k3s/vendor/gonum.org/v1/gonum/mat/band.go
Darren Shepherd 8031137b79 Update vendor
2019-08-30 23:08:05 -07:00

264 lines
7.4 KiB
Go

// Copyright ©2017 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/blas64"
)
var (
bandDense *BandDense
_ Matrix = bandDense
_ Banded = bandDense
_ RawBander = bandDense
_ NonZeroDoer = bandDense
_ RowNonZeroDoer = bandDense
_ ColNonZeroDoer = bandDense
)
// BandDense represents a band matrix in dense storage format.
type BandDense struct {
mat blas64.Band
}
// Banded is a band matrix representation.
type Banded interface {
Matrix
// Bandwidth returns the lower and upper bandwidth values for
// the matrix. The total bandwidth of the matrix is kl+ku+1.
Bandwidth() (kl, ku int)
// TBand is the equivalent of the T() method in the Matrix
// interface but guarantees the transpose is of banded type.
TBand() Banded
}
// A RawBander can return a blas64.Band representation of the receiver.
// Changes to the blas64.Band.Data slice will be reflected in the original
// matrix, changes to the Rows, Cols, KL, KU and Stride fields will not.
type RawBander interface {
RawBand() blas64.Band
}
// A MutableBanded can set elements of a band matrix.
type MutableBanded interface {
Banded
SetBand(i, j int, v float64)
}
var (
_ Matrix = TransposeBand{}
_ Banded = TransposeBand{}
_ UntransposeBander = TransposeBand{}
)
// TransposeBand is a type for performing an implicit transpose of a band
// matrix. It implements the Banded interface, returning values from the
// transpose of the matrix within.
type TransposeBand struct {
Banded Banded
}
// 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 Banded field.
func (t TransposeBand) At(i, j int) float64 {
return t.Banded.At(j, i)
}
// Dims returns the dimensions of the transposed matrix.
func (t TransposeBand) Dims() (r, c int) {
c, r = t.Banded.Dims()
return r, c
}
// T performs an implicit transpose by returning the Banded field.
func (t TransposeBand) T() Matrix {
return t.Banded
}
// Bandwidth returns the lower and upper bandwidth values for
// the transposed matrix.
func (t TransposeBand) Bandwidth() (kl, ku int) {
kl, ku = t.Banded.Bandwidth()
return ku, kl
}
// TBand performs an implicit transpose by returning the Banded field.
func (t TransposeBand) TBand() Banded {
return t.Banded
}
// Untranspose returns the Banded field.
func (t TransposeBand) Untranspose() Matrix {
return t.Banded
}
// UntransposeBand returns the Banded field.
func (t TransposeBand) UntransposeBand() Banded {
return t.Banded
}
// NewBandDense creates a new Band matrix with r rows and c columns. If data == nil,
// a new slice is allocated for the backing slice. If len(data) == min(r, c+kl)*(kl+ku+1),
// data is used as the backing slice, and changes to the elements of the returned
// BandDense will be reflected in data. If neither of these is true, NewBandDense
// will panic. kl must be at least zero and less r, and ku must be at least zero and
// less than c, otherwise NewBandDense will panic.
// NewBandDense will panic if either r or c is zero.
//
// The data must be arranged in row-major order constructed by removing the zeros
// from the rows outside the band 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
// 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 passed to NewBandDense as []float64{*, 1, 2, 3, 4, ...} with kl=1 and ku=2.
// Only the values in the band portion of the matrix are used.
func NewBandDense(r, c, kl, ku int, data []float64) *BandDense {
if r <= 0 || c <= 0 || kl < 0 || ku < 0 {
if r == 0 || c == 0 {
panic(ErrZeroLength)
}
panic("mat: negative dimension")
}
if kl+1 > r || ku+1 > c {
panic("mat: band out of range")
}
bc := kl + ku + 1
if data != nil && len(data) != min(r, c+kl)*bc {
panic(ErrShape)
}
if data == nil {
data = make([]float64, min(r, c+kl)*bc)
}
return &BandDense{
mat: blas64.Band{
Rows: r,
Cols: c,
KL: kl,
KU: ku,
Stride: bc,
Data: data,
},
}
}
// NewDiagonalRect is a convenience function that returns a diagonal matrix represented by a
// BandDense. The length of data must be min(r, c) otherwise NewDiagonalRect will panic.
func NewDiagonalRect(r, c int, data []float64) *BandDense {
return NewBandDense(r, c, 0, 0, data)
}
// Dims returns the number of rows and columns in the matrix.
func (b *BandDense) Dims() (r, c int) {
return b.mat.Rows, b.mat.Cols
}
// Bandwidth returns the upper and lower bandwidths of the matrix.
func (b *BandDense) Bandwidth() (kl, ku int) {
return b.mat.KL, b.mat.KU
}
// T performs an implicit transpose by returning the receiver inside a Transpose.
func (b *BandDense) T() Matrix {
return Transpose{b}
}
// TBand performs an implicit transpose by returning the receiver inside a TransposeBand.
func (b *BandDense) TBand() Banded {
return TransposeBand{b}
}
// RawBand returns the underlying blas64.Band used by the receiver.
// Changes to elements in the receiver following the call will be reflected
// in returned blas64.Band.
func (b *BandDense) RawBand() blas64.Band {
return b.mat
}
// SetRawBand sets the underlying blas64.Band used by the receiver.
// Changes to elements in the receiver following the call will be reflected
// in the input.
func (b *BandDense) SetRawBand(mat blas64.Band) {
b.mat = mat
}
// DiagView returns the diagonal as a matrix backed by the original data.
func (b *BandDense) DiagView() Diagonal {
n := min(b.mat.Rows, b.mat.Cols)
return &DiagDense{
mat: blas64.Vector{
N: n,
Inc: b.mat.Stride,
Data: b.mat.Data[b.mat.KL : (n-1)*b.mat.Stride+b.mat.KL+1],
},
}
}
// DoNonZero calls the function fn for each of the non-zero elements of b. The function fn
// takes a row/column index and the element value of b at (i, j).
func (b *BandDense) DoNonZero(fn func(i, j int, v float64)) {
for i := 0; i < min(b.mat.Rows, b.mat.Cols+b.mat.KL); i++ {
for j := max(0, i-b.mat.KL); j < min(b.mat.Cols, i+b.mat.KU+1); j++ {
v := b.at(i, j)
if v != 0 {
fn(i, j, v)
}
}
}
}
// DoRowNonZero calls the function fn for each of the non-zero elements of row i of b. The function fn
// takes a row/column index and the element value of b at (i, j).
func (b *BandDense) DoRowNonZero(i int, fn func(i, j int, v float64)) {
if i < 0 || b.mat.Rows <= i {
panic(ErrRowAccess)
}
for j := max(0, i-b.mat.KL); j < min(b.mat.Cols, i+b.mat.KU+1); j++ {
v := b.at(i, j)
if v != 0 {
fn(i, j, v)
}
}
}
// DoColNonZero calls the function fn for each of the non-zero elements of column j of b. The function fn
// takes a row/column index and the element value of b at (i, j).
func (b *BandDense) DoColNonZero(j int, fn func(i, j int, v float64)) {
if j < 0 || b.mat.Cols <= j {
panic(ErrColAccess)
}
for i := 0; i < min(b.mat.Rows, b.mat.Cols+b.mat.KL); i++ {
if i-b.mat.KL <= j && j < i+b.mat.KU+1 {
v := b.at(i, j)
if v != 0 {
fn(i, j, v)
}
}
}
}
// Zero sets all of the matrix elements to zero.
func (b *BandDense) Zero() {
m := b.mat.Rows
kL := b.mat.KL
nCol := b.mat.KU + 1 + kL
for i := 0; i < m; i++ {
l := max(0, kL-i)
u := min(nCol, m+kL-i)
zero(b.mat.Data[i*b.mat.Stride+l : i*b.mat.Stride+u])
}
}