//
// Math.NET Numerics, part of the Math.NET Project
// http://numerics.mathdotnet.com
// http://github.com/mathnet/mathnet-numerics
//
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//
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// obtaining a copy of this software and associated documentation
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using System;
using System.Collections.Generic;
using System.Diagnostics;
using System.Linq;
using IStation.Numerics.Distributions;
using IStation.Numerics.LinearAlgebra.Storage;
using IStation.Numerics.Providers.LinearAlgebra;
using IStation.Numerics.Threading;
namespace IStation.Numerics.LinearAlgebra.Complex
{
using Complex = System.Numerics.Complex;
///
/// A matrix type for diagonal matrices.
///
///
/// Diagonal matrices can be non-square matrices but the diagonal always starts
/// at element 0,0. A diagonal matrix will throw an exception if non diagonal
/// entries are set. The exception to this is when the off diagonal elements are
/// 0.0 or NaN; these settings will cause no change to the diagonal matrix.
///
[Serializable]
[DebuggerDisplay("DiagonalMatrix {RowCount}x{ColumnCount}-Complex")]
public class DiagonalMatrix : Matrix
{
///
/// Gets the matrix's data.
///
/// The matrix's data.
readonly Complex[] _data;
///
/// Create a new diagonal matrix straight from an initialized matrix storage instance.
/// The storage is used directly without copying.
/// Intended for advanced scenarios where you're working directly with
/// storage for performance or interop reasons.
///
public DiagonalMatrix(DiagonalMatrixStorage storage)
: base(storage)
{
_data = storage.Data;
}
///
/// Create a new square diagonal matrix with the given number of rows and columns.
/// All cells of the matrix will be initialized to zero.
///
/// If the order is less than one.
public DiagonalMatrix(int order)
: this(new DiagonalMatrixStorage(order, order))
{
}
///
/// Create a new diagonal matrix with the given number of rows and columns.
/// All cells of the matrix will be initialized to zero.
///
/// If the row or column count is less than one.
public DiagonalMatrix(int rows, int columns)
: this(new DiagonalMatrixStorage(rows, columns))
{
}
///
/// Create a new diagonal matrix with the given number of rows and columns.
/// All diagonal cells of the matrix will be initialized to the provided value, all non-diagonal ones to zero.
///
/// If the row or column count is less than one.
public DiagonalMatrix(int rows, int columns, Complex diagonalValue)
: this(rows, columns)
{
for (var i = 0; i < _data.Length; i++)
{
_data[i] = diagonalValue;
}
}
///
/// Create a new diagonal matrix with the given number of rows and columns directly binding to a raw array.
/// The array is assumed to contain the diagonal elements only and is used directly without copying.
/// Very efficient, but changes to the array and the matrix will affect each other.
///
public DiagonalMatrix(int rows, int columns, Complex[] diagonalStorage)
: this(new DiagonalMatrixStorage(rows, columns, diagonalStorage))
{
}
///
/// Create a new diagonal matrix as a copy of the given other matrix.
/// This new matrix will be independent from the other matrix.
/// The matrix to copy from must be diagonal as well.
/// A new memory block will be allocated for storing the matrix.
///
public static DiagonalMatrix OfMatrix(Matrix matrix)
{
return new DiagonalMatrix(DiagonalMatrixStorage.OfMatrix(matrix.Storage));
}
///
/// Create a new diagonal matrix as a copy of the given two-dimensional array.
/// This new matrix will be independent from the provided array.
/// The array to copy from must be diagonal as well.
/// A new memory block will be allocated for storing the matrix.
///
public static DiagonalMatrix OfArray(Complex[,] array)
{
return new DiagonalMatrix(DiagonalMatrixStorage.OfArray(array));
}
///
/// Create a new diagonal matrix and initialize each diagonal value from the provided indexed enumerable.
/// Keys must be provided at most once, zero is assumed if a key is omitted.
/// This new matrix will be independent from the enumerable.
/// A new memory block will be allocated for storing the matrix.
///
public static DiagonalMatrix OfIndexedDiagonal(int rows, int columns, IEnumerable> diagonal)
{
return new DiagonalMatrix(DiagonalMatrixStorage.OfIndexedEnumerable(rows, columns, diagonal));
}
///
/// Create a new diagonal matrix and initialize each diagonal value from the provided enumerable.
/// This new matrix will be independent from the enumerable.
/// A new memory block will be allocated for storing the matrix.
///
public static DiagonalMatrix OfDiagonal(int rows, int columns, IEnumerable diagonal)
{
return new DiagonalMatrix(DiagonalMatrixStorage.OfEnumerable(rows, columns, diagonal));
}
///
/// Create a new diagonal matrix and initialize each diagonal value using the provided init function.
///
public static DiagonalMatrix Create(int rows, int columns, Func init)
{
return new DiagonalMatrix(DiagonalMatrixStorage.OfInit(rows, columns, init));
}
///
/// Create a new square sparse identity matrix where each diagonal value is set to One.
///
public static DiagonalMatrix CreateIdentity(int order)
{
return new DiagonalMatrix(DiagonalMatrixStorage.OfValue(order, order, One));
}
///
/// Create a new diagonal matrix with diagonal values sampled from the provided random distribution.
///
public static DiagonalMatrix CreateRandom(int rows, int columns, IContinuousDistribution distribution)
{
return new DiagonalMatrix(new DiagonalMatrixStorage(rows, columns, Generate.RandomComplex(Math.Min(rows, columns), distribution)));
}
///
/// Negate each element of this matrix and place the results into the result matrix.
///
/// The result of the negation.
protected override void DoNegate(Matrix result)
{
if (result is DiagonalMatrix diagResult)
{
LinearAlgebraControl.Provider.ScaleArray(-1, _data, diagResult._data);
return;
}
result.Clear();
for (var i = 0; i < _data.Length; i++)
{
result.At(i, i, -_data[i]);
}
}
///
/// Complex conjugates each element of this matrix and place the results into the result matrix.
///
/// The result of the conjugation.
protected override void DoConjugate(Matrix result)
{
if (result is DiagonalMatrix diagResult)
{
LinearAlgebraControl.Provider.ConjugateArray(_data, diagResult._data);
return;
}
result.Clear();
for (var i = 0; i < _data.Length; i++)
{
result.At(i, i, _data[i].Conjugate());
}
}
///
/// Adds another matrix to this matrix.
///
/// The matrix to add to this matrix.
/// The matrix to store the result of the addition.
/// If the two matrices don't have the same dimensions.
protected override void DoAdd(Matrix other, Matrix result)
{
// diagonal + diagonal = diagonal
if (other is DiagonalMatrix diagOther && result is DiagonalMatrix diagResult)
{
LinearAlgebraControl.Provider.AddArrays(_data, diagOther._data, diagResult._data);
return;
}
other.CopyTo(result);
for (int i = 0; i < _data.Length; i++)
{
result.At(i, i, result.At(i, i) + _data[i]);
}
}
///
/// Subtracts another matrix from this matrix.
///
/// The matrix to subtract.
/// The matrix to store the result of the subtraction.
/// If the two matrices don't have the same dimensions.
protected override void DoSubtract(Matrix other, Matrix result)
{
// diagonal - diagonal = diagonal
if (other is DiagonalMatrix diagOther && result is DiagonalMatrix diagResult)
{
LinearAlgebraControl.Provider.SubtractArrays(_data, diagOther._data, diagResult._data);
return;
}
other.Negate(result);
for (int i = 0; i < _data.Length; i++)
{
result.At(i, i, result.At(i, i) + _data[i]);
}
}
///
/// Multiplies each element of the matrix by a scalar and places results into the result matrix.
///
/// The scalar to multiply the matrix with.
/// The matrix to store the result of the multiplication.
/// If the result matrix's dimensions are not the same as this matrix.
protected override void DoMultiply(Complex scalar, Matrix result)
{
if (scalar == 0.0)
{
result.Clear();
return;
}
if (scalar == 1.0)
{
CopyTo(result);
return;
}
if (result is DiagonalMatrix diagResult)
{
LinearAlgebraControl.Provider.ScaleArray(scalar, _data, diagResult._data);
}
else
{
base.DoMultiply(scalar, result);
}
}
///
/// Multiplies this matrix with a vector and places the results into the result vector.
///
/// The vector to multiply with.
/// The result of the multiplication.
protected override void DoMultiply(Vector rightSide, Vector result)
{
var d = Math.Min(ColumnCount, RowCount);
if (d < RowCount)
{
result.ClearSubVector(ColumnCount, RowCount - ColumnCount);
}
if (d == ColumnCount)
{
if (rightSide.Storage is DenseVectorStorage denseOther && result.Storage is DenseVectorStorage denseResult)
{
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(_data, denseOther.Data, denseResult.Data);
return;
}
}
for (var i = 0; i < d; i++)
{
result.At(i, _data[i]*rightSide.At(i));
}
}
///
/// Multiplies this matrix with another matrix and places the results into the result matrix.
///
/// The matrix to multiply with.
/// The result of the multiplication.
protected override void DoMultiply(Matrix other, Matrix result)
{
if (other is DiagonalMatrix diagonalOther && result is DiagonalMatrix diagonalResult)
{
var thisDataCopy = new Complex[diagonalResult._data.Length];
var otherDataCopy = new Complex[diagonalResult._data.Length];
Array.Copy(_data, 0, thisDataCopy, 0, (diagonalResult._data.Length > _data.Length) ? _data.Length : diagonalResult._data.Length);
Array.Copy(diagonalOther._data, 0, otherDataCopy, 0, (diagonalResult._data.Length > diagonalOther._data.Length) ? diagonalOther._data.Length : diagonalResult._data.Length);
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(thisDataCopy, otherDataCopy, diagonalResult._data);
return;
}
if (other.Storage is DenseColumnMajorMatrixStorage denseOther)
{
var dense = denseOther.Data;
var diagonal = _data;
var d = Math.Min(denseOther.RowCount, RowCount);
if (d < RowCount)
{
result.ClearSubMatrix(denseOther.RowCount, RowCount - denseOther.RowCount, 0, denseOther.ColumnCount);
}
int index = 0;
for (int i = 0; i < denseOther.ColumnCount; i++)
{
for (int j = 0; j < d; j++)
{
result.At(j, i, dense[index]*diagonal[j]);
index++;
}
index += (denseOther.RowCount - d);
}
return;
}
if (ColumnCount == RowCount)
{
other.Storage.MapIndexedTo(result.Storage, (i, j, x) => x*_data[i], Zeros.AllowSkip, ExistingData.Clear);
}
else
{
result.Clear();
other.Storage.MapSubMatrixIndexedTo(result.Storage, (i, j, x) => x*_data[i], 0, 0, Math.Min(RowCount, other.RowCount), 0, 0, other.ColumnCount, Zeros.AllowSkip, ExistingData.AssumeZeros);
}
}
///
/// Multiplies this matrix with transpose of another matrix and places the results into the result matrix.
///
/// The matrix to multiply with.
/// The result of the multiplication.
protected override void DoTransposeAndMultiply(Matrix other, Matrix result)
{
if (other is DiagonalMatrix diagonalOther && result is DiagonalMatrix diagonalResult)
{
var thisDataCopy = new Complex[diagonalResult._data.Length];
var otherDataCopy = new Complex[diagonalResult._data.Length];
Array.Copy(_data, 0, thisDataCopy, 0, (diagonalResult._data.Length > _data.Length) ? _data.Length : diagonalResult._data.Length);
Array.Copy(diagonalOther._data, 0, otherDataCopy, 0, (diagonalResult._data.Length > diagonalOther._data.Length) ? diagonalOther._data.Length : diagonalResult._data.Length);
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(thisDataCopy, otherDataCopy, diagonalResult._data);
return;
}
if (other.Storage is DenseColumnMajorMatrixStorage denseOther)
{
var dense = denseOther.Data;
var diagonal = _data;
var d = Math.Min(denseOther.ColumnCount, RowCount);
if (d < RowCount)
{
result.ClearSubMatrix(denseOther.ColumnCount, RowCount - denseOther.ColumnCount, 0, denseOther.RowCount);
}
int index = 0;
for (int j = 0; j < d; j++)
{
for (int i = 0; i < denseOther.RowCount; i++)
{
result.At(j, i, dense[index]*diagonal[j]);
index++;
}
}
return;
}
base.DoTransposeAndMultiply(other, result);
}
///
/// Multiplies this matrix with the conjugate transpose of another matrix and places the results into the result matrix.
///
/// The matrix to multiply with.
/// The result of the multiplication.
protected override void DoConjugateTransposeAndMultiply(Matrix other, Matrix result)
{
if (other is DiagonalMatrix diagonalOther && result is DiagonalMatrix diagonalResult)
{
var thisDataCopy = new Complex[diagonalResult._data.Length];
var otherDataCopy = new Complex[diagonalResult._data.Length];
Array.Copy(_data, 0, thisDataCopy, 0, (diagonalResult._data.Length > _data.Length) ? _data.Length : diagonalResult._data.Length);
Array.Copy(diagonalOther._data, 0, otherDataCopy, 0, (diagonalResult._data.Length > diagonalOther._data.Length) ? diagonalOther._data.Length : diagonalResult._data.Length);
// TODO: merge/MulByConj
LinearAlgebraControl.Provider.ConjugateArray(otherDataCopy, otherDataCopy);
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(thisDataCopy, otherDataCopy, diagonalResult._data);
return;
}
if (other.Storage is DenseColumnMajorMatrixStorage denseOther)
{
var dense = denseOther.Data;
var diagonal = _data;
var d = Math.Min(denseOther.ColumnCount, RowCount);
if (d < RowCount)
{
result.ClearSubMatrix(denseOther.ColumnCount, RowCount - denseOther.ColumnCount, 0, denseOther.RowCount);
}
int index = 0;
for (int j = 0; j < d; j++)
{
for (int i = 0; i < denseOther.RowCount; i++)
{
result.At(j, i, dense[index].Conjugate()*diagonal[j]);
index++;
}
}
return;
}
base.DoConjugateTransposeAndMultiply(other, result);
}
///
/// Multiplies the transpose of this matrix with another matrix and places the results into the result matrix.
///
/// The matrix to multiply with.
/// The result of the multiplication.
protected override void DoTransposeThisAndMultiply(Matrix other, Matrix result)
{
if (other is DiagonalMatrix diagonalOther && result is DiagonalMatrix diagonalResult)
{
var thisDataCopy = new Complex[diagonalResult._data.Length];
var otherDataCopy = new Complex[diagonalResult._data.Length];
Array.Copy(_data, 0, thisDataCopy, 0, (diagonalResult._data.Length > _data.Length) ? _data.Length : diagonalResult._data.Length);
Array.Copy(diagonalOther._data, 0, otherDataCopy, 0, (diagonalResult._data.Length > diagonalOther._data.Length) ? diagonalOther._data.Length : diagonalResult._data.Length);
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(thisDataCopy, otherDataCopy, diagonalResult._data);
return;
}
if (other.Storage is DenseColumnMajorMatrixStorage denseOther)
{
var dense = denseOther.Data;
var diagonal = _data;
var d = Math.Min(denseOther.RowCount, ColumnCount);
if (d < ColumnCount)
{
result.ClearSubMatrix(denseOther.RowCount, ColumnCount - denseOther.RowCount, 0, denseOther.ColumnCount);
}
int index = 0;
for (int i = 0; i < denseOther.ColumnCount; i++)
{
for (int j = 0; j < d; j++)
{
result.At(j, i, dense[index]*diagonal[j]);
index++;
}
index += (denseOther.RowCount - d);
}
return;
}
if (ColumnCount == RowCount)
{
other.Storage.MapIndexedTo(result.Storage, (i, j, x) => x*_data[i], Zeros.AllowSkip, ExistingData.Clear);
}
else
{
result.Clear();
other.Storage.MapSubMatrixIndexedTo(result.Storage, (i, j, x) => x*_data[i], 0, 0, other.RowCount, 0, 0, other.ColumnCount, Zeros.AllowSkip, ExistingData.AssumeZeros);
}
}
///
/// Multiplies the transpose of this matrix with another matrix and places the results into the result matrix.
///
/// The matrix to multiply with.
/// The result of the multiplication.
protected override void DoConjugateTransposeThisAndMultiply(Matrix other, Matrix result)
{
if (other is DiagonalMatrix diagonalOther && result is DiagonalMatrix diagonalResult)
{
var thisDataCopy = new Complex[diagonalResult._data.Length];
var otherDataCopy = new Complex[diagonalResult._data.Length];
Array.Copy(_data, 0, thisDataCopy, 0, (diagonalResult._data.Length > _data.Length) ? _data.Length : diagonalResult._data.Length);
Array.Copy(diagonalOther._data, 0, otherDataCopy, 0, (diagonalResult._data.Length > diagonalOther._data.Length) ? diagonalOther._data.Length : diagonalResult._data.Length);
// TODO: merge/MulByConj
LinearAlgebraControl.Provider.ConjugateArray(thisDataCopy, thisDataCopy);
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(thisDataCopy, otherDataCopy, diagonalResult._data);
return;
}
if (other.Storage is DenseColumnMajorMatrixStorage denseOther)
{
var dense = denseOther.Data;
var conjugateDiagonal = new Complex[_data.Length];
for (int i = 0; i < _data.Length; i++)
{
conjugateDiagonal[i] = _data[i].Conjugate();
}
var d = Math.Min(denseOther.RowCount, ColumnCount);
if (d < ColumnCount)
{
result.ClearSubMatrix(denseOther.RowCount, ColumnCount - denseOther.RowCount, 0, denseOther.ColumnCount);
}
int index = 0;
for (int i = 0; i < denseOther.ColumnCount; i++)
{
for (int j = 0; j < d; j++)
{
result.At(j, i, dense[index]*conjugateDiagonal[j]);
index++;
}
index += (denseOther.RowCount - d);
}
return;
}
base.DoConjugateTransposeThisAndMultiply(other, result);
}
///
/// Multiplies the transpose of this matrix with a vector and places the results into the result vector.
///
/// The vector to multiply with.
/// The result of the multiplication.
protected override void DoTransposeThisAndMultiply(Vector rightSide, Vector result)
{
var d = Math.Min(ColumnCount, RowCount);
if (d < ColumnCount)
{
result.ClearSubVector(RowCount, ColumnCount - RowCount);
}
if (d == RowCount)
{
if (rightSide.Storage is DenseVectorStorage denseOther && result.Storage is DenseVectorStorage denseResult)
{
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(_data, denseOther.Data, denseResult.Data);
return;
}
}
for (var i = 0; i < d; i++)
{
result.At(i, _data[i]*rightSide.At(i));
}
}
///
/// Multiplies the conjugate transpose of this matrix with a vector and places the results into the result vector.
///
/// The vector to multiply with.
/// The result of the multiplication.
protected override void DoConjugateTransposeThisAndMultiply(Vector rightSide, Vector result)
{
var d = Math.Min(ColumnCount, RowCount);
if (d < ColumnCount)
{
result.ClearSubVector(RowCount, ColumnCount - RowCount);
}
if (d == RowCount)
{
if (rightSide.Storage is DenseVectorStorage denseOther && result.Storage is DenseVectorStorage denseResult)
{
// TODO: merge/MulByConj
LinearAlgebraControl.Provider.ConjugateArray(_data, denseResult.Data);
LinearAlgebraControl.Provider.PointWiseMultiplyArrays(denseResult.Data, denseOther.Data, denseResult.Data);
return;
}
}
for (var i = 0; i < d; i++)
{
result.At(i, _data[i].Conjugate()*rightSide.At(i));
}
}
///
/// Divides each element of the matrix by a scalar and places results into the result matrix.
///
/// The scalar to divide the matrix with.
/// The matrix to store the result of the division.
protected override void DoDivide(Complex divisor, Matrix result)
{
if (divisor == Complex.One)
{
CopyTo(result);
return;
}
if (result is DiagonalMatrix diagResult)
{
LinearAlgebraControl.Provider.ScaleArray(1.0/divisor, _data, diagResult._data);
return;
}
result.Clear();
for (int i = 0; i < _data.Length; i++)
{
result.At(i, i, _data[i]/divisor);
}
}
///
/// Divides a scalar by each element of the matrix and stores the result in the result matrix.
///
/// The scalar to add.
/// The matrix to store the result of the division.
protected override void DoDivideByThis(Complex dividend, Matrix result)
{
if (result is DiagonalMatrix diagResult)
{
var resultData = diagResult._data;
CommonParallel.For(0, _data.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
resultData[i] = dividend/_data[i];
}
});
return;
}
result.Clear();
for (int i = 0; i < _data.Length; i++)
{
result.At(i, i, dividend/_data[i]);
}
}
///
/// Computes the determinant of this matrix.
///
/// The determinant of this matrix.
public override Complex Determinant()
{
if (RowCount != ColumnCount)
{
throw new ArgumentException("Matrix must be square.");
}
return _data.Aggregate(Complex.One, (current, t) => current * t);
}
///
/// Returns the elements of the diagonal in a .
///
/// The elements of the diagonal.
/// For non-square matrices, the method returns Min(Rows, Columns) elements where
/// i == j (i is the row index, and j is the column index).
public override Vector Diagonal()
{
return new DenseVector(_data).Clone();
}
///
/// Copies the values of the given array to the diagonal.
///
/// The array to copy the values from. The length of the vector should be
/// Min(Rows, Columns).
/// If the length of does not
/// equal Min(Rows, Columns).
/// For non-square matrices, the elements of are copied to
/// this[i,i].
public override void SetDiagonal(Complex[] source)
{
if (source.Length != _data.Length)
{
throw new ArgumentException("The array arguments must have the same length.", nameof(source));
}
Array.Copy(source, 0, _data, 0, source.Length);
}
///
/// Copies the values of the given to the diagonal.
///
/// The vector to copy the values from. The length of the vector should be
/// Min(Rows, Columns).
/// If the length of does not
/// equal Min(Rows, Columns).
/// For non-square matrices, the elements of are copied to
/// this[i,i].
public override void SetDiagonal(Vector source)
{
if (source is DenseVector denseSource)
{
if (_data.Length != denseSource.Values.Length)
{
throw new ArgumentException("All vectors must have the same dimensionality.", nameof(source));
}
Array.Copy(denseSource.Values, 0, _data, 0, denseSource.Values.Length);
}
else
{
base.SetDiagonal(source);
}
}
/// Calculates the induced L1 norm of this matrix.
/// The maximum absolute column sum of the matrix.
public override double L1Norm()
{
return _data.Aggregate(0d, (current, t) => Math.Max(current, t.Magnitude));
}
/// Calculates the induced L2 norm of the matrix.
/// The largest singular value of the matrix.
public override double L2Norm()
{
return _data.Aggregate(0d, (current, t) => Math.Max(current, t.Magnitude));
}
/// Calculates the induced infinity norm of this matrix.
/// The maximum absolute row sum of the matrix.
public override double InfinityNorm()
{
return L1Norm();
}
/// Calculates the Frobenius norm of this matrix.
/// The Frobenius norm of this matrix.
public override double FrobeniusNorm()
{
return Math.Sqrt(_data.Sum(t => t.Magnitude * t.Magnitude));
}
/// Calculates the condition number of this matrix.
/// The condition number of the matrix.
public override Complex ConditionNumber()
{
var maxSv = double.NegativeInfinity;
var minSv = double.PositiveInfinity;
foreach (var t in _data)
{
maxSv = Math.Max(maxSv, t.Magnitude);
minSv = Math.Min(minSv, t.Magnitude);
}
return maxSv / minSv;
}
/// Computes the inverse of this matrix.
/// If is not a square matrix.
/// If is singular.
/// The inverse of this matrix.
public override Matrix Inverse()
{
if (RowCount != ColumnCount)
{
throw new ArgumentException("Matrix must be square.");
}
var inverse = (DiagonalMatrix)Clone();
for (var i = 0; i < _data.Length; i++)
{
if (_data[i] != 0.0)
{
inverse._data[i] = 1.0 / _data[i];
}
else
{
throw new ArgumentException("Matrix must not be singular.");
}
}
return inverse;
}
///
/// Returns a new matrix containing the lower triangle of this matrix.
///
/// The lower triangle of this matrix.
public override Matrix LowerTriangle()
{
return Clone();
}
///
/// Puts the lower triangle of this matrix into the result matrix.
///
/// Where to store the lower triangle.
/// If the result matrix's dimensions are not the same as this matrix.
public override void LowerTriangle(Matrix result)
{
if (result.RowCount != RowCount || result.ColumnCount != ColumnCount)
{
throw DimensionsDontMatch(this, result, "result");
}
if (ReferenceEquals(this, result))
{
return;
}
result.Clear();
for (var i = 0; i < _data.Length; i++)
{
result.At(i, i, _data[i]);
}
}
///
/// Returns a new matrix containing the lower triangle of this matrix. The new matrix
/// does not contain the diagonal elements of this matrix.
///
/// The lower triangle of this matrix.
public override Matrix StrictlyLowerTriangle()
{
return new DiagonalMatrix(RowCount, ColumnCount);
}
///
/// Puts the strictly lower triangle of this matrix into the result matrix.
///
/// Where to store the lower triangle.
/// If the result matrix's dimensions are not the same as this matrix.
public override void StrictlyLowerTriangle(Matrix result)
{
if (result.RowCount != RowCount || result.ColumnCount != ColumnCount)
{
throw DimensionsDontMatch(this, result, "result");
}
result.Clear();
}
///
/// Returns a new matrix containing the upper triangle of this matrix.
///
/// The upper triangle of this matrix.
public override Matrix UpperTriangle()
{
return Clone();
}
///
/// Puts the upper triangle of this matrix into the result matrix.
///
/// Where to store the lower triangle.
/// If the result matrix's dimensions are not the same as this matrix.
public override void UpperTriangle(Matrix result)
{
if (result.RowCount != RowCount || result.ColumnCount != ColumnCount)
{
throw DimensionsDontMatch(this, result, "result");
}
result.Clear();
for (var i = 0; i < _data.Length; i++)
{
result.At(i, i, _data[i]);
}
}
///
/// Returns a new matrix containing the upper triangle of this matrix. The new matrix
/// does not contain the diagonal elements of this matrix.
///
/// The upper triangle of this matrix.
public override Matrix StrictlyUpperTriangle()
{
return new DiagonalMatrix(RowCount, ColumnCount);
}
///
/// Puts the strictly upper triangle of this matrix into the result matrix.
///
/// Where to store the lower triangle.
/// If the result matrix's dimensions are not the same as this matrix.
public override void StrictlyUpperTriangle(Matrix result)
{
if (result.RowCount != RowCount || result.ColumnCount != ColumnCount)
{
throw DimensionsDontMatch(this, result, "result");
}
result.Clear();
}
///
/// Creates a matrix that contains the values from the requested sub-matrix.
///
/// The row to start copying from.
/// The number of rows to copy. Must be positive.
/// The column to start copying from.
/// The number of columns to copy. Must be positive.
/// The requested sub-matrix.
/// If: - is
/// negative, or greater than or equal to the number of rows.
/// - is negative, or greater than or equal to the number
/// of columns.
/// - (columnIndex + columnLength) >= Columns
/// - (rowIndex + rowLength) >= Rows
/// If or
/// is not positive.
public override Matrix SubMatrix(int rowIndex, int rowCount, int columnIndex, int columnCount)
{
var target = rowIndex == columnIndex
? (Matrix)new DiagonalMatrix(rowCount, columnCount)
: new SparseMatrix(rowCount, columnCount);
Storage.CopySubMatrixTo(target.Storage, rowIndex, 0, rowCount, columnIndex, 0, columnCount, ExistingData.AssumeZeros);
return target;
}
///
/// Permute the columns of a matrix according to a permutation.
///
/// The column permutation to apply to this matrix.
/// Always thrown
/// Permutation in diagonal matrix are senseless, because of matrix nature
public override void PermuteColumns(Permutation p)
{
throw new InvalidOperationException("Permutations in diagonal matrix are not allowed");
}
///
/// Permute the rows of a matrix according to a permutation.
///
/// The row permutation to apply to this matrix.
/// Always thrown
/// Permutation in diagonal matrix are senseless, because of matrix nature
public override void PermuteRows(Permutation p)
{
throw new InvalidOperationException("Permutations in diagonal matrix are not allowed");
}
///
/// Evaluates whether this matrix is symmetric.
///
public sealed override bool IsSymmetric()
{
return true;
}
///
/// Evaluates whether this matrix is Hermitian (conjugate symmetric).
///
public sealed override bool IsHermitian()
{
for (var k = 0; k < _data.Length; k ++)
{
if (!_data[k].IsReal())
{
return false;
}
}
return true;
}
}
}