本文整理汇总了C#中Complex32.Clone方法的典型用法代码示例。如果您正苦于以下问题：C# Complex32.Clone方法的具体用法？C# Complex32.Clone怎么用？C# Complex32.Clone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Complex32的用法示例。
在下文中一共展示了Complex32.Clone方法的5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: MatrixMultiplyWithUpdate
//.........这里部分代码省略.........
{
throw new ArgumentOutOfRangeException();
}
rowsC = rowsA;
}
else
{
if (columnsA != rowsB)
{
throw new ArgumentOutOfRangeException();
}
if (rowsA * columnsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
rowsC = rowsA;
}
if (alpha.IsZero() && beta.IsZero())
{
Array.Clear(c, 0, c.Length);
return;
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex32[] adata;
if (ReferenceEquals(a, c))
{
adata = (Complex32[])a.Clone();
}
else
{
adata = a;
}
Complex32[] bdata;
if (ReferenceEquals(b, c))
{
bdata = (Complex32[])b.Clone();
}
else
{
bdata = b;
}
if (alpha.IsOne())
{
if (beta.IsZero())
{
if ((int)transposeA > 111 && (int)transposeB > 111)
{
CommonParallel.For(
0,
columnsA,
j =>
{
var jIndex = j * rowsC;
for (var i = 0; i != rowsB; i++)
{
var iIndex = i * rowsA;
Complex32 s = 0;示例2: MatrixMultiply
/// <summary>
/// Multiples two matrices. <c>result = x * y</c>
/// </summary>
/// <param name="x">The x matrix.</param>
/// <param name="rowsX">The number of rows in the x matrix.</param>
/// <param name="columnsX">The number of columns in the x matrix.</param>
/// <param name="y">The y matrix.</param>
/// <param name="rowsY">The number of rows in the y matrix.</param>
/// <param name="columnsY">The number of columns in the y matrix.</param>
/// <param name="result">Where to store the result of the multiplication.</param>
/// <remarks>This is a simplified version of the BLAS GEMM routine with alpha
/// set to 1.0 and beta set to 0.0, and x and y are not transposed.</remarks>
public void MatrixMultiply(Complex32[] x, int rowsX, int columnsX, Complex32[] y, int rowsY, int columnsY, Complex32[] result)
{
// First check some basic requirement on the parameters of the matrix multiplication.
if (x == null)
{
throw new ArgumentNullException("x");
}
if (y == null)
{
throw new ArgumentNullException("y");
}
if (result == null)
{
throw new ArgumentNullException("result");
}
if (rowsX * columnsX != x.Length)
{
throw new ArgumentException("x.Length != xRows * xColumns");
}
if (rowsY * columnsY != y.Length)
{
throw new ArgumentException("y.Length != yRows * yColumns");
}
if (columnsX != rowsY)
{
throw new ArgumentException("xColumns != yRows");
}
if (rowsX * columnsY != result.Length)
{
throw new ArgumentException("xRows * yColumns != result.Length");
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex32[] xdata;
if (ReferenceEquals(x, result))
{
xdata = (Complex32[])x.Clone();
}
else
{
xdata = x;
}
Complex32[] ydata;
if (ReferenceEquals(y, result))
{
ydata = (Complex32[])y.Clone();
}
else
{
ydata = y;
}
// Start the actual matrix multiplication.
// TODO - For small matrices we should get rid of the parallelism because of startup costs.
// Perhaps the following implementations would be a good one
// http://blog.feradz.com/2009/01/cache-efficient-matrix-multiplication/
MatrixMultiplyWithUpdate(Transpose.DontTranspose, Transpose.DontTranspose, Complex32.One, xdata, rowsX, columnsX, ydata, rowsY, columnsY, Complex32.Zero, result);
}示例3: MatrixMultiply
/// <summary>
/// Multiples two matrices. <c>result = x * y</c>
/// </summary>
/// <param name="x">The x matrix.</param>
/// <param name="rowsX">The number of rows in the x matrix.</param>
/// <param name="columnsX">The number of columns in the x matrix.</param>
/// <param name="y">The y matrix.</param>
/// <param name="rowsY">The number of rows in the y matrix.</param>
/// <param name="columnsY">The number of columns in the y matrix.</param>
/// <param name="result">Where to store the result of the multiplication.</param>
/// <remarks>This is a simplified version of the BLAS GEMM routine with alpha
/// set to 1.0 and beta set to 0.0, and x and y are not transposed.</remarks>
public virtual void MatrixMultiply(Complex32[] x, int rowsX, int columnsX, Complex32[] y, int rowsY, int columnsY, Complex32[] result)
{
// First check some basic requirement on the parameters of the matrix multiplication.
if (x == null)
{
throw new ArgumentNullException("x");
}
if (y == null)
{
throw new ArgumentNullException("y");
}
if (result == null)
{
throw new ArgumentNullException("result");
}
if (rowsX * columnsX != x.Length)
{
throw new ArgumentException("x.Length != xRows * xColumns");
}
if (rowsY * columnsY != y.Length)
{
throw new ArgumentException("y.Length != yRows * yColumns");
}
if (columnsX != rowsY)
{
throw new ArgumentException("xColumns != yRows");
}
if (rowsX * columnsY != result.Length)
{
throw new ArgumentException("xRows * yColumns != result.Length");
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex32[] xdata;
if (ReferenceEquals(x, result))
{
xdata = (Complex32[])x.Clone();
}
else
{
xdata = x;
}
Complex32[] ydata;
if (ReferenceEquals(y, result))
{
ydata = (Complex32[])y.Clone();
}
else
{
ydata = y;
}
MatrixMultiplyWithUpdate(Transpose.DontTranspose, Transpose.DontTranspose, Complex32.One, xdata, rowsX, columnsX, ydata, rowsY, columnsY, Complex32.Zero, result);
}示例4: MatrixMultiplyWithUpdate
//.........这里部分代码省略.........
}
m = columnsA;
n = rowsB;
k = rowsA;
}
else if ((int)transposeA > 111)
{
if (rowsA != rowsB)
{
throw new ArgumentOutOfRangeException();
}
if (columnsA * columnsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = columnsA;
n = columnsB;
k = rowsA;
}
else if ((int)transposeB > 111)
{
if (columnsA != columnsB)
{
throw new ArgumentOutOfRangeException();
}
if (rowsA * rowsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = rowsA;
n = rowsB;
k = columnsA;
}
else
{
if (columnsA != rowsB)
{
throw new ArgumentOutOfRangeException();
}
if (rowsA * columnsB != c.Length)
{
throw new ArgumentOutOfRangeException();
}
m = rowsA;
n = columnsB;
k = columnsA;
}
if (alpha.IsZero() && beta.IsZero())
{
Array.Clear(c, 0, c.Length);
return;
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex32[] adata;
if (ReferenceEquals(a, c))
{
adata = (Complex32[])a.Clone();
}
else
{
adata = a;
}
Complex32[] bdata;
if (ReferenceEquals(b, c))
{
bdata = (Complex32[])b.Clone();
}
else
{
bdata = b;
}
if (beta.IsZero())
{
Array.Clear(c, 0, c.Length);
}
else if (!beta.IsOne())
{
Control.LinearAlgebraProvider.ScaleArray(beta, c, c);
}
if (alpha.IsZero())
{
return;
}
CacheObliviousMatrixMultiply(transposeA, transposeB, alpha, adata, 0, 0, bdata, 0, 0, c, 0, 0, m, n, k, m, n, k, true);
}示例5: MatrixMultiplyWithUpdate
//.........这里部分代码省略.........
}
cRows = aRows;
cColumns = bRows;
}
else
{
if (aColumns != bRows)
{
throw new ArgumentOutOfRangeException();
}
if (aRows * bColumns != c.Length)
{
throw new ArgumentOutOfRangeException();
}
cRows = aRows;
cColumns = bColumns;
}
if (alpha.IsZero && beta.IsZero)
{
Array.Clear(c, 0, c.Length);
return;
}
// Check whether we will be overwriting any of our inputs and make copies if necessary.
// TODO - we can don't have to allocate a completely new matrix when x or y point to the same memory
// as result, we can do it on a row wise basis. We should investigate this.
Complex32[] adata;
if (ReferenceEquals(a, c))
{
adata = (Complex32[])a.Clone();
}
else
{
adata = a;
}
Complex32[] bdata;
if (ReferenceEquals(b, c))
{
bdata = (Complex32[])b.Clone();
}
else
{
bdata = b;
}
if (alpha.IsOne)
{
if (beta.IsZero)
{
if ((int)transposeA > 111 && (int)transposeB > 111)
{
Parallel.For(0, aColumns, j =>
{
int jIndex = j * cRows;
for (int i = 0; i != bRows; i++)
{
int iIndex = i * aRows;
Complex32 s = 0;
for (int l = 0; l != bColumns; l++)
{
s += adata[iIndex + l] * bdata[l * bRows + j];