM) {
suggestions = mBigramSuggestions;
priorities = mBigramPriorities;
prefMaxSuggestions = PREF_MAX_BIGRAMS;
} else {
suggestions = mSuggestions;
priorities = mPriorities;
prefMaxSuggestions = mPrefMaxSuggestions;
}
int pos = 0;
// Check if it's the same word, only caps are different
if (compareCaseInsensitive(mLowerOriginalWord, word, offset, length)) {
pos = 0;
} else {
if (dataType == Dictionary.DataType.UNIGRAM) {
// Check if the word was already added before (by bigram data)
int bigramSuggestion = searchBigramSuggestion(word,offset,length);
if(bigramSuggestion >= 0) {
dataTypeForLog = Dictionary.DataType.BIGRAM;
// turn freq from bigram into multiplier specified above
double multiplier = (((double) mBigramPriorities[bigramSuggestion])
/ MAXIMUM_BIGRAM_FREQUENCY)
* (BIGRAM_MULTIPLIER_MAX - BIGRAM_MULTIPLIER_MIN)
+ BIGRAM_MULTIPLIER_MIN;
/* Log.d(TAG,"bigram num: " + bigramSuggestion
+ " wordB: " + mBigramSuggestions.get(bigramSuggestion).toString()
+ " currentPriority: " + freq + " bigramPriority: "
+ mBigramPriorities[bigramSuggestion]
+ " multiplier: " + multiplier); */
freq = (int)Math.round((freq * multiplier));
}
}
// Check the last one's priority and bail
if (priorities[prefMaxSuggestions - 1] >= freq) return true;
while (pos < prefMaxSuggestions) {
if (priorities[pos] < freq
|| (priorities[pos] == freq && length < suggestions.get(pos).length())) {
break;
}
pos++;
}
}
if (pos >= prefMaxSuggestions) {
return true;
}
System.arraycopy(priorities, pos, priorities, pos + 1,
prefMaxSuggestions - pos - 1);
priorities[pos] = freq;
int poolSize = mStringPool.size();
StringBuilder sb = poolSize > 0 ? (StringBuilder) mStringPool.remove(poolSize - 1)
: new StringBuilder(getApproxMaxWordLength());
sb.setLength(0);
if (mIsAllUpperCase) {
sb.append(new String(word, offset, length).toUpperCase());
} else if (mIsFirstCharCapitalized) {
sb.append(Character.toUpperCase(word[offset]));
if (length > 1) {
sb.append(word, offset + 1, length - 1);
}
} else {
sb.append(word, offset, length);
}
suggestions.add(pos, sb);
if (suggestions.size() > prefMaxSuggestions) {
CharSequence garbage = suggestions.remove(prefMaxSuggestions);
if (garbage instanceof StringBuilder) {
mStringPool.add(garbage);
}
} else {
IMELogger.onAddSuggestedWord(sb.toString(), dicTypeId, dataTypeForLog);
}
return true;
}
private int searchBigramSuggestion(final char[] word, final int offset, final int length) {
// TODO This is almost O(n^2). Might need fix.
// search whether the word appeared in bigram data
int bigramSuggestSize = mBigramSuggestions.size();
for(int i = 0; i < bigramSuggestSize; i++) {
if(mBigramSuggestions.get(i).length() == length) {
boolean chk = true;
for(int j = 0; j < length; j++) {
if(mBigramSuggestions.get(i).charAt(j) != word[offset+j]) {
chk = false;
break;
}
}
if(chk) return i;
}
}
return -1;
}
public boolean isValidWord(final CharSequence word) {
if (word == null || word.length() == 0) {
return false;
}
return mMainDict.isValidWord(word)
|| (mUserDictionary != null && mUserDictionary.isValidWord(word))
|| (mAutoDictionary != null && mAutoDictionary.isValidWord(word))
|| (mContactsDictionary != null && mContactsDictionary.isValidWord(word));
}
private void collectGarbage(ArrayList<CharSequence> suggestions, int prefMaxSuggestions) {
int poolSize = mStringPool.size();
int garbageSize = suggestions.size();
while (poolSize < prefMaxSuggestions && garbageSize > 0) {
CharSequence garbage = suggestions.get(garbageSize - 1);
if (garbage != null && garbage instanceof StringBuilder) {
mStringPool.add(garbage);
poolSize++;
}
garbageSize--;
}
if (poolSize == prefMaxSuggestions + 1) {
Log.w("Suggest", "String pool got too big: " + poolSize);
}
suggestions.clear();
}
public void close() {
if (mMainDict != null) {
mMainDict.close();
}
}
}