public void solveModel()
{
int n = 5;
IElementalAccessMatrix A = new SparseRowMatrix(n, n, 5);
IElementalAccessVector b = new DenseVector(n), x = new DenseVector(n);
x.SetValue(0, 0.1);
x.SetValue(1, 0.2);
x.SetValue(2, 0.3);
x.SetValue(3, 0.4);
x.SetValue(4, 0.5);
b = new DenseVector(x.Length);
for (int it = 0; it < 100; it++)
{
model(b, x);
grad(A, x);
IElementalAccessVector dx = new DenseVector(n);
ILinearSolver solver = new BiCGSolver();
IPreconditioner M = new IdentityPreconditioner();
DefaultLinearIteration iter = new DefaultLinearIteration();
iter.SetParameters(1e-10, 1e-50, 1e+5, 1000000);
double[] ans = solve(A, b, dx, solver, M, iter);
for (int i = 0; i < x.Length; i++)
{
x.AddValue(i, -0.2 * dx.GetValue(i));
}
int iii = 1;
}
}
private void grad(IElementalAccessMatrix dy, IElementalAccessVector x)
{
IElementalAccessVector y0 = new DenseVector(x.Length);
IElementalAccessVector y = new DenseVector(x.Length);
model(y0, x);
for (int i = 0; i < x.Length; i++)
{
x.AddValue(i, 0.000001);
model(y, x);
for (int j = 0; j < x.Length; j++)
{
dy.SetValue(j, i, (y.GetValue(j) - y0.GetValue(j)) / 0.000001);
}
x.AddValue(i, -0.000001);
}
}
