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      1 /*
      2 **
      3 ** Copyright 2014, The Android Open Source Project
      4 **
      5 ** Licensed under the Apache License, Version 2.0 (the "License");
      6 ** you may not use this file except in compliance with the License.
      7 ** You may obtain a copy of the License at
      8 **
      9 **     http://www.apache.org/licenses/LICENSE-2.0
     10 **
     11 ** Unless required by applicable law or agreed to in writing, software
     12 ** distributed under the License is distributed on an "AS IS" BASIS,
     13 ** WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     14 ** See the License for the specific language governing permissions and
     15 ** limitations under the License.
     16 */
     17 
     18 #ifndef CLOCK_ESTIMATOR_H_
     19 
     20 #define CLOCK_ESTIMATOR_H_
     21 
     22 
     23 #include <utils/RefBase.h>
     24 #include <utils/Vector.h>
     25 
     26 namespace android {
     27 // ---------------------------------------------------------------------------
     28 
     29 struct ClockEstimator : RefBase {
     30     virtual double estimate(double x, double y) = 0;
     31     virtual void reset() = 0;
     32 };
     33 
     34 struct WindowedLinearFitEstimator : ClockEstimator {
     35     struct LinearFit {
     36         /**
     37          * Fit y = a * x + b, where each input has a weight
     38          */
     39         double mX;  // sum(w_i * x_i)
     40         double mXX; // sum(w_i * x_i^2)
     41         double mY;  // sum(w_i * y_i)
     42         double mYY; // sum(w_i * y_i^2)
     43         double mXY; // sum(w_i * x_i * y_i)
     44         double mW;  // sum(w_i)
     45 
     46         LinearFit();
     47         void reset();
     48         void combine(const LinearFit &lf);
     49         void add(double x, double y, double w);
     50         void scale(double w);
     51         double interpolate(double x);
     52         double size() const;
     53 
     54         DISALLOW_EVIL_CONSTRUCTORS(LinearFit);
     55     };
     56 
     57     /**
     58      * Estimator for f(x) = y' where input y' is noisy, but
     59      * theoretically linear:
     60      *
     61      *      y' =~ y = a * x + b
     62      *
     63      * It uses linear fit regression over a tapering rolling window
     64      * to get an estimate for y (from the current and past inputs
     65      * (x, y')).
     66      *
     67      *     ____________
     68      *    /|          |\
     69      *   / |          | \
     70      *  /  |          |  \   <--- new data (x, y')
     71      * /   |   main   |   \
     72      * <--><----------><-->
     73      * tail            head
     74      *
     75      * weight is 1 under the main window, tapers exponentially by
     76      * the factors given in the head and the tail.
     77      *
     78      * Assuming that x and y' are monotonic, that x is somewhat
     79      * evenly sampled, and that a =~ 1, the estimated y is also
     80      * going to be monotonic.
     81      */
     82     WindowedLinearFitEstimator(
     83             size_t headLength = 5, double headFactor = 0.5,
     84             size_t mainLength = 0, double tailFactor = 0.99);
     85 
     86     virtual void reset();
     87 
     88     // add a new sample (x -> y') and return an estimated value for the true y
     89     virtual double estimate(double x, double y);
     90 
     91 private:
     92     Vector<double> mXHistory; // circular buffer
     93     Vector<double> mYHistory; // circular buffer
     94     LinearFit mHead;
     95     LinearFit mMain;
     96     LinearFit mTail;
     97     double mHeadFactorInv;
     98     double mTailFactor;
     99     double mFirstWeight;
    100     size_t mHistoryLength;
    101     size_t mHeadLength;
    102     size_t mNumSamples;
    103     size_t mSampleIx;
    104 
    105     DISALLOW_EVIL_CONSTRUCTORS(WindowedLinearFitEstimator);
    106 };
    107 
    108 }; // namespace android
    109 
    110 #endif
    111