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k3s/vendor/gonum.org/v1/gonum/mat/vector.go

789 lines
17 KiB

5 years ago
// Copyright ©2013 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 mat
import (
"gonum.org/v1/gonum/blas"
"gonum.org/v1/gonum/blas/blas64"
"gonum.org/v1/gonum/internal/asm/f64"
)
var (
vector *VecDense
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_ Matrix = vector
_ allMatrix = vector
_ Vector = vector
_ Reseter = vector
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)
// Vector is a vector.
type Vector interface {
Matrix
AtVec(int) float64
Len() int
}
// TransposeVec is a type for performing an implicit transpose of a Vector.
// It implements the Vector interface, returning values from the transpose
// of the vector within.
type TransposeVec struct {
Vector Vector
}
// At returns the value of the element at row i and column j of the transposed
// matrix, that is, row j and column i of the Vector field.
func (t TransposeVec) At(i, j int) float64 {
return t.Vector.At(j, i)
}
// AtVec returns the element at position i. It panics if i is out of bounds.
func (t TransposeVec) AtVec(i int) float64 {
return t.Vector.AtVec(i)
}
// Dims returns the dimensions of the transposed vector.
func (t TransposeVec) Dims() (r, c int) {
c, r = t.Vector.Dims()
return r, c
}
// T performs an implicit transpose by returning the Vector field.
func (t TransposeVec) T() Matrix {
return t.Vector
}
// Len returns the number of columns in the vector.
func (t TransposeVec) Len() int {
return t.Vector.Len()
}
// TVec performs an implicit transpose by returning the Vector field.
func (t TransposeVec) TVec() Vector {
return t.Vector
}
// Untranspose returns the Vector field.
func (t TransposeVec) Untranspose() Matrix {
return t.Vector
}
func (t TransposeVec) UntransposeVec() Vector {
return t.Vector
}
// VecDense represents a column vector.
type VecDense struct {
mat blas64.Vector
// A BLAS vector can have a negative increment, but allowing this
// in the mat type complicates a lot of code, and doesn't gain anything.
// VecDense must have positive increment in this package.
}
// NewVecDense creates a new VecDense of length n. If data == nil,
// a new slice is allocated for the backing slice. If len(data) == n, data is
// used as the backing slice, and changes to the elements of the returned VecDense
// will be reflected in data. If neither of these is true, NewVecDense will panic.
// NewVecDense will panic if n is zero.
func NewVecDense(n int, data []float64) *VecDense {
if n <= 0 {
if n == 0 {
panic(ErrZeroLength)
}
panic("mat: negative dimension")
}
if len(data) != n && data != nil {
panic(ErrShape)
}
if data == nil {
data = make([]float64, n)
}
return &VecDense{
mat: blas64.Vector{
N: n,
Inc: 1,
Data: data,
},
}
}
// SliceVec returns a new Vector that shares backing data with the receiver.
// The returned matrix starts at i of the receiver and extends k-i elements.
// SliceVec panics with ErrIndexOutOfRange if the slice is outside the capacity
// of the receiver.
func (v *VecDense) SliceVec(i, k int) Vector {
if i < 0 || k <= i || v.Cap() < k {
panic(ErrIndexOutOfRange)
}
return &VecDense{
mat: blas64.Vector{
N: k - i,
Inc: v.mat.Inc,
Data: v.mat.Data[i*v.mat.Inc : (k-1)*v.mat.Inc+1],
},
}
}
// Dims returns the number of rows and columns in the matrix. Columns is always 1
// for a non-Reset vector.
func (v *VecDense) Dims() (r, c int) {
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if v.IsEmpty() {
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return 0, 0
}
return v.mat.N, 1
}
// Caps returns the number of rows and columns in the backing matrix. Columns is always 1
// for a non-Reset vector.
func (v *VecDense) Caps() (r, c int) {
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if v.IsEmpty() {
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return 0, 0
}
return v.Cap(), 1
}
// Len returns the length of the vector.
func (v *VecDense) Len() int {
return v.mat.N
}
// Cap returns the capacity of the vector.
func (v *VecDense) Cap() int {
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if v.IsEmpty() {
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return 0
}
return (cap(v.mat.Data)-1)/v.mat.Inc + 1
}
// T performs an implicit transpose by returning the receiver inside a Transpose.
func (v *VecDense) T() Matrix {
return Transpose{v}
}
// TVec performs an implicit transpose by returning the receiver inside a TransposeVec.
func (v *VecDense) TVec() Vector {
return TransposeVec{v}
}
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// Reset empties the matrix so that it can be reused as the
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// receiver of a dimensionally restricted operation.
//
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// Reset should not be used when the matrix shares backing data.
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// See the Reseter interface for more information.
func (v *VecDense) Reset() {
// No change of Inc or N to 0 may be
// made unless both are set to 0.
v.mat.Inc = 0
v.mat.N = 0
v.mat.Data = v.mat.Data[:0]
}
// Zero sets all of the matrix elements to zero.
func (v *VecDense) Zero() {
for i := 0; i < v.mat.N; i++ {
v.mat.Data[v.mat.Inc*i] = 0
}
}
// CloneVec makes a copy of a into the receiver, overwriting the previous value
// of the receiver.
func (v *VecDense) CloneVec(a Vector) {
if v == a {
return
}
n := a.Len()
v.mat = blas64.Vector{
N: n,
Inc: 1,
Data: use(v.mat.Data, n),
}
if r, ok := a.(RawVectorer); ok {
blas64.Copy(r.RawVector(), v.mat)
return
}
for i := 0; i < a.Len(); i++ {
v.SetVec(i, a.AtVec(i))
}
}
// VecDenseCopyOf returns a newly allocated copy of the elements of a.
func VecDenseCopyOf(a Vector) *VecDense {
v := &VecDense{}
v.CloneVec(a)
return v
}
func (v *VecDense) RawVector() blas64.Vector {
return v.mat
}
// CopyVec makes a copy of elements of a into the receiver. It is similar to the
// built-in copy; it copies as much as the overlap between the two vectors and
// returns the number of elements it copied.
func (v *VecDense) CopyVec(a Vector) int {
n := min(v.Len(), a.Len())
if v == a {
return n
}
if r, ok := a.(RawVectorer); ok {
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src := r.RawVector()
src.N = n
dst := v.mat
dst.N = n
blas64.Copy(src, dst)
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return n
}
for i := 0; i < n; i++ {
v.setVec(i, a.AtVec(i))
}
return n
}
// ScaleVec scales the vector a by alpha, placing the result in the receiver.
func (v *VecDense) ScaleVec(alpha float64, a Vector) {
n := a.Len()
if v == a {
if v.mat.Inc == 1 {
f64.ScalUnitary(alpha, v.mat.Data)
return
}
f64.ScalInc(alpha, v.mat.Data, uintptr(n), uintptr(v.mat.Inc))
return
}
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v.reuseAsNonZeroed(n)
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if rv, ok := a.(RawVectorer); ok {
mat := rv.RawVector()
v.checkOverlap(mat)
if v.mat.Inc == 1 && mat.Inc == 1 {
f64.ScalUnitaryTo(v.mat.Data, alpha, mat.Data)
return
}
f64.ScalIncTo(v.mat.Data, uintptr(v.mat.Inc),
alpha, mat.Data, uintptr(n), uintptr(mat.Inc))
return
}
for i := 0; i < n; i++ {
v.setVec(i, alpha*a.AtVec(i))
}
}
// AddScaledVec adds the vectors a and alpha*b, placing the result in the receiver.
func (v *VecDense) AddScaledVec(a Vector, alpha float64, b Vector) {
if alpha == 1 {
v.AddVec(a, b)
return
}
if alpha == -1 {
v.SubVec(a, b)
return
}
ar := a.Len()
br := b.Len()
if ar != br {
panic(ErrShape)
}
var amat, bmat blas64.Vector
fast := true
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aU, _ := untransposeExtract(a)
if rv, ok := aU.(*VecDense); ok {
amat = rv.mat
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if v != a {
v.checkOverlap(amat)
}
} else {
fast = false
}
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bU, _ := untransposeExtract(b)
if rv, ok := bU.(*VecDense); ok {
bmat = rv.mat
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if v != b {
v.checkOverlap(bmat)
}
} else {
fast = false
}
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v.reuseAsNonZeroed(ar)
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switch {
case alpha == 0: // v <- a
if v == a {
return
}
v.CopyVec(a)
case v == a && v == b: // v <- v + alpha * v = (alpha + 1) * v
blas64.Scal(alpha+1, v.mat)
case !fast: // v <- a + alpha * b without blas64 support.
for i := 0; i < ar; i++ {
v.setVec(i, a.AtVec(i)+alpha*b.AtVec(i))
}
case v == a && v != b: // v <- v + alpha * b
if v.mat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
f64.AxpyUnitaryTo(v.mat.Data, alpha, bmat.Data, amat.Data)
} else {
f64.AxpyInc(alpha, bmat.Data, v.mat.Data,
uintptr(ar), uintptr(bmat.Inc), uintptr(v.mat.Inc), 0, 0)
}
default: // v <- a + alpha * b or v <- a + alpha * v
if v.mat.Inc == 1 && amat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
f64.AxpyUnitaryTo(v.mat.Data, alpha, bmat.Data, amat.Data)
} else {
f64.AxpyIncTo(v.mat.Data, uintptr(v.mat.Inc), 0,
alpha, bmat.Data, amat.Data,
uintptr(ar), uintptr(bmat.Inc), uintptr(amat.Inc), 0, 0)
}
}
}
// AddVec adds the vectors a and b, placing the result in the receiver.
func (v *VecDense) AddVec(a, b Vector) {
ar := a.Len()
br := b.Len()
if ar != br {
panic(ErrShape)
}
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v.reuseAsNonZeroed(ar)
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aU, _ := untransposeExtract(a)
bU, _ := untransposeExtract(b)
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if arv, ok := aU.(*VecDense); ok {
if brv, ok := bU.(*VecDense); ok {
amat := arv.mat
bmat := brv.mat
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if v != a {
v.checkOverlap(amat)
}
if v != b {
v.checkOverlap(bmat)
}
if v.mat.Inc == 1 && amat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
f64.AxpyUnitaryTo(v.mat.Data, 1, bmat.Data, amat.Data)
return
}
f64.AxpyIncTo(v.mat.Data, uintptr(v.mat.Inc), 0,
1, bmat.Data, amat.Data,
uintptr(ar), uintptr(bmat.Inc), uintptr(amat.Inc), 0, 0)
return
}
}
for i := 0; i < ar; i++ {
v.setVec(i, a.AtVec(i)+b.AtVec(i))
}
}
// SubVec subtracts the vector b from a, placing the result in the receiver.
func (v *VecDense) SubVec(a, b Vector) {
ar := a.Len()
br := b.Len()
if ar != br {
panic(ErrShape)
}
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v.reuseAsNonZeroed(ar)
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aU, _ := untransposeExtract(a)
bU, _ := untransposeExtract(b)
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if arv, ok := aU.(*VecDense); ok {
if brv, ok := bU.(*VecDense); ok {
amat := arv.mat
bmat := brv.mat
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if v != a {
v.checkOverlap(amat)
}
if v != b {
v.checkOverlap(bmat)
}
if v.mat.Inc == 1 && amat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
f64.AxpyUnitaryTo(v.mat.Data, -1, bmat.Data, amat.Data)
return
}
f64.AxpyIncTo(v.mat.Data, uintptr(v.mat.Inc), 0,
-1, bmat.Data, amat.Data,
uintptr(ar), uintptr(bmat.Inc), uintptr(amat.Inc), 0, 0)
return
}
}
for i := 0; i < ar; i++ {
v.setVec(i, a.AtVec(i)-b.AtVec(i))
}
}
// MulElemVec performs element-wise multiplication of a and b, placing the result
// in the receiver.
func (v *VecDense) MulElemVec(a, b Vector) {
ar := a.Len()
br := b.Len()
if ar != br {
panic(ErrShape)
}
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v.reuseAsNonZeroed(ar)
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aU, _ := untransposeExtract(a)
bU, _ := untransposeExtract(b)
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if arv, ok := aU.(*VecDense); ok {
if brv, ok := bU.(*VecDense); ok {
amat := arv.mat
bmat := brv.mat
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if v != a {
v.checkOverlap(amat)
}
if v != b {
v.checkOverlap(bmat)
}
if v.mat.Inc == 1 && amat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
for i, a := range amat.Data {
v.mat.Data[i] = a * bmat.Data[i]
}
return
}
var ia, ib int
for i := 0; i < ar; i++ {
v.setVec(i, amat.Data[ia]*bmat.Data[ib])
ia += amat.Inc
ib += bmat.Inc
}
return
}
}
for i := 0; i < ar; i++ {
v.setVec(i, a.AtVec(i)*b.AtVec(i))
}
}
// DivElemVec performs element-wise division of a by b, placing the result
// in the receiver.
func (v *VecDense) DivElemVec(a, b Vector) {
ar := a.Len()
br := b.Len()
if ar != br {
panic(ErrShape)
}
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v.reuseAsNonZeroed(ar)
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aU, _ := untransposeExtract(a)
bU, _ := untransposeExtract(b)
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if arv, ok := aU.(*VecDense); ok {
if brv, ok := bU.(*VecDense); ok {
amat := arv.mat
bmat := brv.mat
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if v != a {
v.checkOverlap(amat)
}
if v != b {
v.checkOverlap(bmat)
}
if v.mat.Inc == 1 && amat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
for i, a := range amat.Data {
v.setVec(i, a/bmat.Data[i])
}
return
}
var ia, ib int
for i := 0; i < ar; i++ {
v.setVec(i, amat.Data[ia]/bmat.Data[ib])
ia += amat.Inc
ib += bmat.Inc
}
}
}
for i := 0; i < ar; i++ {
v.setVec(i, a.AtVec(i)/b.AtVec(i))
}
}
// MulVec computes a * b. The result is stored into the receiver.
// MulVec panics if the number of columns in a does not equal the number of rows in b
// or if the number of columns in b does not equal 1.
func (v *VecDense) MulVec(a Matrix, b Vector) {
r, c := a.Dims()
br, bc := b.Dims()
if c != br || bc != 1 {
panic(ErrShape)
}
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aU, trans := untransposeExtract(a)
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var bmat blas64.Vector
fast := true
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bU, _ := untransposeExtract(b)
if rv, ok := bU.(*VecDense); ok {
bmat = rv.mat
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if v != b {
v.checkOverlap(bmat)
}
} else {
fast = false
}
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v.reuseAsNonZeroed(r)
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var restore func()
if v == aU {
v, restore = v.isolatedWorkspace(aU.(*VecDense))
defer restore()
} else if v == b {
v, restore = v.isolatedWorkspace(b)
defer restore()
}
// TODO(kortschak): Improve the non-fast paths.
switch aU := aU.(type) {
case Vector:
if b.Len() == 1 {
// {n,1} x {1,1}
v.ScaleVec(b.AtVec(0), aU)
return
}
// {1,n} x {n,1}
if fast {
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if rv, ok := aU.(*VecDense); ok {
amat := rv.mat
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if v != aU {
v.checkOverlap(amat)
}
if amat.Inc == 1 && bmat.Inc == 1 {
// Fast path for a common case.
v.setVec(0, f64.DotUnitary(amat.Data, bmat.Data))
return
}
v.setVec(0, f64.DotInc(amat.Data, bmat.Data,
uintptr(c), uintptr(amat.Inc), uintptr(bmat.Inc), 0, 0))
return
}
}
var sum float64
for i := 0; i < c; i++ {
sum += aU.AtVec(i) * b.AtVec(i)
}
v.setVec(0, sum)
return
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case *SymBandDense:
if fast {
aU.checkOverlap(v.asGeneral())
blas64.Sbmv(1, aU.mat, bmat, 0, v.mat)
return
}
case *SymDense:
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if fast {
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aU.checkOverlap(v.asGeneral())
blas64.Symv(1, aU.mat, bmat, 0, v.mat)
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return
}
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case *TriDense:
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v.CopyVec(b)
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aU.checkOverlap(v.asGeneral())
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ta := blas.NoTrans
if trans {
ta = blas.Trans
}
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blas64.Trmv(ta, aU.mat, v.mat)
case *Dense:
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if fast {
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aU.checkOverlap(v.asGeneral())
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t := blas.NoTrans
if trans {
t = blas.Trans
}
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blas64.Gemv(t, 1, aU.mat, bmat, 0, v.mat)
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return
}
default:
if fast {
for i := 0; i < r; i++ {
var f float64
for j := 0; j < c; j++ {
f += a.At(i, j) * bmat.Data[j*bmat.Inc]
}
v.setVec(i, f)
}
return
}
}
for i := 0; i < r; i++ {
var f float64
for j := 0; j < c; j++ {
f += a.At(i, j) * b.AtVec(j)
}
v.setVec(i, f)
}
}
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// ReuseAsVec changes the receiver if it IsEmpty() to be of size n×1.
//
// ReuseAsVec re-uses the backing data slice if it has sufficient capacity,
// otherwise a new slice is allocated. The backing data is zero on return.
//
// ReuseAsVec panics if the receiver is not empty, and panics if
// the input size is less than one. To empty the receiver for re-use,
// Reset should be used.
func (v *VecDense) ReuseAsVec(n int) {
if n <= 0 {
if n == 0 {
panic(ErrZeroLength)
}
panic(ErrNegativeDimension)
}
if !v.IsEmpty() {
panic(ErrReuseNonEmpty)
}
v.reuseAsZeroed(n)
}
// reuseAsNonZeroed resizes an empty vector to a r×1 vector,
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// or checks that a non-empty matrix is r×1.
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func (v *VecDense) reuseAsNonZeroed(r int) {
// reuseAsNonZeroed must be kept in sync with reuseAsZeroed.
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if r == 0 {
panic(ErrZeroLength)
}
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if v.IsEmpty() {
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v.mat = blas64.Vector{
N: r,
Inc: 1,
Data: use(v.mat.Data, r),
}
return
}
if r != v.mat.N {
panic(ErrShape)
}
}
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// reuseAsZeroed resizes an empty vector to a r×1 vector,
// or checks that a non-empty matrix is r×1.
func (v *VecDense) reuseAsZeroed(r int) {
// reuseAsZeroed must be kept in sync with reuseAsNonZeroed.
if r == 0 {
panic(ErrZeroLength)
}
if v.IsEmpty() {
v.mat = blas64.Vector{
N: r,
Inc: 1,
Data: useZeroed(v.mat.Data, r),
}
return
}
if r != v.mat.N {
panic(ErrShape)
}
v.Zero()
}
// IsEmpty returns whether the receiver is empty. Empty matrices can be the
// receiver for size-restricted operations. The receiver can be emptied using
// Reset.
func (v *VecDense) IsEmpty() bool {
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// It must be the case that v.Dims() returns
// zeros in this case. See comment in Reset().
return v.mat.Inc == 0
}
func (v *VecDense) isolatedWorkspace(a Vector) (n *VecDense, restore func()) {
l := a.Len()
if l == 0 {
panic(ErrZeroLength)
}
n = getWorkspaceVec(l, false)
return n, func() {
v.CopyVec(n)
putWorkspaceVec(n)
}
}
// asDense returns a Dense representation of the receiver with the same
// underlying data.
func (v *VecDense) asDense() *Dense {
return &Dense{
mat: v.asGeneral(),
capRows: v.mat.N,
capCols: 1,
}
}
// asGeneral returns a blas64.General representation of the receiver with the
// same underlying data.
func (v *VecDense) asGeneral() blas64.General {
return blas64.General{
Rows: v.mat.N,
Cols: 1,
Stride: v.mat.Inc,
Data: v.mat.Data,
}
}
// ColViewOf reflects the column j of the RawMatrixer m, into the receiver
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// backed by the same underlying data. The receiver must either be empty
// have length equal to the number of rows of m.
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func (v *VecDense) ColViewOf(m RawMatrixer, j int) {
rm := m.RawMatrix()
if j >= rm.Cols || j < 0 {
panic(ErrColAccess)
}
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if !v.IsEmpty() && v.mat.N != rm.Rows {
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panic(ErrShape)
}
v.mat.Inc = rm.Stride
v.mat.Data = rm.Data[j : (rm.Rows-1)*rm.Stride+j+1]
v.mat.N = rm.Rows
}
// RowViewOf reflects the row i of the RawMatrixer m, into the receiver
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// backed by the same underlying data. The receiver must either be
// empty or have length equal to the number of columns of m.
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func (v *VecDense) RowViewOf(m RawMatrixer, i int) {
rm := m.RawMatrix()
if i >= rm.Rows || i < 0 {
panic(ErrRowAccess)
}
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if !v.IsEmpty() && v.mat.N != rm.Cols {
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panic(ErrShape)
}
v.mat.Inc = 1
v.mat.Data = rm.Data[i*rm.Stride : i*rm.Stride+rm.Cols]
v.mat.N = rm.Cols
}