本文整理汇总了C#中DenseMatrix.SetColumn方法的典型用法代码示例。如果您正苦于以下问题：C# DenseMatrix.SetColumn方法的具体用法？C# DenseMatrix.SetColumn怎么用？C# DenseMatrix.SetColumn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DenseMatrix的用法示例。
在下文中一共展示了DenseMatrix.SetColumn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: FilterColumnsBy
public static DenseMatrix FilterColumnsBy(this Matrix m, int[] filter)
{
var result = new DenseMatrix(m.Rows, filter.Length);
for (int j = 0; j < filter.Length; ++j) {
result.SetColumn(j, m.GetColumn(j));
}
return result;
}示例2: CreateStartingVectors
/// <summary>
/// Returns an array of starting vectors.
/// </summary>
/// <param name="maximumNumberOfStartingVectors">The maximum number of starting vectors that should be created.</param>
/// <param name="numberOfVariables">The number of variables.</param>
/// <returns>
/// An array with starting vectors. The array will never be larger than the
/// <paramref name="maximumNumberOfStartingVectors"/> but it may be smaller if
/// the <paramref name="numberOfVariables"/> is smaller than
/// the <paramref name="maximumNumberOfStartingVectors"/>.
/// </returns>
private static IList<Vector> CreateStartingVectors(int maximumNumberOfStartingVectors, int numberOfVariables)
{
// Create no more starting vectors than the size of the problem - 1
// Get random values and then orthogonalize them with
// modified Gramm - Schmidt
var count = NumberOfStartingVectorsToCreate(maximumNumberOfStartingVectors, numberOfVariables);
// Get a random set of samples based on the standard normal distribution with
// mean = 0 and sd = 1
var distribution = new Normal();
Matrix matrix = new DenseMatrix(numberOfVariables, count);
for (var i = 0; i < matrix.ColumnCount; i++)
{
var samples = new Complex[matrix.RowCount];
var samplesRe = distribution.Samples().Take(matrix.RowCount).ToArray();
var samplesIm = distribution.Samples().Take(matrix.RowCount).ToArray();
for (int j = 0; j < matrix.RowCount; j++)
{
samples[j] = new Complex(samplesRe[j], samplesIm[j]);
}
// Set the column
matrix.SetColumn(i, samples);
}
// Compute the orthogonalization.
var gs = matrix.GramSchmidt();
var orthogonalMatrix = gs.Q;
// Now transfer this to vectors
var result = new List<Vector>();
for (var i = 0; i < orthogonalMatrix.ColumnCount; i++)
{
result.Add((Vector)orthogonalMatrix.Column(i));
// Normalize the result vector
result[i].Multiply(1 / result[i].Norm(2), result[i]);
}
return result;
}示例3: SortColumnsBy
public static DenseMatrix SortColumnsBy(this Matrix m, int[] order)
{
var cols = m.GetColumns().ToArray();
DenseMatrix result = new DenseMatrix(m.Rows, m.Columns);
for (int j = 0; j < cols.Length; ++j) {
result.SetColumn(j, cols[order[j]]);
}
return result;
}