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ldlbku_test.go
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// Copyright (c) Harri Rautila, 2012,2013
// This file is part of github.com/hrautila/matops package. It is free software,
// distributed under the terms of GNU Lesser General Public License Version 3, or
// any later version. See the COPYING tile included in this archive.
package matops
import (
"github.com/henrylee2cn/algorithm/linalg"
"github.com/henrylee2cn/algorithm/linalg/lapack"
"github.com/henrylee2cn/algorithm/matrix"
"testing"
)
func ldlbkDecomposeUpperTest(A *matrix.FloatMatrix, t *testing.T) {
TriU(A)
N := A.Cols()
nb := 0
W := matrix.FloatZeros(A.Rows(), 5)
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("L:\n%v\n", L)
t.Logf("unblked ipiv: %v\n", ipiv)
ipiv0 := make([]int, N, N)
nb = 4
L0, _ := DecomposeBK(A.Copy(), W, ipiv0, UPPER, nb)
t.Logf("L:\n%v\n", L0)
t.Logf("blked ipiv: %v\n", ipiv0)
ipiv2 := make([]int32, N, N)
lapack.SytrfFloat(A, ipiv2, linalg.OptUpper)
t.Logf("lapack A:\n%v\n", A)
t.Logf("lapack ipiv: %v\n", ipiv2)
}
func _TestBKSavedUpper(t *testing.T) {
Aorig := fromFile("test/saved.dat", t)
ldlbkDecomposeUpperTest(Aorig, t)
}
func _TestBKpivot2U(t *testing.T) {
Ldata := [][]float64{
[]float64{7.0, 6.0, 5.0, 9.0, 3.0, 2.0, 1.0},
[]float64{1.0, 6.0, 9.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 2.0, 5.0, 4.0, 3.0, 5.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 5.0, 3.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 9.0, 2.0, 1.0},
[]float64{1.0, 2.0, 3.0, 9.0, 5.0, 6.0, 1.0}}
Bdata := [][]float64{
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0}}
A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
N := A.Rows()
B := matrix.FloatZeros(N, 2)
MultSym(B, A, X, 1.0, 0.0, UPPER|LEFT)
//t.Logf("initial B:\n%v\n", B)
nb := 0
W := matrix.FloatWithValue(A.Rows(), 5, 0.0)
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
ipiv0 := make([]int, N, N)
nb = 4
L0, _ := DecomposeBK(A.Copy(), W, ipiv0, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv0)
t.Logf("L:\n%v\n", L0)
//B0 := B.Copy()
//SolveBK(B0, L0, ipiv0, LOWER)
//t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.SytrfFloat(A, ipiv2, linalg.OptUpper)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
//lapack.Sytrs(A, B, ipiv2, linalg.OptUpper)
//t.Logf("lapack B:\n%v\n", B)
//t.Logf("B == B0: %v\n", B.AllClose(B0))
}
func _TestBKpivot2n1U(t *testing.T) {
Ldata := [][]float64{
[]float64{7.0, 6.0, 5.0, 9.0, 3.0, 2.0, 1.0},
[]float64{1.0, 6.0, 9.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 2.0, 5.0, 4.0, 3.0, 5.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 5.0, 3.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 9.0, 2.0, 1.0},
[]float64{1.0, 2.0, 3.0, 9.0, 5.0, 6.0, 1.0}}
Bdata := [][]float64{
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0}}
A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
N := A.Rows()
B := matrix.FloatZeros(N, 2)
MultSym(B, A, X, 1.0, 0.0, UPPER|LEFT)
//t.Logf("initial B:\n%v\n", B)
nb := 0
W := matrix.FloatWithValue(A.Rows(), 5, 0.0)
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
//ipiv0 := make([]int, N, N)
//nb = 4
//L0, _ := DecomposeBK(A.Copy(), W, ipiv0, UPPER, nb)
//t.Logf("ipiv: %v\n", ipiv0)
//t.Logf("L:\n%v\n", L0)
//B0 := B.Copy()
//SolveBK(B0, L0, ipiv0, LOWER)
//t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.SytrfFloat(A, ipiv2, linalg.OptUpper)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
//lapack.Sytrs(A, B, ipiv2, linalg.OptUpper)
//t.Logf("lapack B:\n%v\n", B)
//t.Logf("B == B0: %v\n", B.AllClose(B0))
}
func _TestBKpivot2n2U(t *testing.T) {
Ldata := [][]float64{
[]float64{1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0},
[]float64{1.0, 2.0, 2.0, 2.0, 5.0, 2.0, 2.0},
[]float64{1.0, 2.0, 3.0, 3.0, 3.0, 3.0, 3.0},
[]float64{1.0, 2.0, 3.0, 4.0, 4.0, 4.0, 10.0},
[]float64{1.0, 5.0, 3.0, 4.0, 5.0, 9.0, 5.0},
[]float64{1.0, 2.0, 3.0, 4.0, 9.0, 6.0, 6.0},
[]float64{1.0, 2.0, 3.0, 10.0, 5.0, 6.0, 7.0}}
Bdata := [][]float64{
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0}}
A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
N := A.Rows()
B := matrix.FloatZeros(N, 2)
MultSym(B, A, X, 1.0, 0.0, UPPER|LEFT)
//t.Logf("initial B:\n%v\n", B)
nb := 0
W := matrix.FloatWithValue(A.Rows(), 5, 0.0)
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
//ipiv0 := make([]int, N, N)
//nb = 4
//L0, _ := DecomposeBK(A.Copy(), W, ipiv0, UPPER, nb)
//t.Logf("ipiv: %v\n", ipiv0)
//t.Logf("L:\n%v\n", L0)
//B0 := B.Copy()
//SolveBK(B0, L0, ipiv0, UPPER)
//t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.SytrfFloat(A, ipiv2, linalg.OptUpper)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
//lapack.Sytrs(A, B, ipiv2, linalg.OptUpper)
//t.Logf("lapack B:\n%v\n", B)
//t.Logf("B == B0: %v\n", B.AllClose(B0))
}
func _TestBKpivot1U(t *testing.T) {
Ldata := [][]float64{
[]float64{7.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 6.0, 5.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 2.0, 5.0, 4.0, 3.0, 5.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 5.0, 3.0, 4.0, 3.0, 2.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 5.0, 2.0, 1.0},
[]float64{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 1.0}}
Bdata := [][]float64{
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0}}
A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
N := A.Rows()
B := matrix.FloatZeros(N, 2)
MultSym(B, A, X, 1.0, 0.0, UPPER|LEFT)
//t.Logf("initial B:\n%v\n", B)
//N := 8
//A := matrix.FloatUniformSymmetric(N)
W := matrix.FloatWithValue(A.Rows(), 5, 0.0)
nb := 0
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
nb = 4
//ipiv0 := make([]int, N, N)
//L0, _ := DecomposeBK(A.Copy(), W, ipiv0, LOWER, nb)
//t.Logf("ipiv: %v\n", ipiv0)
//t.Logf("L:\n%v\n", L0)
//B0 := B.Copy()
//SolveBK(B0, L0, ipiv0, LOWER)
//t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.SytrfFloat(A, ipiv2, linalg.OptUpper)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
//lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
//t.Logf("lapack B:\n%v\n", B)
//t.Logf("B == B0: %v\n", B.AllClose(B0))
}
func _TestBKpivot1n2U(t *testing.T) {
Ldata := [][]float64{
[]float64{1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0},
[]float64{1.0, 2.0, 2.0, 2.0, 5.0, 2.0, 2.0},
[]float64{1.0, 2.0, 3.0, 3.0, 3.0, 3.0, 3.0},
[]float64{1.0, 2.0, 3.0, 4.0, 4.0, 7.0, 4.0},
[]float64{1.0, 5.0, 3.0, 4.0, 5.0, 5.0, 5.0},
[]float64{1.0, 2.0, 3.0, 7.0, 5.0, 6.0, 6.0},
[]float64{1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0}}
Bdata := [][]float64{
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0}}
A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
N := A.Rows()
B := matrix.FloatZeros(N, 2)
MultSym(B, A, X, 1.0, 0.0, UPPER|LEFT)
t.Logf("initial B:\n%v\n", B)
nb := 0
W := matrix.FloatWithValue(A.Rows(), 5, 0.0)
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
ipiv0 := make([]int, N, N)
nb = 4
L0, _ := DecomposeBK(A.Copy(), W, ipiv0, UPPER, nb)
t.Logf("ipiv0: %v\n", ipiv0)
t.Logf("L0:\n%v\n", L0)
//B0 := B.Copy()
//SolveBK(B0, L0, ipiv0, LOWER)
//t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.Sytrf(A, ipiv2, linalg.OptUpper)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
//lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
//t.Logf("lapack B:\n%v\n", B)
//t.Logf("B == B0: %v\n", B.AllClose(B0))
}
func _TestBK2U(t *testing.T) {
Bdata := [][]float64{
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0},
[]float64{10.0, 20.0}}
N := 7
A0 := matrix.FloatNormal(N, N)
A := matrix.FloatZeros(N, N)
// A is symmetric, posivite definite
Mult(A, A0, A0, 1.0, 1.0, TRANSB)
X := matrix.FloatMatrixFromTable(Bdata, matrix.RowOrder)
B := matrix.FloatZeros(N, 2)
MultSym(B, A, X, 1.0, 0.0, LOWER|LEFT)
t.Logf("initial B:\n%v\n", B)
nb := 0
W := matrix.FloatWithValue(A.Rows(), 5, 1.0)
A.SetAt(4, 1, A.GetAt(4, 1)+1.0)
A.SetAt(1, 4, A.GetAt(4, 1))
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, LOWER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
ipiv0 := make([]int, N, N)
nb = 4
L0, _ := DecomposeBK(A.Copy(), W, ipiv0, LOWER, nb)
t.Logf("ipiv: %v\n", ipiv0)
t.Logf("L:\n%v\n", L0)
B0 := B.Copy()
SolveBK(B0, L0, ipiv0, LOWER)
t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.Sytrf(A, ipiv2, linalg.OptLower)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
t.Logf("lapack B:\n%v\n", B)
t.Logf("B == B0: %v\n", B.AllClose(B0))
}
func _TestBKSolveU(t *testing.T) {
Ldata := [][]float64{
[]float64{1.0, 2.0, 3.0, 4.0},
[]float64{2.0, 2.0, 3.0, 4.0},
[]float64{3.0, 3.0, 3.0, 4.0},
[]float64{4.0, 4.0, 4.0, 4.0}}
Xdata := [][]float64{
[]float64{1.0, 2.0},
[]float64{1.0, 2.0},
[]float64{1.0, 2.0},
[]float64{1.0, 2.0}}
A := matrix.FloatMatrixFromTable(Ldata, matrix.RowOrder)
X := matrix.FloatMatrixFromTable(Xdata, matrix.RowOrder)
N := A.Rows()
B := matrix.FloatZeros(N, 2)
Mult(B, A, X, 1.0, 0.0, NOTRANS)
S := matrix.FloatZeros(N, 2)
MultSym(S, A, X, 1.0, 0.0, LOWER|UPPER)
_, _ = S, B
//t.Logf("B:\n%v\n", B)
//t.Logf("S:\n%v\n", S)
nb := 0
W := matrix.FloatWithValue(A.Rows(), 5, 0.0)
ipiv := make([]int, N, N)
L, _ := DecomposeBK(A.Copy(), W, ipiv, UPPER, nb)
t.Logf("ipiv: %v\n", ipiv)
t.Logf("L:\n%v\n", L)
//B0 := B.Copy()
//SolveBK(B0, L, ipiv, LOWER)
//t.Logf("B0:\n%v\n", B0)
ipiv2 := make([]int32, N, N)
lapack.Sytrf(A, ipiv2, linalg.OptUpper)
t.Logf("ipiv2: %v\n", ipiv2)
t.Logf("lapack A:\n%v\n", A)
//lapack.Sytrs(A, B, ipiv2, linalg.OptLower)
//t.Logf("lapack B:\n%v\n", B)
}
// Local Variables:
// tab-width: 4
// indent-tabs-mode: nil
// End: