/**
* Sets the matrices to operate upon.
*/
public virtual void SetParameters(DoubleMatrix2D A, DoubleMatrix2D B)
{
this.A = A;
this.B = B;
this.C = A.Copy();
this.D = B.Copy();
}
/// <summary>
/// Solves <i>A*X = B</i>; returns <i>X</i>.
/// </summary>
/// <param name="B">A Matrix with as many rows as <i>A</i> and any number of columns.</param>
/// <returns><i>X</i> so that <i>L*L'*X = B</i>.</returns>
/// <exception cref="ArgumentException">if <i>B.Rows != A.Rows</i>.</exception>
/// <exception cref="ArgumentException">if <i>!isSymmetricPositiveDefinite()</i>.</exception>
public DoubleMatrix2D Solve(DoubleMatrix2D B)
{
// Copy right hand side.
DoubleMatrix2D X = B.Copy();
int nx = B.Columns;
// fix by MG Ferreira <*****@*****.**>
// old code is in method xxxSolveBuggy()
for (int c = 0; c < nx; c++)
{
// Solve L*Y = B;
for (int i = 0; i < n; i++)
{
double sum = B[i, c];
for (int k = i - 1; k >= 0; k--)
{
sum -= mL[i, k] * X[k, c];
}
X[i, c] = sum / mL[i, i];
}
// Solve L'*X = Y;
for (int i = n - 1; i >= 0; i--)
{
double sum = X[i, c];
for (int k = i + 1; k < n; k++)
{
sum -= mL[k, i] * X[k, c];
}
X[i, c] = sum / mL[i, i];
}
}
return(X);
}
/// <summary>
/// 9 point stencil operation.
/// Applies a function to a moving <i>3 x 3</i> window.
/// </summary>
/// <param name="A">
/// the matrix to operate on.
/// </param>
/// <param name="function">
/// the function to be applied to each window.
/// </param>
/// <param name="maxIterations">
/// the maximum number of times the stencil shall be applied to the matrixd
/// Should be a multiple of 2 because two iterations are always done in one atomic step.
/// </param>
/// <param name="hasConverged">
/// Convergence condition; will return before maxIterations are done when <i>hasConverged.apply(A)==true</i>.
/// Set this parameter to <i>null</i> to indicate that no convergence checks shall be made.
/// </param>
/// <param name="convergenceIterations">
/// the number of iterations to pass between each convergence check.
/// (Since a convergence may be expensive, you may want to do it only every 2,4 or 8 iterationsd)
/// </param>
/// <returns><the number of iterations actually executedd /returns>
public static int Stencil9(DoubleMatrix2D A, Cern.Colt.Function.Double9Function function, int maxIterations, DoubleMatrix2DProcedure hasConverged, int convergenceIterations)
{
DoubleMatrix2D B = A.Copy();
if (convergenceIterations <= 1)
{
convergenceIterations = 2;
}
if (convergenceIterations % 2 != 0)
{
convergenceIterations++; // odd -> make it even
}
int i = 0;
while (i < maxIterations)
{ // do two steps at a time for efficiency
A.ZAssign8Neighbors(B, function);
B.ZAssign8Neighbors(A, function);
i = i + 2;
if (i % convergenceIterations == 0 && hasConverged != null)
{
if (hasConverged(A))
{
return(i);
}
}
}
return(i);
}
/// <summary>
/// Linear algebraic matrix power; <i>B = A<sup>k</sup> <==> B = A*A*...*A</i>.
/// </summary>
/// <param name="A">the source matrix; must be square.</param>
/// <param name="k">the exponent, can be any number.</param>
/// <returns>a new result matrix.</returns>
/// <exception cref="ArgumentException">if <i>!Testing.isSquare(A)</i>.</exception>
private static DoubleMatrix2D XPowSlow(DoubleMatrix2D A, int k)
{
//cern.colt.Timer timer = new cern.colt.Timer().start();
DoubleMatrix2D result = A.Copy();
for (int i = 0; i < k - 1; i++)
{
result = Mult(result, A);
}
//timer.stop().Display();
return(result);
}
/// <summary>
/// Least squares solution of <i>A*X = B</i>; <i>returns X</i>.
/// </summary>
/// <param name="B">A matrix with as many rows as <i>A</i> and any number of columns.</param>
/// <returns><i>X</i> that minimizes the two norm of <i>Q*R*X - B</i>.</returns>
/// <exception cref="ArgumentException">if <i>B.Rows != A.Rows</i>.</exception>
/// <exception cref="ArgumentException">if <i>!this.hasFullRank()</i> (<i>A</i> is rank deficient).</exception>
public DoubleMatrix2D Solve(DoubleMatrix2D B)
{
Functions F = Functions.functions;
if (B.Rows != m)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatrixRowDimensionsMustAgree);
}
if (!this.HasFullRank)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatrixIsRankDeficient);
}
// Copy right hand side
int nx = B.Columns;
DoubleMatrix2D X = B.Copy();
// Compute Y = transpose(Q)*B
for (int k = 0; k < n; k++)
{
for (int j = 0; j < nx; j++)
{
double s = 0.0;
for (int i = k; i < m; i++)
{
s += QR[i, k] * X[i, j];
}
s = -s / QR[k, k];
for (int i = k; i < m; i++)
{
X[i, j] = X[i, j] + s * QR[i, k];
}
}
}
// Solve R*X = Y;
for (int k = n - 1; k >= 0; k--)
{
for (int j = 0; j < nx; j++)
{
X[k, j] = X[k, j] / Rdiag[k];
}
for (int i = 0; i < k; i++)
{
for (int j = 0; j < nx; j++)
{
X[i, j] = X[i, j] - X[k, j] * QR[i, k];
}
}
}
return(X.ViewPart(0, 0, n, nx));
}
public static DoubleMatrix2D Inverse(DoubleMatrix2D A)
{
if (A.IsSquare && A.IsDiagonal)
{
DoubleMatrix2D inv = A.Copy();
Boolean isNonSingular = Diagonal.Inverse(inv);
if (!isNonSingular)
{
throw new ArgumentException("A is singular.");
}
return(inv);
}
return(Solve(A, DoubleFactory2D.Dense.Identity(A.Rows)));
}
public static DoubleMatrix2D Inverse(DoubleMatrix2D A)
{
if (A.IsSquare && A.IsDiagonal)
{
DoubleMatrix2D inv = A.Copy();
Boolean IsNonSingular = Diagonal.Inverse(inv);
if (!IsNonSingular)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatrixIsSingular);
}
return(inv);
}
return(Solve(A, DoubleFactory2D.Dense.Identity(A.Rows)));
}
/// <summary>
/// Solves <i>A*X = B</i>; returns <i>X</i>.
/// </summary>
/// <param name="B">A Matrix with as many rows as <i>A</i> and any number of columns.</param>
/// <returns><i>X</i> so that <i>L*L'*X = B</i>.</returns>
/// <exception cref="ArgumentException">if <i>B.Rows != A.Rows</i>.</exception>
/// <exception cref="ArgumentException">if <i>!isSymmetricPositiveDefinite()</i>.</exception>
private DoubleMatrix2D XXXsolveBuggy(DoubleMatrix2D B)
{
var F = Cern.Jet.Math.Functions.functions;
if (B.Rows != n)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatrixRowDimensionsMustAgree);
}
if (!isSymmetricPositiveDefinite)
{
throw new ArgumentException(Cern.LocalizedResources.Instance().Exception_MatrixIsNotSymmetricPositiveDefinite);
}
// Copy right hand side.
DoubleMatrix2D X = B.Copy();
int nx = B.Columns;
// precompute and cache some views to avoid regenerating them time and again
DoubleMatrix1D[] Xrows = new DoubleMatrix1D[n];
for (int k = 0; k < n; k++)
{
Xrows[k] = X.ViewRow(k);
}
// Solve L*Y = B;
for (int k = 0; k < n; k++)
{
for (int i = k + 1; i < n; i++)
{
// X[i,j] -= X[k,j]*L[i,k]
Xrows[i].Assign(Xrows[k], F2.MinusMult(mL[i, k]));
}
Xrows[k].Assign(F1.Div(mL[k, k]));
}
// Solve L'*X = Y;
for (int k = n - 1; k >= 0; k--)
{
Xrows[k].Assign(F1.Div(mL[k, k]));
for (int i = 0; i < k; i++)
{
// X[i,j] -= X[k,j]*L[k,i]
Xrows[i].Assign(Xrows[k], F2.MinusMult(mL[k, i]));
}
}
return(X);
}
/// <summary>
/// Constructs and returns a new QR decomposition object; computed by Householder reflections;
/// The decomposed matrices can be retrieved via instance methods of the returned decomposition object.
/// Return a decomposition object to access <i>R</i> and the Householder vectors <i>H</i>, and to compute <i>Q</i>.
/// </summary>
/// <param name="A">A rectangular matrix.</param>
/// <exception cref="ArgumentException">if <i>A.Rows < A.Columns</i>.</exception>
public QRDecomposition(DoubleMatrix2D A)
{
Property.DEFAULT.CheckRectangular(A);
Functions F = Functions.functions;
// Initialize.
QR = A.Copy();
m = A.Rows;
n = A.Columns;
Rdiag = A.Like1D(n);
//Rdiag = new double[n];
DoubleDoubleFunction hypot = Algebra.HypotFunction();
// precompute and cache some views to avoid regenerating them time and again
DoubleMatrix1D[] QRcolumns = new DoubleMatrix1D[n];
DoubleMatrix1D[] QRcolumnsPart = new DoubleMatrix1D[n];
for (int k = 0; k < n; k++)
{
QRcolumns[k] = QR.ViewColumn(k);
QRcolumnsPart[k] = QR.ViewColumn(k).ViewPart(k, m - k);
}
// Main loop.
for (int k = 0; k < n; k++)
{
//DoubleMatrix1D QRcolk = QR.ViewColumn(k).ViewPart(k,m-k);
// Compute 2-norm of k-th column without under/overflow.
double nrm = 0;
//if (k<m) nrm = QRcolumnsPart[k].aggregate(hypot,F.identity);
for (int i = k; i < m; i++)
{ // fixes bug reported by [email protected]
nrm = Algebra.Hypot(nrm, QR[i, k]);
}
if (nrm != 0.0)
{
// Form k-th Householder vector.
if (QR[k, k] < 0)
{
nrm = -nrm;
}
QRcolumnsPart[k].Assign(F2.Div(nrm));
/*
* for (int i = k; i < m; i++) {
* QR[i][k] /= nrm;
* }
*/
QR[k, k] = QR[k, k] + 1;
// Apply transformation to remaining columns.
for (int j = k + 1; j < n; j++)
{
DoubleMatrix1D QRcolj = QR.ViewColumn(j).ViewPart(k, m - k);
double s = QRcolumnsPart[k].ZDotProduct(QRcolj);
/*
* // fixes bug reported by John Chambers
* DoubleMatrix1D QRcolj = QR.ViewColumn(j).ViewPart(k,m-k);
* double s = QRcolumnsPart[k].ZDotProduct(QRcolumns[j]);
* double s = 0.0;
* for (int i = k; i < m; i++) {
* s += QR[i][k]*QR[i][j];
* }
*/
s = -s / QR[k, k];
//QRcolumnsPart[j].Assign(QRcolumns[k], F.PlusMult(s));
for (int i = k; i < m; i++)
{
QR[i, j] = QR[i, j] + s * QR[i, k];
}
}
}
Rdiag[k] = -nrm;
}
}
/// <summary>
/// Constructs and returns a new LU Decomposition object;
/// The decomposed matrices can be retrieved via instance methods of the returned decomposition object.
/// Return structure to access L, U and piv.
/// </summary>
/// <param name="A">Rectangular matrix</param>
public LUDecomposition(DoubleMatrix2D A)
{
quick = new LUDecompositionQuick(0); // zero tolerance for compatibility with Jama
quick.Decompose(A.Copy());
}
/// <summary>
/// Solves <i>A*X = B</i>.
/// </summary>
/// <param name="B">A matrix with as many rows as <i>A</i> and any number of columns.</param>
/// <returns><i>X</i> so that <i>L*U*X = B(piv,:)</i>.</returns>
/// <exception cref="ArgumentException">if B.rows() != A.rows().</exception>
/// <exception cref="ArgumentException">if A is singular, that is, if !this.isNonsingular().</exception>
/// <exception cref="ArgumentException">if A.rows() < A.columns().</exception>
public DoubleMatrix2D Solve(DoubleMatrix2D B)
{
DoubleMatrix2D X = B.Copy();
quick.Solve(X);
return X;
}
/// <summary>
/// Linear algebraic matrix power; <i>B = A<sup>k</sup> <==> B = A*A*...*A</i>.
/// <ul>
/// <li><i>p >= 1: B = A*A*...*A</i>.</li>
/// <li><i>p == 0: B = identity matrix</i>.</li>
/// <li><i>p < 0: B = pow(inverse(A),-p)</i>.</li>
/// </ul>
/// Implementation: Based on logarithms of 2, memory usage minimized.
/// </summary>
/// <param name="A">the source matrix; must be square; stays unaffected by this operation.</param>
/// <param name="p">the exponent, can be any number.</param>
/// <returns><i>B</i>, a newly constructed result matrix; storage-independent of <i>A</i>.</returns>
///<exception cref="ArgumentException">if <i>!property().isSquare(A)</i>.</exception>
public static DoubleMatrix2D Pow(DoubleMatrix2D A, int p)
{
// matrix multiplication based on log2 method: A*A*....*A is slow, ((A * A)^2)^2 * ..D is faster
// allocates two auxiliary matrices as work space
IBlas blas = SmpBlas.smpBlas; // for parallel matrix mult; if not initialized defaults to sequential blas
Property.DEFAULT.CheckSquare(A);
if (p < 0)
{
A = Inverse(A);
p = -p;
}
if (p == 0)
{
return(DoubleFactory2D.Dense.Identity(A.Rows));
}
DoubleMatrix2D T = A.Like(); // temporary
if (p == 1)
{
return(T.Assign(A)); // safes one auxiliary matrix allocation
}
if (p == 2)
{
blas.Dgemm(false, false, 1, A, A, 0, T); // mult(A,A); // safes one auxiliary matrix allocation
return(T);
}
int k = Cern.Colt.Bitvector.QuickBitVector.MostSignificantBit(p); // index of highest bit in state "true"
/*
* this is the naive version:
* DoubleMatrix2D B = A.Copy();
* for (int i=0; i<p-1; i++) {
* B = mult(B,A);
* }
* return B;
*/
// here comes the optimized version:
//cern.colt.Timer timer = new cern.colt.Timer().start();
int i = 0;
while (i <= k && (p & (1 << i)) == 0)
{ // while (bit i of p == false)
// A = mult(A,A); would allocate a lot of temporary memory
blas.Dgemm(false, false, 1, A, A, 0, T); // A.zMult(A,T);
DoubleMatrix2D swap = A; A = T; T = swap; // swap A with T
i++;
}
DoubleMatrix2D B = A.Copy();
i++;
for (; i <= k; i++)
{
// A = mult(A,A); would allocate a lot of temporary memory
blas.Dgemm(false, false, 1, A, A, 0, T); // A.zMult(A,T);
DoubleMatrix2D swap = A; A = T; T = swap; // swap A with T
if ((p & (1 << i)) != 0)
{ // if (bit i of p == true)
// B = mult(B,A); would allocate a lot of temporary memory
blas.Dgemm(false, false, 1, B, A, 0, T); // B.zMult(A,T);
swap = B; B = T; T = swap; // swap B with T
}
}
//timer.stop().Display();
return(B);
}
