Decomposition Operations<TReal, TComplex>.QRDecompose Method
Definition
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2
Overload List
QRDecompose( | Computes a QR factorization of a real M-by-N matrix A: A = Q * R. |
QRDecompose( | ZGEQRF computes a QR decomposition of a real M-by-N matrix A: A = Q * R. Arguments ========= M (input) INTEGER The number of rows of the matrix A. M >= 0. N (input) INTEGER The number of columns of the matrix A. N >= 0. A (input/output) DOUBLE PRECISION array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the min(M,N)-by-N upper trapezoidal matrix R (R is upper triangular if m >= n); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of min(m,n) elementary reflectors (see Further Zetails). LDA (input) INTEGER The leading dimension of the array A. LDA >= max(1,M). TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) The scalar factors of the elementary reflectors (see Further Zetails). WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) On exit, if INFO = 0, WORK(1) returns the optimal LWORK. LWORK (input) INTEGER The dimension of the array WORK. LWORK >= max(1,N). For optimum performance LWORK >= N*NB, where NB is the optimal blocksize. If LWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LWORK is issued by XERBLA. INFO (output) INTEGER = 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value Further Zetails =============== The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v' where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit inthis. A(i+1:m,i), and tau inthis. TAU(i). |
QRDecompose( | Computes a QR factorization of a real M-by-N matrix A: A = Q * R. |
QRDecompose( | ZGEQRF computes a QR decomposition of a real M-by-N matrix A: A = Q * R. Arguments ========= M (input) INTEGER The number of rows of the matrix A. M >= 0. N (input) INTEGER The number of columns of the matrix A. N >= 0. A (input/output) DOUBLE PRECISION array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the min(M,N)-by-N upper trapezoidal matrix R (R is upper triangular if m >= n); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of min(m,n) elementary reflectors (see Further Zetails). LDA (input) INTEGER The leading dimension of the array A. LDA >= max(1,M). TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) The scalar factors of the elementary reflectors (see Further Zetails). WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) On exit, if INFO = 0, WORK(1) returns the optimal LWORK. LWORK (input) INTEGER The dimension of the array WORK. LWORK >= max(1,N). For optimum performance LWORK >= N*NB, where NB is the optimal blocksize. If LWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LWORK is issued by XERBLA. INFO (output) INTEGER = 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value Further Zetails =============== The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v' where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit inthis. A(i+1:m,i), and tau inthis. TAU(i). |
QRDecompose( | Computes a QR factorization with column pivoting of a matrix A: A*P = Q*R using Level 3 BLAS. |
QRDecompose( | Computes a QR factorization with column pivoting of a matrix A: A*P = Q*R using Level 3 BLAS. |
QRDecompose( | Computes a QR factorization of a real M-by-N matrix A: A = Q * R. |
QRDecompose( | ZGEQRF computes a QR decomposition of a real M-by-N matrix A: A = Q * R. Arguments ========= M (input) INTEGER The number of rows of the matrix A. M >= 0. N (input) INTEGER The number of columns of the matrix A. N >= 0. A (input/output) DOUBLE PRECISION array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the min(M,N)-by-N upper trapezoidal matrix R (R is upper triangular if m >= n); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of min(m,n) elementary reflectors (see Further Zetails). LDA (input) INTEGER The leading dimension of the array A. LDA >= max(1,M). TAU (output) DOUBLE PRECISION array, dimension (min(M,N)) The scalar factors of the elementary reflectors (see Further Zetails). WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK) On exit, if INFO = 0, WORK(1) returns the optimal LWORK. LWORK (input) INTEGER The dimension of the array WORK. LWORK >= max(1,N). For optimum performance LWORK >= N*NB, where NB is the optimal blocksize. If LWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of the WORK array, returns this value as the first entry of the WORK array, and no error message related to LWORK is issued by XERBLA. INFO (output) INTEGER = 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value Further Zetails =============== The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v' where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit inthis. A(i+1:m,i), and tau inthis. TAU(i). |
QRDecompose( | Computes a QR factorization with column pivoting of a matrix A: A*P = Q*R using Level 3 BLAS. |
QRDecompose(Int32, Int32, Array2D<TReal>, Array1D<TReal>, Int32)
Computes a QR factorization of a real M-by-N matrix A: A = Q * R.
public void QRDecompose(
int m,
int n,
Array2D<TReal> a,
Array1D<TReal> tau,
out int info
)
Parameters
- m Int32
The number of rows of the matrix A. M >= 0.
- n Int32
The number of columns of the matrix A. N >= 0.
- a Array2D<TReal>
A is TReal array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the min(M,N)-by-N upper trapezoidal matrix R (R is upper triangular if m >= n); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of min(m,n) elementary reflectors (see Further Details).
The leading dimension of the array A. LDA >= max(1,M).
- tau Array1D<TReal>
TAU is TReal array, dimension (min(M,N)) The scalar factors of the elementary reflectors (see Further Details).
- info Int32
= 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value
Remarks
Further Details:
The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v**T where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), and tau in TAU(i).
This method corresponds to the LAPACK routine ?GEQRF.
QRDecompose(Int32, Int32, Array2D<TComplex>, Array1D<TComplex>, Int32)
public void QRDecompose(
int m,
int n,
Array2D<TComplex> a,
Array1D<TComplex> tau,
out int info
)
Parameters
QRDecompose(Int32, Int32, Span2D<TReal>, Span<TReal>, Int32)
Computes a QR factorization of a real M-by-N matrix A: A = Q * R.
public void QRDecompose(
int m,
int n,
Span2D<TReal> a,
Span<TReal> tau,
out int info
)
Parameters
- m Int32
The number of rows of the matrix A. M >= 0.
- n Int32
The number of columns of the matrix A. N >= 0.
- a Span2D<TReal>
A is TReal array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the min(M,N)-by-N upper trapezoidal matrix R (R is upper triangular if m >= n); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of min(m,n) elementary reflectors (see Further Details).
The leading dimension of the array A. LDA >= max(1,M).
- tau Span<TReal>
TAU is TReal array, dimension (min(M,N)) The scalar factors of the elementary reflectors (see Further Details).
- info Int32
= 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value
Remarks
Further Details:
The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v**T where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), and tau in TAU(i).
This method corresponds to the LAPACK routine ?GEQRF.
QRDecompose(Int32, Int32, Span2D<TComplex>, Span<TComplex>, Int32)
public void QRDecompose(
int m,
int n,
Span2D<TComplex> a,
Span<TComplex> tau,
out int info
)
Parameters
QRDecompose(Int32, Int32, Array2D<TReal>, Array1D<Int32>, Array1D<TReal>, Int32)
Computes a QR factorization with column pivoting of a matrix A: A*P = Q*R using Level 3 BLAS.
public void QRDecompose(
int m,
int n,
Array2D<TReal> a,
Array1D<int> jpvt,
Array1D<TReal> tau,
out int info
)
Parameters
- m Int32
The number of rows of the matrix A. M >= 0.
- n Int32
The number of columns of the matrix A. N >= 0.
- a Array2D<TReal>
A is TReal array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the upper triangle of the array contains the min(M,N)-by-N upper trapezoidal matrix R; the elements below the diagonal, together with the array TAU, represent the orthogonal matrix Q as a product of min(M,N) elementary reflectors.
The leading dimension of the array A. LDA >= max(1,M).
- jpvt Array1D<Int32>
Dimension (N) On entry, if JPVT(J).ne.0, the J-th column of A is permuted to the front of A*P (a leading column); if JPVT(J)=0, the J-th column of A is a free column. On exit, if JPVT(J)=K, then the J-th column of A*P was the the K-th column of A.
- tau Array1D<TReal>
TAU is TReal array, dimension (min(M,N)) The scalar factors of the elementary reflectors.
- info Int32
= 0: successful exit. < 0: if INFO = -i, the i-th argument had an illegal value.
Remarks
Further Details:
The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v**T where tau is a real/complex scalar, and v is a real/complex vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), and tau in TAU(i).
Contributors:
G. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain X. Sun, Computer Science Dept., Duke University, USA
This method corresponds to the LAPACK routine DGEQP3.
QRDecompose(Int32, Int32, Span2D<TReal>, Span<Int32>, Span<TReal>, Int32)
Computes a QR factorization with column pivoting of a matrix A: A*P = Q*R using Level 3 BLAS.
public void QRDecompose(
int m,
int n,
Span2D<TReal> a,
Span<int> jpvt,
Span<TReal> tau,
out int info
)
Parameters
- m Int32
The number of rows of the matrix A. M >= 0.
- n Int32
The number of columns of the matrix A. N >= 0.
- a Span2D<TReal>
A is TReal array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the upper triangle of the array contains the min(M,N)-by-N upper trapezoidal matrix R; the elements below the diagonal, together with the array TAU, represent the orthogonal matrix Q as a product of min(M,N) elementary reflectors.
The leading dimension of the array A. LDA >= max(1,M).
- jpvt Span<Int32>
Dimension (N) On entry, if JPVT(J).ne.0, the J-th column of A is permuted to the front of A*P (a leading column); if JPVT(J)=0, the J-th column of A is a free column. On exit, if JPVT(J)=K, then the J-th column of A*P was the the K-th column of A.
- tau Span<TReal>
TAU is TReal array, dimension (min(M,N)) The scalar factors of the elementary reflectors.
- info Int32
= 0: successful exit. < 0: if INFO = -i, the i-th argument had an illegal value.
Remarks
Further Details:
The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v**T where tau is a real/complex scalar, and v is a real/complex vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), and tau in TAU(i).
Contributors:
G. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain X. Sun, Computer Science Dept., Duke University, USA
This method corresponds to the LAPACK routine DGEQP3.
QRDecompose(Int32, Int32, Span<TReal>, Int32, Span<TReal>, Int32)
Computes a QR factorization of a real M-by-N matrix A: A = Q * R.
public abstract void QRDecompose(
int m,
int n,
Span<TReal> a,
int lda,
Span<TReal> tau,
out int info
)
Parameters
- m Int32
The number of rows of the matrix A. M >= 0.
- n Int32
The number of columns of the matrix A. N >= 0.
- a Span<TReal>
A is TReal array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the elements on and above the diagonal of the array contain the min(M,N)-by-N upper trapezoidal matrix R (R is upper triangular if m >= n); the elements below the diagonal, with the array TAU, represent the orthogonal matrix Q as a product of min(m,n) elementary reflectors (see Further Details).
- lda Int32
The leading dimension of the array A. LDA >= max(1,M).
- tau Span<TReal>
TAU is TReal array, dimension (min(M,N)) The scalar factors of the elementary reflectors (see Further Details).
- info Int32
= 0: successful exit < 0: if INFO = -i, the i-th argument had an illegal value
Remarks
Further Details:
The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v**T where tau is a real scalar, and v is a real vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), and tau in TAU(i).
This method corresponds to the LAPACK routine ?GEQRF.
QRDecompose(Int32, Int32, Span<TComplex>, Int32, Span<TComplex>, Int32)
public abstract void QRDecompose(
int m,
int n,
Span<TComplex> a,
int lda,
Span<TComplex> tau,
out int info
)
Parameters
QRDecompose(Int32, Int32, Span<TReal>, Int32, Span<Int32>, Span<TReal>, Int32)
Computes a QR factorization with column pivoting of a matrix A: A*P = Q*R using Level 3 BLAS.
public abstract void QRDecompose(
int m,
int n,
Span<TReal> a,
int lda,
Span<int> jpvt,
Span<TReal> tau,
out int info
)
Parameters
- m Int32
The number of rows of the matrix A. M >= 0.
- n Int32
The number of columns of the matrix A. N >= 0.
- a Span<TReal>
A is TReal array, dimension (LDA,N) On entry, the M-by-N matrix A. On exit, the upper triangle of the array contains the min(M,N)-by-N upper trapezoidal matrix R; the elements below the diagonal, together with the array TAU, represent the orthogonal matrix Q as a product of min(M,N) elementary reflectors.
- lda Int32
The leading dimension of the array A. LDA >= max(1,M).
- jpvt Span<Int32>
Dimension (N) On entry, if JPVT(J).ne.0, the J-th column of A is permuted to the front of A*P (a leading column); if JPVT(J)=0, the J-th column of A is a free column. On exit, if JPVT(J)=K, then the J-th column of A*P was the the K-th column of A.
- tau Span<TReal>
TAU is TReal array, dimension (min(M,N)) The scalar factors of the elementary reflectors.
- info Int32
= 0: successful exit. < 0: if INFO = -i, the i-th argument had an illegal value.
Remarks
Further Details:
The matrix Q is represented as a product of elementary reflectors Q = H(1) H(2) . . . H(k), where k = min(m,n). Each H(i) has the form H(i) = I - tau * v * v**T where tau is a real/complex scalar, and v is a real/complex vector with v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i), and tau in TAU(i).
Contributors:
G. Quintana-Orti, Depto. de Informatica, Universidad Jaime I, Spain X. Sun, Computer Science Dept., Duke University, USA
This method corresponds to the LAPACK routine DGEQP3.