func main() {
// input matrix in Triplet format
// including repeated positions. e.g. (0,0)
var A la.Triplet
A.Init(5, 5, 13)
A.Put(0, 0, 1.0) // << repeated
A.Put(0, 0, 1.0) // << repeated
A.Put(1, 0, 3.0)
A.Put(0, 1, 3.0)
A.Put(2, 1, -1.0)
A.Put(4, 1, 4.0)
A.Put(1, 2, 4.0)
A.Put(2, 2, -3.0)
A.Put(3, 2, 1.0)
A.Put(4, 2, 2.0)
A.Put(2, 3, 2.0)
A.Put(1, 4, 6.0)
A.Put(4, 4, 1.0)
// right-hand-side
b := []float64{8.0, 45.0, -3.0, 3.0, 19.0}
// solve
x, err := la.SolveRealLinSys(&A, b)
if err != nil {
io.Pfred("solver failed:\n%v", err)
return
}
// output
la.PrintMat("a", A.ToMatrix(nil).ToDense(), "%5g", false)
la.PrintVec("b", b, "%v ", false)
la.PrintVec("x", x, "%v ", false)
}
func main() {
// input matrix in Triplet format
// including repeated positions. e.g. (0,0)
var A la.Triplet
A.Init(5, 5, 13)
A.Put(0, 0, 1.0) // << repeated
A.Put(0, 0, 1.0) // << repeated
A.Put(1, 0, 3.0)
A.Put(0, 1, 3.0)
A.Put(2, 1, -1.0)
A.Put(4, 1, 4.0)
A.Put(1, 2, 4.0)
A.Put(2, 2, -3.0)
A.Put(3, 2, 1.0)
A.Put(4, 2, 2.0)
A.Put(2, 3, 2.0)
A.Put(1, 4, 6.0)
A.Put(4, 4, 1.0)
// right-hand-side
b := []float64{8.0, 45.0, -3.0, 3.0, 19.0}
// allocate solver
lis := la.GetSolver("umfpack")
defer lis.Clean()
// info
symmetric := false
verbose := false
timing := false
// initialise solver (R)eal
err := lis.InitR(&A, symmetric, verbose, timing)
if err != nil {
io.Pfred("solver failed:\n%v", err)
return
}
// factorise
err = lis.Fact()
if err != nil {
io.Pfred("solver failed:\n%v", err)
return
}
// solve (R)eal
var dummy bool
x := make([]float64, len(b))
err = lis.SolveR(x, b, dummy) // x := inv(a) * b
if err != nil {
io.Pfred("solver failed:\n%v", err)
return
}
// output
la.PrintMat("a", A.ToMatrix(nil).ToDense(), "%5g", false)
la.PrintVec("b", b, "%v ", false)
la.PrintVec("x", x, "%v ", false)
}
func CompareJac(tst *testing.T, ffcn Cb_f, Jfcn Cb_J, x []float64, tol float64, distr bool) {
n := len(x)
// numerical
fx := make([]float64, n)
w := make([]float64, n) // workspace
ffcn(fx, x)
var Jnum la.Triplet
Jnum.Init(n, n, n*n)
Jacobian(&Jnum, ffcn, x, fx, w, distr)
jn := Jnum.ToMatrix(nil)
// analytical
var Jana la.Triplet
Jana.Init(n, n, n*n)
Jfcn(&Jana, x)
ja := Jana.ToMatrix(nil)
// compare
//la.PrintMat(fmt.Sprintf("Jana(%d)",mpi.Rank()), ja.ToDense(), "%13.6f", false)
//la.PrintMat(fmt.Sprintf("Jnum(%d)",mpi.Rank()), jn.ToDense(), "%13.6f", false)
max_diff := la.MatMaxDiff(jn.ToDense(), ja.ToDense())
if max_diff > tol {
tst.Errorf("[1;31mmax_diff = %g[0m\n", max_diff)
} else {
io.Pf("[1;32mmax_diff = %g[0m\n", max_diff)
}
}
// CompareJacMpi compares Jacobian matrix (e.g. for testing)
func CompareJacMpi(tst *testing.T, ffcn Cb_f, Jfcn Cb_J, x []float64, tol float64, distr bool) {
// numerical
n := len(x)
fx := make([]float64, n)
w := make([]float64, n) // workspace
ffcn(fx, x)
var Jnum la.Triplet
Jnum.Init(n, n, n*n)
JacobianMpi(&Jnum, ffcn, x, fx, w, distr)
jn := Jnum.ToMatrix(nil)
// analytical
var Jana la.Triplet
Jana.Init(n, n, n*n)
Jfcn(&Jana, x)
ja := Jana.ToMatrix(nil)
// compare
max_diff := la.MatMaxDiff(jn.ToDense(), ja.ToDense())
if max_diff > tol {
tst.Errorf("[1;31mmax_diff = %g[0m\n", max_diff)
} else {
io.Pf("[1;32mmax_diff = %g[0m\n", max_diff)
}
}
// CheckJ check Jacobian matrix
// Ouptut: cnd -- condition number (with Frobenius norm)
func (o *NlSolver) CheckJ(x []float64, tol float64, chkJnum, silent bool) (cnd float64, err error) {
// Jacobian matrix
var Jmat [][]float64
if o.useDn {
Jmat = la.MatAlloc(o.neq, o.neq)
err = o.JfcnDn(Jmat, x)
if err != nil {
return 0, chk.Err(_nls_err5, "dense", err.Error())
}
} else {
if o.numJ {
err = Jacobian(&o.Jtri, o.Ffcn, x, o.fx, o.w, false)
if err != nil {
return 0, chk.Err(_nls_err5, "sparse", err.Error())
}
} else {
err = o.JfcnSp(&o.Jtri, x)
if err != nil {
return 0, chk.Err(_nls_err5, "sparse(num)", err.Error())
}
}
Jmat = o.Jtri.ToMatrix(nil).ToDense()
}
//la.PrintMat("J", Jmat, "%23g", false)
// condition number
cnd, err = la.MatCondG(Jmat, "F", 1e-10)
if err != nil {
return cnd, chk.Err(_nls_err6, err.Error())
}
if math.IsInf(cnd, 0) || math.IsNaN(cnd) {
return cnd, chk.Err(_nls_err7, cnd)
}
// numerical Jacobian
if !chkJnum {
return
}
var Jtmp la.Triplet
ws := make([]float64, o.neq)
err = o.Ffcn(o.fx, x)
if err != nil {
return
}
Jtmp.Init(o.neq, o.neq, o.neq*o.neq)
Jacobian(&Jtmp, o.Ffcn, x, o.fx, ws, false)
Jnum := Jtmp.ToMatrix(nil).ToDense()
for i := 0; i < o.neq; i++ {
for j := 0; j < o.neq; j++ {
chk.PrintAnaNum(io.Sf("J[%d][%d]", i, j), tol, Jmat[i][j], Jnum[i][j], !silent)
}
}
maxdiff := la.MatMaxDiff(Jmat, Jnum)
if maxdiff > tol {
err = chk.Err(_nls_err8, maxdiff)
}
return
}
func main() {
mpi.Start(false)
defer func() {
mpi.Stop(false)
}()
if mpi.Rank() == 0 {
chk.PrintTitle("Test SumToRoot 01")
}
M := [][]float64{
{1000, 1000, 1000, 1011, 1021, 1000},
{1000, 1000, 1000, 1012, 1022, 1000},
{1000, 1000, 1000, 1013, 1023, 1000},
{1011, 1012, 1013, 1000, 1000, 1000},
{1021, 1022, 1023, 1000, 1000, 1000},
{1000, 1000, 1000, 1000, 1000, 1000},
}
id, sz, m := mpi.Rank(), mpi.Size(), len(M)
start, endp1 := (id*m)/sz, ((id+1)*m)/sz
if sz > 6 {
chk.Panic("this test works with at most 6 processors")
}
var J la.Triplet
J.Init(m, m, m*m)
for i := start; i < endp1; i++ {
for j := 0; j < m; j++ {
J.Put(i, j, M[i][j])
}
}
la.PrintMat(fmt.Sprintf("J @ proc # %d", id), J.ToMatrix(nil).ToDense(), "%10.1f", false)
la.SpTriSumToRoot(&J)
var tst testing.T
if mpi.Rank() == 0 {
chk.Matrix(&tst, "J @ proc 0", 1.0e-17, J.ToMatrix(nil).ToDense(), [][]float64{
{1000, 1000, 1000, 1011, 1021, 1000},
{1000, 1000, 1000, 1012, 1022, 1000},
{1000, 1000, 1000, 1013, 1023, 1000},
{1011, 1012, 1013, 1000, 1000, 1000},
{1021, 1022, 1023, 1000, 1000, 1000},
{1000, 1000, 1000, 1000, 1000, 1000},
})
}
}
func Test_assemb01(tst *testing.T) {
chk.PrintTitle("assemb01")
// grid
var g Grid2D
g.Init(1.0, 1.0, 3, 3)
// equations numbering
var e Equations
e.Init(g.N, []int{0, 3, 6})
// K11 and K12
var K11, K12 la.Triplet
InitK11andK12(&K11, &K12, &e)
// assembly
F1 := make([]float64, e.N1)
Assemble(&K11, &K12, F1, nil, &g, &e)
// check
K11d := K11.ToMatrix(nil).ToDense()
K12d := K12.ToMatrix(nil).ToDense()
K11c := [][]float64{
{16.0, -4.0, -8.0, 0.0, 0.0, 0.0},
{-8.0, 16.0, 0.0, -8.0, 0.0, 0.0},
{-4.0, 0.0, 16.0, -4.0, -4.0, 0.0},
{0.0, -4.0, -8.0, 16.0, 0.0, -4.0},
{0.0, 0.0, -8.0, 0.0, 16.0, -4.0},
{0.0, 0.0, 0.0, -8.0, -8.0, 16.0},
}
K12c := [][]float64{
{-4.0, 0.0, 0.0},
{0.0, 0.0, 0.0},
{0.0, -4.0, 0.0},
{0.0, 0.0, 0.0},
{0.0, 0.0, -4.0},
{0.0, 0.0, 0.0},
}
chk.Matrix(tst, "K11: ", 1e-16, K11d, K11c)
chk.Matrix(tst, "K12: ", 1e-16, K12d, K12c)
}
func TestJacobian03(tst *testing.T) {
//verbose()
chk.PrintTitle("TestJacobian 03")
// grid
var g fdm.Grid2D
//g.Init(1.0, 1.0, 4, 4)
g.Init(1.0, 1.0, 6, 6)
//g.Init(1.0, 1.0, 11, 11)
// equations numbering
var e fdm.Equations
peq := utl.IntUnique(g.L, g.R, g.B, g.T)
e.Init(g.N, peq)
// K11 and K12
var K11, K12 la.Triplet
fdm.InitK11andK12(&K11, &K12, &e)
// assembly
F1 := make([]float64, e.N1)
fdm.Assemble(&K11, &K12, F1, nil, &g, &e)
// prescribed values
U2 := make([]float64, e.N2)
for _, eq := range g.L {
U2[e.FR2[eq]] = 50.0
}
for _, eq := range g.R {
U2[e.FR2[eq]] = 0.0
}
for _, eq := range g.B {
U2[e.FR2[eq]] = 0.0
}
for _, eq := range g.T {
U2[e.FR2[eq]] = 50.0
}
// functions
k11 := K11.ToMatrix(nil)
k12 := K12.ToMatrix(nil)
ffcn := func(fU1, U1 []float64) error { // K11*U1 + K12*U2 - F1
la.VecCopy(fU1, -1, F1) // fU1 := (-F1)
la.SpMatVecMulAdd(fU1, 1, k11, U1) // fU1 += K11*U1
la.SpMatVecMulAdd(fU1, 1, k12, U2) // fU1 += K12*U2
return nil
}
Jfcn := func(dfU1dU1 *la.Triplet, U1 []float64) error {
fdm.Assemble(dfU1dU1, &K12, F1, nil, &g, &e)
return nil
}
U1 := make([]float64, e.N1)
CompareJac(tst, ffcn, Jfcn, U1, 0.0075)
print_jac := false
if print_jac {
W1 := make([]float64, e.N1)
fU1 := make([]float64, e.N1)
ffcn(fU1, U1)
var Jnum la.Triplet
Jnum.Init(e.N1, e.N1, e.N1*e.N1)
Jacobian(&Jnum, ffcn, U1, fU1, W1)
la.PrintMat("K11 ", K11.ToMatrix(nil).ToDense(), "%g ", false)
la.PrintMat("Jnum", Jnum.ToMatrix(nil).ToDense(), "%g ", false)
}
test_ffcn := false
if test_ffcn {
Uc := []float64{0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0, 25.0, 325.0 / 22.0, 100.0 / 11.0, 50.0 / 11.0,
0.0, 50.0, 775.0 / 22.0, 25.0, 375.0 / 22.0, 100.0 / 11.0, 0.0, 50.0, 450.0 / 11.0, 725.0 / 22.0,
25.0, 325.0 / 22.0, 0.0, 50.0, 500.0 / 11.0, 450.0 / 11.0, 775.0 / 22.0, 25.0, 0.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0,
}
for i := 0; i < e.N1; i++ {
U1[i] = Uc[e.RF1[i]]
}
fU1 := make([]float64, e.N1)
min, max := la.VecMinMax(fU1)
io.Pf("min/max fU1 = %v\n", min, max)
}
}
func TestDiffusion1D(tst *testing.T) {
//verbose()
chk.PrintTitle("Test Diffusion 1D (cooling)")
// solution parameters
silent := false
fixstp := true
//fixstp := false
//method := "FwEuler"
method := "BwEuler"
//method := "Dopri5"
//method := "Radau5"
//numjac := true
numjac := false
rtol := 1e-4
atol := rtol
// timestep
t0, tf, dt := 0.0, 0.2, 0.03
// problem data
kx := 1.0 // conductivity
N := 6 // number of nodes
//Nb := N + 2 // augmented system dimension
xmax := 1.0 // length
dx := xmax / float64(N-1) // spatial step size
dxx := dx * dx
mol := []float64{kx / dxx, -2.0 * kx / dxx, kx / dxx}
// function
fcn := func(f []float64, t float64, y []float64, args ...interface{}) error {
for i := 0; i < N; i++ {
f[i] = 0
if i == 0 || i == N-1 {
continue // skip presc node
}
for p, j := range []int{i - 1, i, i + 1} {
if j < 0 {
j = i + 1
} // left boundary
if j == N {
j = i - 1
} // right boundary
f[i] += mol[p] * y[j]
}
}
//io.Pfgrey("y = %v\n", y)
//io.Pfcyan("f = %v\n", f)
return nil
}
// Jacobian
jac := func(dfdy *la.Triplet, t float64, y []float64, args ...interface{}) error {
//chk.Panic("jac is not available")
if dfdy.Max() == 0 {
//dfdy.Init(Nb, Nb, 3*N)
dfdy.Init(N, N, 3*N)
}
dfdy.Start()
for i := 0; i < N; i++ {
if i == 0 || i == N-1 {
dfdy.Put(i, i, 0.0)
continue
}
for p, j := range []int{i - 1, i, i + 1} {
if j < 0 {
j = i + 1
} // left boundary
if j == N {
j = i - 1
} // right boundary
dfdy.Put(i, j, mol[p])
}
}
return nil
}
// initial values
x := utl.LinSpace(0.0, xmax, N)
y := make([]float64, N)
//y := make([]float64, Nb)
for i := 0; i < N; i++ {
y[i] = 4.0*x[i] - 4.0*x[i]*x[i]
}
// debug
f0 := make([]float64, N)
//f0 := make([]float64, Nb)
fcn(f0, 0, y)
if false {
io.Pforan("y0 = %v\n", y)
io.Pforan("f0 = %v\n", f0)
var J la.Triplet
jac(&J, 0, y)
la.PrintMat("J", J.ToMatrix(nil).ToDense(), "%8.3f", false)
}
//chk.Panic("stop")
/*
// constraints
var A la.Triplet
A.Init(2, N, 2)
A.Put(0, 0, 1.0)
A.Put(1, N-1, 1.0)
io.Pfcyan("A = %+v\n", A)
Am := A.ToMatrix(nil)
c := make([]float64, 2)
la.SpMatVecMul(c, 1, Am, y) // c := Am*y
la.PrintMat("A", Am.ToDense(), "%3g", false)
io.Pfcyan("c = %v ([0, 0] => consistent)\n", c)
*/
/*
// mass matrix
var M la.Triplet
M.Init(Nb, Nb, N + 4)
for i := 0; i < N; i++ {
M.Put(i, i, 1.0)
}
M.PutMatAndMatT(&A)
Mm := M.ToMatrix(nil)
la.PrintMat("M", Mm.ToDense(), "%3g", false)
*/
// output
var b0, b1, b2 bytes.Buffer
fmt.Fprintf(&b0, "from gosl import *\n")
fmt.Fprintf(&b1, "T = array([")
fmt.Fprintf(&b2, "U = array([")
out := func(first bool, dt, t float64, y []float64, args ...interface{}) error {
fmt.Fprintf(&b1, "%23.15E,", t)
fmt.Fprintf(&b2, "[")
for i := 0; i < N; i++ {
fmt.Fprintf(&b2, "%23.15E,", y[i])
}
fmt.Fprintf(&b2, "],")
return nil
}
defer func() {
fmt.Fprintf(&b1, "])\n")
fmt.Fprintf(&b2, "])\n")
fmt.Fprintf(&b2, "X = linspace(0.0, %g, %d)\n", xmax, N)
fmt.Fprintf(&b2, "tt, xx = meshgrid(T, X)\n")
fmt.Fprintf(&b2, "ax = PlotSurf(tt, xx, vstack(transpose(U)), 't', 'x', 'u', 0.0, 1.0)\n")
fmt.Fprintf(&b2, "ax.view_init(20.0, 30.0)\n")
fmt.Fprintf(&b2, "show()\n")
io.WriteFileD("/tmp/gosl", "plot_diffusion_1d.py", &b0, &b1, &b2)
}()
// ode solver
var Jfcn Cb_jac
var osol ODE
if !numjac {
Jfcn = jac
}
osol.Init(method, N, fcn, Jfcn, nil, out, silent)
//osol.Init(method, Nb, fcn, Jfcn, &M, out, silent)
osol.SetTol(atol, rtol)
// constant Jacobian
if method == "BwEuler" {
osol.CteTg = true
osol.Verbose = true
}
// run
wallt0 := time.Now()
if !fixstp {
dt = tf - t0
}
osol.Solve(y, t0, tf, dt, fixstp)
io.Pfmag("elapsed time = %v\n", time.Now().Sub(wallt0))
}
func Test_nls04(tst *testing.T) {
//verbose()
chk.PrintTitle("nls04. finite differences problem")
// grid
var g fdm.Grid2D
g.Init(1.0, 1.0, 6, 6)
// equations numbering
var e fdm.Equations
peq := utl.IntUnique(g.L, g.R, g.B, g.T)
e.Init(g.N, peq)
// K11 and K12
var K11, K12 la.Triplet
fdm.InitK11andK12(&K11, &K12, &e)
// assembly
F1 := make([]float64, e.N1)
fdm.Assemble(&K11, &K12, F1, nil, &g, &e)
// prescribed values
U2 := make([]float64, e.N2)
for _, eq := range g.L {
U2[e.FR2[eq]] = 50.0
}
for _, eq := range g.R {
U2[e.FR2[eq]] = 0.0
}
for _, eq := range g.B {
U2[e.FR2[eq]] = 0.0
}
for _, eq := range g.T {
U2[e.FR2[eq]] = 50.0
}
// functions
k11 := K11.ToMatrix(nil)
k12 := K12.ToMatrix(nil)
ffcn := func(fU1, U1 []float64) error { // K11*U1 + K12*U2 - F1
la.VecCopy(fU1, -1, F1) // fU1 := (-F1)
la.SpMatVecMulAdd(fU1, 1, k11, U1) // fU1 += K11*U1
la.SpMatVecMulAdd(fU1, 1, k12, U2) // fU1 += K12*U2
return nil
}
Jfcn := func(dfU1dU1 *la.Triplet, U1 []float64) error {
fdm.Assemble(dfU1dU1, &K12, F1, nil, &g, &e)
return nil
}
JfcnD := func(dfU1dU1 [][]float64, U1 []float64) error {
la.MatCopy(dfU1dU1, 1, K11.ToMatrix(nil).ToDense())
return nil
}
prms := map[string]float64{
"atol": 1e-8,
"rtol": 1e-8,
"ftol": 1e-12,
"lSearch": 0.0,
}
// init
var nls_sps NlSolver // sparse analytical
var nls_num NlSolver // sparse numerical
var nls_den NlSolver // dense analytical
nls_sps.Init(e.N1, ffcn, Jfcn, nil, false, false, prms)
nls_num.Init(e.N1, ffcn, nil, nil, false, true, prms)
nls_den.Init(e.N1, ffcn, nil, JfcnD, true, false, prms)
defer nls_sps.Clean()
defer nls_num.Clean()
defer nls_den.Clean()
// results
U1sps := make([]float64, e.N1)
U1num := make([]float64, e.N1)
U1den := make([]float64, e.N1)
Usps := make([]float64, e.N)
Unum := make([]float64, e.N)
Uden := make([]float64, e.N)
// solution
Uc := []float64{0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 50.0, 25.0, 325.0 / 22.0, 100.0 / 11.0, 50.0 / 11.0,
0.0, 50.0, 775.0 / 22.0, 25.0, 375.0 / 22.0, 100.0 / 11.0, 0.0, 50.0, 450.0 / 11.0, 725.0 / 22.0,
25.0, 325.0 / 22.0, 0.0, 50.0, 500.0 / 11.0, 450.0 / 11.0, 775.0 / 22.0, 25.0, 0.0, 50.0, 50.0,
50.0, 50.0, 50.0, 50.0,
}
io.PfYel("\n---- sparse -------- Analytical Jacobian -------------------\n")
// solve
err := nls_sps.Solve(U1sps, false)
if err != nil {
chk.Panic(err.Error())
}
// check
fdm.JoinVecs(Usps, U1sps, U2, &e)
chk.Vector(tst, "Usps", 1e-14, Usps, Uc)
// plot
if false {
g.Contour("results", "fig_t_heat_square", nil, Usps, 11, false)
}
io.PfYel("\n---- dense -------- Analytical Jacobian -------------------\n")
// solve
err = nls_den.Solve(U1den, false)
if err != nil {
chk.Panic(err.Error())
}
// check
fdm.JoinVecs(Uden, U1den, U2, &e)
chk.Vector(tst, "Uden", 1e-14, Uden, Uc)
io.PfYel("\n---- sparse -------- Numerical Jacobian -------------------\n")
// solve
err = nls_num.Solve(U1num, false)
if err != nil {
chk.Panic(err.Error())
}
// check
fdm.JoinVecs(Unum, U1num, U2, &e)
chk.Vector(tst, "Unum", 1e-14, Unum, Uc)
}
func Test_linipm02(tst *testing.T) {
//verbose()
chk.PrintTitle("linipm02")
// linear program
// min 2*x0 + x1
// s.t. -x0 + x1 ≤ 1
// x0 + x1 ≥ 2 → -x0 - x1 ≤ -2
// x0 - 2*x1 ≤ 4
// x1 ≥ 0
// standard (step 1) add slack
// s.t. -x0 + x1 + x2 = 1
// -x0 - x1 + x3 = -2
// x0 - 2*x1 + x4 = 4
// standard (step 2)
// replace x0 := x0_ - x5
// because it's unbounded
// min 2*x0_ + x1 - 2*x5
// s.t. -x0_ + x1 + x2 + x5 = 1
// -x0_ - x1 + x3 + x5 = -2
// x0_ - 2*x1 + x4 - x5 = 4
// x0_,x1,x2,x3,x4,x5 ≥ 0
var T la.Triplet
T.Init(3, 6, 12)
T.Put(0, 0, -1)
T.Put(0, 1, 1)
T.Put(0, 2, 1)
T.Put(0, 5, 1)
T.Put(1, 0, -1)
T.Put(1, 1, -1)
T.Put(1, 3, 1)
T.Put(1, 5, 1)
T.Put(2, 0, 1)
T.Put(2, 1, -2)
T.Put(2, 4, 1)
T.Put(2, 5, -1)
Am := T.ToMatrix(nil)
A := Am.ToDense()
c := []float64{2, 1, 0, 0, 0, -2}
b := []float64{1, -2, 4}
// print LP
la.PrintMat("A", A, "%6g", false)
la.PrintVec("b", b, "%6g", false)
la.PrintVec("c", c, "%6g", false)
io.Pf("\n")
// solve LP
var ipm LinIpm
defer ipm.Clean()
ipm.Init(Am, b, c, nil)
err := ipm.Solve(chk.Verbose)
if err != nil {
tst.Errorf("ipm failed:\n%v", err)
return
}
// check
io.Pf("\n")
bres := make([]float64, len(b))
la.MatVecMul(bres, 1, A, ipm.X)
io.Pforan("bres = %v\n", bres)
chk.Vector(tst, "A*x=b", 1e-8, bres, b)
// fix and check x
x := ipm.X[:2]
x[0] -= ipm.X[5]
io.Pforan("x = %v\n", x)
chk.Vector(tst, "x", 1e-8, x, []float64{0.5, 1.5})
// plot
if true && chk.Verbose {
f := func(x []float64) float64 {
return c[0]*x[0] + c[1]*x[1]
}
g := func(x []float64, i int) float64 {
return A[i][0]*x[0] + A[i][1]*x[1] - b[i]
}
np := 41
vmin, vmax := []float64{-2.0, -2.0}, []float64{2.0, 2.0}
PlotTwoVarsContour("/tmp/gosl", "test_linipm02", x, np, nil, true, vmin, vmax, f,
func(x []float64) float64 { return g(x, 0) },
func(x []float64) float64 { return g(x, 1) },
)
}
}
func Test_linipm01(tst *testing.T) {
//verbose()
chk.PrintTitle("linipm01")
// linear programming problem
// min -4*x0 - 5*x1
// s.t. 2*x0 + x1 ≤ 3
// x0 + 2*x1 ≤ 3
// x0,x1 ≥ 0
// standard:
// 2*x0 + x1 + x2 = 3
// x0 + 2*x1 + x3 = 3
// x0,x1,x2,x3 ≥ 0
var T la.Triplet
T.Init(2, 4, 6)
T.Put(0, 0, 2.0)
T.Put(0, 1, 1.0)
T.Put(0, 2, 1.0)
T.Put(1, 0, 1.0)
T.Put(1, 1, 2.0)
T.Put(1, 3, 1.0)
Am := T.ToMatrix(nil)
A := Am.ToDense()
c := []float64{-4, -5, 0, 0}
b := []float64{3, 3}
// print LP
la.PrintMat("A", A, "%6g", false)
la.PrintVec("b", b, "%6g", false)
la.PrintVec("c", c, "%6g", false)
io.Pf("\n")
// solve LP
var ipm LinIpm
defer ipm.Clean()
ipm.Init(Am, b, c, nil)
err := ipm.Solve(chk.Verbose)
if err != nil {
tst.Errorf("ipm failed:\n%v", err)
return
}
// check
io.Pf("\n")
io.Pforan("x = %v\n", ipm.X)
io.Pfcyan("λ = %v\n", ipm.L)
io.Pforan("s = %v\n", ipm.S)
x := ipm.X[:2]
bres := make([]float64, 2)
la.MatVecMul(bres, 1, A, x)
io.Pforan("bres = %v\n", bres)
chk.Vector(tst, "x", 1e-9, x, []float64{1, 1})
chk.Vector(tst, "A*x=b", 1e-8, bres, b)
// plot
if true && chk.Verbose {
f := func(x []float64) float64 {
return c[0]*x[0] + c[1]*x[1]
}
g := func(x []float64, i int) float64 {
return A[i][0]*x[0] + A[i][1]*x[1] - b[i]
}
np := 41
vmin, vmax := []float64{-2.0, -2.0}, []float64{2.0, 2.0}
PlotTwoVarsContour("/tmp/gosl", "test_linipm01", x, np, nil, true, vmin, vmax, f,
func(x []float64) float64 { return g(x, 0) },
func(x []float64) float64 { return g(x, 1) },
)
}
}
