mat: rename pool helpers to be consistent with type names

mat/band.go

@@ -347,15 +347,15 @@ func (b *BandDense) MulVecTo(dst *VecDense, trans bool, x Vector) {
 			dst.checkOverlap(xVec.mat)
 			blas64.Gbmv(t, 1, b.mat, xVec.mat, 0, dst.mat)
 		} else {
-			xCopy := getWorkspaceVec(n, false)
+			xCopy := getVecDenseWorkspace(n, false)
 			xCopy.CloneFromVec(xVec)
 			blas64.Gbmv(t, 1, b.mat, xCopy.mat, 0, dst.mat)
-			putWorkspaceVec(xCopy)
+			putVecDenseWorkspace(xCopy)
 		}
 	} else {
-		xCopy := getWorkspaceVec(n, false)
+		xCopy := getVecDenseWorkspace(n, false)
 		xCopy.CloneFromVec(x)
 		blas64.Gbmv(t, 1, b.mat, xCopy.mat, 0, dst.mat)
-		putWorkspaceVec(xCopy)
+		putVecDenseWorkspace(xCopy)
 	}
 }

mat/cdense.go

@@ -226,10 +226,10 @@ func (m *CDense) isolatedWorkspace(a CMatrix) (w *CDense, restore func()) {
 	if r == 0 || c == 0 {
 		panic(ErrZeroLength)
 	}
-	w = getWorkspaceCmplx(r, c, false)
+	w = getCDenseWorkspace(r, c, false)
 	return w, func() {
 		m.Copy(w)
-		putWorkspaceCmplx(w)
+		putCDenseWorkspace(w)
 	}
 }
 

mat/cholesky.go

@@ -55,8 +55,8 @@ type Cholesky struct {
 // the norm is estimated from the decomposition.
 func (c *Cholesky) updateCond(norm float64) {
 	n := c.chol.mat.N
-	work := getFloats(3*n, false)
-	defer putFloats(work)
+	work := getFloat64s(3*n, false)
+	defer putFloat64s(work)
 	if norm < 0 {
 		// This is an approximation. By the definition of a norm,
 		//  |AB| <= |A| |B|.
@@ -139,9 +139,9 @@ func (c *Cholesky) Factorize(a Symmetric) (ok bool) {
 	copySymIntoTriangle(c.chol, a)
 
 	sym := c.chol.asSymBlas()
-	work := getFloats(c.chol.mat.N, false)
+	work := getFloat64s(c.chol.mat.N, false)
 	norm := lapack64.Lansy(CondNorm, sym, work)
-	putFloats(work)
+	putFloat64s(work)
 	_, ok = lapack64.Potrf(sym)
 	if ok {
 		c.updateCond(norm)
@@ -592,8 +592,8 @@ func (c *Cholesky) SymRankOne(orig *Cholesky, alpha float64, x Vector) (ok bool)
 	//   EPFL Technical Report 161468 (2004)
 	//   http://infoscience.epfl.ch/record/161468
 
-	work := getFloats(n, false)
-	defer putFloats(work)
+	work := getFloat64s(n, false)
+	defer putFloat64s(work)
 	var xmat blas64.Vector
 	if rv, ok := x.(RawVectorer); ok {
 		xmat = rv.RawVector()
@@ -660,10 +660,10 @@ func (c *Cholesky) SymRankOne(orig *Cholesky, alpha float64, x Vector) (ok bool)
 		return false
 	}
 	norm = math.Sqrt((1 + norm) * (1 - norm))
-	cos := getFloats(n, false)
-	defer putFloats(cos)
-	sin := getFloats(n, false)
-	defer putFloats(sin)
+	cos := getFloat64s(n, false)
+	defer putFloat64s(cos)
+	sin := getFloat64s(n, false)
+	defer putFloat64s(sin)
 	for i := n - 1; i >= 0; i-- {
 		// Compute parameters of Givens matrices that zero elements of p
 		// backwards.
@@ -674,8 +674,8 @@ func (c *Cholesky) SymRankOne(orig *Cholesky, alpha float64, x Vector) (ok bool)
 			sin[i] *= -1
 		}
 	}
-	workMat := getWorkspaceTri(c.chol.mat.N, c.chol.triKind(), false)
-	defer putWorkspaceTri(workMat)
+	workMat := getTriDenseWorkspace(c.chol.mat.N, c.chol.triKind(), false)
+	defer putTriWorkspace(workMat)
 	workMat.Copy(c.chol)
 	umat := workMat.mat
 	stride := workMat.mat.Stride
@@ -752,12 +752,12 @@ func (ch *BandCholesky) Factorize(a SymBanded) (ok bool) {
 		ch.Reset()
 		return false
 	}
-	work := getFloats(3*n, false)
+	work := getFloat64s(3*n, false)
 	iwork := getInts(n, false)
 	aNorm := lapack64.Lansb(CondNorm, cSym, work)
 	ch.cond = 1 / lapack64.Pbcon(cSym, aNorm, work, iwork)
 	putInts(iwork)
-	putFloats(work)
+	putFloat64s(work)
 	return true
 }
 

mat/dense.go

@@ -166,10 +166,10 @@ func (m *Dense) isolatedWorkspace(a Matrix) (w *Dense, restore func()) {
 	if r == 0 || c == 0 {
 		panic(ErrZeroLength)
 	}
-	w = getWorkspace(r, c, false)
+	w = getDenseWorkspace(r, c, false)
 	return w, func() {
 		m.Copy(w)
-		putWorkspace(w)
+		putDenseWorkspace(w)
 	}
 }
 
@@ -606,8 +606,8 @@ func (m *Dense) Norm(norm float64) float64 {
 	}
 	lnorm := normLapack(norm, false)
 	if lnorm == lapack.MaxColumnSum {
-		work := getFloats(m.mat.Cols, false)
-		defer putFloats(work)
+		work := getFloat64s(m.mat.Cols, false)
+		defer putFloat64s(work)
 		return lapack64.Lange(lnorm, m.mat, work)
 	}
 	return lapack64.Lange(lnorm, m.mat, nil)

mat/dense_arithmetic.go

@@ -226,10 +226,10 @@ func (m *Dense) Inverse(a Matrix) error {
 	case *Dense:
 		if m != aU || aTrans {
 			if m == aU || m.checkOverlap(rm.mat) {
-				tmp := getWorkspace(r, c, false)
+				tmp := getDenseWorkspace(r, c, false)
 				tmp.Copy(a)
 				m.Copy(tmp)
-				putWorkspace(tmp)
+				putDenseWorkspace(tmp)
 				break
 			}
 			m.Copy(a)
@@ -238,7 +238,7 @@ func (m *Dense) Inverse(a Matrix) error {
 		m.Copy(a)
 	}
 	// Compute the norm of A.
-	work := getFloats(4*r, false) // Length must be at least 4*r for Gecon.
+	work := getFloat64s(4*r, false) // Length must be at least 4*r for Gecon.
 	norm := lapack64.Lange(CondNorm, m.mat, work)
 	// Compute the LU factorization of A.
 	ipiv := getInts(r, false)
@@ -256,10 +256,10 @@ func (m *Dense) Inverse(a Matrix) error {
 	lapack64.Getri(m.mat, ipiv, work, -1)
 	if int(work[0]) > len(work) {
 		l := int(work[0])
-		putFloats(work)
-		work = getFloats(l, false)
+		putFloat64s(work)
+		work = getFloat64s(l, false)
 	}
-	defer putFloats(work)
+	defer putFloat64s(work)
 	ok = lapack64.Getri(m.mat, ipiv, work, len(work))
 	if !ok || rcond == 0 {
 		// A is exactly singular.
@@ -321,10 +321,10 @@ func (m *Dense) Mul(a, b Matrix) {
 
 		case *SymDense:
 			if aTrans {
-				c := getWorkspace(ac, ar, false)
+				c := getDenseWorkspace(ac, ar, false)
 				blas64.Symm(blas.Left, 1, bU.mat, aU.mat, 0, c.mat)
 				strictCopy(m, c.T())
-				putWorkspace(c)
+				putDenseWorkspace(c)
 				return
 			}
 			blas64.Symm(blas.Right, 1, bU.mat, aU.mat, 0, m.mat)
@@ -333,7 +333,7 @@ func (m *Dense) Mul(a, b Matrix) {
 		case *TriDense:
 			// Trmm updates in place, so copy aU first.
 			if aTrans {
-				c := getWorkspace(ac, ar, false)
+				c := getDenseWorkspace(ac, ar, false)
 				var tmp Dense
 				tmp.SetRawMatrix(aU.mat)
 				c.Copy(&tmp)
@@ -343,7 +343,7 @@ func (m *Dense) Mul(a, b Matrix) {
 				}
 				blas64.Trmm(blas.Left, bT, 1, bU.mat, c.mat)
 				strictCopy(m, c.T())
-				putWorkspace(c)
+				putDenseWorkspace(c)
 				return
 			}
 			m.Copy(a)
@@ -380,10 +380,10 @@ func (m *Dense) Mul(a, b Matrix) {
 		switch aU := aU.(type) {
 		case *SymDense:
 			if bTrans {
-				c := getWorkspace(bc, br, false)
+				c := getDenseWorkspace(bc, br, false)
 				blas64.Symm(blas.Right, 1, aU.mat, bU.mat, 0, c.mat)
 				strictCopy(m, c.T())
-				putWorkspace(c)
+				putDenseWorkspace(c)
 				return
 			}
 			blas64.Symm(blas.Left, 1, aU.mat, bU.mat, 0, m.mat)
@@ -392,7 +392,7 @@ func (m *Dense) Mul(a, b Matrix) {
 		case *TriDense:
 			// Trmm updates in place, so copy bU first.
 			if bTrans {
-				c := getWorkspace(bc, br, false)
+				c := getDenseWorkspace(bc, br, false)
 				var tmp Dense
 				tmp.SetRawMatrix(bU.mat)
 				c.Copy(&tmp)
@@ -402,7 +402,7 @@ func (m *Dense) Mul(a, b Matrix) {
 				}
 				blas64.Trmm(blas.Right, aT, 1, aU.mat, c.mat)
 				strictCopy(m, c.T())
-				putWorkspace(c)
+				putDenseWorkspace(c)
 				return
 			}
 			m.Copy(b)
@@ -441,8 +441,8 @@ func (m *Dense) Mul(a, b Matrix) {
 
 	m.checkOverlapMatrix(aU)
 	m.checkOverlapMatrix(bU)
-	row := getFloats(ac, false)
-	defer putFloats(row)
+	row := getFloat64s(ac, false)
+	defer putFloat64s(row)
 	for r := 0; r < ar; r++ {
 		for i := range row {
 			row[i] = a.At(r, i)
@@ -504,19 +504,19 @@ func (m *Dense) Exp(a Matrix) {
 
 	a1 := m
 	a1.Copy(a)
-	v := getWorkspace(r, r, true)
+	v := getDenseWorkspace(r, r, true)
 	vraw := v.RawMatrix()
 	n := r * r
 	vvec := blas64.Vector{N: n, Inc: 1, Data: vraw.Data}
-	defer putWorkspace(v)
+	defer putDenseWorkspace(v)
 
-	u := getWorkspace(r, r, true)
+	u := getDenseWorkspace(r, r, true)
 	uraw := u.RawMatrix()
 	uvec := blas64.Vector{N: n, Inc: 1, Data: uraw.Data}
-	defer putWorkspace(u)
+	defer putDenseWorkspace(u)
 
-	a2 := getWorkspace(r, r, false)
-	defer putWorkspace(a2)
+	a2 := getDenseWorkspace(r, r, false)
+	defer putDenseWorkspace(a2)
 
 	n1 := Norm(a, 1)
 	for i, t := range pade {
@@ -526,10 +526,10 @@ func (m *Dense) Exp(a Matrix) {
 
 		// This loop only executes once, so
 		// this is not as horrible as it looks.
-		p := getWorkspace(r, r, true)
+		p := getDenseWorkspace(r, r, true)
 		praw := p.RawMatrix()
 		pvec := blas64.Vector{N: n, Inc: 1, Data: praw.Data}
-		defer putWorkspace(p)
+		defer putDenseWorkspace(p)
 
 		for k := 0; k < r; k++ {
 			p.set(k, k, 1)
@@ -571,27 +571,27 @@ func (m *Dense) Exp(a Matrix) {
 	}
 	a2.Mul(a1, a1)
 
-	i := getWorkspace(r, r, true)
+	i := getDenseWorkspace(r, r, true)
 	for j := 0; j < r; j++ {
 		i.set(j, j, 1)
 	}
 	iraw := i.RawMatrix()
 	ivec := blas64.Vector{N: n, Inc: 1, Data: iraw.Data}
-	defer putWorkspace(i)
+	defer putDenseWorkspace(i)
 
 	a2raw := a2.RawMatrix()
 	a2vec := blas64.Vector{N: n, Inc: 1, Data: a2raw.Data}
 
-	a4 := getWorkspace(r, r, false)
+	a4 := getDenseWorkspace(r, r, false)
 	a4raw := a4.RawMatrix()
 	a4vec := blas64.Vector{N: n, Inc: 1, Data: a4raw.Data}
-	defer putWorkspace(a4)
+	defer putDenseWorkspace(a4)
 	a4.Mul(a2, a2)
 
-	a6 := getWorkspace(r, r, false)
+	a6 := getDenseWorkspace(r, r, false)
 	a6raw := a6.RawMatrix()
 	a6vec := blas64.Vector{N: n, Inc: 1, Data: a6raw.Data}
-	defer putWorkspace(a6)
+	defer putDenseWorkspace(a6)
 	a6.Mul(a2, a4)
 
 	// V = A_6(b_12*A_6 + b_10*A_4 + b_8*A_2) + b_6*A_6 + b_4*A_4 + b_2*A_2 +b_0*I
@@ -659,11 +659,11 @@ func (m *Dense) Pow(a Matrix, n int) {
 	}
 
 	// Perform iterative exponentiation by squaring in work space.
-	w := getWorkspace(r, r, false)
+	w := getDenseWorkspace(r, r, false)
 	w.Copy(a)
-	s := getWorkspace(r, r, false)
+	s := getDenseWorkspace(r, r, false)
 	s.Copy(a)
-	x := getWorkspace(r, r, false)
+	x := getDenseWorkspace(r, r, false)
 	for n--; n > 0; n >>= 1 {
 		if n&1 != 0 {
 			x.Mul(w, s)
@@ -675,9 +675,9 @@ func (m *Dense) Pow(a Matrix, n int) {
 		}
 	}
 	m.Copy(w)
-	putWorkspace(w)
-	putWorkspace(s)
-	putWorkspace(x)
+	putDenseWorkspace(w)
+	putDenseWorkspace(s)
+	putDenseWorkspace(x)
 }
 
 // Kronecker calculates the Kronecker product of a and b, placing the result in

mat/eigen.go

@@ -50,9 +50,9 @@ func (e *EigenSym) Factorize(a Symmetric, vectors bool) (ok bool) {
 	work := []float64{0}
 	lapack64.Syev(jobz, sd.mat, w, work, -1)
 
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	ok = lapack64.Syev(jobz, sd.mat, w, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 	if !ok {
 		e.vectorsComputed = false
 		e.values = nil
@@ -195,16 +195,16 @@ func (e *Eigen) Factorize(a Matrix, kind EigenKind) (ok bool) {
 		jobvr = lapack.RightEVCompute
 	}
 
-	wr := getFloats(c, false)
-	defer putFloats(wr)
-	wi := getFloats(c, false)
-	defer putFloats(wi)
+	wr := getFloat64s(c, false)
+	defer putFloat64s(wr)
+	wi := getFloat64s(c, false)
+	defer putFloat64s(wi)
 
 	work := []float64{0}
 	lapack64.Geev(jobvl, jobvr, sd.mat, wr, wi, vl.mat, vr.mat, work, -1)
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	first := lapack64.Geev(jobvl, jobvr, sd.mat, wr, wi, vl.mat, vr.mat, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 
 	if first != 0 {
 		e.values = nil

mat/hogsvd.go

@@ -79,10 +79,10 @@ func (gsvd *HOGSVD) Factorize(m ...Matrix) (ok bool) {
 		}
 	}
 
-	s := getWorkspace(c, c, true)
-	defer putWorkspace(s)
-	sij := getWorkspace(c, c, false)
-	defer putWorkspace(sij)
+	s := getDenseWorkspace(c, c, true)
+	defer putDenseWorkspace(s)
+	sij := getDenseWorkspace(c, c, false)
+	defer putDenseWorkspace(sij)
 	for i, ai := range a {
 		for _, aj := range a[i+1:] {
 			gsvd.err = ai.SolveCholTo(sij, &aj)
@@ -126,8 +126,8 @@ func (gsvd *HOGSVD) Factorize(m ...Matrix) (ok bool) {
 	}
 
 	b := make([]Dense, len(m))
-	biT := getWorkspace(c, r, false)
-	defer putWorkspace(biT)
+	biT := getDenseWorkspace(c, r, false)
+	defer putDenseWorkspace(biT)
 	for i, d := range m {
 		// All calls to reset will leave an emptied
 		// matrix with capacity to store the result

mat/lq.go

@@ -31,12 +31,12 @@ func (lq *LQ) updateCond(norm lapack.MatrixNorm) {
 	// is not the case for CondNorm. Hopefully the error is negligible: κ
 	// is only a qualitative measure anyway.
 	m := lq.lq.mat.Rows
-	work := getFloats(3*m, false)
+	work := getFloat64s(3*m, false)
 	iwork := getInts(m, false)
 	l := lq.lq.asTriDense(m, blas.NonUnit, blas.Lower)
 	v := lapack64.Trcon(norm, l.mat, work, iwork)
 	lq.cond = 1 / v
-	putFloats(work)
+	putFloat64s(work)
 	putInts(iwork)
 }
 
@@ -63,9 +63,9 @@ func (lq *LQ) factorize(a Matrix, norm lapack.MatrixNorm) {
 	work := []float64{0}
 	lq.tau = make([]float64, k)
 	lapack64.Gelqf(lq.lq.mat, lq.tau, work, -1)
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	lapack64.Gelqf(lq.lq.mat, lq.tau, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 	lq.updateCond(norm)
 }
 
@@ -159,9 +159,9 @@ func (lq *LQ) QTo(dst *Dense) {
 	// Construct Q from the elementary reflectors.
 	work := []float64{0}
 	lapack64.Ormlq(blas.Left, blas.NoTrans, lq.lq.mat, lq.tau, q, work, -1)
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	lapack64.Ormlq(blas.Left, blas.NoTrans, lq.lq.mat, lq.tau, q, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 }
 
 // SolveTo finds a minimum-norm solution to a system of linear equations defined
@@ -199,15 +199,15 @@ func (lq *LQ) SolveTo(dst *Dense, trans bool, b Matrix) error {
 	}
 	// Do not need to worry about overlap between x and b because w has its own
 	// independent storage.
-	w := getWorkspace(max(r, c), bc, false)
+	w := getDenseWorkspace(max(r, c), bc, false)
 	w.Copy(b)
 	t := lq.lq.asTriDense(lq.lq.mat.Rows, blas.NonUnit, blas.Lower).mat
 	if trans {
 		work := []float64{0}
 		lapack64.Ormlq(blas.Left, blas.NoTrans, lq.lq.mat, lq.tau, w.mat, work, -1)
-		work = getFloats(int(work[0]), false)
+		work = getFloat64s(int(work[0]), false)
 		lapack64.Ormlq(blas.Left, blas.NoTrans, lq.lq.mat, lq.tau, w.mat, work, len(work))
-		putFloats(work)
+		putFloat64s(work)
 
 		ok := lapack64.Trtrs(blas.Trans, t, w.mat)
 		if !ok {
@@ -223,13 +223,13 @@ func (lq *LQ) SolveTo(dst *Dense, trans bool, b Matrix) error {
 		}
 		work := []float64{0}
 		lapack64.Ormlq(blas.Left, blas.Trans, lq.lq.mat, lq.tau, w.mat, work, -1)
-		work = getFloats(int(work[0]), false)
+		work = getFloat64s(int(work[0]), false)
 		lapack64.Ormlq(blas.Left, blas.Trans, lq.lq.mat, lq.tau, w.mat, work, len(work))
-		putFloats(work)
+		putFloat64s(work)
 	}
 	// x was set above to be the correct size for the result.
 	dst.Copy(w)
-	putWorkspace(w)
+	putDenseWorkspace(w)
 	if lq.cond > ConditionTolerance {
 		return Condition(lq.cond)
 	}

mat/lu.go

@@ -30,8 +30,8 @@ type LU struct {
 // norm of the original matrix. If anorm is negative it will be estimated.
 func (lu *LU) updateCond(anorm float64, norm lapack.MatrixNorm) {
 	n := lu.lu.mat.Cols
-	work := getFloats(4*n, false)
-	defer putFloats(work)
+	work := getFloat64s(4*n, false)
+	defer putFloat64s(work)
 	iwork := getInts(n, false)
 	defer putInts(iwork)
 	if anorm < 0 {
@@ -79,9 +79,9 @@ func (lu *LU) factorize(a Matrix, norm lapack.MatrixNorm) {
 		lu.pivot = make([]int, r)
 	}
 	lu.pivot = lu.pivot[:r]
-	work := getFloats(r, false)
+	work := getFloat64s(r, false)
 	anorm := lapack64.Lange(norm, lu.lu.mat, work)
-	putFloats(work)
+	putFloat64s(work)
 	lapack64.Getrf(lu.lu.mat, lu.pivot)
 	lu.updateCond(anorm, norm)
 }
@@ -131,8 +131,8 @@ func (lu *LU) LogDet() (det float64, sign float64) {
 	}
 
 	_, n := lu.lu.Dims()
-	logDiag := getFloats(n, false)
-	defer putFloats(logDiag)
+	logDiag := getFloat64s(n, false)
+	defer putFloat64s(logDiag)
 	sign = 1.0
 	for i := 0; i < n; i++ {
 		v := lu.lu.at(i, i)
@@ -214,10 +214,10 @@ func (lu *LU) RankOne(orig *LU, alpha float64, x, y Vector) {
 		lu.lu.Copy(orig.lu)
 	}
 
-	xs := getFloats(n, false)
-	defer putFloats(xs)
-	ys := getFloats(n, false)
-	defer putFloats(ys)
+	xs := getFloat64s(n, false)
+	defer putFloat64s(xs)
+	ys := getFloat64s(n, false)
+	defer putFloat64s(ys)
 	for i := 0; i < n; i++ {
 		xs[i] = x.AtVec(i)
 		ys[i] = y.AtVec(i)

mat/pool.go

@@ -94,10 +94,10 @@ func init() {
 	}
 }
 
-// getWorkspace returns a *Dense of size r×c and a data slice
+// getDenseWorkspace returns a *Dense of size r×c and a data slice
 // with a cap that is less than 2*r*c. If clear is true, the
 // data slice visible through the Matrix interface is zeroed.
-func getWorkspace(r, c int, clear bool) *Dense {
+func getDenseWorkspace(r, c int, clear bool) *Dense {
 	l := uint(r * c)
 	w := poolDense[poolFor(l)].Get().(*Dense)
 	w.mat.Data = w.mat.Data[:l]
@@ -112,17 +112,17 @@ func getWorkspace(r, c int, clear bool) *Dense {
 	return w
 }
 
-// putWorkspace replaces a used *Dense into the appropriate size
-// workspace pool. putWorkspace must not be called with a matrix
+// putDenseWorkspace replaces a used *Dense into the appropriate size
+// workspace pool. putDenseWorkspace must not be called with a matrix
 // where references to the underlying data slice have been kept.
-func putWorkspace(w *Dense) {
+func putDenseWorkspace(w *Dense) {
 	poolDense[poolFor(uint(cap(w.mat.Data)))].Put(w)
 }
 
-// getWorkspaceSym returns a *SymDense of size n and a cap that
+// getSymDenseWorkspace returns a *SymDense of size n and a cap that
 // is less than 2*n. If clear is true, the data slice visible
 // through the Matrix interface is zeroed.
-func getWorkspaceSym(n int, clear bool) *SymDense {
+func getSymDenseWorkspace(n int, clear bool) *SymDense {
 	l := uint(n)
 	l *= l
 	s := poolSymDense[poolFor(l)].Get().(*SymDense)
@@ -136,17 +136,17 @@ func getWorkspaceSym(n int, clear bool) *SymDense {
 	return s
 }
 
-// putWorkspaceSym replaces a used *SymDense into the appropriate size
-// workspace pool. putWorkspaceSym must not be called with a matrix
+// putSymDenseWorkspace replaces a used *SymDense into the appropriate size
+// workspace pool. putSymDenseWorkspace must not be called with a matrix
 // where references to the underlying data slice have been kept.
-func putWorkspaceSym(s *SymDense) {
+func putSymDenseWorkspace(s *SymDense) {
 	poolSymDense[poolFor(uint(cap(s.mat.Data)))].Put(s)
 }
 
-// getWorkspaceTri returns a *TriDense of size n and a cap that
+// getTriDenseWorkspace returns a *TriDense of size n and a cap that
 // is less than 2*n. If clear is true, the data slice visible
 // through the Matrix interface is zeroed.
-func getWorkspaceTri(n int, kind TriKind, clear bool) *TriDense {
+func getTriDenseWorkspace(n int, kind TriKind, clear bool) *TriDense {
 	l := uint(n)
 	l *= l
 	t := poolTriDense[poolFor(l)].Get().(*TriDense)
@@ -168,17 +168,17 @@ func getWorkspaceTri(n int, kind TriKind, clear bool) *TriDense {
 	return t
 }
 
-// putWorkspaceTri replaces a used *TriDense into the appropriate size
-// workspace pool. putWorkspaceTri must not be called with a matrix
+// putTriWorkspace replaces a used *TriDense into the appropriate size
+// workspace pool. putTriWorkspace must not be called with a matrix
 // where references to the underlying data slice have been kept.
-func putWorkspaceTri(t *TriDense) {
+func putTriWorkspace(t *TriDense) {
 	poolTriDense[poolFor(uint(cap(t.mat.Data)))].Put(t)
 }
 
-// getWorkspaceVec returns a *VecDense of length n and a cap that
+// getVecDenseWorkspace returns a *VecDense of length n and a cap that
 // is less than 2*n. If clear is true, the data slice visible
 // through the Matrix interface is zeroed.
-func getWorkspaceVec(n int, clear bool) *VecDense {
+func getVecDenseWorkspace(n int, clear bool) *VecDense {
 	l := uint(n)
 	v := poolVecDense[poolFor(l)].Get().(*VecDense)
 	v.mat.Data = v.mat.Data[:l]
@@ -189,16 +189,41 @@ func getWorkspaceVec(n int, clear bool) *VecDense {
 	return v
 }
 
-// putWorkspaceVec replaces a used *VecDense into the appropriate size
-// workspace pool. putWorkspaceVec must not be called with a matrix
+// putVecDenseWorkspace replaces a used *VecDense into the appropriate size
+// workspace pool. putVecDenseWorkspace must not be called with a matrix
 // where references to the underlying data slice have been kept.
-func putWorkspaceVec(v *VecDense) {
+func putVecDenseWorkspace(v *VecDense) {
 	poolVecDense[poolFor(uint(cap(v.mat.Data)))].Put(v)
 }
 
-// getFloats returns a []float64 of length l and a cap that is
+// getCDenseWorkspace returns a *CDense of size r×c and a data slice
+// with a cap that is less than 2*r*c. If clear is true, the
+// data slice visible through the CMatrix interface is zeroed.
+func getCDenseWorkspace(r, c int, clear bool) *CDense {
+	l := uint(r * c)
+	w := poolCDense[poolFor(l)].Get().(*CDense)
+	w.mat.Data = w.mat.Data[:l]
+	if clear {
+		zeroC(w.mat.Data)
+	}
+	w.mat.Rows = r
+	w.mat.Cols = c
+	w.mat.Stride = c
+	w.capRows = r
+	w.capCols = c
+	return w
+}
+
+// putCDenseWorkspace replaces a used *CDense into the appropriate size
+// workspace pool. putWorkspace must not be called with a matrix
+// where references to the underlying data slice have been kept.
+func putCDenseWorkspace(w *CDense) {
+	poolCDense[poolFor(uint(cap(w.mat.Data)))].Put(w)
+}
+
+// getFloat64s returns a []float64 of length l and a cap that is
 // less than 2*l. If clear is true, the slice visible is zeroed.
-func getFloats(l int, clear bool) []float64 {
+func getFloat64s(l int, clear bool) []float64 {
 	w := *poolFloat64s[poolFor(uint(l))].Get().(*[]float64)
 	w = w[:l]
 	if clear {
@@ -207,14 +232,14 @@ func getFloats(l int, clear bool) []float64 {
 	return w
 }
 
-// putFloats replaces a used []float64 into the appropriate size
-// workspace pool. putFloats must not be called with a slice
+// putFloat64s replaces a used []float64 into the appropriate size
+// workspace pool. putFloat64s must not be called with a slice
 // where references to the underlying data have been kept.
-func putFloats(w []float64) {
+func putFloat64s(w []float64) {
 	poolFloat64s[poolFor(uint(cap(w)))].Put(&w)
 }
 
-// getInts returns a []ints of length l and a cap that is
+// getInts returns a []int of length l and a cap that is
 // less than 2*l. If clear is true, the slice visible is zeroed.
 func getInts(l int, clear bool) []int {
 	w := *poolInts[poolFor(uint(l))].Get().(*[]int)
@@ -233,28 +258,3 @@ func getInts(l int, clear bool) []int {
 func putInts(w []int) {
 	poolInts[poolFor(uint(cap(w)))].Put(&w)
 }
-
-// getWorkspaceCmplx returns a *CDense of size r×c and a data slice
-// with a cap that is less than 2*r*c. If clear is true, the
-// data slice visible through the CMatrix interface is zeroed.
-func getWorkspaceCmplx(r, c int, clear bool) *CDense {
-	l := uint(r * c)
-	w := poolCDense[poolFor(l)].Get().(*CDense)
-	w.mat.Data = w.mat.Data[:l]
-	if clear {
-		zeroC(w.mat.Data)
-	}
-	w.mat.Rows = r
-	w.mat.Cols = c
-	w.mat.Stride = c
-	w.capRows = r
-	w.capCols = c
-	return w
-}
-
-// putWorkspaceCmplx replaces a used *CDense into the appropriate size
-// workspace pool. putWorkspace must not be called with a matrix
-// where references to the underlying data slice have been kept.
-func putWorkspaceCmplx(w *CDense) {
-	poolCDense[poolFor(uint(cap(w.mat.Data)))].Put(w)
-}

mat/pool_test.go

@@ -20,7 +20,7 @@ func TestPool(t *testing.T) {
 			for k := 0; k < 5; k++ {
 				work := make([]*Dense, rand.Intn(10)+1)
 				for l := range work {
-					w := getWorkspace(i, j, true)
+					w := getDenseWorkspace(i, j, true)
 					if !reflect.DeepEqual(w.mat, m.mat) {
 						t.Error("unexpected non-zeroed matrix returned by getWorkspace")
 					}
@@ -37,7 +37,7 @@ func TestPool(t *testing.T) {
 					work[l] = w
 				}
 				for _, w := range work {
-					putWorkspace(w)
+					putDenseWorkspace(w)
 				}
 			}
 		}
@@ -48,8 +48,8 @@ var benchmat *Dense
 
 func poolBenchmark(n, r, c int, clear bool) {
 	for i := 0; i < n; i++ {
-		benchmat = getWorkspace(r, c, clear)
-		putWorkspace(benchmat)
+		benchmat = getDenseWorkspace(r, c, clear)
+		putDenseWorkspace(benchmat)
 	}
 }
 

mat/product.go

@@ -45,7 +45,7 @@ func (m *Dense) Product(factors ...Matrix) {
 	result := p.multiply()
 	m.reuseAsNonZeroed(result.Dims())
 	m.Copy(result)
-	putWorkspace(result)
+	putDenseWorkspace(result)
 }
 
 // debugProductWalk enables debugging output for Product.
@@ -154,13 +154,13 @@ func (p *multiplier) multiplySubchain(i, j int) (m Matrix, intermediate bool) {
 			i, ar, ac, result(aTmp), j, br, bc, result(bTmp))
 	}
 
-	r := getWorkspace(ar, bc, false)
+	r := getDenseWorkspace(ar, bc, false)
 	r.Mul(a, b)
 	if aTmp {
-		putWorkspace(a.(*Dense))
+		putDenseWorkspace(a.(*Dense))
 	}
 	if bTmp {
-		putWorkspace(b.(*Dense))
+		putDenseWorkspace(b.(*Dense))
 	}
 	return r, true
 }

mat/qr.go

@@ -31,11 +31,11 @@ func (qr *QR) updateCond(norm lapack.MatrixNorm) {
 	// is not the case for CondNorm. Hopefully the error is negligible: κ
 	// is only a qualitative measure anyway.
 	n := qr.qr.mat.Cols
-	work := getFloats(3*n, false)
+	work := getFloat64s(3*n, false)
 	iwork := getInts(n, false)
 	r := qr.qr.asTriDense(n, blas.NonUnit, blas.Upper)
 	v := lapack64.Trcon(norm, r.mat, work, iwork)
-	putFloats(work)
+	putFloat64s(work)
 	putInts(iwork)
 	qr.cond = 1 / v
 }
@@ -63,9 +63,9 @@ func (qr *QR) factorize(a Matrix, norm lapack.MatrixNorm) {
 	work := []float64{0}
 	qr.tau = make([]float64, k)
 	lapack64.Geqrf(qr.qr.mat, qr.tau, work, -1)
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	lapack64.Geqrf(qr.qr.mat, qr.tau, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 	qr.updateCond(norm)
 }
 
@@ -154,9 +154,9 @@ func (qr *QR) QTo(dst *Dense) {
 	// Construct Q from the elementary reflectors.
 	work := []float64{0}
 	lapack64.Ormqr(blas.Left, blas.NoTrans, qr.qr.mat, qr.tau, dst.mat, work, -1)
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	lapack64.Ormqr(blas.Left, blas.NoTrans, qr.qr.mat, qr.tau, dst.mat, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 }
 
 // SolveTo finds a minimum-norm solution to a system of linear equations defined
@@ -194,7 +194,7 @@ func (qr *QR) SolveTo(dst *Dense, trans bool, b Matrix) error {
 	}
 	// Do not need to worry about overlap between m and b because x has its own
 	// independent storage.
-	w := getWorkspace(max(r, c), bc, false)
+	w := getDenseWorkspace(max(r, c), bc, false)
 	w.Copy(b)
 	t := qr.qr.asTriDense(qr.qr.mat.Cols, blas.NonUnit, blas.Upper).mat
 	if trans {
@@ -207,15 +207,15 @@ func (qr *QR) SolveTo(dst *Dense, trans bool, b Matrix) error {
 		}
 		work := []float64{0}
 		lapack64.Ormqr(blas.Left, blas.NoTrans, qr.qr.mat, qr.tau, w.mat, work, -1)
-		work = getFloats(int(work[0]), false)
+		work = getFloat64s(int(work[0]), false)
 		lapack64.Ormqr(blas.Left, blas.NoTrans, qr.qr.mat, qr.tau, w.mat, work, len(work))
-		putFloats(work)
+		putFloat64s(work)
 	} else {
 		work := []float64{0}
 		lapack64.Ormqr(blas.Left, blas.Trans, qr.qr.mat, qr.tau, w.mat, work, -1)
-		work = getFloats(int(work[0]), false)
+		work = getFloat64s(int(work[0]), false)
 		lapack64.Ormqr(blas.Left, blas.Trans, qr.qr.mat, qr.tau, w.mat, work, len(work))
-		putFloats(work)
+		putFloat64s(work)
 
 		ok := lapack64.Trtrs(blas.NoTrans, t, w.mat)
 		if !ok {
@@ -224,7 +224,7 @@ func (qr *QR) SolveTo(dst *Dense, trans bool, b Matrix) error {
 	}
 	// X was set above to be the correct size for the result.
 	dst.Copy(w)
-	putWorkspace(w)
+	putDenseWorkspace(w)
 	if qr.cond > ConditionTolerance {
 		return Condition(qr.cond)
 	}

mat/solve.go

@@ -52,10 +52,10 @@ func (m *Dense) Solve(a, b Matrix) error {
 		case RawMatrixer:
 			if m != bU || bTrans {
 				if m == bU || m.checkOverlap(rm.RawMatrix()) {
-					tmp := getWorkspace(br, bc, false)
+					tmp := getDenseWorkspace(br, bc, false)
 					tmp.Copy(b)
 					m.Copy(tmp)
-					putWorkspace(tmp)
+					putDenseWorkspace(tmp)
 					break
 				}
 				m.Copy(b)
@@ -65,19 +65,19 @@ func (m *Dense) Solve(a, b Matrix) error {
 				m.Copy(b)
 			} else if bTrans {
 				// m and b share data so Copy cannot be used directly.
-				tmp := getWorkspace(br, bc, false)
+				tmp := getDenseWorkspace(br, bc, false)
 				tmp.Copy(b)
 				m.Copy(tmp)
-				putWorkspace(tmp)
+				putDenseWorkspace(tmp)
 			}
 		}
 
 		rm := rma.RawTriangular()
 		blas64.Trsm(side, tA, 1, rm, m.mat)
-		work := getFloats(3*rm.N, false)
+		work := getFloat64s(3*rm.N, false)
 		iwork := getInts(rm.N, false)
 		cond := lapack64.Trcon(CondNorm, rm, work, iwork)
-		putFloats(work)
+		putFloat64s(work)
 		putInts(iwork)
 		if cond > ConditionTolerance {
 			return Condition(cond)

mat/svd.go

@@ -131,9 +131,9 @@ func (svd *SVD) Factorize(a Matrix, kind SVDKind) (ok bool) {
 
 	work := []float64{0}
 	lapack64.Gesvd(jobU, jobVT, aCopy.mat, svd.u, svd.vt, svd.s, work, -1)
-	work = getFloats(int(work[0]), false)
+	work = getFloat64s(int(work[0]), false)
 	ok = lapack64.Gesvd(jobU, jobVT, aCopy.mat, svd.u, svd.vt, svd.s, work, len(work))
-	putFloats(work)
+	putFloat64s(work)
 	if !ok {
 		svd.kind = 0
 	}
@@ -318,12 +318,12 @@ func (svd *SVD) SolveTo(dst *Dense, b Matrix, rank int) []float64 {
 	s := svd.s[:rank]
 
 	_, bc := b.Dims()
-	c := getWorkspace(svd.u.Cols, bc, false)
-	defer putWorkspace(c)
+	c := getDenseWorkspace(svd.u.Cols, bc, false)
+	defer putDenseWorkspace(c)
 	c.Mul(u.T(), b)
 
-	y := getWorkspace(rank, bc, false)
-	defer putWorkspace(y)
+	y := getDenseWorkspace(rank, bc, false)
+	defer putDenseWorkspace(y)
 	y.DivElem(c.slice(0, rank, 0, bc), repVector{vec: s, cols: bc})
 	dst.Mul(vt.slice(0, rank, 0, svd.vt.Cols).T(), y)
 
@@ -395,12 +395,12 @@ func (svd *SVD) SolveVecTo(dst *VecDense, b Vector, rank int) float64 {
 	}
 	s := svd.s[:rank]
 
-	c := getWorkspaceVec(svd.u.Cols, false)
-	defer putWorkspaceVec(c)
+	c := getVecDenseWorkspace(svd.u.Cols, false)
+	defer putVecDenseWorkspace(c)
 	c.MulVec(u.T(), b)
 
-	y := getWorkspaceVec(rank, false)
-	defer putWorkspaceVec(y)
+	y := getVecDenseWorkspace(rank, false)
+	defer putVecDenseWorkspace(y)
 	y.DivElemVec(c.sliceVec(0, rank), NewVecDense(rank, s))
 	dst.MulVec(vt.slice(0, rank, 0, svd.vt.Cols).T(), y)
 

mat/symband.go

@@ -257,8 +257,8 @@ func (s *SymBandDense) Norm(norm float64) float64 {
 	}
 	lnorm := normLapack(norm, false)
 	if lnorm == lapack.MaxColumnSum || lnorm == lapack.MaxRowSum {
-		work := getFloats(s.mat.N, false)
-		defer putFloats(work)
+		work := getFloat64s(s.mat.N, false)
+		defer putFloat64s(work)
 		return lapack64.Lansb(lnorm, s.mat, work)
 	}
 	return lapack64.Lansb(lnorm, s.mat, nil)
@@ -293,15 +293,15 @@ func (s *SymBandDense) MulVecTo(dst *VecDense, _ bool, x Vector) {
 			dst.checkOverlap(xVec.mat)
 			blas64.Sbmv(1, s.mat, xVec.mat, 0, dst.mat)
 		} else {
-			xCopy := getWorkspaceVec(n, false)
+			xCopy := getVecDenseWorkspace(n, false)
 			xCopy.CloneFromVec(xVec)
 			blas64.Sbmv(1, s.mat, xCopy.mat, 0, dst.mat)
-			putWorkspaceVec(xCopy)
+			putVecDenseWorkspace(xCopy)
 		}
 	} else {
-		xCopy := getWorkspaceVec(n, false)
+		xCopy := getVecDenseWorkspace(n, false)
 		xCopy.CloneFromVec(x)
 		blas64.Sbmv(1, s.mat, xCopy.mat, 0, dst.mat)
-		putWorkspaceVec(xCopy)
+		putVecDenseWorkspace(xCopy)
 	}
 }

mat/symmetric.go

@@ -238,10 +238,10 @@ func (s *SymDense) isolatedWorkspace(a Symmetric) (w *SymDense, restore func())
 	if n == 0 {
 		panic(ErrZeroLength)
 	}
-	w = getWorkspaceSym(n, false)
+	w = getSymDenseWorkspace(n, false)
 	return w, func() {
 		s.CopySym(w)
-		putWorkspaceSym(w)
+		putSymDenseWorkspace(w)
 	}
 }
 
@@ -405,10 +405,10 @@ func (s *SymDense) SymOuterK(alpha float64, x Matrix) {
 		panic(badSymTriangle)
 	case s.mat.N == n:
 		if s == x {
-			w := getWorkspaceSym(n, true)
+			w := getSymDenseWorkspace(n, true)
 			w.SymRankK(w, alpha, x)
 			s.CopySym(w)
-			putWorkspaceSym(w)
+			putSymDenseWorkspace(w)
 		} else {
 			switch r := x.(type) {
 			case RawMatrixer:
@@ -592,8 +592,8 @@ func (s *SymDense) Norm(norm float64) float64 {
 	}
 	lnorm := normLapack(norm, false)
 	if lnorm == lapack.MaxColumnSum || lnorm == lapack.MaxRowSum {
-		work := getFloats(s.mat.N, false)
-		defer putFloats(work)
+		work := getFloat64s(s.mat.N, false)
+		defer putFloat64s(work)
 		return lapack64.Lansy(lnorm, s.mat, work)
 	}
 	return lapack64.Lansy(lnorm, s.mat, nil)

mat/triangular.go

@@ -366,10 +366,10 @@ func (t *TriDense) isolatedWorkspace(a Triangular) (w *TriDense, restore func())
 	if n == 0 {
 		panic(ErrZeroLength)
 	}
-	w = getWorkspaceTri(n, kind, false)
+	w = getTriDenseWorkspace(n, kind, false)
 	return w, func() {
 		t.Copy(w)
-		putWorkspaceTri(w)
+		putTriWorkspace(w)
 	}
 }
 
@@ -459,10 +459,10 @@ func (t *TriDense) InverseTri(a Triangular) error {
 	n, _ := a.Triangle()
 	t.reuseAsNonZeroed(a.Triangle())
 	t.Copy(a)
-	work := getFloats(3*n, false)
+	work := getFloat64s(3*n, false)
 	iwork := getInts(n, false)
 	cond := lapack64.Trcon(CondNorm, t.mat, work, iwork)
-	putFloats(work)
+	putFloat64s(work)
 	putInts(iwork)
 	if math.IsInf(cond, 1) {
 		return Condition(cond)
@@ -634,8 +634,8 @@ func (t *TriDense) Norm(norm float64) float64 {
 	}
 	lnorm := normLapack(norm, false)
 	if lnorm == lapack.MaxColumnSum {
-		work := getFloats(t.mat.N, false)
-		defer putFloats(work)
+		work := getFloat64s(t.mat.N, false)
+		defer putFloat64s(work)
 		return lapack64.Lantr(lnorm, t.mat, work)
 	}
 	return lapack64.Lantr(lnorm, t.mat, nil)

mat/triband.go

@@ -461,8 +461,8 @@ func (t *TriBandDense) Norm(norm float64) float64 {
 	}
 	lnorm := normLapack(norm, false)
 	if lnorm == lapack.MaxColumnSum {
-		work := getFloats(t.mat.N, false)
-		defer putFloats(work)
+		work := getFloat64s(t.mat.N, false)
+		defer putFloat64s(work)
 		return lapack64.Lantb(lnorm, t.mat, work)
 	}
 	return lapack64.Lantb(lnorm, t.mat, nil)

mat/tridiag.go

@@ -216,10 +216,10 @@ func (a *Tridiag) MulVecTo(dst *VecDense, trans bool, x Vector) {
 		dst.checkOverlap(xVec.mat)
 		lapack64.Lagtm(t, 1, a.mat, xVec.asGeneral(), 0, dst.asGeneral())
 	} else {
-		xCopy := getWorkspaceVec(n, false)
+		xCopy := getVecDenseWorkspace(n, false)
 		xCopy.CloneFromVec(x)
 		lapack64.Lagtm(t, 1, a.mat, xCopy.asGeneral(), 0, dst.asGeneral())
-		putWorkspaceVec(xCopy)
+		putVecDenseWorkspace(xCopy)
 	}
 }
 

mat/vector.go

@@ -773,10 +773,10 @@ func (v *VecDense) isolatedWorkspace(a Vector) (n *VecDense, restore func()) {
 	if l == 0 {
 		panic(ErrZeroLength)
 	}
-	n = getWorkspaceVec(l, false)
+	n = getVecDenseWorkspace(l, false)
 	return n, func() {
 		v.CopyVec(n)
-		putWorkspaceVec(n)
+		putVecDenseWorkspace(n)
 	}
 }