1 /* 2 * Copyright (C) 2015 The Android Open Source Project 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License 15 */ 16 17 package com.android.systemui.classifier; 18 19 import android.os.SystemClock; 20 21 import java.util.ArrayList; 22 23 /** 24 * Holds the evaluations for ended strokes and gestures. These values are decreased through time. 25 */ 26 public class HistoryEvaluator { 27 private static final float INTERVAL = 50.0f; 28 private static final float HISTORY_FACTOR = 0.9f; 29 private static final float EPSILON = 1e-5f; 30 31 private final ArrayList<Data> mStrokes = new ArrayList<>(); 32 private final ArrayList<Data> mGestureWeights = new ArrayList<>(); 33 private long mLastUpdate; 34 HistoryEvaluator()35 public HistoryEvaluator() { 36 mLastUpdate = SystemClock.elapsedRealtime(); 37 } 38 addStroke(float evaluation)39 public void addStroke(float evaluation) { 40 decayValue(); 41 mStrokes.add(new Data(evaluation)); 42 } 43 addGesture(float evaluation)44 public void addGesture(float evaluation) { 45 decayValue(); 46 mGestureWeights.add(new Data(evaluation)); 47 } 48 49 /** 50 * Calculates the weighted average of strokes and adds to it the weighted average of gestures 51 */ getEvaluation()52 public float getEvaluation() { 53 return weightedAverage(mStrokes) + weightedAverage(mGestureWeights); 54 } 55 weightedAverage(ArrayList<Data> list)56 private float weightedAverage(ArrayList<Data> list) { 57 float sumValue = 0.0f; 58 float sumWeight = 0.0f; 59 int size = list.size(); 60 for (int i = 0; i < size; i++) { 61 Data data = list.get(i); 62 sumValue += data.evaluation * data.weight; 63 sumWeight += data.weight; 64 } 65 66 if (sumWeight == 0.0f) { 67 return 0.0f; 68 } 69 70 return sumValue / sumWeight; 71 } 72 decayValue()73 private void decayValue() { 74 long time = SystemClock.elapsedRealtime(); 75 76 if (time <= mLastUpdate) { 77 return; 78 } 79 80 // All weights are multiplied by HISTORY_FACTOR after each INTERVAL milliseconds. 81 float factor = (float) Math.pow(HISTORY_FACTOR, (time - mLastUpdate) / INTERVAL); 82 83 decayValue(mStrokes, factor); 84 decayValue(mGestureWeights, factor); 85 mLastUpdate = time; 86 } 87 decayValue(ArrayList<Data> list, float factor)88 private void decayValue(ArrayList<Data> list, float factor) { 89 int size = list.size(); 90 for (int i = 0; i < size; i++) { 91 list.get(i).weight *= factor; 92 } 93 94 // Removing evaluations with such small weights that they do not matter anymore 95 while (!list.isEmpty() && isZero(list.get(0).weight)) { 96 list.remove(0); 97 } 98 } 99 isZero(float x)100 private boolean isZero(float x) { 101 return x <= EPSILON && x >= -EPSILON; 102 } 103 104 /** 105 * For each stroke it holds its initial value and the current weight. Initially the 106 * weight is set to 1.0 107 */ 108 private static class Data { 109 public float evaluation; 110 public float weight; 111 Data(float evaluation)112 public Data(float evaluation) { 113 this.evaluation = evaluation; 114 weight = 1.0f; 115 } 116 } 117 } 118