public void FitTest1()
{
double[] values =
{
0, 1, 2, 4, 2, 3, 5, 7, 4, 3, 2, 1, 4,
};
var exp = new ExponentialDistribution();
exp.Fit(values);
string actual;
var cultureInfo = CultureInfo.GetCultureInfo("fr-FR");
#if NETCORE
System.Globalization.CultureInfo.DefaultThreadCurrentCulture = cultureInfo;
System.Globalization.CultureInfo.DefaultThreadCurrentUICulture = cultureInfo;
#else
Thread.CurrentThread.CurrentCulture = cultureInfo;
#endif
actual = exp.ToString("G3", CultureInfo.InvariantCulture);
Assert.AreEqual("Exp(x; λ = 0.342)", actual);
actual = exp.ToString("G3");
Assert.AreEqual("Exp(x; λ = 0,342)", actual);
actual = exp.ToString(CultureInfo.InvariantCulture);
Assert.AreEqual("Exp(x; λ = 0.342105263157895)", actual);
actual = exp.ToString();
Assert.AreEqual("Exp(x; λ = 0,342105263157895)", actual);
}
public void FitTest1()
{
double[] values =
{
0, 1, 2, 4, 2, 3, 5, 7, 4, 3, 2, 1, 4,
};
var exp = new ExponentialDistribution();
exp.Fit(values);
string actual;
Thread.CurrentThread.CurrentCulture = CultureInfo.GetCultureInfo("fr-FR");
actual = exp.ToString("G3", CultureInfo.InvariantCulture);
Assert.AreEqual("Exp(x; λ = 0.342)", actual);
actual = exp.ToString("G3");
Assert.AreEqual("Exp(x; λ = 0,342)", actual);
actual = exp.ToString(CultureInfo.InvariantCulture);
Assert.AreEqual("Exp(x; λ = 0.342105263157895)", actual);
actual = exp.ToString();
Assert.AreEqual("Exp(x; λ = 0,342105263157895)", actual);
}
private UnivariateContinuousDistribution FitDistribution(double [] samples)
{
if (samples.Length < 10)
{
return(new EmpiricalDistribution(samples));
}
else
{
var exp = new ExponentialDistribution(); // new LognormalDistribution(); //
exp.Fit(samples);
return(exp);
}
}
public FuncionExponencial(double[] eventos) : base(eventos)
{
try
{
DistribucionContinua = new ExponentialDistribution();
DistribucionContinua.Fit(eventos);
this.L = ((ExponentialDistribution)DistribucionContinua).Rate.ToString("0.0000");
Resultado = new ResultadoAjuste(StringFDP, StringInversa, DistribucionContinua.StandardDeviation, DistribucionContinua.Mean, DistribucionContinua.Variance, this);
}
catch (Exception)
{
Resultado = null;
}
}
public void FitTest1()
{
double[] values =
{
0, 1, 2, 4, 2, 3, 5, 7, 4, 3, 2, 1, 4,
};
var exp = new ExponentialDistribution();
exp.Fit(values);
string actual;
Thread.CurrentThread.CurrentCulture = CultureInfo.GetCultureInfo("fr-FR");
actual = exp.ToString("G3", CultureInfo.InvariantCulture);
Assert.AreEqual("Exp(x; λ = 0.342)", actual);
actual = exp.ToString("G3");
Assert.AreEqual("Exp(x; λ = 0,342)", actual);
actual = exp.ToString(CultureInfo.InvariantCulture);
Assert.AreEqual("Exp(x; λ = 0.342105263157895)", actual);
actual = exp.ToString();
Assert.AreEqual("Exp(x; λ = 0,342105263157895)", actual);
}