public void CalculateNormalizedPower_With_No_Samples_Returns_Zero()
{
var samples = new WorkoutSamples(0);
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(samples,athlete);
var average = workoutCalculator.GetNormalizedPower();
Assert.Equal(0, average);
}
public void CalculateNonZero_Average_With_No_Data_Returns_Zero()
{
var samples = new WorkoutSamples(0);
var vector = new WorkoutSampleVector(3, WorkoutSampleDataType.Power);
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(samples, athlete);
var average = workoutCalculator.CalculateNonZeroVectorAverage(vector);
Assert.Equal(0, average);
}
public void CalculatCadenceClassificatoion_Under_2_Samples_returns_()
{
var samples = new WorkoutSamples(0);
var vector = new WorkoutSampleVector(1, WorkoutSampleDataType.Cadence);
vector.AddPoint(1, 2);
samples.CadenceVector = vector;
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(samples, athlete);
var classification = workoutCalculator.ClassifyWorkoutCadenceRanges();
Assert.IsType<List<ICadenceRange>>(classification);
}
public void CalculateNormalizedPower_With_Under_30_Samples_Returns_Average()
{
//Initialise();
var samples = new WorkoutSamples(0);
var vector = new WorkoutSampleVector(2, WorkoutSampleDataType.Power);
vector.AddPoint(1, 2);
vector.AddPoint(2, 4);
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(samples, athlete);
var average = workoutCalculator.CalculateVectorNormalizedAverage(vector);
Assert.Equal(3, average);
}
public void CalculateNonZero_Average_Returns_Average()
{
var samples = new WorkoutSamples(0);
var vector = new WorkoutSampleVector(3, WorkoutSampleDataType.Power);
vector.AddPoint(1, 2);
vector.AddPoint(2, 4);
vector.AddPoint(3, 0);
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(samples,athlete);
var average = workoutCalculator.CalculateNonZeroVectorAverage(vector);
Assert.Equal(3, average);
}
public static IWorkout MapExtendedCycleWorkout(pwx pwx, IWorkout shortWorkout)
{
pwxWorkout pwxWo = pwx.workout[0];
IAthlete athlete = new Athlete();
athlete.FTBikePower = 231;
shortWorkout.TrainingStressScore = pwxWo.summarydata.tss;
ICycleWorkout cycleWorkout = shortWorkout as ICycleWorkout;
if (cycleWorkout == null)
return shortWorkout;
PWXDataExtractor dataExtractor = new PWXDataExtractor(pwx);
var workoutSamples = dataExtractor.ExtractData();
WorkoutSamplesCalculator calc = new WorkoutSamplesCalculator(workoutSamples, athlete);
cycleWorkout.IntensityFactor = calc.CalcualteIntensityFactor();
cycleWorkout.NormalizedPower = (int)calc.GetNormalizedPower();
return shortWorkout;
}
public void CalculateVectorAverage_With_No_Samples_Returns_Zero()
{
var samples = new WorkoutSamples(0);
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(samples, athlete);
var average = workoutCalculator.GetAverageCadence();
Assert.Equal(0, average);
}
public void Test_Workout_Energy_System_Classiication_with_Power()
{
Initialise();
var data = new PWXDataExtractor(_test);
var samples = data.ExtractData();
IAthlete athlete = new Athlete();
var calc = new WorkoutSamplesCalculator(samples, athlete);
var systems = calc.ClassifyWorkoutPowerRanges(240);
Assert.IsType<List<IEnergySystemRange>> (systems);
}
public void TestPowerBasedTrainingStressScoreCalculation()
{
Initialise();
var calc = new PWXDataExtractor(_test);
var workoutSample = calc.ExtractData();
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(workoutSample, athlete);
var summaryTSS = _test.workout[0].summarydata.tss;
var roundedTPTSS = Math.Round(summaryTSS, 0);
var myTSSCalc = workoutCalculator.Calculate_Power_TrainingStressScore(272);
var roundedMyTSS = Math.Round(myTSSCalc, 0);
Assert.Equal(roundedTPTSS, roundedMyTSS);
}
public void TestNormalizedPower()
{
Initialise();
var calc = new PWXDataExtractor(_test);
var workoutSample = calc.ExtractData();
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(workoutSample, athlete);
var myPowerAverage = workoutCalculator.GetNormalizedPower();
Assert.Equal(231, myPowerAverage);
}
public void TestIntensityFactor()
{
Initialise();
var calc = new PWXDataExtractor(_test);
var workoutSample = calc.ExtractData();
IAthlete athlete = new Athlete();
athlete.FTBikePower = 240;
var workoutCalculator = new WorkoutSamplesCalculator(workoutSample,athlete);
var intensityFactor = workoutCalculator.CalcualteIntensityFactor();
Assert.Equal(0.96, intensityFactor);
}
public void TestCadenceClassification()
{
var pwx =
GetPwxDataFromXml(
GetSamplePwxFile(@"c:\dev\autocoach\testxmldata\TestTurboPowerCyclePZoneClassificationPWX.xml"));
var dataExtractor = new PWXDataExtractor(pwx);
var workoutSample = dataExtractor.ExtractData();
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(workoutSample,athlete);
var buckets = workoutCalculator.ClassifyWorkoutCadenceRanges();
Assert.IsType<List<ICadenceRange>>(buckets);
Assert.Equal(1, buckets[0].QuanityOfSamples);
Assert.Equal(14, buckets[0].PercentOfTotal);
Assert.Equal(3, buckets[1].QuanityOfSamples);
Assert.Equal(43, buckets[1].PercentOfTotal);
Assert.Equal(0, buckets[2].QuanityOfSamples);
Assert.Equal(0, buckets[2].PercentOfTotal);
Assert.Equal(2, buckets[3].QuanityOfSamples);
Assert.Equal(29, buckets[3].PercentOfTotal);
Assert.Equal(1, buckets[4].QuanityOfSamples);
Assert.Equal(14, buckets[4].PercentOfTotal);
}
public void TestAverageSpeed()
{
Initialise();
var calc = new PWXDataExtractor(_test);
var workoutSample = calc.ExtractData();
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(workoutSample,athlete);
var mySpdAverage = workoutCalculator.GetAverageSpeed();
// double pwxSummaryAvgHR = _test.workout[0].summarydata.spd.avg;
mySpdAverage = Math.Round(mySpdAverage);
//Assert.Equal(mySpdAverage, pwxSummaryAvgHR);
}
public void TestAveragePower()
{
Initialise();
var calc = new PWXDataExtractor(_test);
var workoutSample = calc.ExtractData();
IAthlete athlete = new Athlete();
var workoutCalculator = new WorkoutSamplesCalculator(workoutSample,athlete);
var myPowerAverage = workoutCalculator.GetAveragePower();
var pwxSummaryPowerAverage = _test.workout[0].summarydata.pwr.avg;
myPowerAverage = Math.Round(myPowerAverage);
Assert.Equal(pwxSummaryPowerAverage, myPowerAverage);
}
public Athlete SetupFakeAthlete(string username, string password, TrainingPeaksAthleteAccountTypes accountType)
{
var athlete = new Athlete
{
TPData = new TrainingPeaksAthleteData
{
LoginName = username,
LoginPassword = password,
AccountType = accountType
}
};
return athlete;
}
