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lapack,mat: rename SVDInPlace constant to SVDStore

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This commit is contained in:
Vladimir Chalupecky
2018-10-14 07:37:09 +02:00
committed by Vladimír Chalupecký
parent ac10ac454b
commit 3a1f3daf9f
5 changed files with 23 additions and 24 deletions
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14
lapack/gonum/dgesvd.go
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@@ -26,7 +26,7 @@ const noSVDO = "dgesvd: not coded for overwrite"
// jobU and jobVT are options for computing the singular vectors. The behavior // jobU and jobVT are options for computing the singular vectors. The behavior
// is as follows // is as follows
// jobU == lapack.SVDAll All m columns of U are returned in u // jobU == lapack.SVDAll All m columns of U are returned in u
// jobU == lapack.SVDInPlace The first min(m,n) columns are returned in u // jobU == lapack.SVDStore The first min(m,n) columns are returned in u
// jobU == lapack.SVDOverwrite The first min(m,n) columns of U are written into a // jobU == lapack.SVDOverwrite The first min(m,n) columns of U are written into a
// jobU == lapack.SVDNone The columns of U are not computed. // jobU == lapack.SVDNone The columns of U are not computed.
// The behavior is the same for jobVT and the rows of V^T. At most one of jobU // The behavior is the same for jobVT and the rows of V^T. At most one of jobU
@@ -40,12 +40,12 @@ const noSVDO = "dgesvd: not coded for overwrite"
// values in decreasing order. // values in decreasing order.
// //
// u contains the left singular vectors on exit, stored column-wise. If // u contains the left singular vectors on exit, stored column-wise. If
// jobU == lapack.SVDAll, u is of size m×m. If jobU == lapack.SVDInPlace u is // jobU == lapack.SVDAll, u is of size m×m. If jobU == lapack.SVDStore u is
// of size m×min(m,n). If jobU == lapack.SVDOverwrite or lapack.SVDNone, u is // of size m×min(m,n). If jobU == lapack.SVDOverwrite or lapack.SVDNone, u is
// not used. // not used.
// //
// vt contains the left singular vectors on exit, stored row-wise. If // vt contains the left singular vectors on exit, stored row-wise. If
// jobV == lapack.SVDAll, vt is of size n×m. If jobVT == lapack.SVDInPlace vt is // jobV == lapack.SVDAll, vt is of size n×m. If jobVT == lapack.SVDStore vt is
// of size min(m,n)×n. If jobVT == lapack.SVDOverwrite or lapack.SVDNone, vt is // of size min(m,n)×n. If jobVT == lapack.SVDOverwrite or lapack.SVDNone, vt is
// not used. // not used.
// //
@@ -61,12 +61,12 @@ func (impl Implementation) Dgesvd(jobU, jobVT lapack.SVDJob, m, n int, a []float
checkMatrix(m, n, a, lda) checkMatrix(m, n, a, lda)
if jobU == lapack.SVDAll { if jobU == lapack.SVDAll {
checkMatrix(m, m, u, ldu) checkMatrix(m, m, u, ldu)
} else if jobU == lapack.SVDInPlace { } else if jobU == lapack.SVDStore {
checkMatrix(m, minmn, u, ldu) checkMatrix(m, minmn, u, ldu)
} }
if jobVT == lapack.SVDAll { if jobVT == lapack.SVDAll {
checkMatrix(n, n, vt, ldvt) checkMatrix(n, n, vt, ldvt)
} else if jobVT == lapack.SVDInPlace { } else if jobVT == lapack.SVDStore {
checkMatrix(minmn, n, vt, ldvt) checkMatrix(minmn, n, vt, ldvt)
} }
if jobU == lapack.SVDOverwrite && jobVT == lapack.SVDOverwrite { if jobU == lapack.SVDOverwrite && jobVT == lapack.SVDOverwrite {
@@ -83,13 +83,13 @@ func (impl Implementation) Dgesvd(jobU, jobVT lapack.SVDJob, m, n int, a []float
} }
wantua := jobU == lapack.SVDAll wantua := jobU == lapack.SVDAll
wantus := jobU == lapack.SVDInPlace wantus := jobU == lapack.SVDStore
wantuas := wantua || wantus wantuas := wantua || wantus
wantuo := jobU == lapack.SVDOverwrite wantuo := jobU == lapack.SVDOverwrite
wantun := jobU == lapack.SVDNone wantun := jobU == lapack.SVDNone
wantva := jobVT == lapack.SVDAll wantva := jobVT == lapack.SVDAll
wantvs := jobVT == lapack.SVDInPlace wantvs := jobVT == lapack.SVDStore
wantvas := wantva || wantvs wantvas := wantva || wantvs
wantvo := jobVT == lapack.SVDOverwrite wantvo := jobVT == lapack.SVDOverwrite
wantvn := jobVT == lapack.SVDNone wantvn := jobVT == lapack.SVDNone

8
lapack/lapack.go
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@@ -108,10 +108,10 @@ const (
type SVDJob byte type SVDJob byte
const ( const (
SVDAll SVDJob = 'A' // Compute all singular vectors SVDAll SVDJob = 'A' // Compute all columns of the matrix U or V.
SVDInPlace SVDJob = 'S' // Compute the first singular vectors and store them in provided storage. SVDStore SVDJob = 'S' // Compute the singular vectors and store them in the matrix U or V.
SVDOverwrite SVDJob = 'O' // Compute the singular vectors and store them in input matrix SVDOverwrite SVDJob = 'O' // Compute the singular vectors and overwrite them on the input matrix A.
SVDNone SVDJob = 'N' // Do not compute singular vectors SVDNone SVDJob = 'N' // Do not compute singular vectors.
) )
// GSVDJob specifies the singular vector computation type for Generalized SVD. // GSVDJob specifies the singular vector computation type for Generalized SVD.

6
lapack/lapack64/lapack64.go
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@@ -152,7 +152,7 @@ func Gelqf(a blas64.General, tau, work []float64, lwork int) {
// jobU and jobVT are options for computing the singular vectors. The behavior // jobU and jobVT are options for computing the singular vectors. The behavior
// is as follows // is as follows
// jobU == lapack.SVDAll All m columns of U are returned in u // jobU == lapack.SVDAll All m columns of U are returned in u
// jobU == lapack.SVDInPlace The first min(m,n) columns are returned in u // jobU == lapack.SVDStore The first min(m,n) columns are returned in u
// jobU == lapack.SVDOverwrite The first min(m,n) columns of U are written into a // jobU == lapack.SVDOverwrite The first min(m,n) columns of U are written into a
// jobU == lapack.SVDNone The columns of U are not computed. // jobU == lapack.SVDNone The columns of U are not computed.
// The behavior is the same for jobVT and the rows of V^T. At most one of jobU // The behavior is the same for jobVT and the rows of V^T. At most one of jobU
@@ -166,12 +166,12 @@ func Gelqf(a blas64.General, tau, work []float64, lwork int) {
// values in decreasing order. // values in decreasing order.
// //
// u contains the left singular vectors on exit, stored columnwise. If // u contains the left singular vectors on exit, stored columnwise. If
// jobU == lapack.SVDAll, u is of size m×m. If jobU == lapack.SVDInPlace u is // jobU == lapack.SVDAll, u is of size m×m. If jobU == lapack.SVDStore u is
// of size m×min(m,n). If jobU == lapack.SVDOverwrite or lapack.SVDNone, u is // of size m×min(m,n). If jobU == lapack.SVDOverwrite or lapack.SVDNone, u is
// not used. // not used.
// //
// vt contains the left singular vectors on exit, stored rowwise. If // vt contains the left singular vectors on exit, stored rowwise. If
// jobV == lapack.SVDAll, vt is of size n×m. If jobVT == lapack.SVDInPlace vt is // jobV == lapack.SVDAll, vt is of size n×m. If jobVT == lapack.SVDStore vt is
// of size min(m,n)×n. If jobVT == lapack.SVDOverwrite or lapack.SVDNone, vt is // of size min(m,n)×n. If jobVT == lapack.SVDOverwrite or lapack.SVDNone, vt is
// not used. // not used.
// //

8
lapack/testlapack/dgesvd.go
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@@ -111,16 +111,16 @@ func DgesvdTest(t *testing.T, impl Dgesvder) {
svdCheck(t, false, errStr, m, n, s, a, u, ldu, vt, ldvt, aCopy, lda) svdCheck(t, false, errStr, m, n, s, a, u, ldu, vt, ldvt, aCopy, lda)
svdCheckPartial(t, impl, lapack.SVDAll, errStr, uAllOrig, vtAllOrig, aCopy, m, n, a, lda, s, u, ldu, vt, ldvt, work, false) svdCheckPartial(t, impl, lapack.SVDAll, errStr, uAllOrig, vtAllOrig, aCopy, m, n, a, lda, s, u, ldu, vt, ldvt, work, false)
// Test InPlace // Test SVDStore
jobU = lapack.SVDInPlace jobU = lapack.SVDStore
jobVT = lapack.SVDInPlace jobVT = lapack.SVDStore
copy(a, aCopy) copy(a, aCopy)
copy(u, uAllOrig) copy(u, uAllOrig)
copy(vt, vtAllOrig) copy(vt, vtAllOrig)
impl.Dgesvd(jobU, jobVT, m, n, a, lda, s, u, ldu, vt, ldvt, work, len(work)) impl.Dgesvd(jobU, jobVT, m, n, a, lda, s, u, ldu, vt, ldvt, work, len(work))
svdCheck(t, true, errStr, m, n, s, a, u, ldu, vt, ldvt, aCopy, lda) svdCheck(t, true, errStr, m, n, s, a, u, ldu, vt, ldvt, aCopy, lda)
svdCheckPartial(t, impl, lapack.SVDInPlace, errStr, uAllOrig, vtAllOrig, aCopy, m, n, a, lda, s, u, ldu, vt, ldvt, work, false) svdCheckPartial(t, impl, lapack.SVDStore, errStr, uAllOrig, vtAllOrig, aCopy, m, n, a, lda, s, u, ldu, vt, ldvt, work, false)
} }
} }

11
mat/svd.go
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@@ -26,15 +26,14 @@ type SVD struct {
// //
// The full singular value decomposition (kind == SVDFull) deconstructs A as // The full singular value decomposition (kind == SVDFull) deconstructs A as
// A = U * Σ * V^T // A = U * Σ * V^T
// where Σ is an m×n diagonal matrix of singular vectors, U is an m×m unitary // where Σ is an m×n diagonal matrix of singular values, U is an m×m unitary
// matrix of left singular vectors, and V is an n×n matrix of right singular vectors. // matrix of left singular vectors, and V is an n×n matrix of right singular vectors.
// //
// It is frequently not necessary to compute the full SVD. Computation time and // It is frequently not necessary to compute the full SVD. Computation time and
// storage costs can be reduced using the appropriate kind. Only the singular // storage costs can be reduced using the appropriate kind. Only the singular
// values can be computed (kind == SVDNone), or a "thin" representation of the // values can be computed (kind == SVDNone), or a "thin" representation of the
// singular vectors (kind = SVDThin). The thin representation can save a significant // singular vectors (kind = SVDThin). The thin representation can save a significant
// amount of memory if m >> n. See the documentation for the lapack.SVDKind values // amount of memory if m >> n.
// for more information.
// //
// Factorize returns whether the decomposition succeeded. If the decomposition // Factorize returns whether the decomposition succeeded. If the decomposition
// failed, routines that require a successful factorization will panic. // failed, routines that require a successful factorization will panic.
@@ -81,8 +80,8 @@ func (svd *SVD) Factorize(a Matrix, kind SVDKind) (ok bool) {
Stride: n, Stride: n,
Data: use(svd.vt.Data, min(m, n)*n), Data: use(svd.vt.Data, min(m, n)*n),
} }
jobU = lapack.SVDInPlace jobU = lapack.SVDStore
jobVT = lapack.SVDInPlace jobVT = lapack.SVDStore
} }
// A is destroyed on call, so copy the matrix. // A is destroyed on call, so copy the matrix.
@@ -119,7 +118,7 @@ func (svd *SVD) Cond() float64 {
// Values returns the singular values of the factorized matrix in decreasing order. // Values returns the singular values of the factorized matrix in decreasing order.
// If the input slice is non-nil, the values will be stored in-place into the slice. // If the input slice is non-nil, the values will be stored in-place into the slice.
// In this case, the slice must have length min(m,n), and Values will panic with // In this case, the slice must have length min(m,n), and Values will panic with
// matrix.ErrSliceLengthMismatch otherwise. If the input slice is nil, // ErrSliceLengthMismatch otherwise. If the input slice is nil,
// a new slice of the appropriate length will be allocated and returned. // a new slice of the appropriate length will be allocated and returned.
// //
// Values will panic if the receiver does not contain a successful factorization. // Values will panic if the receiver does not contain a successful factorization.