// 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 cblas128 import ( "gonum.org/v1/gonum/blas" "gonum.org/v1/gonum/blas/gonum" ) var cblas128 blas.Complex128 = gonum.Implementation{} // Use sets the BLAS complex128 implementation to be used by subsequent BLAS calls. // The default implementation is // gonum.org/v1/gonum/blas/gonum.Implementation. func Use(b blas.Complex128) { cblas128 = b } // Implementation returns the current BLAS complex128 implementation. // // Implementation allows direct calls to the current the BLAS complex128 implementation // giving finer control of parameters. func Implementation() blas.Complex128 { return cblas128 } // Vector represents a vector with an associated element increment. type Vector struct { Inc int Data []complex128 } // General represents a matrix using the conventional storage scheme. type General struct { Rows, Cols int Stride int Data []complex128 } // Band represents a band matrix using the band storage scheme. type Band struct { Rows, Cols int KL, KU int Stride int Data []complex128 } // Triangular represents a triangular matrix using the conventional storage scheme. type Triangular struct { N int Stride int Data []complex128 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 []complex128 Uplo blas.Uplo Diag blas.Diag } // TriangularPacked represents a triangular matrix using the packed storage scheme. type TriangularPacked struct { N int Data []complex128 Uplo blas.Uplo Diag blas.Diag } // Symmetric represents a symmetric matrix using the conventional storage scheme. type Symmetric struct { N int Stride int Data []complex128 Uplo blas.Uplo } // SymmetricBand represents a symmetric matrix using the band storage scheme. type SymmetricBand struct { N, K int Stride int Data []complex128 Uplo blas.Uplo } // SymmetricPacked represents a symmetric matrix using the packed storage scheme. type SymmetricPacked struct { N int Data []complex128 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 = "cblas128: 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) complex128 { return cblas128.Zdotu(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) complex128 { return cblas128.Zdotc(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) float64 { if x.Inc < 0 { panic(negInc) } return cblas128.Dznrm2(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) float64 { if x.Inc < 0 { panic(negInc) } return cblas128.Dzasum(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 cblas128.Izamax(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) { cblas128.Zswap(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) { cblas128.Zcopy(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 complex128, x, y Vector) { cblas128.Zaxpy(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 complex128, x Vector) { if x.Inc < 0 { panic(negInc) } cblas128.Zscal(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 float64, x Vector) { if x.Inc < 0 { panic(negInc) } cblas128.Zdscal(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 complex128, a General, x Vector, beta complex128, y Vector) { cblas128.Zgemv(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 complex128, a Band, x Vector, beta complex128, y Vector) { cblas128.Zgbmv(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) { cblas128.Ztrmv(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) { cblas128.Ztbmv(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) { cblas128.Ztpmv(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) { cblas128.Ztrsv(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) { cblas128.Ztbsv(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) { cblas128.Ztpsv(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 complex128, a Hermitian, x Vector, beta complex128, y Vector) { cblas128.Zhemv(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 complex128, a HermitianBand, x Vector, beta complex128, y Vector) { cblas128.Zhbmv(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 complex128, a HermitianPacked, x Vector, beta complex128, y Vector) { cblas128.Zhpmv(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 complex128, x, y Vector, a General) { cblas128.Zgeru(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 complex128, x, y Vector, a General) { cblas128.Zgerc(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 float64, x Vector, a Hermitian) { cblas128.Zher(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 float64, x Vector, a HermitianPacked) { cblas128.Zhpr(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 complex128, x, y Vector, a Hermitian) { cblas128.Zher2(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 complex128, x, y Vector, a HermitianPacked) { cblas128.Zhpr2(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 complex128, a, b General, beta complex128, 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 } cblas128.Zgemm(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 complex128, a Symmetric, b General, beta complex128, c General) { var m, n int if s == blas.Left { m, n = a.N, b.Cols } else { m, n = b.Rows, a.N } cblas128.Zsymm(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 complex128, a General, beta complex128, c Symmetric) { var n, k int if t == blas.NoTrans { n, k = a.Rows, a.Cols } else { n, k = a.Cols, a.Rows } cblas128.Zsyrk(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 complex128, a, b General, beta complex128, c Symmetric) { var n, k int if t == blas.NoTrans { n, k = a.Rows, a.Cols } else { n, k = a.Cols, a.Rows } cblas128.Zsyr2k(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 complex128, a Triangular, b General) { cblas128.Ztrmm(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 complex128, a Triangular, b General) { cblas128.Ztrsm(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 complex128, a Hermitian, b General, beta complex128, c General) { var m, n int if s == blas.Left { m, n = a.N, b.Cols } else { m, n = b.Rows, a.N } cblas128.Zhemm(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 float64, a General, beta float64, c Hermitian) { var n, k int if t == blas.NoTrans { n, k = a.Rows, a.Cols } else { n, k = a.Cols, a.Rows } cblas128.Zherk(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 complex128, a, b General, beta float64, c Hermitian) { var n, k int if t == blas.NoTrans { n, k = a.Rows, a.Cols } else { n, k = a.Cols, a.Rows } cblas128.Zher2k(c.Uplo, t, n, k, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride) }