public void Dsymv(Boolean isUpperTriangular, double alpha, DoubleMatrix2D A, DoubleMatrix1D x, double beta, DoubleMatrix1D y)
{
if (isUpperTriangular)
{
A = A.ViewDice();
}
Property.DEFAULT.CheckSquare(A);
int size = A.Rows;
if (size != x.Size || size != y.Size)
{
throw new ArgumentException(A.ToStringShort() + ", " + x.ToStringShort() + ", " + y.ToStringShort());
}
DoubleMatrix1D tmp = x.Like();
for (int i = 0; i < size; i++)
{
double sum = 0;
for (int j = 0; j <= i; j++)
{
sum += A[i, j] * x[j];
}
for (int j = i + 1; j < size; j++)
{
sum += A[j, i] * x[j];
}
tmp[i] = alpha * sum + beta * y[i];
}
y.Assign(tmp);
}
/// <summary>
/// Update the SVD with the addition of a new column.
/// </summary>
/// <param name="c">
/// The new column.
/// </param>
/// <param name="wantV">
/// Whether the matrix V is needed.
/// </param>
public void Update(DoubleMatrix1D c, bool wantV)
{
int nRows = c.Size - _m;
if (nRows > 0)
{
_u = DoubleFactory2D.Dense.AppendRows(_u, new SparseDoubleMatrix2D(nRows, _n));
_m = c.Size;
}
else if (nRows < 0)
{
c = DoubleFactory1D.Sparse.AppendColumns(c, DoubleFactory1D.Sparse.Make(-nRows));
}
var d = DoubleFactory2D.Dense.Make(c.ToArray(), c.Size);
// l = U'd is the eigencoding of d
var l = _u.ViewDice().ZMult(d, null);
////var uu = _u.ZMult(_u.ViewDice(), null);
// Ul = UU'd
////var ul = uu.ZMult(d, null);
var ul = _u.ZMult(l, null);
// h = d - UU'd = d - Ul is the component of d orthogonal to the subspace spanned by U
////var h = d.Copy().Assign(uu.ZMult(d, null), BinaryFunctions.Minus);
////var h = d.Copy().Assign(ul, BinaryFunctions.Minus);
// k is the projection of d onto the subspace othogonal to U
var k = Math.Sqrt(d.Aggregate(BinaryFunctions.Plus, a => a * a) - (2 * l.Aggregate(BinaryFunctions.Plus, a => a * a)) + ul.Aggregate(BinaryFunctions.Plus, a => a * a));
// truncation
if (k == 0 || double.IsNaN(k))
{
return;
}
_n++;
// j = d - UU'd = d - Ul is an orthogonal basis for the component of d orthogonal to the subspace spanned by U
////var j = h.Assign(UnaryFunctions.Div(k));
var j = d.Assign(ul, BinaryFunctions.Minus).Assign(UnaryFunctions.Div(k));
// Q = [ S, l; 0, ||h||]
var q =
DoubleFactory2D.Sparse.Compose(
new[] { new[] { S, l }, new[] { null, DoubleFactory2D.Dense.Make(1, 1, k) } });
var svdq = new SingularValueDecomposition(q, true, wantV, true);
_u = DoubleFactory2D.Dense.AppendColumns(_u, j).ZMult(svdq.U, null);
_s = svdq.SingularValues;
if (wantV)
{
_v = DoubleFactory2D.Dense.ComposeDiagonal(_v, DoubleFactory2D.Dense.Identity(1)).ZMult(
svdq.V, null);
}
}
public void Dtrmv(Boolean isUpperTriangular, Boolean transposeA, Boolean isUnitTriangular, DoubleMatrix2D A, DoubleMatrix1D x)
{
if (transposeA)
{
A = A.ViewDice();
isUpperTriangular = !isUpperTriangular;
}
Property.DEFAULT.CheckSquare(A);
int size = A.Rows;
if (size != x.Size)
{
throw new ArgumentException(A.ToStringShort() + ", " + x.ToStringShort());
}
DoubleMatrix1D b = x.Like();
DoubleMatrix1D y = x.Like();
if (isUnitTriangular)
{
y.Assign(1);
}
else
{
for (int i = 0; i < size; i++)
{
y[i] = A[i, i];
}
}
for (int i = 0; i < size; i++)
{
double sum = 0;
if (!isUpperTriangular)
{
for (int j = 0; j < i; j++)
{
sum += A[i, j] * x[j];
}
sum += y[i] * x[i];
}
else
{
sum += y[i] * x[i];
for (int j = i + 1; j < size; j++)
{
sum += A[i, j] * x[j];
}
}
b[i] = sum;
}
x.Assign(b);
}
/// <summary>
/// A matrix <i>A</i> is <i>symmetric</i> if <i>A = tranpose(A)</i>, that is <i>A[i,j] == A[j,i]</i>.
/// <summary>
/// <exception cref="ArgumentException">if <i>!isSquare(A)</i>. </exception>
public Boolean IsSymmetric(DoubleMatrix2D A)
{
CheckSquare(A);
return(Equals(A, A.ViewDice()));
}
/// <summary>
/// Linear algebraic matrix-matrix multiplication; <tt>C = alpha * A x B + beta*C</tt>.
/// </summary>
/// <param name="b">
/// The econd source matrix.
/// </param>
/// <param name="c">
/// The matrix where results are to be stored. Set this parameter to <tt>null</tt> to indicate that a new result matrix shall be constructed.
/// </param>
/// <param name="alpha">
/// The alpha.
/// </param>
/// <param name="beta">
/// The beta.
/// </param>
/// <param name="transposeA">
/// Whether A must be transposed.
/// </param>
/// <param name="transposeB">
/// Whether B must be transposed.
/// </param>
/// <returns>
/// C (for convenience only).
/// </returns>
/// <exception cref="ArgumentOutOfRangeException">
/// If <tt>B.rows() != A.columns()</tt>.
/// </exception>
/// <exception cref="ArgumentException">
/// If <tt>C.rows() != A.rows() || C.columns() != B.columns()</tt>.
/// </exception>
/// <exception cref="ArithmeticException">
/// If <tt>A == C || B == C</tt>.
/// </exception>
public override DoubleMatrix2D ZMult(DoubleMatrix2D b, DoubleMatrix2D c, double alpha, double beta, bool transposeA, bool transposeB)
{
// overriden for performance only
if (transposeA)
{
return(ViewDice().ZMult(b, c, alpha, beta, false, transposeB));
}
if (b is SparseDoubleMatrix2D)
{
// exploit quick sparse mult
// A*B = (B' * A')'
if (c == null)
{
return(b.ZMult(this, null, alpha, beta, !transposeB, true).ViewDice());
}
b.ZMult(this, c.ViewDice(), alpha, beta, !transposeB, true);
return(c);
}
if (transposeB)
{
return(ZMult(b.ViewDice(), c, alpha, beta, false, false));
}
int m = Rows;
int n = Columns;
int p = b.Columns;
if (c == null)
{
c = new DenseDoubleMatrix2D(m, p);
}
if (!(c is DenseDoubleMatrix2D))
{
return(base.ZMult(b, c, alpha, beta, false, false));
}
if (b.Rows != n)
{
throw new ArgumentOutOfRangeException("b", "Matrix2D inner dimensions must agree:" + this + ", " + b);
}
if (c.Rows != m || c.Columns != p)
{
throw new ArgumentException("Incompatible result matrix: " + this + ", " + b + ", " + c);
}
if (this == c || b == c)
{
throw new ArgumentException("Matrices must not be identical");
}
var bb = (DenseDoubleMatrix2D)b;
var cc = (DenseDoubleMatrix2D)c;
double[] aElems = Elements;
double[] bElems = bb.Elements;
double[] cElems = cc.Elements;
if (aElems == null || bElems == null || cElems == null)
{
throw new ApplicationException();
}
int cA = ColumnStride;
int cB = bb.ColumnStride;
int cC = cc.ColumnStride;
int rA = RowStride;
int rB = bb.RowStride;
int rC = cc.RowStride;
/*
* A is blocked to hide memory latency
* xxxxxxx B
* xxxxxxx
* xxxxxxx
* A
* xxx xxxxxxx C
* xxx xxxxxxx
* --- -------
* xxx xxxxxxx
* xxx xxxxxxx
* --- -------
* xxx xxxxxxx
*/
const int BLOCK_SIZE = 30000;
int m_optimal = (BLOCK_SIZE - n) / (n + 1);
if (m_optimal <= 0)
{
m_optimal = 1;
}
int blocks = m / m_optimal;
int rr = 0;
if (m % m_optimal != 0)
{
blocks++;
}
for (; --blocks >= 0;)
{
int jB = bb.Index(0, 0);
int indexA = Index(rr, 0);
int jC = cc.Index(rr, 0);
rr += m_optimal;
if (blocks == 0)
{
m_optimal += m - rr;
}
for (int j = p; --j >= 0;)
{
int iA = indexA;
int iC = jC;
for (int i = m_optimal; --i >= 0;)
{
int kA = iA;
int kB = jB;
double s = 0;
/*
* // not unrolled:
* for (int k = n; --k >= 0;) {
* //s += getQuick(i,k) * B.getQuick(k,j);
* s += AElems[kA] * BElems[kB];
* kB += rB;
* kA += cA;
* }
*/
// loop unrolled
kA -= cA;
kB -= rB;
for (int k = n % 4; --k >= 0;)
{
s += aElems[kA += cA] * bElems[kB += rB];
}
for (int k = n / 4; --k >= 0;)
{
s += (aElems[kA += cA] * bElems[kB += rB]) +
(aElems[kA += cA] * bElems[kB += rB]) +
(aElems[kA += cA] * bElems[kB += rB]) +
(aElems[kA += cA] * bElems[kB += rB]);
}
cElems[iC] = (alpha * s) + (beta * cElems[iC]);
iA += rA;
iC += rC;
}
jB += cB;
jC += cC;
}
}
return(c);
}
public void Dgemv(bool transposeA, double alpha, DoubleMatrix2D A, DoubleMatrix1D x, double beta, DoubleMatrix1D y)
{
/*
* split A, as follows:
*
* x x
* x
* x
* A
* xxx x y
* xxx x
* --- -
* xxx x
* xxx x
* --- -
* xxx x
*
*/
if (transposeA)
{
Dgemv(false, alpha, A.ViewDice(), x, beta, y);
return;
}
int m = A.Rows;
int n = A.Columns;
long flops = 2L * m * n;
int noOfTasks = (int)System.Math.Min(flops / 30000, this.maxThreads); // each thread should process at least 30000 flops
int width = A.Rows;
noOfTasks = System.Math.Min(width, noOfTasks);
if (noOfTasks < 2)
{ // parallelization doesn't pay off (too much start up overhead)
seqBlas.Dgemv(transposeA, alpha, A, x, beta, y);
return;
}
// set up concurrent tasks
int span = width / noOfTasks;
//FJTask[] subTasks = new FJTask[noOfTasks];
for (int i = 0; i < noOfTasks; i++)
{
int offset = i * span;
if (i == noOfTasks - 1)
{
span = width - span * i; // last span may be a bit larger
}
// split A along rows into blocks
DoubleMatrix2D AA = A.ViewPart(offset, 0, span, n);
DoubleMatrix1D yy = y.ViewPart(offset, span);
// subTasks[i] = new FJTask()
// {
// public void run()
// {
// seqBlas.Dgemv(transposeA, alpha, AA, x, beta, yy);
// //Console.WriteLine("Hello "+offset);
// }
//};
Action task = (() =>
{
seqBlas.Dgemv(transposeA, alpha, AA, x, beta, yy);
});
// run tasks and wait for completion
try
{
this.smp.TaskGroup.QueueTask(() => task());
}
catch (TaskCanceledException exc) { }
}
}
public void Dgemm(bool transposeA, bool transposeB, double alpha, DoubleMatrix2D A, DoubleMatrix2D B, double beta, DoubleMatrix2D C)
{
/*
* determine how to split and parallelize best into blocks
* if more B.columns than tasks --> split B.columns, as follows:
*
* xx|xx|xxx B
* xx|xx|xxx
* xx|xx|xxx
* A
* xxx xx|xx|xxx C
* xxx xx|xx|xxx
* xxx xx|xx|xxx
* xxx xx|xx|xxx
* xxx xx|xx|xxx
*
* if less B.columns than tasks --> split A.rows, as follows:
*
* xxxxxxx B
* xxxxxxx
* xxxxxxx
* A
* xxx xxxxxxx C
* xxx xxxxxxx
* --- -------
* xxx xxxxxxx
* xxx xxxxxxx
* --- -------
* xxx xxxxxxx
*
*/
if (transposeA)
{
Dgemm(false, transposeB, alpha, A.ViewDice(), B, beta, C);
return;
}
if (transposeB)
{
Dgemm(transposeA, false, alpha, A, B.ViewDice(), beta, C);
return;
}
int m = A.Rows;
int n = A.Columns;
int p = B.Columns;
if (B.Rows != n)
{
throw new ArgumentException("Matrix2D inner dimensions must agree:" + A.ToStringShort() + ", " + B.ToStringShort());
}
if (C.Rows != m || C.Columns != p)
{
throw new ArgumentException("Incompatibel result matrix: " + A.ToStringShort() + ", " + B.ToStringShort() + ", " + C.ToStringShort());
}
if (A == C || B == C)
{
throw new ArgumentException("Matrices must not be identical");
}
long flops = 2L * m * n * p;
int noOfTasks = (int)System.Math.Min(flops / 30000, this.maxThreads); // each thread should process at least 30000 flops
Boolean splitB = (p >= noOfTasks);
int width = splitB ? p : m;
noOfTasks = System.Math.Min(width, noOfTasks);
if (noOfTasks < 2)
{ // parallelization doesn't pay off (too much start up overhead)
seqBlas.Dgemm(transposeA, transposeB, alpha, A, B, beta, C);
return;
}
// set up concurrent tasks
int span = width / noOfTasks;
//FJTask[] subTasks = new FJTask[noOfTasks];
for (int i = 0; i < noOfTasks; i++)
{
int offset = i * span;
if (i == noOfTasks - 1)
{
span = width - span * i; // last span may be a bit larger
}
DoubleMatrix2D AA, BB, CC;
if (splitB)
{
// split B along columns into blocks
AA = A;
BB = B.ViewPart(0, offset, n, span);
CC = C.ViewPart(0, offset, m, span);
}
else
{
// split A along rows into blocks
AA = A.ViewPart(offset, 0, span, n);
BB = B;
CC = C.ViewPart(offset, 0, span, p);
}
Action task = (() =>
{
seqBlas.Dgemm(transposeA, transposeB, alpha, AA, BB, beta, CC);
});
// run tasks and wait for completion
try
{
this.smp.TaskGroup.QueueTask(() => task());
}
catch (TaskCanceledException exc) { }
}
}
public override DoubleMatrix2D ZMult(DoubleMatrix2D B, DoubleMatrix2D C, double alpha, double beta, Boolean transposeA, Boolean transposeB)
{
if (transposeB)
{
B = B.ViewDice();
}
int m = Rows;
int n = Columns;
if (transposeA)
{
m = Columns;
n = Rows;
}
int p = B.Columns;
Boolean ignore = (C == null);
if (C == null)
{
C = new DenseDoubleMatrix2D(m, p);
}
if (B.Rows != n)
{
throw new ArgumentException(String.Format(Cern.LocalizedResources.Instance().Exception_Matrix2DInnerDimensionMustAgree, ToStringShort(), (transposeB ? B.ViewDice() : B).ToStringShort()));
}
if (C.Rows != m || C.Columns != p)
{
throw new ArgumentException(String.Format(Cern.LocalizedResources.Instance().Exception_IncompatibleResultMatrix, ToStringShort(), (transposeB ? B.ViewDice() : B).ToStringShort(), C.ToStringShort()));
}
if (this == C || B == C)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatricesMustNotBeIdentical);
}
if (!ignore)
{
C.Assign(F1.Mult(beta));
}
// cache views
DoubleMatrix1D[] Brows = new DoubleMatrix1D[n];
for (int i = n; --i >= 0;)
{
Brows[i] = B.ViewRow(i);
}
DoubleMatrix1D[] Crows = new DoubleMatrix1D[m];
for (int i = m; --i >= 0;)
{
Crows[i] = C.ViewRow(i);
}
ForEachNonZero(
new Cern.Colt.Function.IntIntDoubleFunction((i, j, value) =>
{
var fun = F2.PlusMult(value * alpha);
//fun.multiplicator = value * alpha;
if (!transposeA)
{
Crows[i].Assign(Brows[j], fun);
}
else
{
Crows[j].Assign(Brows[i], fun);
}
return(value);
}
));
return(C);
}
///// <summary>
/////
///// </summary>
///// <param name="matrix"></param>
///// <param name="rowNames"></param>
///// <param name="columnNames"></param>
///// <param name="rowAxisName"></param>
///// <param name="columnAxisName"></param>
///// <param name="title"></param>
///// <returns></returns>
//public String ToTitleString(ObjectMatrix2D matrix, String[] rowNames, String[] columnNames, String rowAxisName, String columnAxisName, String title)
//{
// if (matrix.Size == 0) return "Empty matrix";
// String oldFormat = this.formatString;
// this.formatString = LEFT;
// int rows = matrix.Rows;
// int columns = matrix.Columns;
// // determine how many rows and columns are needed
// int r = 0;
// int c = 0;
// r += (columnNames == null ? 0 : 1);
// c += (rowNames == null ? 0 : 1);
// c += (rowAxisName == null ? 0 : 1);
// c += (rowNames != null || rowAxisName != null ? 1 : 0);
// int height = r + System.Math.Max(rows, rowAxisName == null ? 0 : rowAxisName.Length);
// int width = c + columns;
// // make larger matrix holding original matrix and naming strings
// Cern.Colt.Matrix.ObjectMatrix2D titleMatrix = matrix.Like(height, width);
// // insert original matrix into larger matrix
// titleMatrix.ViewPart(r, c, rows, columns).Assign(matrix);
// // insert column axis name in leading row
// if (r > 0) titleMatrix.ViewRow(0).ViewPart(c, columns).Assign(columnNames);
// // insert row axis name in leading column
// if (rowAxisName != null)
// {
// String[] rowAxisStrings = new String[rowAxisName.Length];
// for (int i = rowAxisName.Length; --i >= 0;) rowAxisStrings[i] = rowAxisName.Substring(i, i + 1);
// titleMatrix.ViewColumn(0).ViewPart(r, rowAxisName.Length).Assign(rowAxisStrings);
// }
// // insert row names in next leading columns
// if (rowNames != null) titleMatrix.ViewColumn(c - 2).ViewPart(r, rows).Assign(rowNames);
// // insert vertical "---------" separator line in next leading column
// if (c > 0) titleMatrix.ViewColumn(c - 2 + 1).ViewPart(0, rows + r).Assign("|");
// // convert the large matrix to a string
// Boolean oldPrintShape = this.printShape;
// this.printShape = false;
// String str = ToString(titleMatrix);
// this.printShape = oldPrintShape;
// // insert horizontal "--------------" separator line
// var total = new StringBuilder(str);
// if (columnNames != null)
// {
// int i = str.IndexOf(rowSeparator);
// total.Insert(i + 1, Repeat('-', i) + rowSeparator);
// }
// else if (columnAxisName != null)
// {
// int i = str.IndexOf(rowSeparator);
// total.Insert(0, Repeat('-', i) + rowSeparator);
// }
// // insert line for column axis name
// if (columnAxisName != null)
// {
// int j = 0;
// if (c > 0) j = str.IndexOf('|');
// String s = Blanks(j);
// if (c > 0) s = s + "| ";
// s = s + columnAxisName + "\n";
// total.Insert(0, s);
// }
// // insert title
// if (title != null) total.Insert(0, title + "\n");
// this.formatString = oldFormat;
// return total.ToString();
//}
/// <summary>
/// Same as <i>toTitleString</i> except that additionally statistical aggregates (mean, median, sum, etcd) of rows and columns are printed.
/// Pass <i>null</i> to one or more parameters to indicate that the corresponding decoration element shall not appear in the string converted matrix.
/// </summary>
/// <param name="matrix">The matrix to format.</param>
/// <param name="rowNames">The headers of all rows (to be put to the left of the matrix).</param>
/// <param name="columnNames">The headers of all columns (to be put to above the matrix).</param>
/// <param name="rowAxisName">The label of the y-axis.</param>
/// <param name="columnAxisName">The label of the x-axis.</param>
/// <param name="title">The overall title of the matrix to be formatted.</param>
/// <param name="aggr">the aggregation functions to be applied to columns and rows.</param>
/// <returns>the matrix converted to a string.</returns>
/// <see cref="Hep.Aida.Bin.BinFunction1D"/>
/// <see cref="Hep.Aida.Bin.BinFunctions1D"/>
public String ToTitleString(DoubleMatrix2D matrix, String[] rowNames, String[] columnNames, String rowAxisName, String columnAxisName, String title, Hep.Aida.Bin.BinFunction1D[] aggr)
{
if (matrix.Size == 0)
{
return("Empty matrix");
}
if (aggr == null || aggr.Length == 0)
{
return(ToTitleString(matrix, rowNames, columnNames, rowAxisName, columnAxisName, title));
}
DoubleMatrix2D rowStats = matrix.Like(matrix.Rows, aggr.Length); // hold row aggregations
DoubleMatrix2D colStats = matrix.Like(aggr.Length, matrix.Columns); // hold column aggregations
Cern.Colt.Matrix.DoubleAlgorithms.Statistics.Aggregate(matrix, aggr, colStats); // aggregate an entire column at a time
Cern.Colt.Matrix.DoubleAlgorithms.Statistics.Aggregate(matrix.ViewDice(), aggr, rowStats.ViewDice()); // aggregate an entire row at a time
// turn into strings
// tmp holds "matrix" plus "colStats" below (needed so that numbers in a columns can be decimal point aligned)
DoubleMatrix2D tmp = matrix.Like(matrix.Rows + aggr.Length, matrix.Columns);
tmp.ViewPart(0, 0, matrix.Rows, matrix.Columns).Assign(matrix);
tmp.ViewPart(matrix.Rows, 0, aggr.Length, matrix.Columns).Assign(colStats);
String[][] s1 = Format(tmp); Align(s1);
String[][] s2 = Format(rowStats); Align(s2);
// copy strings into a large matrix holding the source matrix and all aggregations
Cern.Colt.Matrix.ObjectMatrix2D allStats = Cern.Colt.Matrix.ObjectFactory2D.Dense.Make(matrix.Rows + aggr.Length, matrix.Columns + aggr.Length + 1);
allStats.ViewPart(0, 0, matrix.Rows + aggr.Length, matrix.Columns).Assign(s1);
allStats.ViewColumn(matrix.Columns).Assign("|");
allStats.ViewPart(0, matrix.Columns + 1, matrix.Rows, aggr.Length).Assign(s2);
// append a vertical "|" separator plus names of aggregation functions to line holding columnNames
if (columnNames != null)
{
var list = new List <Object>(columnNames);
list.Add("|");
list.AddRange(aggr.Select(x => x.Method.Name).ToList());
columnNames = list.ToStringArray();
}
// append names of aggregation functions to line holding rowNames
if (rowNames != null)
{
var list = new List <Object>(rowNames);
list.AddRange(aggr.Select(x => x.Method.Name).ToList());
rowNames = list.ToStringArray();
}
// turn large matrix into string
String s = new Cern.Colt.Matrix.ObjectAlgorithms.Formatter().ToTitleString(allStats, rowNames, columnNames, rowAxisName, columnAxisName, title);
// insert a horizontal "----------------------" separation line above the column stats
// determine insertion position and line width
int last = s.Length + 1;
int secondLast = last;
int v = System.Math.Max(0, rowAxisName == null ? 0 : rowAxisName.Length - matrix.Rows - aggr.Length);
for (int k = 0; k < aggr.Length + 1 + v; k++)
{ // scan "aggr.Length+1+v" lines backwards
secondLast = last;
last = s.LastIndexOf(rowSeparator, last - 1);
}
StringBuilder buf = new StringBuilder(s);
buf.Insert(secondLast, rowSeparator + Repeat('-', secondLast - last - 1));
return(buf.ToString());
}
public override DoubleMatrix2D ZMult(DoubleMatrix2D B, DoubleMatrix2D C, double alpha, double beta, Boolean transposeA, Boolean transposeB)
{
if (transposeB)
{
B = B.ViewDice();
}
int m = Rows;
int n = Columns;
if (transposeA)
{
m = Columns;
n = Rows;
}
int p = B.Columns;
Boolean ignore = (C == null);
if (C == null)
{
C = new DenseDoubleMatrix2D(m, p);
}
if (B.Rows != n)
{
throw new ArgumentException("Matrix2D inner dimensions must agree:" + ToStringShort() + ", " + (transposeB ? B.ViewDice() : B).ToStringShort());
}
if (C.Rows != m || C.Columns != p)
{
throw new ArgumentException("Incompatibel result matrix: " + ToStringShort() + ", " + (transposeB ? B.ViewDice() : B).ToStringShort() + ", " + C.ToStringShort());
}
if (this == C || B == C)
{
throw new ArgumentException("Matrices must not be identical");
}
if (!ignore)
{
C.Assign(F1.Mult(beta));
}
// cache views
DoubleMatrix1D[] Brows = new DoubleMatrix1D[n];
for (int i = n; --i >= 0;)
{
Brows[i] = B.ViewRow(i);
}
DoubleMatrix1D[] Crows = new DoubleMatrix1D[m];
for (int i = m; --i >= 0;)
{
Crows[i] = C.ViewRow(i);
}
ForEachNonZero(
new Cern.Colt.Function.IntIntDoubleFunction((i, j, value) =>
{
var fun = F2.PlusMult(value * alpha);
//fun.multiplicator = value * alpha;
if (!transposeA)
{
Crows[i].Assign(Brows[j], fun);
}
else
{
Crows[j].Assign(Brows[i], fun);
}
return(value);
}
));
return(C);
}
/// <summary>
/// Constructs and returns a new view which is the transposition of the given matrix <i>A</i>.
/// </summary>
/// <param name="a">
/// The matrix A.
/// </param>
/// <returns>
/// The transpose of A.
/// </returns>
public static DoubleMatrix2D Transpose(DoubleMatrix2D a)
{
return(a.ViewDice());
}
public static DoubleMatrix2D PermuteColumns(DoubleMatrix2D A, int[] indexes, int[] work)
{
return(PermuteRows(A.ViewDice(), indexes, work));
}
public override DoubleMatrix2D ZMult(DoubleMatrix2D B, DoubleMatrix2D C, double alpha, double beta, Boolean transposeA, Boolean transposeB)
{
if (transposeB)
{
B = B.ViewDice();
}
int m = Rows;
int n = Columns;
if (transposeA)
{
m = Columns;
n = Rows;
}
int p = B.Columns;
Boolean ignore = (C == null);
if (C == null)
{
C = new DenseDoubleMatrix2D(m, p);
}
if (B.Rows != n)
{
throw new ArgumentException(String.Format(Cern.LocalizedResources.Instance().Exception_Matrix2DInnerDimensionMustAgree, ToStringShort(), (transposeB ? B.ViewDice() : B).ToStringShort()));
}
if (C.Rows != m || C.Columns != p)
{
throw new ArgumentException(String.Format(Cern.LocalizedResources.Instance().Exception_IncompatibleResultMatrix, ToStringShort(), (transposeB ? B.ViewDice() : B).ToStringShort(), C.ToStringShort()));
}
if (this == C || B == C)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatricesMustNotBeIdentical);
}
if (!ignore)
{
C.Assign(F1.Mult(beta));
}
// cache views
DoubleMatrix1D[] Brows = new DoubleMatrix1D[n];
for (int i = n; --i >= 0;)
{
Brows[i] = B.ViewRow(i);
}
DoubleMatrix1D[] Crows = new DoubleMatrix1D[m];
for (int i = m; --i >= 0;)
{
Crows[i] = C.ViewRow(i);
}
int[] idx = Indexes.ToArray();
double[] vals = Values.ToArray();
for (int i = Starts.Length - 1; --i >= 0;)
{
int low = Starts[i];
for (int k = Starts[i + 1]; --k >= low;)
{
int j = idx[k];
var fun = F2.PlusMult(vals[k] * alpha);
//fun.Multiplicator = vals[k] * alpha;
if (!transposeA)
{
Crows[i].Assign(Brows[j], fun);
}
else
{
Crows[j].Assign(Brows[i], fun);
}
}
}
return(C);
}