GoldenCheetah/src/WPrime.cpp

/*
 * Copyright (c) 2013 Mark Liversedge (liversedge@gmail.com)
 *
 * This program is free software; you can redistribute it and/or modify it
 * under the terms of the GNU General Public License as published by the Free
 * Software Foundation; either version 2 of the License, or (at your option)
 * any later version.
 *
 * This program is distributed in the hope that it will be useful, but WITHOUT
 * ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
 * FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for
 * more details.
 *
 * You should have received a copy of the GNU General Public License along
 * with this program; if not, write to the Free Software Foundation, Inc., 51
 * Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA
 */

// Many thanks for the gracious support from Dr Philip Skiba for this
// component. Not only did Dr Phil happily agree for us to re-use his
// research, but also provided information and guidance to assist in the
// implementation.
//
// This code implements the W replenishment / utilisation algorithm
// as defined in "Modeling the Expenditure and Reconstitution of Work Capacity 
// above Critical Power." Med Sci Sports Exerc 2012;:1.
//
// The actual code is derived from an MS Office Excel spreadsheet shared
// privately to assist in the development of the code.
// 
// There is definitely room form a performance improvement from anyone
// with a greater math expertise than this developer. I suspect that is
// most!
//

#include "WPrime.h"

const double WprimeMultConst = -1.0;
const double WprimeDecayConst = 336;
const int WprimeDecayPeriod = 1200; // 1200 seconds or 20 minutes
const double E = 2.71828183;

inline double decaySchedule(double sec) { return pow(E, -(sec/WprimeDecayConst)); }

WPrime::WPrime()
{
    // XXX will need to reset metrics when they are added
    minY = maxY = 0;
}

void
WPrime::setRide(RideFile *input)
{
    QTime time; // for profiling performance of the code
    time.start();

    // remember the ride for next time
    rideFile = input;

    // no data or no power data then forget it.
    if (!input || input->dataPoints().count() == 0 || input->areDataPresent()->watts == false) {
        values.resize(0); // the memory is kept for next time so this is efficient
        xvalues.resize(0);

        //XXX will need to reset metrics when they are added
        minY = maxY = 0;
        //qDebug()<<"now work to do"<<time.elapsed();
        return;
    }

    // STEP 1: CONVERT POWER DATA TO A 1 SECOND TIME SERIES

    // create a raw time series in the format QwtSpline wants
    QVector<QPointF> points;
    int last=0;
    foreach(RideFilePoint *p, input->dataPoints()) {
        points << QPointF(p->secs, p->watts);
        last = p->secs;
    }

    // Create a spline
    QwtSpline smoothed;
    smoothed.setSplineType(QwtSpline::Natural);
    smoothed.setPoints(QPolygonF(points));

    // Get CP
    int CP = 250; // default
    if (input->context->athlete->zones()) {
        int zoneRange = input->context->athlete->zones()->whichRange(input->startTime().date());
        CP = zoneRange >= 0 ? input->context->athlete->zones()->getCP(zoneRange) : 0;
    }

    // since we will be running up and down the data series multiple times
    // as we iterate and run a SUMPRODUCT it is best to extract the data
    // into a vector of ints for the watts above CP
    QVector<int> inputArray(last+1);
    for (int i=0; i<last; i++) {

        int value = smoothed.value(i);
        inputArray[i] = value > CP ? value-CP : 0;
    }

    //qDebug()<<"data preparation took"<<time.elapsed();

    // STEP 2: ITERATE OVER DATA TO CREATE W' DATA SERIES

    // wipe away whatever is there
    minY = maxY = 0;
    values.resize(last+1);
    xvalues.resize(last+1);
    for(int i=last; i>=0; i--) {

        // used by AllPlot to plot the curve, we might as well
        // create it here whilst we're iterating. But bear in mind
        // that its in minutes, a bit of a legacy that one.
        xvalues[i] = double(i)/60.00f;

        // W' is a SUMPRODUCT of the previous 1200 samples
        // of power over CP * the associated decay factor * the mult factor
        // it will be zero for first 20 minutes

        double sumproduct = 0;
        for (int j=0; j<1200 && (i-j) > 0; j++) {
            sumproduct += inputArray.at(i-j) * pow(E, -(j/WprimeDecayConst)); 
        }
        values[i] = sumproduct * WprimeMultConst;

        // min / max
        if (values[i] < minY) minY = values[i];
        if (values[i] > maxY) maxY = values[i];
    }

    // STEP 3: CALCULATE METRICS XXX when they are added

    //qDebug()<<values;
    //qDebug()<<"completed"<<time.elapsed();
}

//
// Associated Metrics
//

class MinWPrime : public RideMetric {
    Q_DECLARE_TR_FUNCTIONS(WPrimeMin)

    public:

    MinWPrime()
    {
        setSymbol("skiba_wprime_low");
        setInternalName("Minimum W'");
    }
    void initialize() {
        setName(tr("Minimum W'"));
        setType(RideMetric::Low);
        setMetricUnits(tr("Kj"));
        setImperialUnits(tr("Kj"));
        setPrecision(1);
    }
    void compute(const RideFile *r, const Zones *, int,
                 const HrZones *, int,
                 const QHash<QString,RideMetric*> &,
                 const Context *) {

        WPrime w;
        w.setRide((RideFile*)r);
        setValue(w.minY/1000.00f);
    }

    bool canAggregate() { return false; }
    RideMetric *clone() const { return new MinWPrime(*this); }
};

#if 0 // NEEDS OPTIMISING -- DISABLED UNTIL ISSUE RESOLVED
// add to catalogue
static bool addMetrics() {
    RideMetricFactory::instance().addMetric(MinWPrime());
    return true;
}

static bool added = addMetrics();
#endif