public DIPMethod(Matrix a, Matrix b, double eps, FunctionVector func)
{
this.a = a;
this.a = b;
this.eps = eps;
functions = new FunctionVector(func);
}
public SvenMethod(Matrix x0, FunctionVector func)
{
c = x0;
h = new Matrix(c.N, c.M);
h[0][0] = 3;
functions = new FunctionVector(func);
}
public void ExecuteFunctionsCastTest()
{
functionsMask[] f = new functionsMask[8];
f[0] = (Matrix x) => { return(x[0][0]); };
f[1] = (Matrix x) => { return(x[0][1]); };
f[2] = (Matrix x) => { return(x[0][2]); };
f[3] = (Matrix x) => { return(x[0][3]); };
f[4] = (Matrix x) => { return(x[0][4]); };
f[5] = (Matrix x) => { return(x[0][5]); };
f[6] = (Matrix x) => { return(x[0][6]); };
f[7] = (Matrix x) => { return(x[0][7]); };
Matrix arg = new Matrix(1, f.Length);
for (int i = 0; i < f.Length; i++)
{
arg[0][i] = i;
}
FunctionVector functionVector = new FunctionVector(f);
Vector res = functionVector.ExecuteFunctions(arg);
for (int i = 0; i < f.Length; i++)
{
Assert.AreEqual(res[i], i);
}
}
public SquereInterpolationMethod(Matrix a, Matrix b, double eps, FunctionVector func)
{
this.a = a;
this.a = b;
U = (a + b) / 2;
this.eps = eps;
functions = new FunctionVector(func);
}
public void DelegateIntoFuncCastTest()
{
functionsMask[] f = new functionsMask[1];
f[0] = (Matrix x) => { return(x[0][0]); };
FunctionVector functionVector = new FunctionVector(f);
}
public StepAdaptationMethod(Matrix x0, Matrix h, double Eps, FunctionVector func)
{
x = x0;
this.Eps = Eps;
bool IsColumn = h.M == 1;
int ZerosCount = 0;
if (x.M != h.M || x.N != h.M)
{
throw new ArgumentException("Размер вектора аргументов и " +
"вектора шага должны быть одинаковы");
}
if (IsColumn)
{
for (int i = 0; i < h.M; i++)
{
if (h[1][i] != 0)
{
break;
}
else
{
ZerosCount++;
}
}
if (ZerosCount == h.M)
{
throw new ArgumentException("Шаг должен быть не нулевым.");
}
}
else
{
for (int i = 0; i < h.N; i++)
{
if (h[i][1] != 0)
{
break;
}
else
{
ZerosCount++;
}
}
if (ZerosCount == h.N)
{
throw new ArgumentException("Шаг должен быть не нулевым.");
}
}
this.h = (Matrix)h.Clone();
functions = new FunctionVector(func);
}
public DIPMethod(Matrix x0, double eps, FunctionVector func)
{
SvenMethod sv = new SvenMethod(x0, func);
sv.Start();
Dictionary <string, Matrix> borderPoints = sv.BorderPoints;
a = borderPoints["a"];
b = borderPoints["b"];
this.eps = eps;
functions = new FunctionVector(func);
}
public SquereInterpolationMethod(Matrix x0, FunctionVector func)
{
SvenMethod sv = new SvenMethod(x0, func);
sv.Start();
Dictionary <string, Matrix> borderPoints = sv.BorderPoints;
a = borderPoints["a"];
U = borderPoints["c"];
b = borderPoints["b"];
eps = 0.001;
functions = new FunctionVector(func);
}
public StepAdaptationMethod(Matrix x0, FunctionVector func)
{
x = x0;
int len = x.M == 1 ? x.N : x.M;
h = new Matrix(1, len);
for (int i = 0; i < len; i++)
{
h[0][i] = 4;
}
functions = new FunctionVector(func);
}
public SvenMethod(Matrix x0, Matrix h, FunctionVector func)
{
c = x0;
this.h = h;
functions = new FunctionVector(func);
}
public Huk_DjivsMethod(Matrix x0, double eps, FunctionVector func)
{
x = x0;
this.eps = eps;
functions = new FunctionVector(func);
}
public Huk_DjivsMethod(Matrix x0, FunctionVector func)
{
x = x0;
functions = new FunctionVector(func);
}
public NewtonMethod(Matrix x0, double Eps, FunctionVector func)
{
x = x0;
this.Eps = Eps;
functions = new FunctionVector(func);
}
public NewtonMethod(Matrix x0, FunctionVector func)
{
x = x0;
Eps = 0.001;
functions = new FunctionVector(func);
}
public SteepestDescendMethod(Matrix x0, double Eps, FunctionVector func)
{
x = x0;
this.Eps = Eps;
functions = new FunctionVector(func);
}
public SteepestDescendMethod(Matrix x0, FunctionVector func)
{
x = x0;
Eps = 0.001;
functions = new FunctionVector(func);
}
