private double[] FullMatrix(double t, double[] y, double[] yK, double[] f)
{
var jacobian = new double[N + 1, N + 1]; // f'(Xn)
jacobian[0, 0] = jacobian[N, N] = 1;
for (int n = 1; n < N; n++)
{
double l = equation.dK_du(x[n], t, y[n]) * (yK[n - 1] - yK[n + 1]) / (2 * h * h);
double r = equation.K(x[n], t, y[n]) / (h * h);
jacobian[n, n - 1] = l + r;
jacobian[n, n + 1] = -l + r;
jacobian[n, n] = -2 * r - 1 / tau;
f[n] *= betaCalculator.Multiplier;
}
f[0] *= betaCalculator.Multiplier;
f[N] *= betaCalculator.Multiplier;
return(ResolvingSystem.Gauss(jacobian, f));
}
private double[] MakeAndSolveSystem(double t, double[] y, double[] yK, double[] f)
{
var a = new double[N + 1];
var c = new double[N + 1];
var b = new double[N + 1];
c[0] = c[N] = 1;
for (int n = 1; n < N; n++)
{
double l = equation.dK_du(x[n], t, y[n]) * (yK[n - 1] - yK[n + 1]) / (2 * h * h);
double r = equation.K(x[n], t, y[n]) / (h * h);
a[n - 1] = l + r; // or a[n],b[n]?
b[n - 1] = -l + r;
c[n] = -2 * r - 1 / tau;
f[n] *= betaCalculator.Multiplier;
}
f[0] *= betaCalculator.Multiplier;
f[N] *= betaCalculator.Multiplier;
return(ResolvingSystem.TridiagonalMatrixAlgorithm(a, c, b, f));
}
private double[] ReqularizedMethod(double t, double[] y, double[] yK, double[] f)
{
double alphaBetaNorm = settings.Alpha * betaCalculator.Beta * Norm;
var jacobian = new double[N + 1, N + 1]; // f'(Xn)
jacobian[0, 0] = jacobian[N, N] = 1;
for (int n = 1; n < N; n++)
{
double l = equation.dK_du(x[n], t, y[n]) * (yK[n - 1] - yK[n + 1]) / (2 * h * h);
double r = equation.K(x[n], t, y[n]) / (h * h);
jacobian[n, n - 1] = l + r;
jacobian[n, n + 1] = -l + r;
jacobian[n, n] = -2 * r - 1 / tau;
}
var a = jacobian.Transpose();
a = a.AddDiag(alphaBetaNorm);
var matrix = a.Multiply(jacobian).AddDiag(alphaBetaNorm);
var freeMembers = a.Multiply(f).MultiplyConst(betaCalculator.Multiplier);
return(ResolvingSystem.Gauss(matrix, freeMembers));
}
