本文整理汇总了C#中MathNet.Numerics.LinearAlgebra.Double.DenseVector.ToList方法的典型用法代码示例。如果您正苦于以下问题：C# DenseVector.ToList方法的具体用法？C# DenseVector.ToList怎么用？C# DenseVector.ToList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MathNet.Numerics.LinearAlgebra.Double.DenseVector的用法示例。
在下文中一共展示了DenseVector.ToList方法的2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: ModificatedDualIteration
private static bool ModificatedDualIteration()
{
var vectorCollection = new List<Vector<double>>();
foreach (var item in _task.Jb)
{
vectorCollection.Add(_task.A.Column(item));
}
var aBMatrix = DenseMatrix.OfColumnVectors(vectorCollection.ToArray());
var bMatrix = aBMatrix.Inverse();
// Step3
var kappaList = bMatrix * _task.b;
Vector<double> allKappaList = new DenseVector(_task.A.ColumnCount, 0);
for (int i = 0; i < allKappaList.Count; i++)
{
if (_JNbUpper.Contains(i))
{
allKappaList[i] = _task.dLower[i];
}
else if (_JNbLower.Contains(i))
{
allKappaList[i] = _task.dUpper[i];
}
else
{
allKappaList[i] = 0;
}
}
kappaList = bMatrix * (_task.b - _task.A * allKappaList);
for (int i = 0; i < _task.Jb.Count; i++)
{
allKappaList[_task.Jb[i]] = kappaList[i];
}
// Step3
double kappaValue = 0;
int kappaIndex = 0;
var check = false;
for (int i = 0; i < allKappaList.Count; i++)
{
if (allKappaList[i] > _task.dUpper[i] || allKappaList[i] < _task.dLower[i])
{
check = true;
kappaValue = allKappaList[i];
kappaIndex = i;
break;
}
}
if (!check)
{
_task.xo = allKappaList;
//Logger.Log("Stopped at third step");
_stopStep = 3;
return false;
}
// Step4 is unnecessary
// Step5
var nk = kappaValue < _task.dLower[kappaIndex] ? 1 : -1;
var deltaYT =
nk * DenseVector.Create(_task.Jb.Count, i => i == _task.Jb.ToList().IndexOf(kappaIndex) ? 1 : 0)
* DenseMatrix.OfColumnVectors(vectorCollection.ToArray()).Inverse();
var nVector = new DenseVector(_task.A.ColumnCount);
for (int i = 0; i < _task.A.ColumnCount; i++)
{
if (!_task.Jb.Contains(i))
{
nVector[i] = (deltaYT * _task.A.Column(i));
}
}
// Step6
Vector<double> sigmaVector = new DenseVector(_task.A.ColumnCount);
for (int i = 0; i < sigmaVector.Count; i++)
{
if (_task.dLower[i] == _task.dUpper[i])
{
sigmaVector[i] = double.PositiveInfinity;
}
else if (_JNbUpper.Contains(i) && nVector[i] < Eps)
{
sigmaVector[i] = -deltas[i] / nVector[i];
}
else if (_JNbLower.Contains(i) && nVector[i] > Eps)
{
sigmaVector[i] = -deltas[i] / nVector[i];
}
else
{
sigmaVector[i] = double.PositiveInfinity;
}
}
//.........这里部分代码省略.........
示例2: DualIteration
private static bool DualIteration()
{
// Step1
var vectorCollection = new List<Vector<double>>();
foreach (var item in _Jb)
{
vectorCollection.Add(_A.Column(item));
}
var aBMatrix = DenseMatrix.OfColumnVectors(vectorCollection.ToArray());
var bMatrix = aBMatrix.Inverse();
var kappa = bMatrix * _b;
// Step2
if (kappa.ToList().TrueForAll(x => x >= Eps))
{
//Logger.Log("Stopped at second step");
return false;
}
// Step3
var minJ = kappa.MinimumIndex();
var deltaYT = DenseVector.Create(_Jb.Length, i => i == minJ ? 1 : 0) * DenseMatrix.OfColumnVectors(vectorCollection.ToArray()).Inverse();
var nVector = new DenseVector(_A.ColumnCount);
for (int i = 0; i < _A.ColumnCount; i++)
{
if (!_Jb.Contains(i))
{
nVector[i] = (deltaYT * _A.Column(i));
}
}
if (nVector.ToList().TrueForAll(n => n >= Eps))
{
//Logger.Log("Stopped at third step");
return false;
}
// Step4
double sigma0 = Double.PositiveInfinity;
int sigmaIndex = 0;
var sigmaList = new DenseVector(_A.ColumnCount);
for (int i = 0, j = 0; i < _A.ColumnCount; i++)
{
if (!_Jb.Contains(i) && (nVector[i] < 0))
{
sigmaList[i] = ((_C[i] - _A.Column(i) * _Yb) / nVector[i]);
if (sigmaList[i] < sigma0)
{
sigma0 = sigmaList[i];
sigmaIndex = i;
}
}
}
// Step5
var newYb = _Yb.Add(sigma0 * deltaYT);
_Yb = newYb;
_Jb[minJ] = sigmaIndex;
return true;
}