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mat: move SolveLQ* onto LQ

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kortschak
2017-06-30 14:36:12 +09:30
committed by Dan Kortschak
parent 8dc3a3df20
commit f9e7e06e3e
3 changed files with 12 additions and 12 deletions
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14
mat/lq.go
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@@ -121,7 +121,7 @@ func (lq *LQ) QTo(dst *Dense) *Dense {
return dst
}
// SolveLQ finds a minimum-norm solution to a system of linear equations defined
// Solve finds a minimum-norm solution to a system of linear equations defined
// by the matrices A and b, where A is an m×n matrix represented in its LQ factorized
// form. If A is singular or near-singular a Condition error is returned. Please
// see the documentation for Condition for more information.
@@ -129,8 +129,8 @@ func (lq *LQ) QTo(dst *Dense) *Dense {
// The minimization problem solved depends on the input parameters.
// If trans == false, find the minimum norm solution of A * X = b.
// If trans == true, find X such that ||A*X - b||_2 is minimized.
// The solution matrix, X, is stored in place into the receiver.
func (m *Dense) SolveLQ(lq *LQ, trans bool, b Matrix) error {
// The solution matrix, X, is stored in place into m.
func (lq *LQ) Solve(m *Dense, trans bool, b Matrix) error {
r, c := lq.lq.Dims()
br, bc := b.Dims()
@@ -188,9 +188,9 @@ func (m *Dense) SolveLQ(lq *LQ, trans bool, b Matrix) error {
return nil
}
// SolveLQVec finds a minimum-norm solution to a system of linear equations.
// Please see Dense.SolveLQ for the full documentation.
func (v *Vector) SolveLQVec(lq *LQ, trans bool, b *Vector) error {
// SolveVec finds a minimum-norm solution to a system of linear equations.
// Please see LQ.Solve for the full documentation.
func (lq *LQ) SolveVec(v *Vector, trans bool, b *Vector) error {
if v != b {
v.checkOverlap(b.mat)
}
@@ -202,5 +202,5 @@ func (v *Vector) SolveLQVec(lq *LQ, trans bool, b *Vector) error {
} else {
v.reuseAs(c)
}
return v.asDense().SolveLQ(lq, trans, b.asDense())
return lq.Solve(v.asDense(), trans, b.asDense())
}

8
mat/lq_test.go
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@@ -77,7 +77,7 @@ func TestSolveLQ(t *testing.T) {
var x Dense
lq := &LQ{}
lq.Factorize(a)
x.SolveLQ(lq, trans, b)
lq.Solve(&x, trans, b)
// Test that the normal equations hold.
// A^T * A * x = A^T * b if !trans
@@ -130,7 +130,7 @@ func TestSolveLQVec(t *testing.T) {
var x Vector
lq := &LQ{}
lq.Factorize(a)
x.SolveLQVec(lq, trans, b)
lq.SolveVec(&x, trans, b)
// Test that the normal equations hold.
// A^T * A * x = A^T * b if !trans
@@ -166,13 +166,13 @@ func TestSolveLQCond(t *testing.T) {
lq.Factorize(test)
b := NewDense(m, 2, nil)
var x Dense
if err := x.SolveLQ(&lq, false, b); err == nil {
if err := lq.Solve(&x, false, b); err == nil {
t.Error("No error for near-singular matrix in matrix solve.")
}
bvec := NewVector(m, nil)
var xvec Vector
if err := xvec.SolveLQVec(&lq, false, bvec); err == nil {
if err := lq.SolveVec(&xvec, false, bvec); err == nil {
t.Error("No error for near-singular matrix in matrix solve.")
}
}

2
mat/solve.go
View File

@@ -99,7 +99,7 @@ func (m *Dense) Solve(a, b Matrix) error {
default:
var lq LQ
lq.Factorize(a)
return m.SolveLQ(&lq, false, b)
return lq.Solve(m, false, b)
}
}