+++ /dev/null
-// Copyright ©2015 The Gonum Authors. All rights reserved.
-// Use of this source code is governed by a BSD-style
-// license that can be found in the LICENSE file.
-
-package cblas64
-
-import (
- "gonum.org/v1/gonum/blas"
- "gonum.org/v1/gonum/blas/gonum"
-)
-
-var cblas64 blas.Complex64 = gonum.Implementation{}
-
-// Use sets the BLAS complex64 implementation to be used by subsequent BLAS calls.
-// The default implementation is cgo.Implementation.
-func Use(b blas.Complex64) {
- cblas64 = b
-}
-
-// Implementation returns the current BLAS complex64 implementation.
-//
-// Implementation allows direct calls to the current the BLAS complex64 implementation
-// giving finer control of parameters.
-func Implementation() blas.Complex64 {
- return cblas64
-}
-
-// Vector represents a vector with an associated element increment.
-type Vector struct {
- Inc int
- Data []complex64
-}
-
-// General represents a matrix using the conventional storage scheme.
-type General struct {
- Rows, Cols int
- Stride int
- Data []complex64
-}
-
-// Band represents a band matrix using the band storage scheme.
-type Band struct {
- Rows, Cols int
- KL, KU int
- Stride int
- Data []complex64
-}
-
-// Triangular represents a triangular matrix using the conventional storage scheme.
-type Triangular struct {
- N int
- Stride int
- Data []complex64
- Uplo blas.Uplo
- Diag blas.Diag
-}
-
-// TriangularBand represents a triangular matrix using the band storage scheme.
-type TriangularBand struct {
- N, K int
- Stride int
- Data []complex64
- Uplo blas.Uplo
- Diag blas.Diag
-}
-
-// TriangularPacked represents a triangular matrix using the packed storage scheme.
-type TriangularPacked struct {
- N int
- Data []complex64
- Uplo blas.Uplo
- Diag blas.Diag
-}
-
-// Symmetric represents a symmetric matrix using the conventional storage scheme.
-type Symmetric struct {
- N int
- Stride int
- Data []complex64
- Uplo blas.Uplo
-}
-
-// SymmetricBand represents a symmetric matrix using the band storage scheme.
-type SymmetricBand struct {
- N, K int
- Stride int
- Data []complex64
- Uplo blas.Uplo
-}
-
-// SymmetricPacked represents a symmetric matrix using the packed storage scheme.
-type SymmetricPacked struct {
- N int
- Data []complex64
- Uplo blas.Uplo
-}
-
-// Hermitian represents an Hermitian matrix using the conventional storage scheme.
-type Hermitian Symmetric
-
-// HermitianBand represents an Hermitian matrix using the band storage scheme.
-type HermitianBand SymmetricBand
-
-// HermitianPacked represents an Hermitian matrix using the packed storage scheme.
-type HermitianPacked SymmetricPacked
-
-// Level 1
-
-const negInc = "cblas64: negative vector increment"
-
-// Dotu computes the dot product of the two vectors without
-// complex conjugation:
-// x^T * y
-func Dotu(n int, x, y Vector) complex64 {
- return cblas64.Cdotu(n, x.Data, x.Inc, y.Data, y.Inc)
-}
-
-// Dotc computes the dot product of the two vectors with
-// complex conjugation:
-// x^H * y.
-func Dotc(n int, x, y Vector) complex64 {
- return cblas64.Cdotc(n, x.Data, x.Inc, y.Data, y.Inc)
-}
-
-// Nrm2 computes the Euclidean norm of the vector x:
-// sqrt(\sum_i x[i] * x[i]).
-//
-// Nrm2 will panic if the vector increment is negative.
-func Nrm2(n int, x Vector) float32 {
- if x.Inc < 0 {
- panic(negInc)
- }
- return cblas64.Scnrm2(n, x.Data, x.Inc)
-}
-
-// Asum computes the sum of magnitudes of the real and imaginary parts of
-// elements of the vector x:
-// \sum_i (|Re x[i]| + |Im x[i]|).
-//
-// Asum will panic if the vector increment is negative.
-func Asum(n int, x Vector) float32 {
- if x.Inc < 0 {
- panic(negInc)
- }
- return cblas64.Scasum(n, x.Data, x.Inc)
-}
-
-// Iamax returns the index of an element of x with the largest sum of
-// magnitudes of the real and imaginary parts (|Re x[i]|+|Im x[i]|).
-// If there are multiple such indices, the earliest is returned.
-//
-// Iamax returns -1 if n == 0.
-//
-// Iamax will panic if the vector increment is negative.
-func Iamax(n int, x Vector) int {
- if x.Inc < 0 {
- panic(negInc)
- }
- return cblas64.Icamax(n, x.Data, x.Inc)
-}
-
-// Swap exchanges the elements of two vectors:
-// x[i], y[i] = y[i], x[i] for all i.
-func Swap(n int, x, y Vector) {
- cblas64.Cswap(n, x.Data, x.Inc, y.Data, y.Inc)
-}
-
-// Copy copies the elements of x into the elements of y:
-// y[i] = x[i] for all i.
-func Copy(n int, x, y Vector) {
- cblas64.Ccopy(n, x.Data, x.Inc, y.Data, y.Inc)
-}
-
-// Axpy computes
-// y = alpha * x + y,
-// where x and y are vectors, and alpha is a scalar.
-func Axpy(n int, alpha complex64, x, y Vector) {
- cblas64.Caxpy(n, alpha, x.Data, x.Inc, y.Data, y.Inc)
-}
-
-// Scal computes
-// x = alpha * x,
-// where x is a vector, and alpha is a scalar.
-//
-// Scal will panic if the vector increment is negative.
-func Scal(n int, alpha complex64, x Vector) {
- if x.Inc < 0 {
- panic(negInc)
- }
- cblas64.Cscal(n, alpha, x.Data, x.Inc)
-}
-
-// Dscal computes
-// x = alpha * x,
-// where x is a vector, and alpha is a real scalar.
-//
-// Dscal will panic if the vector increment is negative.
-func Dscal(n int, alpha float32, x Vector) {
- if x.Inc < 0 {
- panic(negInc)
- }
- cblas64.Csscal(n, alpha, x.Data, x.Inc)
-}
-
-// Level 2
-
-// Gemv computes
-// y = alpha * A * x + beta * y, if t == blas.NoTrans,
-// y = alpha * A^T * x + beta * y, if t == blas.Trans,
-// y = alpha * A^H * x + beta * y, if t == blas.ConjTrans,
-// where A is an m×n dense matrix, x and y are vectors, and alpha and beta are
-// scalars.
-func Gemv(t blas.Transpose, alpha complex64, a General, x Vector, beta complex64, y Vector) {
- cblas64.Cgemv(t, a.Rows, a.Cols, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
-}
-
-// Gbmv computes
-// y = alpha * A * x + beta * y, if t == blas.NoTrans,
-// y = alpha * A^T * x + beta * y, if t == blas.Trans,
-// y = alpha * A^H * x + beta * y, if t == blas.ConjTrans,
-// where A is an m×n band matrix, x and y are vectors, and alpha and beta are
-// scalars.
-func Gbmv(t blas.Transpose, alpha complex64, a Band, x Vector, beta complex64, y Vector) {
- cblas64.Cgbmv(t, a.Rows, a.Cols, a.KL, a.KU, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
-}
-
-// Trmv computes
-// x = A * x, if t == blas.NoTrans,
-// x = A^T * x, if t == blas.Trans,
-// x = A^H * x, if t == blas.ConjTrans,
-// where A is an n×n triangular matrix, and x is a vector.
-func Trmv(t blas.Transpose, a Triangular, x Vector) {
- cblas64.Ctrmv(a.Uplo, t, a.Diag, a.N, a.Data, a.Stride, x.Data, x.Inc)
-}
-
-// Tbmv computes
-// x = A * x, if t == blas.NoTrans,
-// x = A^T * x, if t == blas.Trans,
-// x = A^H * x, if t == blas.ConjTrans,
-// where A is an n×n triangular band matrix, and x is a vector.
-func Tbmv(t blas.Transpose, a TriangularBand, x Vector) {
- cblas64.Ctbmv(a.Uplo, t, a.Diag, a.N, a.K, a.Data, a.Stride, x.Data, x.Inc)
-}
-
-// Tpmv computes
-// x = A * x, if t == blas.NoTrans,
-// x = A^T * x, if t == blas.Trans,
-// x = A^H * x, if t == blas.ConjTrans,
-// where A is an n×n triangular matrix in packed format, and x is a vector.
-func Tpmv(t blas.Transpose, a TriangularPacked, x Vector) {
- cblas64.Ctpmv(a.Uplo, t, a.Diag, a.N, a.Data, x.Data, x.Inc)
-}
-
-// Trsv solves
-// A * x = b, if t == blas.NoTrans,
-// A^T * x = b, if t == blas.Trans,
-// A^H * x = b, if t == blas.ConjTrans,
-// where 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.
-func Trsv(t blas.Transpose, a Triangular, x Vector) {
- cblas64.Ctrsv(a.Uplo, t, a.Diag, a.N, a.Data, a.Stride, x.Data, x.Inc)
-}
-
-// Tbsv solves
-// A * x = b, if t == blas.NoTrans,
-// A^T * x = b, if t == blas.Trans,
-// A^H * x = b, if t == blas.ConjTrans,
-// where A is an n×n triangular band 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.
-func Tbsv(t blas.Transpose, a TriangularBand, x Vector) {
- cblas64.Ctbsv(a.Uplo, t, a.Diag, a.N, a.K, a.Data, a.Stride, x.Data, x.Inc)
-}
-
-// Tpsv solves
-// A * x = b, if t == blas.NoTrans,
-// A^T * x = b, if t == blas.Trans,
-// A^H * x = b, if t == blas.ConjTrans,
-// 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 Tpsv(t blas.Transpose, a TriangularPacked, x Vector) {
- cblas64.Ctpsv(a.Uplo, t, a.Diag, a.N, a.Data, x.Data, x.Inc)
-}
-
-// Hemv computes
-// y = alpha * A * x + beta * y,
-// where A is an n×n Hermitian matrix, x and y are vectors, and alpha and
-// beta are scalars.
-func Hemv(alpha complex64, a Hermitian, x Vector, beta complex64, y Vector) {
- cblas64.Chemv(a.Uplo, a.N, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
-}
-
-// Hbmv performs
-// y = alpha * A * x + beta * y,
-// where A is an n×n Hermitian band matrix, x and y are vectors, and alpha
-// and beta are scalars.
-func Hbmv(alpha complex64, a HermitianBand, x Vector, beta complex64, y Vector) {
- cblas64.Chbmv(a.Uplo, a.N, a.K, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
-}
-
-// Hpmv performs
-// y = alpha * A * x + beta * y,
-// where A is an n×n Hermitian matrix in packed format, x and y are vectors,
-// and alpha and beta are scalars.
-func Hpmv(alpha complex64, a HermitianPacked, x Vector, beta complex64, y Vector) {
- cblas64.Chpmv(a.Uplo, a.N, alpha, a.Data, x.Data, x.Inc, beta, y.Data, y.Inc)
-}
-
-// Geru performs a rank-1 update
-// A += alpha * x * y^T,
-// where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
-func Geru(alpha complex64, x, y Vector, a General) {
- cblas64.Cgeru(a.Rows, a.Cols, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data, a.Stride)
-}
-
-// Gerc performs a rank-1 update
-// A += alpha * x * y^H,
-// where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
-func Gerc(alpha complex64, x, y Vector, a General) {
- cblas64.Cgerc(a.Rows, a.Cols, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data, a.Stride)
-}
-
-// Her performs a rank-1 update
-// A += alpha * x * y^T,
-// where A is an m×n Hermitian matrix, x and y are vectors, and alpha is a scalar.
-func Her(alpha float32, x Vector, a Hermitian) {
- cblas64.Cher(a.Uplo, a.N, alpha, x.Data, x.Inc, a.Data, a.Stride)
-}
-
-// Hpr performs a rank-1 update
-// A += alpha * x * x^H,
-// where A is an n×n Hermitian matrix in packed format, x is a vector, and
-// alpha is a scalar.
-func Hpr(alpha float32, x Vector, a HermitianPacked) {
- cblas64.Chpr(a.Uplo, a.N, alpha, x.Data, x.Inc, a.Data)
-}
-
-// Her2 performs a rank-2 update
-// A += alpha * x * y^H + conj(alpha) * y * x^H,
-// where A is an n×n Hermitian matrix, x and y are vectors, and alpha is a scalar.
-func Her2(alpha complex64, x, y Vector, a Hermitian) {
- cblas64.Cher2(a.Uplo, a.N, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data, a.Stride)
-}
-
-// Hpr2 performs a rank-2 update
-// A += alpha * x * y^H + conj(alpha) * y * x^H,
-// where A is an n×n Hermitian matrix in packed format, x and y are vectors,
-// and alpha is a scalar.
-func Hpr2(alpha complex64, x, y Vector, a HermitianPacked) {
- cblas64.Chpr2(a.Uplo, a.N, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data)
-}
-
-// Level 3
-
-// Gemm computes
-// C = alpha * A * B + beta * C,
-// where A, B, and C are dense matrices, and alpha and beta are scalars.
-// tA and tB specify whether A or B are transposed or conjugated.
-func Gemm(tA, tB blas.Transpose, alpha complex64, a, b General, beta complex64, c General) {
- var m, n, k int
- if tA == blas.NoTrans {
- m, k = a.Rows, a.Cols
- } else {
- m, k = a.Cols, a.Rows
- }
- if tB == blas.NoTrans {
- n = b.Cols
- } else {
- n = b.Rows
- }
- cblas64.Cgemm(tA, tB, m, n, k, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
-}
-
-// Symm performs
-// C = alpha * A * B + beta * C, if s == blas.Left,
-// C = alpha * B * A + beta * C, if s == blas.Right,
-// where A is an n×n or m×m symmetric matrix, B and C are m×n matrices, and
-// alpha and beta are scalars.
-func Symm(s blas.Side, alpha complex64, a Symmetric, b General, beta complex64, c General) {
- var m, n int
- if s == blas.Left {
- m, n = a.N, b.Cols
- } else {
- m, n = b.Rows, a.N
- }
- cblas64.Csymm(s, a.Uplo, m, n, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
-}
-
-// Syrk performs a symmetric rank-k update
-// C = alpha * A * A^T + beta * C, if t == blas.NoTrans,
-// C = alpha * A^T * A + beta * C, if t == blas.Trans,
-// where C is an n×n symmetric matrix, A is an n×k matrix if t == blas.NoTrans
-// and a k×n matrix otherwise, and alpha and beta are scalars.
-func Syrk(t blas.Transpose, alpha complex64, a General, beta complex64, c Symmetric) {
- var n, k int
- if t == blas.NoTrans {
- n, k = a.Rows, a.Cols
- } else {
- n, k = a.Cols, a.Rows
- }
- cblas64.Csyrk(c.Uplo, t, n, k, alpha, a.Data, a.Stride, beta, c.Data, c.Stride)
-}
-
-// Syr2k performs a symmetric rank-2k update
-// C = alpha * A * B^T + alpha * B * A^T + beta * C, if t == blas.NoTrans,
-// C = alpha * A^T * B + alpha * B^T * A + beta * C, if t == blas.Trans,
-// where C is an n×n symmetric matrix, A and B are n×k matrices if
-// t == blas.NoTrans and k×n otherwise, and alpha and beta are scalars.
-func Syr2k(t blas.Transpose, alpha complex64, a, b General, beta complex64, c Symmetric) {
- var n, k int
- if t == blas.NoTrans {
- n, k = a.Rows, a.Cols
- } else {
- n, k = a.Cols, a.Rows
- }
- cblas64.Csyr2k(c.Uplo, t, n, k, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
-}
-
-// Trmm performs
-// B = alpha * A * B, if tA == blas.NoTrans and s == blas.Left,
-// B = alpha * A^T * B, if tA == blas.Trans and s == blas.Left,
-// B = alpha * A^H * B, if tA == blas.ConjTrans and s == blas.Left,
-// B = alpha * B * A, if tA == blas.NoTrans and s == blas.Right,
-// B = alpha * B * A^T, if tA == blas.Trans and s == blas.Right,
-// B = alpha * B * A^H, if tA == blas.ConjTrans and s == blas.Right,
-// where A is an n×n or m×m triangular matrix, B is an m×n matrix, and alpha is
-// a scalar.
-func Trmm(s blas.Side, tA blas.Transpose, alpha complex64, a Triangular, b General) {
- cblas64.Ctrmm(s, a.Uplo, tA, a.Diag, b.Rows, b.Cols, alpha, a.Data, a.Stride, b.Data, b.Stride)
-}
-
-// Trsm solves
-// A * X = alpha * B, if tA == blas.NoTrans and s == blas.Left,
-// A^T * X = alpha * B, if tA == blas.Trans and s == blas.Left,
-// A^H * X = alpha * B, if tA == blas.ConjTrans and s == blas.Left,
-// X * A = alpha * B, if tA == blas.NoTrans and s == blas.Right,
-// X * A^T = alpha * B, if tA == blas.Trans and s == blas.Right,
-// X * A^H = alpha * B, if tA == blas.ConjTrans and s == blas.Right,
-// where A is an n×n or m×m triangular matrix, X and B are m×n matrices, and
-// alpha is a scalar.
-//
-// At entry to the function, b contains the values of B, and the result is
-// stored in-place into b.
-//
-// No check is made that A is invertible.
-func Trsm(s blas.Side, tA blas.Transpose, alpha complex64, a Triangular, b General) {
- cblas64.Ctrsm(s, a.Uplo, tA, a.Diag, b.Rows, b.Cols, alpha, a.Data, a.Stride, b.Data, b.Stride)
-}
-
-// Hemm performs
-// C = alpha * A * B + beta * C, if s == blas.Left,
-// C = alpha * B * A + beta * C, if s == blas.Right,
-// where A is an n×n or m×m Hermitian matrix, B and C are m×n matrices, and
-// alpha and beta are scalars.
-func Hemm(s blas.Side, alpha complex64, a Hermitian, b General, beta complex64, c General) {
- var m, n int
- if s == blas.Left {
- m, n = a.N, b.Cols
- } else {
- m, n = b.Rows, a.N
- }
- cblas64.Chemm(s, a.Uplo, m, n, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
-}
-
-// Herk performs the Hermitian rank-k update
-// C = alpha * A * A^H + beta*C, if t == blas.NoTrans,
-// C = alpha * A^H * A + beta*C, if t == blas.ConjTrans,
-// where C is an n×n Hermitian matrix, A is an n×k matrix if t == blas.NoTrans
-// and a k×n matrix otherwise, and alpha and beta are scalars.
-func Herk(t blas.Transpose, alpha float32, a General, beta float32, c Hermitian) {
- var n, k int
- if t == blas.NoTrans {
- n, k = a.Rows, a.Cols
- } else {
- n, k = a.Cols, a.Rows
- }
- cblas64.Cherk(c.Uplo, t, n, k, alpha, a.Data, a.Stride, beta, c.Data, c.Stride)
-}
-
-// Her2k performs the Hermitian rank-2k update
-// C = alpha * A * B^H + conj(alpha) * B * A^H + beta * C, if t == blas.NoTrans,
-// C = alpha * A^H * B + conj(alpha) * B^H * A + beta * C, if t == blas.ConjTrans,
-// where C is an n×n Hermitian matrix, A and B are n×k matrices if t == NoTrans
-// and k×n matrices otherwise, and alpha and beta are scalars.
-func Her2k(t blas.Transpose, alpha complex64, a, b General, beta float32, c Hermitian) {
- var n, k int
- if t == blas.NoTrans {
- n, k = a.Rows, a.Cols
- } else {
- n, k = a.Cols, a.Rows
- }
- cblas64.Cher2k(c.Uplo, t, n, k, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
-}
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