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Add QR factorization to lapack64 interface.
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@@ -77,6 +77,71 @@ func (impl Implementation) Dpotrf(ul blas.Uplo, n int, a []float64, lda int) (ok
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return clapack.Dpotrf(ul, n, a, lda)
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return clapack.Dpotrf(ul, n, a, lda)
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}
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}
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// Dgeqr2 computes a QR factorization of the m×n matrix A.
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//
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// In a QR factorization, Q is an m×m orthonormal matrix, and R is an
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// upper triangular m×n matrix.
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//
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// During Dgeqr2, a is modified to contain the information to construct Q and R.
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// The upper triangle of a contains the matrix R. The lower triangular elements
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// (not including the diagonal) contain the elementary reflectors. Tau is modified
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// to contain the reflector scales. Tau must have length at least k = min(m,n), and
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// this function will panic otherwise.
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//
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// The ith elementary reflector can be explicitly constructed by first extracting
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// the
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// v[j] = 0 j < i
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// v[j] = i j == i
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// v[j] = a[i*lda+j] j > i
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// and computing h_i = I - tau[i] * v * v^T.
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//
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// The orthonormal matrix Q can be constucted from a product of these elementary
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// reflectors, Q = H_1*H_2 ... H_k, where k = min(m,n).
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//
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// Work is temporary storage of length at least n and this function will panic otherwise.
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func (impl Implementation) Dgeqr2(m, n int, a []float64, lda int, tau, work []float64) {
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// TODO(btracey): This is oriented such that columns of a are eliminated.
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// This likely could be re-arranged to take better advantage of row-major
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// storage.
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checkMatrix(m, n, a, lda)
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if len(work) < n {
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panic(badWork)
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}
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k := min(m, n)
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if len(tau) < k {
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panic(badTau)
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}
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clapack.Dgeqr2(m, n, a, lda, tau)
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}
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// Dgeqrf computes the QR factorization of the m×n matrix A using a blocked
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// algorithm. Please see the documentation for Dgeqr2 for a description of the
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// parameters at entry and exit.
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//
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// The C interface does not support providing temporary storage. To provide compatibility
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// with native, lwork == -1 will not run Dgeqrf but will instead write the minimum
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// work necessary to work[0]. If len(work) < lwork, Dgels will panic.
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//
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// tau must be at least len min(m,n), and this function will panic otherwise.
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func (impl Implementation) Dgeqrf(m, n int, a []float64, lda int, tau, work []float64, lwork int) {
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if lwork == -1 {
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work[0] = float64(n)
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return
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}
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checkMatrix(m, n, a, lda)
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if len(work) < lwork {
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panic(shortWork)
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}
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if lwork < n {
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panic(badWork)
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}
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k := min(m, n)
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if len(tau) < k {
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panic(badTau)
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}
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clapack.Dgeqrf(m, n, a, lda, tau)
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}
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// Dgetf2 computes the LU decomposition of the m×n matrix A.
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// Dgetf2 computes the LU decomposition of the m×n matrix A.
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// The LU decomposition is a factorization of a into
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// The LU decomposition is a factorization of a into
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// A = P * L * U
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// A = P * L * U
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@@ -16,6 +16,14 @@ func TestDpotrf(t *testing.T) {
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testlapack.DpotrfTest(t, impl)
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testlapack.DpotrfTest(t, impl)
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}
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}
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func TestDgeqr2(t *testing.T) {
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testlapack.Dgeqr2Test(t, impl)
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}
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func TestDgeqrf(t *testing.T) {
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testlapack.DgeqrfTest(t, impl)
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}
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func TestDgetf2(t *testing.T) {
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func TestDgetf2(t *testing.T) {
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testlapack.Dgetf2Test(t, impl)
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testlapack.Dgetf2Test(t, impl)
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}
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}
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@@ -23,6 +23,7 @@ type Complex128 interface{}
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// Float64 defines the public float64 LAPACK API supported by gonum/lapack.
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// Float64 defines the public float64 LAPACK API supported by gonum/lapack.
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type Float64 interface {
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type Float64 interface {
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Dgeqrf(m, n int, a []float64, lda int, tau, work []float64, lwork int)
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Dpotrf(ul blas.Uplo, n int, a []float64, lda int) (ok bool)
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Dpotrf(ul blas.Uplo, n int, a []float64, lda int) (ok bool)
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}
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}
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@@ -47,3 +47,29 @@ func Potrf(a blas64.Symmetric) (t blas64.Triangular, ok bool) {
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t.Diag = blas.NonUnit
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t.Diag = blas.NonUnit
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return
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return
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}
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}
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// Geqrf computes the QR factorization of the m×n matrix A using a blocked
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// algorithm. During Dgeqr2, A is modified to contain the information to construct Q and R.
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// The upper triangle of a contains the matrix R. The lower triangular elements
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// (not including the diagonal) contain the elementary reflectors. Tau is modified
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// to contain the reflector scales. Tau must have length at least k = min(m,n), and
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// this function will panic otherwise.
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//
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// The ith elementary reflector can be explicitly constructed by first extracting
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// the
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// v[j] = 0 j < i
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// v[j] = i j == i
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// v[j] = a[i*lda+j] j > i
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// and computing h_i = I - tau[i] * v * v^T.
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//
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// The orthonormal matrix Q can be constucted from a product of these elementary
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// reflectors, Q = H_1*H_2 ... H_k, where k = min(m,n).
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//
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// Work is temporary storage, and lwork specifies the usable memory length.
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// At minimum, lwork >= m and this function will panic otherwise.
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// Dgeqrf is a blocked LQ factorization, but the block size is limited
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// by the temporary space available. If lwork == -1, instead of performing Dgelqf,
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// the optimal work length will be stored into work[0].
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func Geqrf(a blas64.General, tau, work []float64, lwork int) {
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lapack64.Dgeqrf(a.Rows, a.Cols, a.Data, a.Stride, tau, work, lwork)
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}
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@@ -6,7 +6,7 @@ package native
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import "github.com/gonum/blas"
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import "github.com/gonum/blas"
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// Dgeqr2 computes a QR factorization of the m×n matrix a.
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// Dgeqr2 computes a QR factorization of the m×n matrix A.
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//
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//
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// In a QR factorization, Q is an m×m orthonormal matrix, and R is an
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// In a QR factorization, Q is an m×m orthonormal matrix, and R is an
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// upper triangular m×n matrix.
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// upper triangular m×n matrix.
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@@ -66,7 +66,7 @@ func DgeqrfTest(t *testing.T, impl Dgeqrfer) {
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impl.Dgeqr2(m, n, ans, lda, tau, work)
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impl.Dgeqr2(m, n, ans, lda, tau, work)
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// Compute blocked QR with small work.
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// Compute blocked QR with small work.
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impl.Dgeqrf(m, n, a, lda, tau, work, len(work))
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impl.Dgeqrf(m, n, a, lda, tau, work, len(work))
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if !floats.EqualApprox(ans, a, 1e-14) {
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if !floats.EqualApprox(ans, a, 1e-12) {
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t.Errorf("Case %v, mismatch small work.", c)
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t.Errorf("Case %v, mismatch small work.", c)
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}
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}
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// Try the full length of work.
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// Try the full length of work.
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@@ -80,6 +80,9 @@ func DgeqrfTest(t *testing.T, impl Dgeqrfer) {
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}
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}
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// Try a slightly smaller version of work to test blocking.
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// Try a slightly smaller version of work to test blocking.
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if len(work) <= n {
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continue
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}
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work = work[1:]
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work = work[1:]
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lwork--
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lwork--
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copy(a, aCopy)
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copy(a, aCopy)
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