* commit 'd55ccbf7f95bb1af2d0b4a60994fb05af502e325': Enable touch coordinate correction for new algorithm
This commit is contained in:
commit
da9c04cd45
8 changed files with 94 additions and 48 deletions
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@ -675,7 +675,7 @@ inline static bool isUpperCase(unsigned short c) {
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multiplyIntCapped(typedLetterMultiplier, &finalFreq);
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}
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const float factor =
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SuggestUtils::getDistanceScalingFactor(static_cast<float>(squaredDistance));
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SuggestUtils::getLengthScalingFactor(static_cast<float>(squaredDistance));
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if (factor > 0.0f) {
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multiplyRate(static_cast<int>(factor * 100.0f), &finalFreq);
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} else if (squaredDistance == PROXIMITY_CHAR_WITHOUT_DISTANCE_INFO) {
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@ -81,7 +81,7 @@ void ProximityInfoState::initInputParams(const int pointerId, const float maxPoi
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mSampledTimes.clear();
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mSampledInputIndice.clear();
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mSampledLengthCache.clear();
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mSampledDistanceCache_G.clear();
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mSampledNormalizedSquaredLengthCache.clear();
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mSampledNearKeySets.clear();
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mSampledSearchKeySets.clear();
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mSpeedRates.clear();
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@ -122,14 +122,15 @@ void ProximityInfoState::initInputParams(const int pointerId, const float maxPoi
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if (mSampledInputSize > 0) {
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ProximityInfoStateUtils::initGeometricDistanceInfos(mProximityInfo, mSampledInputSize,
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lastSavedInputSize, verticalSweetSpotScale, &mSampledInputXs, &mSampledInputYs,
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&mSampledNearKeySets, &mSampledDistanceCache_G);
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&mSampledNearKeySets, &mSampledNormalizedSquaredLengthCache);
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if (isGeometric) {
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// updates probabilities of skipping or mapping each key for all points.
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ProximityInfoStateUtils::updateAlignPointProbabilities(
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mMaxPointToKeyLength, mProximityInfo->getMostCommonKeyWidth(),
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mProximityInfo->getKeyCount(), lastSavedInputSize, mSampledInputSize,
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&mSampledInputXs, &mSampledInputYs, &mSpeedRates, &mSampledLengthCache,
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&mSampledDistanceCache_G, &mSampledNearKeySets, &mCharProbabilities);
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&mSampledNormalizedSquaredLengthCache, &mSampledNearKeySets,
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&mCharProbabilities);
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ProximityInfoStateUtils::updateSampledSearchKeySets(mProximityInfo,
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mSampledInputSize, lastSavedInputSize, &mSampledLengthCache,
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&mSampledNearKeySets, &mSampledSearchKeySets,
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@ -171,7 +172,7 @@ float ProximityInfoState::getPointToKeyLength(
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const int keyId = mProximityInfo->getKeyIndexOf(codePoint);
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if (keyId != NOT_AN_INDEX) {
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const int index = inputIndex * mProximityInfo->getKeyCount() + keyId;
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return min(mSampledDistanceCache_G[index], mMaxPointToKeyLength);
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return min(mSampledNormalizedSquaredLengthCache[index], mMaxPointToKeyLength);
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}
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if (isIntentionalOmissionCodePoint(codePoint)) {
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return 0.0f;
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@ -183,7 +184,8 @@ float ProximityInfoState::getPointToKeyLength(
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float ProximityInfoState::getPointToKeyByIdLength(
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const int inputIndex, const int keyId) const {
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return ProximityInfoStateUtils::getPointToKeyByIdLength(mMaxPointToKeyLength,
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&mSampledDistanceCache_G, mProximityInfo->getKeyCount(), inputIndex, keyId);
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&mSampledNormalizedSquaredLengthCache, mProximityInfo->getKeyCount(), inputIndex,
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keyId);
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}
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// In the following function, c is the current character of the dictionary word currently examined.
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@ -49,8 +49,8 @@ class ProximityInfoState {
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mKeyCount(0), mCellHeight(0), mCellWidth(0), mGridHeight(0), mGridWidth(0),
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mIsContinuousSuggestionPossible(false), mSampledInputXs(), mSampledInputYs(),
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mSampledTimes(), mSampledInputIndice(), mSampledLengthCache(),
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mBeelineSpeedPercentiles(), mSampledDistanceCache_G(), mSpeedRates(), mDirections(),
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mCharProbabilities(), mSampledNearKeySets(), mSampledSearchKeySets(),
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mBeelineSpeedPercentiles(), mSampledNormalizedSquaredLengthCache(), mSpeedRates(),
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mDirections(), mCharProbabilities(), mSampledNearKeySets(), mSampledSearchKeySets(),
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mSampledSearchKeyVectors(), mTouchPositionCorrectionEnabled(false),
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mSampledInputSize(0), mMostProbableStringProbability(0.0f) {
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memset(mInputProximities, 0, sizeof(mInputProximities));
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@ -147,7 +147,9 @@ class ProximityInfoState {
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return mIsContinuousSuggestionPossible;
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}
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// TODO: Rename s/Length/NormalizedSquaredLength/
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float getPointToKeyByIdLength(const int inputIndex, const int keyId) const;
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// TODO: Rename s/Length/NormalizedSquaredLength/
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float getPointToKeyLength(const int inputIndex, const int codePoint) const;
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ProximityType getProximityType(const int index, const int codePoint,
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@ -231,7 +233,7 @@ class ProximityInfoState {
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std::vector<int> mSampledInputIndice;
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std::vector<int> mSampledLengthCache;
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std::vector<int> mBeelineSpeedPercentiles;
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std::vector<float> mSampledDistanceCache_G;
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std::vector<float> mSampledNormalizedSquaredLengthCache;
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std::vector<float> mSpeedRates;
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std::vector<float> mDirections;
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// probabilities of skipping or mapping to a key for each point.
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@ -225,13 +225,13 @@ namespace latinime {
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const int lastSavedInputSize, const float verticalSweetSpotScale,
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const std::vector<int> *const sampledInputXs,
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const std::vector<int> *const sampledInputYs,
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std::vector<NearKeycodesSet> *SampledNearKeySets,
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std::vector<float> *SampledDistanceCache_G) {
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SampledNearKeySets->resize(sampledInputSize);
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std::vector<NearKeycodesSet> *sampledNearKeySets,
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std::vector<float> *sampledNormalizedSquaredLengthCache) {
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sampledNearKeySets->resize(sampledInputSize);
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const int keyCount = proximityInfo->getKeyCount();
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SampledDistanceCache_G->resize(sampledInputSize * keyCount);
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sampledNormalizedSquaredLengthCache->resize(sampledInputSize * keyCount);
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for (int i = lastSavedInputSize; i < sampledInputSize; ++i) {
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(*SampledNearKeySets)[i].reset();
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(*sampledNearKeySets)[i].reset();
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for (int k = 0; k < keyCount; ++k) {
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const int index = i * keyCount + k;
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const int x = (*sampledInputXs)[i];
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@ -239,10 +239,10 @@ namespace latinime {
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const float normalizedSquaredDistance =
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proximityInfo->getNormalizedSquaredDistanceFromCenterFloatG(
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k, x, y, verticalSweetSpotScale);
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(*SampledDistanceCache_G)[index] = normalizedSquaredDistance;
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(*sampledNormalizedSquaredLengthCache)[index] = normalizedSquaredDistance;
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if (normalizedSquaredDistance
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< ProximityInfoParams::NEAR_KEY_NORMALIZED_SQUARED_THRESHOLD) {
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(*SampledNearKeySets)[i][k] = true;
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(*sampledNearKeySets)[i][k] = true;
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}
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}
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}
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@ -642,11 +642,11 @@ namespace latinime {
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// This function basically converts from a length to an edit distance. Accordingly, it's obviously
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// wrong to compare with mMaxPointToKeyLength.
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/* static */ float ProximityInfoStateUtils::getPointToKeyByIdLength(const float maxPointToKeyLength,
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const std::vector<float> *const SampledDistanceCache_G, const int keyCount,
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const std::vector<float> *const sampledNormalizedSquaredLengthCache, const int keyCount,
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const int inputIndex, const int keyId) {
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if (keyId != NOT_AN_INDEX) {
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const int index = inputIndex * keyCount + keyId;
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return min((*SampledDistanceCache_G)[index], maxPointToKeyLength);
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return min((*sampledNormalizedSquaredLengthCache)[index], maxPointToKeyLength);
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}
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// If the char is not a key on the keyboard then return the max length.
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return static_cast<float>(MAX_VALUE_FOR_WEIGHTING);
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@ -660,8 +660,8 @@ namespace latinime {
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const std::vector<int> *const sampledInputYs,
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const std::vector<float> *const sampledSpeedRates,
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const std::vector<int> *const sampledLengthCache,
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const std::vector<float> *const SampledDistanceCache_G,
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std::vector<NearKeycodesSet> *SampledNearKeySets,
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const std::vector<float> *const sampledNormalizedSquaredLengthCache,
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std::vector<NearKeycodesSet> *sampledNearKeySets,
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std::vector<hash_map_compat<int, float> > *charProbabilities) {
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charProbabilities->resize(sampledInputSize);
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// Calculates probabilities of using a point as a correlated point with the character
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@ -677,9 +677,9 @@ namespace latinime {
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float nearestKeyDistance = static_cast<float>(MAX_VALUE_FOR_WEIGHTING);
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for (int j = 0; j < keyCount; ++j) {
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if ((*SampledNearKeySets)[i].test(j)) {
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if ((*sampledNearKeySets)[i].test(j)) {
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const float distance = getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i, j);
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount, i, j);
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if (distance < nearestKeyDistance) {
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nearestKeyDistance = distance;
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}
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@ -758,14 +758,15 @@ namespace latinime {
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// Summing up probability densities of all near keys.
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float sumOfProbabilityDensities = 0.0f;
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for (int j = 0; j < keyCount; ++j) {
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if ((*SampledNearKeySets)[i].test(j)) {
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if ((*sampledNearKeySets)[i].test(j)) {
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float distance = sqrtf(getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i, j));
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount, i, j));
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if (i == 0 && i != sampledInputSize - 1) {
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// For the first point, weighted average of distances from first point and the
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// next point to the key is used as a point to key distance.
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const float nextDistance = sqrtf(getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i + 1, j));
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
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i + 1, j));
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if (nextDistance < distance) {
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// The distance of the first point tends to bigger than continuing
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// points because the first touch by the user can be sloppy.
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@ -779,7 +780,8 @@ namespace latinime {
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// For the first point, weighted average of distances from last point and
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// the previous point to the key is used as a point to key distance.
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const float previousDistance = sqrtf(getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i - 1, j));
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
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i - 1, j));
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if (previousDistance < distance) {
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// The distance of the last point tends to bigger than continuing points
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// because the last touch by the user can be sloppy. So we promote the
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@ -798,14 +800,15 @@ namespace latinime {
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// Split the probability of an input point to keys that are close to the input point.
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for (int j = 0; j < keyCount; ++j) {
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if ((*SampledNearKeySets)[i].test(j)) {
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if ((*sampledNearKeySets)[i].test(j)) {
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float distance = sqrtf(getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i, j));
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount, i, j));
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if (i == 0 && i != sampledInputSize - 1) {
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// For the first point, weighted average of distances from the first point and
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// the next point to the key is used as a point to key distance.
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const float prevDistance = sqrtf(getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i + 1, j));
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
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i + 1, j));
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if (prevDistance < distance) {
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distance = (distance
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+ prevDistance * ProximityInfoParams::NEXT_DISTANCE_WEIGHT)
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@ -815,7 +818,8 @@ namespace latinime {
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// For the first point, weighted average of distances from last point and
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// the previous point to the key is used as a point to key distance.
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const float prevDistance = sqrtf(getPointToKeyByIdLength(
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maxPointToKeyLength, SampledDistanceCache_G, keyCount, i - 1, j));
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maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
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i - 1, j));
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if (prevDistance < distance) {
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distance = (distance
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+ prevDistance * ProximityInfoParams::PREV_DISTANCE_WEIGHT)
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@ -882,10 +886,10 @@ namespace latinime {
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for (int j = 0; j < keyCount; ++j) {
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hash_map_compat<int, float>::iterator it = (*charProbabilities)[i].find(j);
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if (it == (*charProbabilities)[i].end()){
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(*SampledNearKeySets)[i].reset(j);
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(*sampledNearKeySets)[i].reset(j);
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} else if(it->second < ProximityInfoParams::MIN_PROBABILITY) {
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// Erases from near keys vector because it has very low probability.
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(*SampledNearKeySets)[i].reset(j);
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(*sampledNearKeySets)[i].reset(j);
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(*charProbabilities)[i].erase(j);
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} else {
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it->second = -logf(it->second);
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@ -899,7 +903,7 @@ namespace latinime {
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const ProximityInfo *const proximityInfo, const int sampledInputSize,
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const int lastSavedInputSize,
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const std::vector<int> *const sampledLengthCache,
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const std::vector<NearKeycodesSet> *const SampledNearKeySets,
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const std::vector<NearKeycodesSet> *const sampledNearKeySets,
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std::vector<NearKeycodesSet> *sampledSearchKeySets,
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std::vector<std::vector<int> > *sampledSearchKeyVectors) {
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sampledSearchKeySets->resize(sampledInputSize);
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@ -916,7 +920,7 @@ namespace latinime {
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if ((*sampledLengthCache)[j] - (*sampledLengthCache)[i] >= readForwordLength) {
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break;
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}
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(*sampledSearchKeySets)[i] |= (*SampledNearKeySets)[j];
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(*sampledSearchKeySets)[i] |= (*sampledNearKeySets)[j];
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}
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}
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const int keyCount = proximityInfo->getKeyCount();
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@ -71,25 +71,25 @@ class ProximityInfoStateUtils {
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const std::vector<int> *const sampledInputYs,
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const std::vector<float> *const sampledSpeedRates,
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const std::vector<int> *const sampledLengthCache,
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const std::vector<float> *const SampledDistanceCache_G,
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std::vector<NearKeycodesSet> *SampledNearKeySets,
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const std::vector<float> *const sampledNormalizedSquaredLengthCache,
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std::vector<NearKeycodesSet> *sampledNearKeySets,
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std::vector<hash_map_compat<int, float> > *charProbabilities);
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static void updateSampledSearchKeySets(const ProximityInfo *const proximityInfo,
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const int sampledInputSize, const int lastSavedInputSize,
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const std::vector<int> *const sampledLengthCache,
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const std::vector<NearKeycodesSet> *const SampledNearKeySets,
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const std::vector<NearKeycodesSet> *const sampledNearKeySets,
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std::vector<NearKeycodesSet> *sampledSearchKeySets,
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std::vector<std::vector<int> > *sampledSearchKeyVectors);
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static float getPointToKeyByIdLength(const float maxPointToKeyLength,
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const std::vector<float> *const SampledDistanceCache_G, const int keyCount,
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const std::vector<float> *const sampledNormalizedSquaredLengthCache, const int keyCount,
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const int inputIndex, const int keyId);
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static void initGeometricDistanceInfos(const ProximityInfo *const proximityInfo,
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const int sampledInputSize, const int lastSavedInputSize,
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const float verticalSweetSpotScale,
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const std::vector<int> *const sampledInputXs,
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const std::vector<int> *const sampledInputYs,
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std::vector<NearKeycodesSet> *SampledNearKeySets,
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std::vector<float> *SampledDistanceCache_G);
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std::vector<NearKeycodesSet> *sampledNearKeySets,
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std::vector<float> *sampledNormalizedSquaredLengthCache);
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static void initPrimaryInputWord(const int inputSize, const int *const inputProximities,
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int *primaryInputWord);
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static void initNormalizedSquaredDistances(const ProximityInfo *const proximityInfo,
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@ -146,6 +146,10 @@ class DicTraverseSession {
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return true;
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}
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bool isTouchPositionCorrectionEnabled() const {
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return mProximityInfoStates[0].touchPositionCorrectionEnabled();
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}
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private:
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DISALLOW_IMPLICIT_CONSTRUCTORS(DicTraverseSession);
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// threshold to start caching
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@ -18,6 +18,7 @@
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#define LATINIME_TYPING_WEIGHTING_H
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#include "defines.h"
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#include "suggest_utils.h"
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#include "suggest/core/dicnode/dic_node_utils.h"
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#include "suggest/core/policy/weighting.h"
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#include "suggest/core/session/dic_traverse_session.h"
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@ -70,10 +71,12 @@ class TypingWeighting : public Weighting {
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const int pointIndex = dicNode->getInputIndex(0);
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// Note: min() required since length can be MAX_POINT_TO_KEY_LENGTH for characters not on
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// the keyboard (like accented letters)
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const float length = min(ScoringParams::MAX_SPATIAL_DISTANCE,
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traverseSession->getProximityInfoState(0)->getPointToKeyLength(
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pointIndex, dicNode->getNodeCodePoint()));
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const float weightedDistance = length * ScoringParams::DISTANCE_WEIGHT_LENGTH;
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const float normalizedSquaredLength = traverseSession->getProximityInfoState(0)
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->getPointToKeyLength(pointIndex, dicNode->getNodeCodePoint());
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const float normalizedDistance = SuggestUtils::getSweetSpotFactor(
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traverseSession->isTouchPositionCorrectionEnabled(), normalizedSquaredLength);
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const float weightedDistance = ScoringParams::DISTANCE_WEIGHT_LENGTH * normalizedDistance;
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const bool isFirstChar = pointIndex == 0;
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const bool isProximity = isProximityDicNode(traverseSession, dicNode);
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const float cost = isProximity ? (isFirstChar ? ScoringParams::FIRST_PROXIMITY_COST
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|
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@ -23,10 +23,8 @@
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namespace latinime {
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class SuggestUtils {
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public:
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static float getDistanceScalingFactor(const float normalizedSquaredDistance) {
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if (normalizedSquaredDistance < 0.0f) {
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return -1.0f;
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}
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// TODO: (OLD) Remove
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static float getLengthScalingFactor(const float normalizedSquaredDistance) {
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// Promote or demote the score according to the distance from the sweet spot
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static const float A = ZERO_DISTANCE_PROMOTION_RATE / 100.0f;
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static const float B = 1.0f;
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@ -50,6 +48,39 @@ class SuggestUtils {
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return factor;
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}
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static float getSweetSpotFactor(const bool isTouchPositionCorrectionEnabled,
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const float normalizedSquaredDistance) {
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// Promote or demote the score according to the distance from the sweet spot
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static const float A = 0.0f;
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static const float B = 0.24f;
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static const float C = 1.20f;
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static const float R0 = 0.0f;
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static const float R1 = 0.25f; // Sweet spot
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static const float R2 = 1.0f;
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const float x = normalizedSquaredDistance;
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if (!isTouchPositionCorrectionEnabled) {
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return min(C, x);
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}
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// factor is a piecewise linear function like:
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// C -------------.
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// / .
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// B / .
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// -/ .
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// A _-^ .
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// .
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// R0 R1 R2 .
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if (x < R0) {
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return A;
|
||||
} else if (x < R1) {
|
||||
return (A * (R1 - x) + B * (x - R0)) / (R1 - R0);
|
||||
} else if (x < R2) {
|
||||
return (B * (R2 - x) + C * (x - R1)) / (R2 - R1);
|
||||
} else {
|
||||
return C;
|
||||
}
|
||||
}
|
||||
private:
|
||||
DISALLOW_IMPLICIT_CONSTRUCTORS(SuggestUtils);
|
||||
};
|
||||
|
|
Loading…
Reference in a new issue