Documentation ¶
Overview ¶
Package native is a Go implementation of the BLAS API. This implementation panics when the input arguments are invalid as per the standard, for example if a vector increment is zero. Please note that the treatment of NaN values is not specified, and differs among the BLAS implementations. github.com/gonum/blas/blas64 provides helpful wrapper functions to the BLAS interface. The rest of this text describes the layout of the data for the input types.
Please note that in the function documentation, x[i] refers to the i^th element of the vector, which will be different from the i^th element of the slice if incX != 1.
See http://www.netlib.org/lapack/explore-html/d4/de1/_l_i_c_e_n_s_e_source.html for more license information.
Vector arguments are effectively strided slices. They have two input arguments, a number of elements, n, and an increment, incX. The increment specifies the distance between elements of the vector. The actual Go slice may be longer than necessary. The increment may be positive or negative, except in functions with only a single vector argument where the increment may only be positive. If the increment is negative, s[0] is the last element in the slice. Note that this is not the same as counting backward from the end of the slice, as len(s) may be longer than necessary. So, for example, if n = 5 and incX = 3, the elements of s are
[0 * * 1 * * 2 * * 3 * * 4 * * * ...]
where ∗ elements are never accessed. If incX = -3, the same elements are accessed, just in reverse order (4, 3, 2, 1, 0).
Dense matrices are specified by a number of rows, a number of columns, and a stride. The stride specifies the number of entries in the slice between the first element of successive rows. The stride must be at least as large as the number of columns but may be longer.
[a00 ... a0n a0* ... a1stride-1 a21 ... amn am* ... amstride-1]
Thus, dense[i*ld + j] refers to the {i, j}th element of the matrix.
Symmetric and triangular matrices (non-packed) are stored identically to Dense, except that only elements in one triangle of the matrix are accessed.
Packed symmetric and packed triangular matrices are laid out with the entries condensed such that all of the unreferenced elements are removed. So, the upper triangular matrix
[ 1 2 3 0 4 5 0 0 6 ]
and the lower-triangular matrix
[ 1 0 0 2 3 0 4 5 6 ]
will both be compacted as [1 2 3 4 5 6]. The (i, j) element of the original dense matrix can be found at element i*n - (i-1)*i/2 + j for upper triangular, and at element i * (i+1) /2 + j for lower triangular.
Banded matrices are laid out in a compact format, constructed by removing the zeros in the rows and aligning the diagonals. For example, the matrix
[ 1 2 3 0 0 0 4 5 6 7 0 0 0 8 9 10 11 0 0 0 12 13 14 15 0 0 0 16 17 18 0 0 0 0 19 20 ]
implicitly becomes (∗ entries are never accessed)
[ * 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 * 19 20 * * ]
which is given to the BLAS routine is [∗ 1 2 3 4 ...].
See http://www.crest.iu.edu/research/mtl/reference/html/banded.html for more information
Index ¶
- type Implementation
- func (Implementation) Dasum(n int, x []float64, incX int) float64
- func (Implementation) Daxpy(n int, alpha float64, x []float64, incX int, y []float64, incY int)
- func (Implementation) Dcopy(n int, x []float64, incX int, y []float64, incY int)
- func (Implementation) Ddot(n int, x []float64, incX int, y []float64, incY int) float64
- func (Implementation) Dgbmv(tA blas.Transpose, m, n, kL, kU int, alpha float64, a []float64, lda int, ...)
- func (Implementation) Dgemm(tA, tB blas.Transpose, m, n, k int, alpha float64, a []float64, lda int, ...)
- func (Implementation) Dgemv(tA blas.Transpose, m, n int, alpha float64, a []float64, lda int, x []float64, ...)
- func (Implementation) Dger(m, n int, alpha float64, x []float64, incX int, y []float64, incY int, ...)
- func (Implementation) Dnrm2(n int, x []float64, incX int) float64
- func (Implementation) Drot(n int, x []float64, incX int, y []float64, incY int, c float64, s float64)
- func (Implementation) Drotg(a, b float64) (c, s, r, z float64)
- func (Implementation) Drotm(n int, x []float64, incX int, y []float64, incY int, p blas.DrotmParams)
- func (Implementation) Drotmg(d1, d2, x1, y1 float64) (p blas.DrotmParams, rd1, rd2, rx1 float64)
- func (Implementation) Dsbmv(ul blas.Uplo, n, k int, alpha float64, a []float64, lda int, x []float64, ...)
- func (Implementation) Dscal(n int, alpha float64, x []float64, incX int)
- func (Implementation) Dspmv(ul blas.Uplo, n int, alpha float64, a []float64, x []float64, incX int, ...)
- func (Implementation) Dspr(ul blas.Uplo, n int, alpha float64, x []float64, incX int, a []float64)
- func (Implementation) Dspr2(ul blas.Uplo, n int, alpha float64, x []float64, incX int, y []float64, ...)
- func (Implementation) Dswap(n int, x []float64, incX int, y []float64, incY int)
- func (Implementation) Dsymm(s blas.Side, ul blas.Uplo, m, n int, alpha float64, a []float64, lda int, ...)
- func (Implementation) Dsymv(ul blas.Uplo, n int, alpha float64, a []float64, lda int, x []float64, ...)
- func (Implementation) Dsyr(ul blas.Uplo, n int, alpha float64, x []float64, incX int, a []float64, ...)
- func (Implementation) Dsyr2(ul blas.Uplo, n int, alpha float64, x []float64, incX int, y []float64, ...)
- func (Implementation) Dsyr2k(ul blas.Uplo, tA blas.Transpose, n, k int, alpha float64, a []float64, lda int, ...)
- func (Implementation) Dsyrk(ul blas.Uplo, tA blas.Transpose, n, k int, alpha float64, a []float64, lda int, ...)
- func (Implementation) Dtbmv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n, k int, a []float64, lda int, ...)
- func (Implementation) Dtbsv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n, k int, a []float64, lda int, ...)
- func (Implementation) Dtpmv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, ap []float64, x []float64, ...)
- func (Implementation) Dtpsv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, a []float64, x []float64, ...)
- func (Implementation) Dtrmm(s blas.Side, ul blas.Uplo, tA blas.Transpose, d blas.Diag, m, n int, ...)
- func (Implementation) Dtrmv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, a []float64, lda int, ...)
- func (Implementation) Dtrsm(s blas.Side, ul blas.Uplo, tA blas.Transpose, d blas.Diag, m, n int, ...)
- func (Implementation) Dtrsv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, a []float64, lda int, ...)
- func (Implementation) Idamax(n int, x []float64, incX int) int
Constants ¶
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Variables ¶
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Functions ¶
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Types ¶
type Implementation ¶
type Implementation struct{}
func (Implementation) Dasum ¶
func (Implementation) Dasum(n int, x []float64, incX int) float64
Dasum computes the sum of the absolute values of the elements of x.
\sum_i |x[i]|
Dasum returns 0 if incX is negative.
func (Implementation) Dcopy ¶
Dcopy copies the elements of x into the elements of y.
y[i] = x[i] for all i
func (Implementation) Dgbmv ¶
func (Implementation) Dgbmv(tA blas.Transpose, m, n, kL, kU int, alpha float64, a []float64, lda int, x []float64, incX int, beta float64, y []float64, incY int)
Dgbmv computes
y = alpha * A * x + beta * y if tA == blas.NoTrans y = alpha * A^T * x + beta * y if tA == blas.Trans
where a is an m×n band matrix kL subdiagonals and kU super-diagonals, and m and n refer to the size of the full dense matrix it represents. x and y are vectors, and alpha and beta are scalars.
func (Implementation) Dgemm ¶
func (Implementation) Dgemm(tA, tB blas.Transpose, m, n, k int, alpha float64, a []float64, lda int, b []float64, ldb int, beta float64, c []float64, ldc int)
Dgemm computes
C = beta * C + alpha * A * B.
tA and tB specify whether A or B are transposed. A, B, and C are n×n dense matrices.
func (Implementation) Dgemv ¶
func (Implementation) Dgemv(tA blas.Transpose, m, n int, alpha float64, a []float64, lda int, x []float64, incX int, beta float64, y []float64, incY int)
Dgemv computes
y = alpha * a * x + beta * y if tA = blas.NoTrans y = alpha * A^T * x + beta * y if tA = blas.Trans or blas.ConjTrans
where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
func (Implementation) Dger ¶
func (Implementation) Dger(m, n int, alpha float64, x []float64, incX int, y []float64, incY int, a []float64, lda int)
Dger performs the rank-one operation
A += alpha * x * y^T
where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
func (Implementation) Dnrm2 ¶
func (Implementation) Dnrm2(n int, x []float64, incX int) float64
Dnrm2 computes the Euclidean norm of a vector,
sqrt(\sum_i x[i] * x[i]).
This function returns 0 if incX is negative.
func (Implementation) Drot ¶
func (Implementation) Drot(n int, x []float64, incX int, y []float64, incY int, c float64, s float64)
Drot applies a plane transformation.
x[i] = c * x[i] + s * y[i] y[i] = c * y[i] - s * x[i]
func (Implementation) Drotg ¶
func (Implementation) Drotg(a, b float64) (c, s, r, z float64)
Drotg computes the plane rotation
_ _ _ _ _ _ | c s | | a | | r | | -s c | * | b | = | 0 | ‾ ‾ ‾ ‾ ‾ ‾
where
r = ±(a^2 + b^2) c = a/r, the cosine of the plane rotation s = b/r, the sine of the plane rotation
NOTE: There is a discrepancy between the refence implementation and the BLAS technical manual regarding the sign for r when a or b are zero. Drotg agrees with the definition in the manual and other common BLAS implementations.
func (Implementation) Drotm ¶
func (Implementation) Drotm(n int, x []float64, incX int, y []float64, incY int, p blas.DrotmParams)
Drotm applies the modified Givens rotation to the 2⨉n matrix.
func (Implementation) Drotmg ¶
func (Implementation) Drotmg(d1, d2, x1, y1 float64) (p blas.DrotmParams, rd1, rd2, rx1 float64)
Drotmg computes the modified Givens rotation. See http://www.netlib.org/lapack/explore-html/df/deb/drotmg_8f.html for more details.
func (Implementation) Dsbmv ¶
func (Implementation) Dsbmv(ul blas.Uplo, n, k int, alpha float64, a []float64, lda int, x []float64, incX int, beta float64, y []float64, incY int)
Dsbmv performs
y = alpha * A * x + beta * y
where A is an n×n symmetric banded matrix, x and y are vectors, and alpha and beta are scalars.
func (Implementation) Dscal ¶
func (Implementation) Dscal(n int, alpha float64, x []float64, incX int)
Dscal scales x by alpha.
x[i] *= alpha
Dscal has no effect if incX < 0.
func (Implementation) Dspmv ¶
func (Implementation) Dspmv(ul blas.Uplo, n int, alpha float64, a []float64, x []float64, incX int, beta float64, y []float64, incY int)
Dspmv performs
y = alpha * A * x + beta * y,
where A is an n×n symmetric matrix in packed format, x and y are vectors and alpha and beta are scalars.
func (Implementation) Dspr ¶
Dspr computes the rank-one operation
a += alpha * x * x^T
where a is an n×n symmetric matrix in packed format, x is a vector, and alpha is a scalar.
func (Implementation) Dspr2 ¶
func (Implementation) Dspr2(ul blas.Uplo, n int, alpha float64, x []float64, incX int, y []float64, incY int, a []float64)
Dspr2 performs the symmetric rank-2 update
a += alpha * x * y^T + alpha * y * x^T
where a is an n×n symmetric matirx in packed format and x and y are vectors.
func (Implementation) Dswap ¶
Dswap exchanges the elements of two vectors.
x[i], y[i] = y[i], x[i] for all i
func (Implementation) Dsymm ¶
func (Implementation) Dsymm(s blas.Side, ul blas.Uplo, m, n int, alpha float64, a []float64, lda int, b []float64, ldb int, beta float64, c []float64, ldc int)
Dsymm performs one of
C = alpha * A * B + beta * C if side == blas.Left C = alpha * B * A + beta * C if side == blas.Right
where A is an n×n symmetric matrix, B and C are m×n matrices, and alpha is a scalar.
func (Implementation) Dsymv ¶
func (Implementation) Dsymv(ul blas.Uplo, n int, alpha float64, a []float64, lda int, x []float64, incX int, beta float64, y []float64, incY int)
Dsymv computes
y = alpha * A * x + beta * y,
where a is an n×n symmetric matrix, x and y are vectors, and alpha and beta are scalars.
func (Implementation) Dsyr ¶
func (Implementation) Dsyr(ul blas.Uplo, n int, alpha float64, x []float64, incX int, a []float64, lda int)
Dsyr performs the rank-one update
a += alpha * x * x^T
where a is an n×n symmetric matrix, and x is a vector.
func (Implementation) Dsyr2 ¶
func (Implementation) Dsyr2(ul blas.Uplo, n int, alpha float64, x []float64, incX int, y []float64, incY int, a []float64, lda int)
Dsyr2 performs the symmetric rank-two update
A += alpha * x * y^T + alpha * y * x^T
where A is a symmetric n×n matrix, x and y are vectors, and alpha is a scalar.
func (Implementation) Dsyr2k ¶
func (Implementation) Dsyr2k(ul blas.Uplo, tA blas.Transpose, n, k int, alpha float64, a []float64, lda int, b []float64, ldb int, beta float64, c []float64, ldc int)
Dsyr2k performs the symmetric rank 2k operation
C = alpha * A * B^T + alpha * B * A^T + beta * C
where C is an n×n symmetric matrix. A and B are n×k matrices if tA == NoTrans and k×n otherwise. alpha and beta are scalars.
func (Implementation) Dsyrk ¶
func (Implementation) Dsyrk(ul blas.Uplo, tA blas.Transpose, n, k int, alpha float64, a []float64, lda int, beta float64, c []float64, ldc int)
Dsyrk performs the symmetric rank-k operation
C = alpha * A * A^T + beta*C
C is an n×n symmetric matrix. A is an n×k matrix if tA == blas.NoTrans, and a k×n matrix otherwise. alpha and beta are scalars.
func (Implementation) Dtbmv ¶
func (Implementation) Dtbmv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n, k int, a []float64, lda int, x []float64, incX int)
Dtbmv computes
x = A * x if tA == blas.NoTrans x = A^T * x if tA == blas.Trans
where A is an n×n triangular banded matrix with k diagonals, and x is a vector.
func (Implementation) Dtbsv ¶
func (Implementation) Dtbsv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n, k int, a []float64, lda int, x []float64, incX int)
Dtbsv solves
A * x = b
where A is an n×n triangular banded matrix with k diagonals in packed format, and x is a vector. At entry to the function, x contains the values of b, and the result is stored in place into x.
No test for singularity or near-singularity is included in this routine. Such tests must be performed before calling this routine.
func (Implementation) Dtpmv ¶
func (Implementation) Dtpmv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, ap []float64, x []float64, incX int)
Dtpmv computes
x = A * x if tA == blas.NoTrans x = A^T * x if tA == blas.Trans
where A is an n×n unit triangular matrix in packed format, and x is a vector.
func (Implementation) Dtpsv ¶
func (Implementation) Dtpsv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, a []float64, x []float64, incX int)
Dtpsv solves
A * x = b if tA == blas.NoTrans A^T * x = b if tA == blas.Trans
where A is an n×n triangular matrix in packed format and x is a vector. At entry to the function, x contains the values of b, and the result is stored in place into x.
No test for singularity or near-singularity is included in this routine. Such tests must be performed before calling this routine.
func (Implementation) Dtrmm ¶
func (Implementation) Dtrmm(s blas.Side, ul blas.Uplo, tA blas.Transpose, d blas.Diag, m, n int, alpha float64, a []float64, lda int, b []float64, ldb int)
Dtrmm performs
B = alpha * A * B if tA == blas.NoTrans and side == blas.Left B = alpha * A^T * B if tA == blas.Trans and side == blas.Left B = alpha * B * A if tA == blas.NoTrans and side == blas.Right B = alpha * B * A^T if tA == blas.Trans and side == blas.Right
where A is an n×n triangular matrix, and B is an m×n matrix.
func (Implementation) Dtrmv ¶
func (Implementation) Dtrmv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, a []float64, lda int, x []float64, incX int)
Dtrmv computes
x = A * x if tA == blas.NoTrans x = A^T * x if tA == blas.Trans
A is an n×n Triangular matrix and x is a vector.
func (Implementation) Dtrsm ¶
func (Implementation) Dtrsm(s blas.Side, ul blas.Uplo, tA blas.Transpose, d blas.Diag, m, n int, alpha float64, a []float64, lda int, b []float64, ldb int)
Dtrsm solves
A * X = alpha * B if tA == blas.NoTrans, side == blas.Left A^T * X = alpha * B if tA == blas.Trans, side == blas.Left X * A = alpha * B if tA == blas.NoTrans, side == blas.Right X * A^T = alpha * B if tA == blas.Trans, side == blas.Right
where A is an n×n triangular matrix, x is an m×n matrix, and alpha is a scalar.
At entry to the function, X contains the values of B, and the result is stored in place into X.
No check is made that A is invertible.
func (Implementation) Dtrsv ¶
func (Implementation) Dtrsv(ul blas.Uplo, tA blas.Transpose, d blas.Diag, n int, a []float64, lda int, x []float64, incX int)
Dtrsv solves
A * x = b if tA == blas.NoTrans A^T * x = b if tA == blas.Trans
A is an n×n triangular matrix and x is a vector. At entry to the function, x contains the values of b, and the result is stored in place into x.
No test for singularity or near-singularity is included in this routine. Such tests must be performed before calling this routine.