public void CanCalculateMeanOfListInts()
{
Assert.AreEqual(5.5, MeanCalculator.Calculate <int> (new List <int> ()
{
1, 2, 3, 4, 5, 6, 7, 8, 9, 10
}));
}
public void ThrowsArgumentExceptionWhenListOfNonNumbersIsPassedInt()
{
MeanCalculator.Calculate <char> (new List <char> ()
{
'a', 'b'
});
}
//JAVA TO C# CONVERTER TODO TASK: Most Java annotations will not have direct .NET equivalent attributes:
//ORIGINAL LINE: @Test public void testDistribution()
public virtual void testDistribution()
{
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final java.util.function.Function<double[], double> meanCalculator = new com.opengamma.strata.math.impl.statistics.descriptive.MeanCalculator();
System.Func <double[], double> meanCalculator = new MeanCalculator();
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final java.util.function.Function<double[], double> medianCalculator = new com.opengamma.strata.math.impl.statistics.descriptive.MedianCalculator();
System.Func <double[], double> medianCalculator = new MedianCalculator();
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final java.util.function.Function<double[], double> varianceCalculator = new com.opengamma.strata.math.impl.statistics.descriptive.PopulationVarianceCalculator();
System.Func <double[], double> varianceCalculator = new PopulationVarianceCalculator();
const int n = 1000000;
const double eps = 0.1;
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double[] data = new double[n];
double[] data = new double[n];
for (int i = 0; i < n; i++)
{
data[i] = DIST.nextRandom();
}
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double mean = MU + SIGMA / (1 - KSI);
double mean = MU + SIGMA / (1 - KSI);
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double median = MU + SIGMA * (Math.pow(2, KSI) - 1) / KSI;
double median = MU + SIGMA * (Math.Pow(2, KSI) - 1) / KSI;
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final double variance = SIGMA * SIGMA / ((1 - KSI) * (1 - KSI) * (1 - 2 * KSI));
double variance = SIGMA * SIGMA / ((1 - KSI) * (1 - KSI) * (1 - 2 * KSI));
assertEquals(meanCalculator(data), mean, eps);
assertEquals(medianCalculator(data), median, eps);
assertEquals(varianceCalculator(data), variance, eps);
}
public void Test_AverageByMean_WithInterface()
{
Calculator calculator = new Calculator();
ICalculator meanCalculator = new MeanCalculator();
double expected = 8.3636363;
double actual = calculator.CalculateAverage(values, meanCalculator);
Assert.AreEqual(expected, actual, 0.000001);
}
public void CanCalculateMeanOfListDecimas()
{
var calc = MeanCalculator.Calculate <double>
(new List <double> ()
{
1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.9, 9.9
});
Assert.AreEqual(5.51, Math.Round(calc, 2));
}
private MeanCalculator record; //Reference to MeanCalculator.cs
//Start function is called at the beginning of a program run
void Start()
{
//Initialization
gameObject.name = "Car";
merging = false;
spd = gameObject.GetComponent <SpeedSearch>();
spd.enabled = true;
nextPos = pointNetwork.nextPos;
privateTimer = 0.0f;
globalTimer = GameObject.Find("Manager").GetComponent <Timer>();
record = GameObject.Find("Manager").GetComponent <MeanCalculator>();
carArray = GameObject.Find("Manager").GetComponent <CarArray>();
}
/// <summary>
/// Normalize x_i as x_i -> (x_i - mean)/(standard deviation) </summary>
/// <param name="xData"> X values of data </param>
/// <returns> Normalized X values </returns>
private double[] normaliseData(double[] xData)
{
int nData = xData.Length;
double[] res = new double[nData];
System.Func <double[], double> calculator = new MeanCalculator();
_renorm[0] = calculator(xData);
calculator = new SampleStandardDeviationCalculator();
_renorm[1] = calculator(xData);
double tmp = _renorm[0] / _renorm[1];
for (int i = 0; i < nData; ++i)
{
res[i] = xData[i] / _renorm[1] - tmp;
}
return(res);
}
public MeanCalculatorTest()
{
_meanCalculator = new MeanCalculator();
}
public void ThrowsArgumentExceptionWhenEmptyListIsPassedIn()
{
MeanCalculator.Calculate <int> (new List <int> ());
}
public void ThrowsArgumentNullExceptionWhenNullIsPassedIn()
{
MeanCalculator.Calculate <int> (null);
}
