public void Dger(double alpha, DoubleMatrix1D x, DoubleMatrix1D y, DoubleMatrix2D A)
{
Cern.Jet.Math.PlusMult fun = new Cern.Jet.Math.PlusMult(0);
for (int i = A.Rows; --i >= 0;)
{
fun.Multiplicator = alpha * x[i];
A.ViewRow(i).Assign(y, fun);
}
}
public DoubleMatrix1D Assign(DoubleMatrix1D y, Cern.Jet.Math.PlusMult function, IntArrayList nonZeroIndexes)
{
CheckSize(y);
int[] nonZeroElements = nonZeroIndexes.ToArray();
double multiplicator = function.Multiplicator;
if (multiplicator == 0)
{ // x[i] = x[i] + 0*y[i]
return(this);
}
else if (multiplicator == 1)
{ // x[i] = x[i] + y[i]
for (int index = nonZeroIndexes.Count; --index >= 0;)
{
int i = nonZeroElements[index];
this[i] = this[i] + y[i];
}
}
else if (multiplicator == -1)
{ // x[i] = x[i] - y[i]
for (int index = nonZeroIndexes.Count; --index >= 0;)
{
int i = nonZeroElements[index];
this[i] = this[i] - y[i];
}
}
else
{ // the general case x[i] = x[i] + mult*y[i]
for (int index = nonZeroIndexes.Count; --index >= 0;)
{
int i = nonZeroElements[index];
this[i] = this[i] + multiplicator * y[i];
}
}
return(this);
}
public DoubleMatrix1D Assign(DoubleMatrix1D y, Cern.Jet.Math.PlusMult function)
{
return(Assign(y, function.Apply));
}
public void Solve(DoubleMatrix2D B)
{
int CUT_OFF = 10;
//algebra.property().checkRectangular(LU);
int m = M;
int n = N;
if (B.Rows != m)
{
throw new ArgumentException("Matrix row dimensions must agree.");
}
if (!this.IsNonsingular)
{
throw new ArgumentException("Matrix is singular.");
}
// right hand side with pivoting
// Matrix Xmat = B.getMatrix(piv,0,nx-1);
if (this.work1 == null || this.work1.Length < m)
{
this.work1 = new int[m];
}
//if (this.work2 == null || this.work2.Length < m) this.work2 = new int[m];
Algebra.PermuteRows(B, this.piv, this.work1);
if (m * n == 0)
{
return; // nothing to do
}
int nx = B.Columns;
//precompute and cache some views to avoid regenerating them time and again
DoubleMatrix1D[] Brows = new DoubleMatrix1D[n];
for (int k = 0; k < n; k++)
{
Brows[k] = B.ViewRow(k);
}
// transformations
Cern.Jet.Math.Mult div = Cern.Jet.Math.Mult.Div(0);
Cern.Jet.Math.PlusMult minusMult = Cern.Jet.Math.PlusMult.MinusMult(0);
IntArrayList nonZeroIndexes = new IntArrayList(); // sparsity
DoubleMatrix1D Browk = Cern.Colt.Matrix.DoubleFactory1D.Dense.Make(nx); // blocked row k
// Solve L*Y = B(piv,:)
for (int k = 0; k < n; k++)
{
// blocking (make copy of k-th row to localize references)
Browk.Assign(Brows[k]);
// sparsity detection
int maxCardinality = nx / CUT_OFF; // == heuristic depending on speedup
Browk.GetNonZeros(nonZeroIndexes, null, maxCardinality);
int cardinality = nonZeroIndexes.Count;
Boolean sparse = (cardinality < maxCardinality);
for (int i = k + 1; i < n; i++)
{
//for (int j = 0; j < nx; j++) B[i][j] -= B[k][j]*LU[i][k];
//for (int j = 0; j < nx; j++) B.set(i,j, B.Get(i,j) - B.Get(k,j)*LU.Get(i,k));
minusMult.Multiplicator = -LU[i, k];
if (minusMult.Multiplicator != 0)
{
if (sparse)
{
Brows[i].Assign(Browk, minusMult, nonZeroIndexes);
}
else
{
Brows[i].Assign(Browk, minusMult);
}
}
}
}
// Solve U*B = Y;
for (int k = n - 1; k >= 0; k--)
{
// for (int j = 0; j < nx; j++) B[k][j] /= LU[k][k];
// for (int j = 0; j < nx; j++) B.set(k,j, B.Get(k,j) / LU.Get(k,k));
div.Multiplicator = 1 / LU[k, k];
Brows[k].Assign(div);
// blocking
if (Browk == null)
{
Browk = Cern.Colt.Matrix.DoubleFactory1D.Dense.Make(B.Columns);
}
Browk.Assign(Brows[k]);
// sparsity detection
int maxCardinality = nx / CUT_OFF; // == heuristic depending on speedup
Browk.GetNonZeros(nonZeroIndexes, null, maxCardinality);
int cardinality = nonZeroIndexes.Count;
Boolean sparse = (cardinality < maxCardinality);
//Browk.GetNonZeros(nonZeroIndexes,null);
//Boolean sparse = nonZeroIndexes.Count < nx/10;
for (int i = 0; i < k; i++)
{
// for (int j = 0; j < nx; j++) B[i][j] -= B[k][j]*LU[i][k];
// for (int j = 0; j < nx; j++) B.set(i,j, B.Get(i,j) - B.Get(k,j)*LU.Get(i,k));
minusMult.Multiplicator = -LU[i, k];
if (minusMult.Multiplicator != 0)
{
if (sparse)
{
Brows[i].Assign(Browk, minusMult, nonZeroIndexes);
}
else
{
Brows[i].Assign(Browk, minusMult);
}
}
}
}
}
