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GoldenCheetah/src/WPrime.cpp
Mark Liversedge 89017fe2a5 Stress Metric Prototypes 
Added a few new training stress metrics whilst discussing
and working on a multicomponent view of training stress.

This is all a wip falling out of discussions around stress
metrics beyond the old TSS/BikeScore models.

For now this just includes;
1. Aerobic Training Impact Scoring System on PM/PMC
2. Work (Kj) above/below CP on PM/PMC
3. Aerobic TISS on the Ride Plot

There is lots more to come; specifically around Anaerobic TISS,
looking again at polarised training and personalised training stress
based upon the individual's CP model.
2014-03-17 20:51:57 +00:00

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/*
* 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.
//
// To optimise the original implementation that computed the integral at
// each point t as a function of the preceding power above CP at time u through t
// we did 2 things;
//
// 1. compute the exp decay for each poweer above CP and integrate the decay
// into the future -- but crucially, no need to bother if power above CP is 0.
// This typically reduces the cpu cycles by a factor of 4
//
// 2. Because the decay is calculated forward at time u we can do these in paralle;
// i.e. run multiple threads for t=0 through t=time/nthreads. This reduced the
// elapsed time by a factor of about 2/3rds on a dual core processor.
//
// We could extend the threading to have more than 2 threads on PCs with more cores
// but this would conflict with the ridefilecache computations anyway.
//
// There may be room for improvement by adopting a different integration strategy
// in the future, but now, a typical 4 hour hilly ride can be computed in 250ms on
// and Athlon dual core CPU where previously it took 4000ms.
#include "WPrime.h"
const double WprimeMultConst = 1.0;
const int WPrimeDecayPeriod = 3600; // 1 hour, tried infinite but costly and limited value
// on long rides anyway
const double E = 2.71828183;
const int WprimeMatchSmoothing = 25; // 25 sec smoothing looking for matches
const int WprimeMatchMinJoules = 100;
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;
// reset from previous
values.resize(0); // the memory is kept for next time so this is efficient
xvalues.resize(0);
EXP = PCP_ = CP = WPRIME = TAU=0;
// no data or no power data then forget it.
if (!input || input->dataPoints().count() == 0 || input->areDataPresent()->watts == false) {
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;
last=0;
double offset = 0; // always start from zero seconds (e.g. intervals start at and offset in ride)
bool first = true;
if (input->recIntSecs() >= 1) {
RideFilePoint *lp=NULL;
foreach(RideFilePoint *p, input->dataPoints()) {
// yuck! nasty data
if (p->secs > (25*60*60)) return;
if (first) {
offset = p->secs;
first = false;
}
// fill gaps in recording with zeroes
if (lp)
for(int t=lp->secs+input->recIntSecs();
(t + input->recIntSecs()) < p->secs;
t += input->recIntSecs())
points << QPointF(t-offset, 0);
// lets not go backwards -- or two sampls at the same time
if ((lp && p->secs > lp->secs) || !lp)
points << QPointF(p->secs - offset, p->watts);
// update state
last = p->secs - offset;
lp = p;
}
} else {
foreach(RideFilePoint *p, input->dataPoints()) {
// yuck! nasty data
if (p->secs > (25*60*60)) return;
if (first) {
offset = p->secs;
first = false;
}
points << QPointF(p->secs - offset, p->watts);
last = p->secs - offset;
}
}
// Create a spline
smoothed.setSplineType(QwtSpline::Natural);
smoothed.setPoints(QPolygonF(points));
// Get CP
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;
WPRIME = zoneRange >= 0 ? input->context->athlete->zones()->getWprime(zoneRange) : 0;
// did we override CP in metadata / metrics ?
int oCP = input->getTag("CP","0").toInt();
if (oCP) CP=oCP;
}
minY = maxY = WPRIME;
// input array contains the actual W' expenditure
// and will also contain non-zero values
double totalBelowCP=0;
double countBelowCP=0;
QVector<int> inputArray(last+1);
EXP = 0;
for (int i=0; i<last; i++) {
int value = smoothed.value(i);
inputArray[i] = value > CP ? value-CP : 0;
if (value < CP) {
totalBelowCP += value;
countBelowCP++;
} else EXP += value; // total expenditure above CP
}
if (countBelowCP > 0)
TAU = 546.00f * pow(E,-0.01*(CP - (totalBelowCP/countBelowCP))) + 316.00f;
else
TAU = 546.00f * pow(E,-0.01*(CP)) + 316.00f;
TAU = int(TAU); // round it down
// STEP 2: ITERATE OVER DATA TO CREATE W' DATA SERIES
// lets run forward from 0s to end of ride
minY = WPRIME;
maxY = WPRIME;
values.resize(last+1);
xvalues.resize(last+1);
QVector<double> myvalues(last+1);
int stop = last / 2;
WPrimeIntegrator a(inputArray, 0, stop, TAU);
WPrimeIntegrator b(inputArray, stop+1, last, TAU);
a.start();
b.start();
a.wait();
b.wait();
// sum values
for (int t=0; t<=last; t++) {
values[t] = a.output[t] + b.output[t];
xvalues[t] = double(t) / 60.00f;
}
// now subtract WPRIME and work out minimum etc
for(int t=0; t <= last; t++) {
double value = WPRIME - values[t];
values[t] = value;
if (value > maxY) maxY = value;
if (value < minY) minY = value;
}
//qDebug()<<"compute W'bal curve took"<<time.elapsed();
// STEP 3: FIND MATCHES
// SMOOTH DATA SERIES
// get raw data adjusted to 1s intervals (as before)
QVector<int> smoothArray(last+1);
QVector<int> rawArray(last+1);
for (int i=0; i<last; i++) {
smoothArray[i] = smoothed.value(i);
rawArray[i] = smoothed.value(i);
}
// initialise rolling average
double rtot = 0;
for (int i=WprimeMatchSmoothing; i>0 && last-i >=0; i--) {
rtot += smoothArray[last-i];
}
// now run backwards setting the rolling average
for (int i=last; i>=WprimeMatchSmoothing; i--) {
int here = smoothArray[i];
smoothArray[i] = rtot / WprimeMatchSmoothing;
rtot -= here;
rtot += smoothArray[i-WprimeMatchSmoothing];
}
// FIND MATCHES -- INTERVALS WHERE POWER > CP
// AND W' DEPLETED BY > WprimeMatchMinJoules
bool inmatch=false;
matches.clear();
mvalues.clear();
mxvalues.clear();
for(int i=0; i<last; i++) {
Match match;
if (!inmatch && (smoothArray[i] >= CP || rawArray[i] >= CP)) {
inmatch=true;
match.start=i;
}
if (inmatch && (smoothArray[i] < CP && rawArray[i] < CP)) {
// lets work backwards as we're at the end
// we only care about raw data to avoid smoothing
// artefacts
int end=i-1;
while (end > match.start && rawArray[end] < CP) {
end--;
}
if (end > match.start) {
match.stop = end;
match.secs = (match.stop-match.start) +1; // don't fencepost!
match.cost = values[match.start] - values[match.stop];
if (match.cost >= WprimeMatchMinJoules) {
matches << match;
}
}
inmatch=false;
}
}
// SET MATCH SERIES FOR ALLPLOT CHART
foreach (struct Match match, matches) {
// we only count 1kj asa match
if (match.cost >= 2000) { //XXX need to agree how to define a match -- or even if we want to...
mvalues << values[match.start];
mxvalues << xvalues[match.start];
mvalues << values[match.stop];
mxvalues << xvalues[match.stop];
}
}
}
void
WPrime::setErg(ErgFile *input)
{
QTime time; // for profiling performance of the code
time.start();
// reset from previous
values.resize(0); // the memory is kept for next time so this is efficient
xvalues.resize(0);
EXP = PCP_ = 0;
// Get CP
CP = 250; // defaults
WPRIME = 20000;
CP=250;
TAU=545;
if (input->context->athlete->zones()) {
int zoneRange = input->context->athlete->zones()->whichRange(QDate::currentDate());
CP = zoneRange >= 0 ? input->context->athlete->zones()->getCP(zoneRange) : 250;
WPRIME = zoneRange >= 0 ? input->context->athlete->zones()->getWprime(zoneRange) : 20000;
}
// no data or no power data then forget it.
bool bydist = (input->format == CRS) ? true : false;
if (!input->isValid() || bydist) {
return; // needs to be a valid erg file...
}
minY = maxY = WPRIME;
last = input->Duration / 1000;
// input array contains the actual W' expenditure
// and will also contain non-zero values
double totalBelowCP=0;
double countBelowCP=0;
QVector<int> inputArray(last+1);
EXP = 0;
for (int i=0; i<last; i++) {
// get watts at point in time
int lap;
int value = input->wattsAt(i*1000, lap);
inputArray[i] = value > CP ? value-CP : 0;
if (value < CP) {
totalBelowCP += value;
countBelowCP++;
} else EXP += value; // total expenditure above CP
}
// STEP 2: ITERATE OVER DATA TO CREATE W' DATA SERIES
// lets run forward from 0s to end of ride
minY = WPRIME;
maxY = WPRIME;
values.resize(last+1);
xvalues.resize(last+1);
QVector<double> myvalues(last+1);
int stop = last / 2;
WPrimeIntegrator a(inputArray, 0, stop, TAU);
WPrimeIntegrator b(inputArray, stop+1, last, TAU);
a.start();
b.start();
a.wait();
b.wait();
// sum values
for (int t=0; t<=last; t++) {
values[t] = a.output[t] + b.output[t];
xvalues[t] = t * 1000;
}
// now subtract WPRIME and work out minimum etc
for(int t=0; t <= last; t++) {
double value = WPRIME - values[t];
values[t] = value;
if (value > maxY) maxY = value;
if (value < minY) minY = value;
}
// STEP 3: FIND MATCHES
// SMOOTH DATA SERIES
// get raw data adjusted to 1s intervals (as before)
QVector<int> smoothArray(last+1);
QVector<int> rawArray(last+1);
for (int i=0; i<last; i++) {
smoothArray[i] = smoothed.value(i);
rawArray[i] = smoothed.value(i);
}
// initialise rolling average
double rtot = 0;
for (int i=WprimeMatchSmoothing; i>0 && last-i >=0; i--) {
rtot += smoothArray[last-i];
}
// now run backwards setting the rolling average
for (int i=last; i>=WprimeMatchSmoothing; i--) {
int here = smoothArray[i];
smoothArray[i] = rtot / WprimeMatchSmoothing;
rtot -= here;
rtot += smoothArray[i-WprimeMatchSmoothing];
}
// FIND MATCHES -- INTERVALS WHERE POWER > CP
// AND W' DEPLETED BY > WprimeMatchMinJoules
bool inmatch=false;
matches.clear();
mvalues.clear();
mxvalues.clear();
for(int i=0; i<last; i++) {
Match match;
if (!inmatch && (smoothArray[i] >= CP || rawArray[i] >= CP)) {
inmatch=true;
match.start=i;
}
if (inmatch && (smoothArray[i] < CP && rawArray[i] < CP)) {
// lets work backwards as we're at the end
// we only care about raw data to avoid smoothing
// artefacts
int end=i-1;
while (end > match.start && rawArray[end] < CP) {
end--;
}
if (end > match.start) {
match.stop = end;
match.secs = (match.stop-match.start) +1; // don't fencepost!
match.cost = values[match.start] - values[match.stop];
if (match.cost >= WprimeMatchMinJoules) {
matches << match;
}
}
inmatch=false;
}
}
// SET MATCH SERIES FOR ALLPLOT CHART
foreach (struct Match match, matches) {
// we only count 1kj asa match
if (match.cost >= 2000) { //XXX need to agree how to define a match -- or even if we want to...
mvalues << values[match.start];
mxvalues << xvalues[match.start];
mvalues << values[match.stop];
mxvalues << xvalues[match.stop];
}
}
}
double
WPrime::PCP()
{
if (PCP_) return PCP_;
// check WPRIME is correct otherwise we will run forever!
// if its way off don't even try!
if (minY < -10000 || WPRIME < 10000) return PCP_ = 0; // Wprime not set properly
int cp = CP;
do {
if (minForCP(cp) > 0) return PCP_=cp;
else cp += 3; // +/- 3w is ok, especially since +/- 2kJ is typical accuracy for W' anyway
} while (cp <= 500);
return PCP_=cp;
}
int
WPrime::minForCP(int cp)
{
QTime time; // for profiling performance of the code
time.start();
// input array contains the actual W' expenditure
// and will also contain non-zero values
double tau;
double totalBelowCP=0;
double countBelowCP=0;
QVector<int> inputArray(last+1);
for (int i=0; i<last; i++) {
int value = smoothed.value(i);
inputArray[i] = value > cp ? value-cp : 0;
if (value < cp) {
totalBelowCP += value;
countBelowCP++;
}
}
if (countBelowCP > 0)
tau = 546.00f * pow(E,-0.01*(CP - (totalBelowCP/countBelowCP))) + 316.00f;
else
tau = 546.00f * pow(E,-0.01*(CP)) + 316.00f;
tau = int(tau); // round it down
// STEP 2: ITERATE OVER DATA TO CREATE W' DATA SERIES
// lets run forward from 0s to end of ride
int min = WPRIME;
QVector<double> myvalues(last+1);
int stop = last / 2;
WPrimeIntegrator a(inputArray, 0, stop, tau);
WPrimeIntegrator b(inputArray, stop+1, last, tau);
a.start();
b.start();
a.wait();
b.wait();
// sum values
for (int t=0; t<=last; t++)
myvalues[t] = a.output[t] + b.output[t];
// now subtract WPRIME and work out minimum etc
for(int t=0; t <= last; t++) {
double value = WPRIME - myvalues[t];
if (value < min) min = value;
}
//qDebug()<<"compute time="<<time.elapsed();
return min;
}
double
WPrime::maxMatch()
{
double max=0;
foreach(struct Match match, matches)
if (match.cost > max) max = match.cost;
return max;
}
// decay and integrate -- split into threads for
// best performance
WPrimeIntegrator::WPrimeIntegrator(QVector<int> &source, int begin, int end, double TAU) :
source(source), begin(begin), end(end), TAU(TAU)
{
output.resize(source.size());
}
void
WPrimeIntegrator::run()
{
// run from start to stop adding decay to end
for (int t=begin; t<end; t++) {
if (source[t] <= 0) continue;
for (int i=0; i < WPrimeDecayPeriod && t+i < source.size(); i++) {
double value = source[t] * pow(E, -(double(i)/TAU));
// integrate
output[t+i] += value;
}
}
}
//
// Associated Metrics
//
class MinWPrime : public RideMetric {
Q_DECLARE_TR_FUNCTIONS(MinWPrime);
public:
MinWPrime()
{
setSymbol("skiba_wprime_low");
setInternalName("Minimum W'bal");
}
void initialize() {
setName(tr("Minimum W' bal"));
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 *) {
setValue(const_cast<RideFile*>(r)->wprimeData()->minY / 1000.00f);
}
bool canAggregate() { return false; }
RideMetric *clone() const { return new MinWPrime(*this); }
};
class MaxWPrime : public RideMetric {
Q_DECLARE_TR_FUNCTIONS(MaxWPrime);
public:
MaxWPrime()
{
setSymbol("skiba_wprime_max"); // its expressing min W'bal as as percentage of WPrime
setInternalName("Max W' Expended");
}
void initialize() {
setName(tr("Max W' Expended"));
setType(RideMetric::Peak);
setMetricUnits(tr("%"));
setImperialUnits(tr("%"));
setPrecision(0);
}
void compute(const RideFile *r, const Zones *, int,
const HrZones *, int,
const QHash<QString,RideMetric*> &,
const Context *) {
setValue(const_cast<RideFile*>(r)->wprimeData()->maxE());
}
bool canAggregate() { return false; }
RideMetric *clone() const { return new MaxWPrime(*this); }
};
class MaxMatch : public RideMetric {
Q_DECLARE_TR_FUNCTIONS(MaxMatch);
public:
MaxMatch()
{
setSymbol("skiba_wprime_maxmatch");
setInternalName("Maximum W'bal Match");
}
void initialize() {
setName(tr("Maximum W'bal Match"));
setType(RideMetric::Peak);
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 *) {
setValue(const_cast<RideFile*>(r)->wprimeData()->maxMatch()/1000.00f);
}
bool canAggregate() { return false; }
RideMetric *clone() const { return new MaxMatch(*this); }
};
class WPrimeTau : public RideMetric {
Q_DECLARE_TR_FUNCTIONS(WPrimeTau);
public:
WPrimeTau()
{
setSymbol("skiba_wprime_tau");
setInternalName("W'bal TAU");
}
void initialize() {
setName(tr("W'bal TAU"));
setType(RideMetric::Low);
setMetricUnits(tr(""));
setImperialUnits(tr(""));
setPrecision(0);
}
void compute(const RideFile *r, const Zones *, int,
const HrZones *, int,
const QHash<QString,RideMetric*> &,
const Context *) {
setValue(const_cast<RideFile*>(r)->wprimeData()->TAU);
}
bool canAggregate() { return false; }
RideMetric *clone() const { return new WPrimeTau(*this); }
};
class WPrimeExp : public RideMetric {
Q_DECLARE_TR_FUNCTIONS(WPrimeExp);
public:
WPrimeExp()
{
setSymbol("skiba_wprime_exp");
setInternalName("W' Work");
}
void initialize() {
setName(tr("W' Work"));
setType(RideMetric::Total);
setMetricUnits(tr("kJ"));
setImperialUnits(tr("kJ"));
setPrecision(0);
}
void compute(const RideFile *r, const Zones *zones, int zonerange,
const HrZones *, int,
const QHash<QString,RideMetric*> &,
const Context *) {
int cp = r->getTag("CP","0").toInt();
if (!cp && zones && zonerange >=0) cp = zones->getCP(zonerange);
double total = 0;
double secs = 0;
foreach(const RideFilePoint *point, r->dataPoints()) {
if (cp && point->watts > cp) total += r->recIntSecs() * point->watts;
secs += r->recIntSecs();
}
setValue(total/1000.00f);
setCount(secs);
}
bool canAggregate() { return false; }
RideMetric *clone() const { return new WPrimeExp(*this); }
};
class CPExp : public RideMetric {
Q_DECLARE_TR_FUNCTIONS(CPExp);
public:
CPExp()
{
setSymbol("skiba_cp_exp");
setInternalName("Below CP Work");
}
void initialize() {
setName(tr("Below CP Work"));
setType(RideMetric::Total);
setMetricUnits(tr("kJ"));
setImperialUnits(tr("kJ"));
setPrecision(0);
}
void compute(const RideFile *r, const Zones *zones, int zonerange,
const HrZones *, int,
const QHash<QString,RideMetric*> &,
const Context *) {
int cp = r->getTag("CP","0").toInt();
if (!cp && zones && zonerange >=0) cp = zones->getCP(zonerange);
double total = 0;
double secs = 0;
foreach(const RideFilePoint *point, r->dataPoints()) {
if (cp && point->watts <= cp) total += r->recIntSecs() * point->watts;
secs += r->recIntSecs();
}
setValue(total/1000.00f);
setCount(secs);
}
bool canAggregate() { return false; }
RideMetric *clone() const { return new CPExp(*this); }
};
// add to catalogue
static bool addMetrics() {
RideMetricFactory::instance().addMetric(MinWPrime());
RideMetricFactory::instance().addMetric(MaxWPrime()); // same thing expressed as a maximum
RideMetricFactory::instance().addMetric(MaxMatch());
RideMetricFactory::instance().addMetric(WPrimeTau());
RideMetricFactory::instance().addMetric(WPrimeExp());
RideMetricFactory::instance().addMetric(CPExp());
return true;
}
static bool added = addMetrics();
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