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am d55ccbf7: am 837f46dc: Enable touch coordinate correction for new algorithm 

* commit 'd55ccbf7f95bb1af2d0b4a60994fb05af502e325':
  Enable touch coordinate correction for new algorithm
main
Satoshi Kataoka 2013-04-17 19:47:11 -07:00 committed by Android Git Automerger
parent ae73133188 d55ccbf7f9
commit da9c04cd45
8 changed files with 94 additions and 48 deletions
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2
native/jni/src/correction.cpp
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@ -675,7 +675,7 @@ inline static bool isUpperCase(unsigned short c) {
multiplyIntCapped(typedLetterMultiplier, &finalFreq);
}
const float factor =
SuggestUtils::getDistanceScalingFactor(static_cast<float>(squaredDistance));
SuggestUtils::getLengthScalingFactor(static_cast<float>(squaredDistance));
if (factor > 0.0f) {
multiplyRate(static_cast<int>(factor * 100.0f), &finalFreq);
} else if (squaredDistance == PROXIMITY_CHAR_WITHOUT_DISTANCE_INFO) {

12
native/jni/src/proximity_info_state.cpp
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@ -81,7 +81,7 @@ void ProximityInfoState::initInputParams(const int pointerId, const float maxPoi
mSampledTimes.clear();
mSampledInputIndice.clear();
mSampledLengthCache.clear();
mSampledDistanceCache_G.clear();
mSampledNormalizedSquaredLengthCache.clear();
mSampledNearKeySets.clear();
mSampledSearchKeySets.clear();
mSpeedRates.clear();
@ -122,14 +122,15 @@ void ProximityInfoState::initInputParams(const int pointerId, const float maxPoi
if (mSampledInputSize > 0) {
ProximityInfoStateUtils::initGeometricDistanceInfos(mProximityInfo, mSampledInputSize,
lastSavedInputSize, verticalSweetSpotScale, &mSampledInputXs, &mSampledInputYs,
&mSampledNearKeySets, &mSampledDistanceCache_G);
&mSampledNearKeySets, &mSampledNormalizedSquaredLengthCache);
if (isGeometric) {
// updates probabilities of skipping or mapping each key for all points.
ProximityInfoStateUtils::updateAlignPointProbabilities(
mMaxPointToKeyLength, mProximityInfo->getMostCommonKeyWidth(),
mProximityInfo->getKeyCount(), lastSavedInputSize, mSampledInputSize,
&mSampledInputXs, &mSampledInputYs, &mSpeedRates, &mSampledLengthCache,
&mSampledDistanceCache_G, &mSampledNearKeySets, &mCharProbabilities);
&mSampledNormalizedSquaredLengthCache, &mSampledNearKeySets,
&mCharProbabilities);
ProximityInfoStateUtils::updateSampledSearchKeySets(mProximityInfo,
mSampledInputSize, lastSavedInputSize, &mSampledLengthCache,
&mSampledNearKeySets, &mSampledSearchKeySets,
@ -171,7 +172,7 @@ float ProximityInfoState::getPointToKeyLength(
const int keyId = mProximityInfo->getKeyIndexOf(codePoint);
if (keyId != NOT_AN_INDEX) {
const int index = inputIndex * mProximityInfo->getKeyCount() + keyId;
return min(mSampledDistanceCache_G[index], mMaxPointToKeyLength);
return min(mSampledNormalizedSquaredLengthCache[index], mMaxPointToKeyLength);
}
if (isIntentionalOmissionCodePoint(codePoint)) {
return 0.0f;
@ -183,7 +184,8 @@ float ProximityInfoState::getPointToKeyLength(
float ProximityInfoState::getPointToKeyByIdLength(
const int inputIndex, const int keyId) const {
return ProximityInfoStateUtils::getPointToKeyByIdLength(mMaxPointToKeyLength,
&mSampledDistanceCache_G, mProximityInfo->getKeyCount(), inputIndex, keyId);
&mSampledNormalizedSquaredLengthCache, mProximityInfo->getKeyCount(), inputIndex,
keyId);
}
// In the following function, c is the current character of the dictionary word currently examined.

8
native/jni/src/proximity_info_state.h
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@ -49,8 +49,8 @@ class ProximityInfoState {
mKeyCount(0), mCellHeight(0), mCellWidth(0), mGridHeight(0), mGridWidth(0),
mIsContinuousSuggestionPossible(false), mSampledInputXs(), mSampledInputYs(),
mSampledTimes(), mSampledInputIndice(), mSampledLengthCache(),
mBeelineSpeedPercentiles(), mSampledDistanceCache_G(), mSpeedRates(), mDirections(),
mCharProbabilities(), mSampledNearKeySets(), mSampledSearchKeySets(),
mBeelineSpeedPercentiles(), mSampledNormalizedSquaredLengthCache(), mSpeedRates(),
mDirections(), mCharProbabilities(), mSampledNearKeySets(), mSampledSearchKeySets(),
mSampledSearchKeyVectors(), mTouchPositionCorrectionEnabled(false),
mSampledInputSize(0), mMostProbableStringProbability(0.0f) {
memset(mInputProximities, 0, sizeof(mInputProximities));
@ -147,7 +147,9 @@ class ProximityInfoState {
return mIsContinuousSuggestionPossible;
}
// TODO: Rename s/Length/NormalizedSquaredLength/
float getPointToKeyByIdLength(const int inputIndex, const int keyId) const;
// TODO: Rename s/Length/NormalizedSquaredLength/
float getPointToKeyLength(const int inputIndex, const int codePoint) const;
ProximityType getProximityType(const int index, const int codePoint,
@ -231,7 +233,7 @@ class ProximityInfoState {
std::vector<int> mSampledInputIndice;
std::vector<int> mSampledLengthCache;
std::vector<int> mBeelineSpeedPercentiles;
std::vector<float> mSampledDistanceCache_G;
std::vector<float> mSampledNormalizedSquaredLengthCache;
std::vector<float> mSpeedRates;
std::vector<float> mDirections;
// probabilities of skipping or mapping to a key for each point.

54
native/jni/src/proximity_info_state_utils.cpp
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@ -225,13 +225,13 @@ namespace latinime {
const int lastSavedInputSize, const float verticalSweetSpotScale,
const std::vector<int> *const sampledInputXs,
const std::vector<int> *const sampledInputYs,
std::vector<NearKeycodesSet> *SampledNearKeySets,
std::vector<float> *SampledDistanceCache_G) {
SampledNearKeySets->resize(sampledInputSize);
std::vector<NearKeycodesSet> *sampledNearKeySets,
std::vector<float> *sampledNormalizedSquaredLengthCache) {
sampledNearKeySets->resize(sampledInputSize);
const int keyCount = proximityInfo->getKeyCount();
SampledDistanceCache_G->resize(sampledInputSize * keyCount);
sampledNormalizedSquaredLengthCache->resize(sampledInputSize * keyCount);
for (int i = lastSavedInputSize; i < sampledInputSize; ++i) {
(*SampledNearKeySets)[i].reset();
(*sampledNearKeySets)[i].reset();
for (int k = 0; k < keyCount; ++k) {
const int index = i * keyCount + k;
const int x = (*sampledInputXs)[i];
@ -239,10 +239,10 @@ namespace latinime {
const float normalizedSquaredDistance =
proximityInfo->getNormalizedSquaredDistanceFromCenterFloatG(
k, x, y, verticalSweetSpotScale);
(*SampledDistanceCache_G)[index] = normalizedSquaredDistance;
(*sampledNormalizedSquaredLengthCache)[index] = normalizedSquaredDistance;
if (normalizedSquaredDistance
< ProximityInfoParams::NEAR_KEY_NORMALIZED_SQUARED_THRESHOLD) {
(*SampledNearKeySets)[i][k] = true;
(*sampledNearKeySets)[i][k] = true;
}
}
}
@ -642,11 +642,11 @@ namespace latinime {
// This function basically converts from a length to an edit distance. Accordingly, it's obviously
// wrong to compare with mMaxPointToKeyLength.
/* static */ float ProximityInfoStateUtils::getPointToKeyByIdLength(const float maxPointToKeyLength,
const std::vector<float> *const SampledDistanceCache_G, const int keyCount,
const std::vector<float> *const sampledNormalizedSquaredLengthCache, const int keyCount,
const int inputIndex, const int keyId) {
if (keyId != NOT_AN_INDEX) {
const int index = inputIndex * keyCount + keyId;
return min((*SampledDistanceCache_G)[index], maxPointToKeyLength);
return min((*sampledNormalizedSquaredLengthCache)[index], maxPointToKeyLength);
}
// If the char is not a key on the keyboard then return the max length.
return static_cast<float>(MAX_VALUE_FOR_WEIGHTING);
@ -660,8 +660,8 @@ namespace latinime {
const std::vector<int> *const sampledInputYs,
const std::vector<float> *const sampledSpeedRates,
const std::vector<int> *const sampledLengthCache,
const std::vector<float> *const SampledDistanceCache_G,
std::vector<NearKeycodesSet> *SampledNearKeySets,
const std::vector<float> *const sampledNormalizedSquaredLengthCache,
std::vector<NearKeycodesSet> *sampledNearKeySets,
std::vector<hash_map_compat<int, float> > *charProbabilities) {
charProbabilities->resize(sampledInputSize);
// Calculates probabilities of using a point as a correlated point with the character
@ -677,9 +677,9 @@ namespace latinime {
float nearestKeyDistance = static_cast<float>(MAX_VALUE_FOR_WEIGHTING);
for (int j = 0; j < keyCount; ++j) {
if ((*SampledNearKeySets)[i].test(j)) {
if ((*sampledNearKeySets)[i].test(j)) {
const float distance = getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i, j);
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount, i, j);
if (distance < nearestKeyDistance) {
nearestKeyDistance = distance;
}
@ -758,14 +758,15 @@ namespace latinime {
// Summing up probability densities of all near keys.
float sumOfProbabilityDensities = 0.0f;
for (int j = 0; j < keyCount; ++j) {
if ((*SampledNearKeySets)[i].test(j)) {
if ((*sampledNearKeySets)[i].test(j)) {
float distance = sqrtf(getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i, j));
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount, i, j));
if (i == 0 && i != sampledInputSize - 1) {
// For the first point, weighted average of distances from first point and the
// next point to the key is used as a point to key distance.
const float nextDistance = sqrtf(getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i + 1, j));
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
i + 1, j));
if (nextDistance < distance) {
// The distance of the first point tends to bigger than continuing
// points because the first touch by the user can be sloppy.
@ -779,7 +780,8 @@ namespace latinime {
// For the first point, weighted average of distances from last point and
// the previous point to the key is used as a point to key distance.
const float previousDistance = sqrtf(getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i - 1, j));
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
i - 1, j));
if (previousDistance < distance) {
// The distance of the last point tends to bigger than continuing points
// because the last touch by the user can be sloppy. So we promote the
@ -798,14 +800,15 @@ namespace latinime {
// Split the probability of an input point to keys that are close to the input point.
for (int j = 0; j < keyCount; ++j) {
if ((*SampledNearKeySets)[i].test(j)) {
if ((*sampledNearKeySets)[i].test(j)) {
float distance = sqrtf(getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i, j));
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount, i, j));
if (i == 0 && i != sampledInputSize - 1) {
// For the first point, weighted average of distances from the first point and
// the next point to the key is used as a point to key distance.
const float prevDistance = sqrtf(getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i + 1, j));
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
i + 1, j));
if (prevDistance < distance) {
distance = (distance
+ prevDistance * ProximityInfoParams::NEXT_DISTANCE_WEIGHT)
@ -815,7 +818,8 @@ namespace latinime {
// For the first point, weighted average of distances from last point and
// the previous point to the key is used as a point to key distance.
const float prevDistance = sqrtf(getPointToKeyByIdLength(
maxPointToKeyLength, SampledDistanceCache_G, keyCount, i - 1, j));
maxPointToKeyLength, sampledNormalizedSquaredLengthCache, keyCount,
i - 1, j));
if (prevDistance < distance) {
distance = (distance
+ prevDistance * ProximityInfoParams::PREV_DISTANCE_WEIGHT)
@ -882,10 +886,10 @@ namespace latinime {
for (int j = 0; j < keyCount; ++j) {
hash_map_compat<int, float>::iterator it = (*charProbabilities)[i].find(j);
if (it == (*charProbabilities)[i].end()){
(*SampledNearKeySets)[i].reset(j);
(*sampledNearKeySets)[i].reset(j);
} else if(it->second < ProximityInfoParams::MIN_PROBABILITY) {
// Erases from near keys vector because it has very low probability.
(*SampledNearKeySets)[i].reset(j);
(*sampledNearKeySets)[i].reset(j);
(*charProbabilities)[i].erase(j);
} else {
it->second = -logf(it->second);
@ -899,7 +903,7 @@ namespace latinime {
const ProximityInfo *const proximityInfo, const int sampledInputSize,
const int lastSavedInputSize,
const std::vector<int> *const sampledLengthCache,
const std::vector<NearKeycodesSet> *const SampledNearKeySets,
const std::vector<NearKeycodesSet> *const sampledNearKeySets,
std::vector<NearKeycodesSet> *sampledSearchKeySets,
std::vector<std::vector<int> > *sampledSearchKeyVectors) {
sampledSearchKeySets->resize(sampledInputSize);
@ -916,7 +920,7 @@ namespace latinime {
if ((*sampledLengthCache)[j] - (*sampledLengthCache)[i] >= readForwordLength) {
break;
}
(*sampledSearchKeySets)[i] |= (*SampledNearKeySets)[j];
(*sampledSearchKeySets)[i] |= (*sampledNearKeySets)[j];
}
}
const int keyCount = proximityInfo->getKeyCount();

12
native/jni/src/proximity_info_state_utils.h
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@ -71,25 +71,25 @@ class ProximityInfoStateUtils {
const std::vector<int> *const sampledInputYs,
const std::vector<float> *const sampledSpeedRates,
const std::vector<int> *const sampledLengthCache,
const std::vector<float> *const SampledDistanceCache_G,
std::vector<NearKeycodesSet> *SampledNearKeySets,
const std::vector<float> *const sampledNormalizedSquaredLengthCache,
std::vector<NearKeycodesSet> *sampledNearKeySets,
std::vector<hash_map_compat<int, float> > *charProbabilities);
static void updateSampledSearchKeySets(const ProximityInfo *const proximityInfo,
const int sampledInputSize, const int lastSavedInputSize,
const std::vector<int> *const sampledLengthCache,
const std::vector<NearKeycodesSet> *const SampledNearKeySets,
const std::vector<NearKeycodesSet> *const sampledNearKeySets,
std::vector<NearKeycodesSet> *sampledSearchKeySets,
std::vector<std::vector<int> > *sampledSearchKeyVectors);
static float getPointToKeyByIdLength(const float maxPointToKeyLength,
const std::vector<float> *const SampledDistanceCache_G, const int keyCount,
const std::vector<float> *const sampledNormalizedSquaredLengthCache, const int keyCount,
const int inputIndex, const int keyId);
static void initGeometricDistanceInfos(const ProximityInfo *const proximityInfo,
const int sampledInputSize, const int lastSavedInputSize,
const float verticalSweetSpotScale,
const std::vector<int> *const sampledInputXs,
const std::vector<int> *const sampledInputYs,
std::vector<NearKeycodesSet> *SampledNearKeySets,
std::vector<float> *SampledDistanceCache_G);
std::vector<NearKeycodesSet> *sampledNearKeySets,
std::vector<float> *sampledNormalizedSquaredLengthCache);
static void initPrimaryInputWord(const int inputSize, const int *const inputProximities,
int *primaryInputWord);
static void initNormalizedSquaredDistances(const ProximityInfo *const proximityInfo,

4
native/jni/src/suggest/core/session/dic_traverse_session.h
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@ -146,6 +146,10 @@ class DicTraverseSession {
return true;
}
bool isTouchPositionCorrectionEnabled() const {
return mProximityInfoStates[0].touchPositionCorrectionEnabled();
}
private:
DISALLOW_IMPLICIT_CONSTRUCTORS(DicTraverseSession);
// threshold to start caching

11
native/jni/src/suggest/policyimpl/typing/typing_weighting.h
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@ -18,6 +18,7 @@
#define LATINIME_TYPING_WEIGHTING_H
#include "defines.h"
#include "suggest_utils.h"
#include "suggest/core/dicnode/dic_node_utils.h"
#include "suggest/core/policy/weighting.h"
#include "suggest/core/session/dic_traverse_session.h"
@ -70,10 +71,12 @@ class TypingWeighting : public Weighting {
const int pointIndex = dicNode->getInputIndex(0);
// Note: min() required since length can be MAX_POINT_TO_KEY_LENGTH for characters not on
// the keyboard (like accented letters)
const float length = min(ScoringParams::MAX_SPATIAL_DISTANCE,
traverseSession->getProximityInfoState(0)->getPointToKeyLength(
pointIndex, dicNode->getNodeCodePoint()));
const float weightedDistance = length * ScoringParams::DISTANCE_WEIGHT_LENGTH;
const float normalizedSquaredLength = traverseSession->getProximityInfoState(0)
->getPointToKeyLength(pointIndex, dicNode->getNodeCodePoint());
const float normalizedDistance = SuggestUtils::getSweetSpotFactor(
traverseSession->isTouchPositionCorrectionEnabled(), normalizedSquaredLength);
const float weightedDistance = ScoringParams::DISTANCE_WEIGHT_LENGTH * normalizedDistance;
const bool isFirstChar = pointIndex == 0;
const bool isProximity = isProximityDicNode(traverseSession, dicNode);
const float cost = isProximity ? (isFirstChar ? ScoringParams::FIRST_PROXIMITY_COST

39
native/jni/src/suggest_utils.h
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@ -23,10 +23,8 @@
namespace latinime {
class SuggestUtils {
public:
static float getDistanceScalingFactor(const float normalizedSquaredDistance) {
if (normalizedSquaredDistance < 0.0f) {
return -1.0f;
}
// TODO: (OLD) Remove
static float getLengthScalingFactor(const float normalizedSquaredDistance) {
// Promote or demote the score according to the distance from the sweet spot
static const float A = ZERO_DISTANCE_PROMOTION_RATE / 100.0f;
static const float B = 1.0f;
@ -50,6 +48,39 @@ class SuggestUtils {
return factor;
}
static float getSweetSpotFactor(const bool isTouchPositionCorrectionEnabled,
const float normalizedSquaredDistance) {
// Promote or demote the score according to the distance from the sweet spot
static const float A = 0.0f;
static const float B = 0.24f;
static const float C = 1.20f;
static const float R0 = 0.0f;
static const float R1 = 0.25f; // Sweet spot
static const float R2 = 1.0f;
const float x = normalizedSquaredDistance;
if (!isTouchPositionCorrectionEnabled) {
return min(C, x);
}
// factor is a piecewise linear function like:
// C -------------.
// / .
// B / .
// -/ .
// A _-^ .
// .
// R0 R1 R2 .
if (x < R0) {
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);
};