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.incallui.answer.impl.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 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 35 public HistoryEvaluator() { 36 mLastUpdate = SystemClock.elapsedRealtime(); 37 } 38 39 public void addStroke(float evaluation) { 40 decayValue(); 41 mStrokes.add(new Data(evaluation)); 42 } 43 44 public void addGesture(float evaluation) { 45 decayValue(); 46 mGestureWeights.add(new Data(evaluation)); 47 } 48 49 /** Calculates the weighted average of strokes and adds to it the weighted average of gestures */ 50 public float getEvaluation() { 51 return weightedAverage(mStrokes) + weightedAverage(mGestureWeights); 52 } 53 54 private float weightedAverage(ArrayList<Data> list) { 55 float sumValue = 0.0f; 56 float sumWeight = 0.0f; 57 int size = list.size(); 58 for (int i = 0; i < size; i++) { 59 Data data = list.get(i); 60 sumValue += data.evaluation * data.weight; 61 sumWeight += data.weight; 62 } 63 64 if (sumWeight == 0.0f) { 65 return 0.0f; 66 } 67 68 return sumValue / sumWeight; 69 } 70 71 private void decayValue() { 72 long time = SystemClock.elapsedRealtime(); 73 74 if (time <= mLastUpdate) { 75 return; 76 } 77 78 // All weights are multiplied by HISTORY_FACTOR after each INTERVAL milliseconds. 79 float factor = (float) Math.pow(HISTORY_FACTOR, (time - mLastUpdate) / INTERVAL); 80 81 decayValue(mStrokes, factor); 82 decayValue(mGestureWeights, factor); 83 mLastUpdate = time; 84 } 85 86 private void decayValue(ArrayList<Data> list, float factor) { 87 int size = list.size(); 88 for (int i = 0; i < size; i++) { 89 list.get(i).weight *= factor; 90 } 91 92 // Removing evaluations with such small weights that they do not matter anymore 93 while (!list.isEmpty() && isZero(list.get(0).weight)) { 94 list.remove(0); 95 } 96 } 97 98 private boolean isZero(float x) { 99 return x <= EPSILON && x >= -EPSILON; 100 } 101 102 /** 103 * For each stroke it holds its initial value and the current weight. Initially the weight is set 104 * to 1.0 105 */ 106 private static class Data { 107 public float evaluation; 108 public float weight; 109 110 public Data(float evaluation) { 111 this.evaluation = evaluation; 112 weight = 1.0f; 113 } 114 } 115 } 116
