本文整理汇总了C#中DenseVector.Subtract方法的典型用法代码示例。如果您正苦于以下问题：C# DenseVector.Subtract方法的具体用法？C# DenseVector.Subtract怎么用？C# DenseVector.Subtract使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类DenseVector的用法示例。
在下文中一共展示了DenseVector.Subtract方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: Solve
//.........这里部分代码省略.........
// Define the temporary scalars
float beta = 0;
float sigma;
// Define the temporary vectors
// rDash_0 = r_0
Vector rdash = new DenseVector(residuals);
// t_-1 = 0
Vector t = new DenseVector(residuals.Count);
Vector t0 = new DenseVector(residuals.Count);
// w_-1 = 0
Vector w = new DenseVector(residuals.Count);
// Define the remaining temporary vectors
Vector c = new DenseVector(residuals.Count);
Vector p = new DenseVector(residuals.Count);
Vector s = new DenseVector(residuals.Count);
Vector u = new DenseVector(residuals.Count);
Vector y = new DenseVector(residuals.Count);
Vector z = new DenseVector(residuals.Count);
Vector temp = new DenseVector(residuals.Count);
Vector temp2 = new DenseVector(residuals.Count);
Vector temp3 = new DenseVector(residuals.Count);
// for (k = 0, 1, .... )
var iterationNumber = 0;
while (ShouldContinue(iterationNumber, xtemp, input, residuals))
{
// p_k = r_k + beta_(k-1) * (p_(k-1) - u_(k-1))
p.Subtract(u, temp);
temp.Multiply(beta, temp2);
residuals.Add(temp2, p);
// Solve M b_k = p_k
_preconditioner.Approximate(p, temp);
// s_k = A b_k
matrix.Multiply(temp, s);
// alpha_k = (r*_0 * r_k) / (r*_0 * s_k)
var alpha = rdash.DotProduct(residuals) / rdash.DotProduct(s);
// y_k = t_(k-1) - r_k - alpha_k * w_(k-1) + alpha_k s_k
s.Subtract(w, temp);
t.Subtract(residuals, y);
temp.Multiply(alpha, temp2);
y.Add(temp2, temp3);
temp3.CopyTo(y);
// Store the old value of t in t0
t.CopyTo(t0);
// t_k = r_k - alpha_k s_k
s.Multiply(-alpha, temp2);
residuals.Add(temp2, t);
// Solve M d_k = t_k
_preconditioner.Approximate(t, temp);
// c_k = A d_k示例2: Initialize
//.........这里部分代码省略.........
// {
// w(j) = w(j) / a(j,j)
// if (w(j) < dropTol)
// {
// w(j) = 0;
// }
// if (w(j) != 0)
// {
// w = w - w(j) * U(j,*)
// }
if (workVector[j] != 0.0)
{
// Calculate the multiplication factors that go into the L matrix
workVector[j] = workVector[j] / _upper[j, j];
if (workVector[j].Magnitude < _dropTolerance)
{
workVector[j] = 0.0;
}
// Calculate the addition factor
if (workVector[j] != 0.0)
{
// vector update all in one go
_upper.Row(j, rowVector);
// zero out columnVector[k] because we don't need that
// one anymore for k = 0 to k = j
for (var k = 0; k <= j; k++)
{
rowVector[k] = 0.0;
}
rowVector.Multiply(workVector[j], rowVector);
workVector.Subtract(rowVector, workVector);
}
}
}
// for j = i, .. ,n
for (var j = i; j < sparseMatrix.RowCount; j++)
{
// if w(j) <= dropTol * ||A(i,*)||
// {
// w(j) = 0
// }
if (workVector[j].Magnitude <= _dropTolerance * vectorNorm.Real)
{
workVector[j] = 0.0;
}
}
// spaceRow = spaceLeft / (n - i + 1) // Determine the space for this row
var spaceRow = spaceLeft / (sparseMatrix.RowCount - i + 1);
// lfil = spaceRow / 2 // space for this row of L
var fillLevel = spaceRow / 2;
FindLargestItems(0, i - 1, indexSorting, workVector);
// l(i,j) = w(j) for j = 1, .. , i -1 // only the largest lfil elements
var lowerNonZeroCount = 0;
var count = 0;
for (var j = 0; j < i; j++)
{
if ((count > fillLevel) || (indexSorting[j] == -1))
{
break;示例3: Solve
//.........这里部分代码省略.........
}
beta = rho * c[k - 1];
if (beta.Real.AlmostEqual(0, 1) && beta.Imaginary.AlmostEqual(0, 1))
{
throw new Exception("Iterative solver experience a numerical break down");
}
// beta^(jk+i)_((j-1)k+k) = -(q^T_1 (r_(jk+1) + rho_(j+1) z_w)) / (rho_(j+1) c_((j-1)k+k))
zw.Multiply(rho, temp2);
residuals.Add(temp2, temp);
beta = -_startingVectors[0].DotProduct(temp) / beta;
// z_g = z_g + beta^(jk+i)_((j-1)k+k) g_((j-1)k+k)
g[k - 1].Multiply(beta, temp);
zg.Add(temp, temp2);
temp2.CopyTo(zg);
// z_w = rho_(j+1) (z_w + beta^(jk+i)_((j-1)k+k) w_((j-1)k+k))
w[k - 1].Multiply(beta, temp);
zw.Add(temp, temp2);
temp2.CopyTo(zw);
zw.Multiply(rho, zw);
// z_d = r_(jk+i) + z_w
residuals.Add(zw, zd);
// FOR (s = 1, ... i - 1)
for (var s = 0; s < i - 1; s++)
{
// beta^(jk+i)_(jk+s) = -q^T_s+1 z_d / c_(jk+s)
beta = -_startingVectors[s + 1].DotProduct(zd) / c[s];
// z_d = z_d + beta^(jk+i)_(jk+s) * d_(jk+s)
d[s].Multiply(beta, temp);
zd.Add(temp, temp2);
temp2.CopyTo(zd);
// z_g = z_g + beta^(jk+i)_(jk+s) * g_(jk+s)
g[s].Multiply(beta, temp);
zg.Add(temp, temp2);
temp2.CopyTo(zg);
}
// d_(jk+i) = z_d - u_(jk+i)
zd.Subtract(u, d[i]);
// g_(jk+i) = z_g + z_w
zg.Add(zw, g[i]);
// IF (i < k - 1)
if (i < k - 1)
{
// c_(jk+1) = q^T_i+1 d_(jk+i)
c[i] = _startingVectors[i + 1].DotProduct(d[i]);
if (c[i].Real.AlmostEqual(0, 1) && c[i].Imaginary.AlmostEqual(0, 1))
{
throw new Exception("Iterative solver experience a numerical break down");
}
// alpha_(jk+i+1) = q^T_(i+1) u_(jk+i) / c_(jk+i)
alpha = _startingVectors[i + 1].DotProduct(u) / c[i];
// u_(jk+i+1) = u_(jk+i) - alpha_(jk+i+1) d_(jk+i)
d[i].Multiply(-alpha, temp);
u.Add(temp, temp2);
temp2.CopyTo(u);
// SOLVE M g~_(jk+i) = g_(jk+i)
_preconditioner.Approximate(g[i], gtemp);
// x_(jk+i+1) = x_(jk+i) + rho_(j+1) alpha_(jk+i+1) g~_(jk+i)
gtemp.Multiply(rho * alpha, temp);
xtemp.Add(temp, temp2);
temp2.CopyTo(xtemp);
// w_(jk+i) = A g~_(jk+i)
matrix.Multiply(gtemp, w[i]);
// r_(jk+i+1) = r_(jk+i) - rho_(j+1) alpha_(jk+i+1) w_(jk+i)
w[i].Multiply(-rho * alpha, temp);
residuals.Add(temp, temp2);
temp2.CopyTo(residuals);
// We can check the residuals here if they're close
if (!ShouldContinue(iterationNumber, xtemp, input, residuals))
{
// Recalculate the residuals and go round again. This is done to ensure that
// we have the proper residuals.
CalculateTrueResidual(matrix, residuals, xtemp, input);
}
}
} // END ITERATION OVER i
iterationNumber++;
}
// copy the temporary result to the real result vector
xtemp.CopyTo(result);
}