/// <summary>
/// Вычисление градиента только для ядра гаусса
/// </summary>
/// <param name="distribution"></param>
public static double Grad(IDistribution distribution, GaussianKernal kernal)
{
double min = distribution.GetSampling().Min();
double max = distribution.GetSampling().Max();
double x0 = new Random().Next((int)min, (int)max);
double xi = x0;
double step = 0.0;
double YMin = kernal.getDerivative(xi);
double xNext = xi - EPSSILON * kernal.getDerivative(xi);
while (kernal.getDerivative(xNext) - kernal.getDerivative(xi) > C)
{
step = xi - EPSSILON * kernal.getDerivative(xi) + xi;
YMin = kernal.getDerivative(xi);
xi = xNext;
xNext = xi + step;
}
return YMin;
}
private void button1_Click(object sender, EventArgs e)
{
switch (_currentTab)
{
case 0:
{
//пока яд.ф тестирую только на гнормальном
double mx = Double.Parse(mxTextBox.Text.Trim().Replace('.', ','));
double dx = Double.Parse(dxTextBox.Text.Trim().Replace('.', ','));
_samplingLenght = Int32.Parse(samplingLengthTextBox.Text.Trim());
GausianDistribution d = new GausianDistribution(mx, dx, _samplingLenght);
EpanichnikovKernal epan = new EpanichnikovKernal(d);
GaussianKernal g = new GaussianKernal(d);
Triangular tr = new Triangular(d);
_presenter.OnSetDistribution(d,tr);
_intervalsCount = Int32.Parse(intervalsLengthTextBox.Text.Trim());
_presenter.OnGetBarChart(_intervalsCount);/*отправили в модель*/
_FP = mx;
_SP = dx;
break;
}
case 1:
{
double alpha = Double.Parse(alphaTetxBox.Text.Trim().Replace('.', ','));
double beta = Double.Parse(betaTextBox.Text.Trim().Replace('.', ','));
_samplingLenght = Int32.Parse(AmountVibTextBox.Text.Trim().Replace('.', ','));
VibrullDistribution vib = new VibrullDistribution(alpha, beta, _samplingLenght);
GaussianKernal gk = new GaussianKernal(vib);
_presenter.OnSetDistribution(vib,gk);
_intervalsCount = Int32.Parse(VIntervalsLenghtTextBox.Text.Trim());
_presenter.OnGetBarChart(_intervalsCount);
_FP = alpha;
_SP = beta;
break;
}
case 2:
{
double inten = Double.Parse(IntenTextBox.Text.Trim().Replace('.', ','));
_samplingLenght = Int32.Parse(ExponAmountSapmlingTextBox.Text.Trim());
ExponentialDistribution expon = new ExponentialDistribution(inten, _samplingLenght);
GaussianKernal gk = new GaussianKernal(expon);
_presenter.OnSetDistribution(expon, gk);
_intervalsCount = Int32.Parse(ExpAmoubtIntervalsTextBox.Text.Trim());
_presenter.OnGetBarChart(_intervalsCount);
_FP = inten;
_SP = 0;
break;
}
case 3:
{
double mu = Double.Parse(MutextBox.Text.Trim().Replace('.', ','));
double lambda = Convert.ToDouble(LambdatextBox.Text.Trim().Replace('.', ','));
_samplingLenght = Int32.Parse(VtextBox.Text.Trim());
LaplasDistribution laplas = new LaplasDistribution(mu, lambda, _samplingLenght);
GaussianKernal gk = new GaussianKernal(laplas);
_presenter.OnSetDistribution(laplas, gk);
_intervalsCount = Int32.Parse(LAmountTextBox.Text.Trim());
_presenter.OnGetBarChart(_intervalsCount);
_FP = mu;
_SP = lambda;
break;
}
case 4:
{
double a = Double.Parse(aUniformTextBox.Text.Trim().Replace('.', ','));
double b = Double.Parse(bUniformTextBox.Text.Trim().Replace('.', ','));
_samplingLenght = Int32.Parse(USLenghtTextBox.Text.Trim());
UniformDistributions uniforn = new UniformDistributions(a, b, _samplingLenght);
GaussianKernal gk = new GaussianKernal(uniforn);
_presenter.OnSetDistribution(uniforn, gk);
_intervalsCount = Int32.Parse(CoolIntUniform.Text.Trim());
_presenter.OnGetBarChart(_intervalsCount);
_FP = a;
_SP = b;
break;
}
case 5:
{
//double aC = Double.Parse(aCTextBox.Text.Trim().Replace('.', ','));
//double muC = Double.Parse(muCTextBox.Text.Trim().Replace('.', ','));
//_samplingLenght = Int32.Parse(VCTextBox.Text.Trim());
//CauchyDistribution c = new CauchyDistribution(aC, muC, _samplingLenght);
//GaussianKernal gk = new GaussianKernal(c);
//_presenter.OnSetDistribution(c,gk);
//_intervalsCount = Int32.Parse(CCTextBox.Text.Trim());
//_presenter.OnGetBarChart(_intervalsCount);
//_FP = aC;
//_SP = muC;
break;
}
}
}