forked from LaconicNetwork/kompose
Upgrade OpenShift and its dependencies.
OpenShift version 1.4.0-alpha.0
This commit is contained in:
Tomas Kral
+434
@@ -0,0 +1,434 @@
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// Copyright ©2015 The gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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// Package blas64 provides a simple interface to the float64 BLAS API.
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package blas64
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import (
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"github.com/gonum/blas"
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"github.com/gonum/blas/native"
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)
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var blas64 blas.Float64 = native.Implementation{}
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// Use sets the BLAS float64 implementation to be used by subsequent BLAS calls.
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// The default implementation is native.Implementation.
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func Use(b blas.Float64) {
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blas64 = b
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}
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// Implementation returns the current BLAS float64 implementation.
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//
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// Implementation allows direct calls to the current the BLAS float64 implementation
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// giving finer control of parameters.
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func Implementation() blas.Float64 {
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return blas64
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}
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// Vector represents a vector with an associated element increment.
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type Vector struct {
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Inc int
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Data []float64
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}
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// General represents a matrix using the conventional storage scheme.
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type General struct {
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Rows, Cols int
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Stride int
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Data []float64
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}
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// Band represents a band matrix using the band storage scheme.
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type Band struct {
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Rows, Cols int
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KL, KU int
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Stride int
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Data []float64
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}
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// Triangular represents a triangular matrix using the conventional storage scheme.
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type Triangular struct {
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N int
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Stride int
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Data []float64
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Uplo blas.Uplo
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Diag blas.Diag
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}
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// TriangularBand represents a triangular matrix using the band storage scheme.
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type TriangularBand struct {
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N, K int
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Stride int
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Data []float64
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Uplo blas.Uplo
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Diag blas.Diag
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}
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// TriangularPacked represents a triangular matrix using the packed storage scheme.
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type TriangularPacked struct {
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N int
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Data []float64
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Uplo blas.Uplo
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Diag blas.Diag
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}
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// Symmetric represents a symmetric matrix using the conventional storage scheme.
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type Symmetric struct {
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N int
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Stride int
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Data []float64
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Uplo blas.Uplo
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}
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// SymmetricBand represents a symmetric matrix using the band storage scheme.
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type SymmetricBand struct {
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N, K int
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Stride int
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Data []float64
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Uplo blas.Uplo
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}
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// SymmetricPacked represents a symmetric matrix using the packed storage scheme.
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type SymmetricPacked struct {
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N int
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Data []float64
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Uplo blas.Uplo
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}
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// Level 1
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const negInc = "blas64: negative vector increment"
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// Dot computes the dot product of the two vectors
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// \sum_i x[i]*y[i]
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func Dot(n int, x, y Vector) float64 {
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return blas64.Ddot(n, x.Data, x.Inc, y.Data, y.Inc)
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}
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// Nrm2 computes the Euclidean norm of a vector,
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// sqrt(\sum_i x[i] * x[i]).
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//
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// Nrm2 will panic if the vector increment is negative.
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func Nrm2(n int, x Vector) float64 {
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if x.Inc < 0 {
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panic(negInc)
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}
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return blas64.Dnrm2(n, x.Data, x.Inc)
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}
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// Asum computes the sum of the absolute values of the elements of x.
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// \sum_i |x[i]|
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//
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// Asum will panic if the vector increment is negative.
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func Asum(n int, x Vector) float64 {
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if x.Inc < 0 {
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panic(negInc)
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}
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return blas64.Dasum(n, x.Data, x.Inc)
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}
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// Iamax returns the index of the largest element of x. If there are multiple
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// such indices the earliest is returned. Iamax returns -1 if n == 0.
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//
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// Iamax will panic if the vector increment is negative.
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func Iamax(n int, x Vector) int {
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if x.Inc < 0 {
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panic(negInc)
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}
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return blas64.Idamax(n, x.Data, x.Inc)
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}
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// Swap exchanges the elements of two vectors.
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// x[i], y[i] = y[i], x[i] for all i
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func Swap(n int, x, y Vector) {
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blas64.Dswap(n, x.Data, x.Inc, y.Data, y.Inc)
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}
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// Copy copies the elements of x into the elements of y.
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// y[i] = x[i] for all i
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func Copy(n int, x, y Vector) {
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blas64.Dcopy(n, x.Data, x.Inc, y.Data, y.Inc)
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}
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// Axpy adds alpha times x to y
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// y[i] += alpha * x[i] for all i
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func Axpy(n int, alpha float64, x, y Vector) {
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blas64.Daxpy(n, alpha, x.Data, x.Inc, y.Data, y.Inc)
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}
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// Rotg computes the plane rotation
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// _ _ _ _ _ _
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// | c s | | a | | r |
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// | -s c | * | b | = | 0 |
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// ‾ ‾ ‾ ‾ ‾ ‾
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// where
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// r = ±(a^2 + b^2)
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// c = a/r, the cosine of the plane rotation
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// s = b/r, the sine of the plane rotation
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func Rotg(a, b float64) (c, s, r, z float64) {
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return blas64.Drotg(a, b)
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}
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// Rotmg computes the modified Givens rotation. See
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// http://www.netlib.org/lapack/explore-html/df/deb/drotmg_8f.html
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// for more details.
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func Rotmg(d1, d2, b1, b2 float64) (p blas.DrotmParams, rd1, rd2, rb1 float64) {
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return blas64.Drotmg(d1, d2, b1, b2)
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}
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// Rot applies a plane transformation.
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// x[i] = c * x[i] + s * y[i]
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// y[i] = c * y[i] - s * x[i]
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func Rot(n int, x, y Vector, c, s float64) {
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blas64.Drot(n, x.Data, x.Inc, y.Data, y.Inc, c, s)
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}
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// Rotm applies the modified Givens rotation to the 2×n matrix.
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func Rotm(n int, x, y Vector, p blas.DrotmParams) {
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blas64.Drotm(n, x.Data, x.Inc, y.Data, y.Inc, p)
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}
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// Scal scales x by alpha.
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// x[i] *= alpha
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//
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// Scal will panic if the vector increment is negative
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func Scal(n int, alpha float64, x Vector) {
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if x.Inc < 0 {
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panic(negInc)
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}
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blas64.Dscal(n, alpha, x.Data, x.Inc)
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}
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// Level 2
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// Gemv computes
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// y = alpha * a * x + beta * y if tA = blas.NoTrans
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// y = alpha * A^T * x + beta * y if tA = blas.Trans or blas.ConjTrans
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// where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
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func Gemv(tA blas.Transpose, alpha float64, a General, x Vector, beta float64, y Vector) {
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blas64.Dgemv(tA, a.Rows, a.Cols, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
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}
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// Gbmv computes
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// y = alpha * A * x + beta * y if tA == blas.NoTrans
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// y = alpha * A^T * x + beta * y if tA == blas.Trans or blas.ConjTrans
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// where a is an m×n band matrix kL subdiagonals and kU super-diagonals, and
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// m and n refer to the size of the full dense matrix it represents.
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// x and y are vectors, and alpha and beta are scalars.
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func Gbmv(tA blas.Transpose, alpha float64, a Band, x Vector, beta float64, y Vector) {
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blas64.Dgbmv(tA, a.Rows, a.Cols, a.KL, a.KU, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
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}
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// Trmv computes
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// x = A * x if tA == blas.NoTrans
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// x = A^T * x if tA == blas.Trans or blas.ConjTrans
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// A is an n×n Triangular matrix and x is a vector.
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func Trmv(tA blas.Transpose, a Triangular, x Vector) {
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blas64.Dtrmv(a.Uplo, tA, a.Diag, a.N, a.Data, a.Stride, x.Data, x.Inc)
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}
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// Tbmv computes
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// x = A * x if tA == blas.NoTrans
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// x = A^T * x if tA == blas.Trans or blas.ConjTrans
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// where A is an n×n triangular banded matrix with k diagonals, and x is a vector.
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func Tbmv(tA blas.Transpose, a TriangularBand, x Vector) {
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blas64.Dtbmv(a.Uplo, tA, a.Diag, a.N, a.K, a.Data, a.Stride, x.Data, x.Inc)
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}
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// Tpmv computes
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// x = A * x if tA == blas.NoTrans
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// x = A^T * x if tA == blas.Trans or blas.ConjTrans
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// where A is an n×n unit triangular matrix in packed format, and x is a vector.
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func Tpmv(tA blas.Transpose, a TriangularPacked, x Vector) {
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blas64.Dtpmv(a.Uplo, tA, a.Diag, a.N, a.Data, x.Data, x.Inc)
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}
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// Trsv solves
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// A * x = b if tA == blas.NoTrans
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// A^T * x = b if tA == blas.Trans or blas.ConjTrans
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// A is an n×n triangular matrix and x is a vector.
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// At entry to the function, x contains the values of b, and the result is
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// stored in place into x.
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//
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// No test for singularity or near-singularity is included in this
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// routine. Such tests must be performed before calling this routine.
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func Trsv(tA blas.Transpose, a Triangular, x Vector) {
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blas64.Dtrsv(a.Uplo, tA, a.Diag, a.N, a.Data, a.Stride, x.Data, x.Inc)
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}
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// Tbsv solves
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// A * x = b
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// where A is an n×n triangular banded matrix with k diagonals in packed format,
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// and x is a vector.
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// At entry to the function, x contains the values of b, and the result is
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// stored in place into x.
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//
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// No test for singularity or near-singularity is included in this
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// routine. Such tests must be performed before calling this routine.
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func Tbsv(tA blas.Transpose, a TriangularBand, x Vector) {
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blas64.Dtbsv(a.Uplo, tA, a.Diag, a.N, a.K, a.Data, a.Stride, x.Data, x.Inc)
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}
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// Tpsv solves
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// A * x = b if tA == blas.NoTrans
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// A^T * x = b if tA == blas.Trans or blas.ConjTrans
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// where A is an n×n triangular matrix in packed format and x is a vector.
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// At entry to the function, x contains the values of b, and the result is
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// stored in place into x.
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//
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// No test for singularity or near-singularity is included in this
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// routine. Such tests must be performed before calling this routine.
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func Tpsv(tA blas.Transpose, a TriangularPacked, x Vector) {
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blas64.Dtpsv(a.Uplo, tA, a.Diag, a.N, a.Data, x.Data, x.Inc)
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}
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// Symv computes
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// y = alpha * A * x + beta * y,
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// where a is an n×n symmetric matrix, x and y are vectors, and alpha and
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// beta are scalars.
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func Symv(alpha float64, a Symmetric, x Vector, beta float64, y Vector) {
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blas64.Dsymv(a.Uplo, a.N, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
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}
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// Sbmv performs
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// y = alpha * A * x + beta * y
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// where A is an n×n symmetric banded matrix, x and y are vectors, and alpha
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// and beta are scalars.
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func Sbmv(alpha float64, a SymmetricBand, x Vector, beta float64, y Vector) {
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blas64.Dsbmv(a.Uplo, a.N, a.K, alpha, a.Data, a.Stride, x.Data, x.Inc, beta, y.Data, y.Inc)
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}
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// Spmv performs
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// y = alpha * A * x + beta * y,
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// where A is an n×n symmetric matrix in packed format, x and y are vectors
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// and alpha and beta are scalars.
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func Spmv(alpha float64, a SymmetricPacked, x Vector, beta float64, y Vector) {
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blas64.Dspmv(a.Uplo, a.N, alpha, a.Data, x.Data, x.Inc, beta, y.Data, y.Inc)
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}
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// Ger performs the rank-one operation
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// A += alpha * x * y^T
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// where A is an m×n dense matrix, x and y are vectors, and alpha is a scalar.
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func Ger(alpha float64, x, y Vector, a General) {
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blas64.Dger(a.Rows, a.Cols, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data, a.Stride)
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}
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// Syr performs the rank-one update
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// a += alpha * x * x^T
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// where a is an n×n symmetric matrix, and x is a vector.
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func Syr(alpha float64, x Vector, a Symmetric) {
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blas64.Dsyr(a.Uplo, a.N, alpha, x.Data, x.Inc, a.Data, a.Stride)
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}
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// Spr computes the rank-one operation
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// a += alpha * x * x^T
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// where a is an n×n symmetric matrix in packed format, x is a vector, and
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// alpha is a scalar.
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func Spr(alpha float64, x Vector, a SymmetricPacked) {
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blas64.Dspr(a.Uplo, a.N, alpha, x.Data, x.Inc, a.Data)
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}
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// Syr2 performs the symmetric rank-two update
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// A += alpha * x * y^T + alpha * y * x^T
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// where A is a symmetric n×n matrix, x and y are vectors, and alpha is a scalar.
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func Syr2(alpha float64, x, y Vector, a Symmetric) {
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||||
blas64.Dsyr2(a.Uplo, a.N, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data, a.Stride)
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}
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// Spr2 performs the symmetric rank-2 update
|
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// a += alpha * x * y^T + alpha * y * x^T
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// where a is an n×n symmetric matirx in packed format and x and y are vectors.
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func Spr2(alpha float64, x, y Vector, a SymmetricPacked) {
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blas64.Dspr2(a.Uplo, a.N, alpha, x.Data, x.Inc, y.Data, y.Inc, a.Data)
|
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}
|
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|
||||
// Level 3
|
||||
|
||||
// Gemm computes
|
||||
// C = beta * C + alpha * A * B.
|
||||
// tA and tB specify whether A or B are transposed. A, B, and C are m×n dense
|
||||
// matrices.
|
||||
func Gemm(tA, tB blas.Transpose, alpha float64, a, b General, beta float64, 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
|
||||
}
|
||||
blas64.Dgemm(tA, tB, m, n, k, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
|
||||
}
|
||||
|
||||
// Symm 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 Symm(s blas.Side, alpha float64, a Symmetric, b General, beta float64, c General) {
|
||||
var m, n int
|
||||
if s == blas.Left {
|
||||
m, n = a.N, b.Cols
|
||||
} else {
|
||||
m, n = b.Rows, a.N
|
||||
}
|
||||
blas64.Dsymm(s, a.Uplo, m, n, alpha, a.Data, a.Stride, b.Data, b.Stride, beta, c.Data, c.Stride)
|
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}
|
||||
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// Syrk 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 Syrk(t blas.Transpose, alpha float64, a General, beta float64, c Symmetric) {
|
||||
var n, k int
|
||||
if t == blas.NoTrans {
|
||||
n, k = a.Rows, a.Cols
|
||||
} else {
|
||||
n, k = a.Cols, a.Rows
|
||||
}
|
||||
blas64.Dsyrk(c.Uplo, t, n, k, alpha, a.Data, a.Stride, beta, c.Data, c.Stride)
|
||||
}
|
||||
|
||||
// Syr2k 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 Syr2k(t blas.Transpose, alpha float64, a, b General, beta float64, c Symmetric) {
|
||||
var n, k int
|
||||
if t == blas.NoTrans {
|
||||
n, k = a.Rows, a.Cols
|
||||
} else {
|
||||
n, k = a.Cols, a.Rows
|
||||
}
|
||||
blas64.Dsyr2k(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 side == blas.Left
|
||||
// B = alpha * A^T * B if tA == blas.Trans or blas.ConjTrans, 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 or blas.ConjTrans, and side == blas.Right
|
||||
// where A is an n×n triangular matrix, and B is an m×n matrix.
|
||||
func Trmm(s blas.Side, tA blas.Transpose, alpha float64, a Triangular, b General) {
|
||||
blas64.Dtrmm(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 side == blas.Left
|
||||
// A^T * X = alpha * B if tA == blas.Trans or blas.ConjTrans, and side == blas.Left
|
||||
// X * A = alpha * B if tA == blas.NoTrans side == blas.Right
|
||||
// X * A^T = alpha * B if tA == blas.Trans or blas.ConjTrans, and 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 Trsm(s blas.Side, tA blas.Transpose, alpha float64, a Triangular, b General) {
|
||||
blas64.Dtrsm(s, a.Uplo, tA, a.Diag, b.Rows, b.Cols, alpha, a.Data, a.Stride, b.Data, b.Stride)
|
||||
}
|
||||
Reference in New Issue
Block a user