本文整理汇总了Golang中github.com/cpmech/gosl/la.Triplet.Start方法的典型用法代码示例。如果您正苦于以下问题：Golang Triplet.Start方法的具体用法？Golang Triplet.Start怎么用？Golang Triplet.Start使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类github.com/cpmech/gosl/la.Triplet的用法示例。
在下文中一共展示了Triplet.Start方法的6个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Golang代码示例。
示例1: IpBmatrix_sparse
func IpBmatrix_sparse(B *la.Triplet, ndim, nne int, G [][]float64, radius float64, S []float64, axisym bool) {
B.Start()
if ndim == 3 {
for i := 0; i < nne; i++ {
B.Put(0, 0+i*3, G[i][0])
B.Put(1, 1+i*3, G[i][1])
B.Put(2, 2+i*3, G[i][2])
B.Put(3, 0+i*3, G[i][1]/SQ2)
B.Put(4, 1+i*3, G[i][2]/SQ2)
B.Put(5, 2+i*3, G[i][0]/SQ2)
B.Put(3, 1+i*3, G[i][0]/SQ2)
B.Put(4, 2+i*3, G[i][1]/SQ2)
B.Put(5, 0+i*3, G[i][2]/SQ2)
}
return
}
if axisym {
for i := 0; i < nne; i++ {
B.Put(0, 0+i*2, G[i][0])
B.Put(1, 1+i*2, G[i][1])
B.Put(2, 0+i*2, S[i]/radius)
B.Put(3, 0+i*2, G[i][1]/SQ2)
B.Put(3, 1+i*2, G[i][0]/SQ2)
}
return
}
for i := 0; i < nne; i++ {
B.Put(0, 0+i*2, G[i][0])
B.Put(1, 1+i*2, G[i][1])
B.Put(3, 0+i*2, G[i][1]/SQ2)
B.Put(3, 1+i*2, G[i][0]/SQ2)
}
}示例2: Jacobian
/* Jacobian
========
Calculates (with N=n-1):
df0dx0, df0dx1, df0dx2, ... df0dxN
df1dx0, df1dx1, df1dx2, ... df1dxN
. . . . . . . . . . . . .
dfNdx0, dfNdx1, dfNdx2, ... dfNdxN
INPUT:
ffcn : f(x) function
x : station where dfdx has to be calculated
fx : f @ x
w : workspace with size == n == len(x)
RETURNS:
J : dfdx @ x [must be pre-allocated] */
func Jacobian(J *la.Triplet, ffcn Cb_f, x, fx, w []float64, distr bool) (err error) {
ndim := len(x)
start, endp1 := 0, ndim
if distr {
id, sz := mpi.Rank(), mpi.Size()
start, endp1 = (id*ndim)/sz, ((id+1)*ndim)/sz
if J.Max() == 0 {
J.Init(ndim, ndim, (endp1-start)*ndim)
}
} else {
if J.Max() == 0 {
J.Init(ndim, ndim, ndim*ndim)
}
}
J.Start()
// NOTE: cannot split calculation by columns unless the f function is
// independently calculated by each MPI processor.
// Otherwise, the AllReduce in f calculation would
// join pieces of f from different processors calculated for
// different x values (δx[col] from different columns).
/*
for col := start; col < endp1; col++ {
xsafe := x[col]
delta := math.Sqrt(EPS * max(CTE1, math.Abs(xsafe)))
x[col] = xsafe + delta
ffcn(w, x) // fnew
io.Pforan("x = %v, f = %v\n", x, w)
for row := 0; row < ndim; row++ {
J.Put(row, col, (w[row]-fx[row])/delta)
}
x[col] = xsafe
}
*/
var df float64
for col := 0; col < ndim; col++ {
xsafe := x[col]
delta := math.Sqrt(EPS * max(CTE1, math.Abs(xsafe)))
x[col] = xsafe + delta
err = ffcn(w, x) // w := f(x+δx[col])
if err != nil {
return
}
for row := start; row < endp1; row++ {
df = w[row] - fx[row]
//if math.Abs(df) > EPS {
J.Put(row, col, df/delta)
//}
}
x[col] = xsafe
}
return
}示例3: Assemble
func Assemble(K11, K12 *la.Triplet, F1 []float64, src Cb_src, g *Grid2D, e *Equations) {
K11.Start()
K12.Start()
la.VecFill(F1, 0.0)
kx, ky := 1.0, 1.0
alp, bet, gam := 2.0*(kx/g.Dxx+ky/g.Dyy), -kx/g.Dxx, -ky/g.Dyy
mol := []float64{alp, bet, bet, gam, gam}
for i, I := range e.RF1 {
col, row := I%g.Nx, I/g.Nx
nodes := []int{I, I - 1, I + 1, I - g.Nx, I + g.Nx} // I, left, right, bottom, top
if col == 0 {
nodes[1] = nodes[2]
}
if col == g.Nx-1 {
nodes[2] = nodes[1]
}
if row == 0 {
nodes[3] = nodes[4]
}
if row == g.Ny-1 {
nodes[4] = nodes[3]
}
for k, J := range nodes {
j1, j2 := e.FR1[J], e.FR2[J] // 1 or 2?
if j1 > -1 { // 11
K11.Put(i, j1, mol[k])
} else { // 12
K12.Put(i, j2, mol[k])
}
}
if src != nil {
x := float64(col) * g.Dx
y := float64(row) * g.Dy
F1[i] += src(x, y)
}
}
}示例4: Jacobian
// Jacobian computes Jacobian (sparse) matrix
// Calculates (with N=n-1):
// df0dx0, df0dx1, df0dx2, ... df0dxN
// df1dx0, df1dx1, df1dx2, ... df1dxN
// . . . . . . . . . . . . .
// dfNdx0, dfNdx1, dfNdx2, ... dfNdxN
// INPUT:
// ffcn : f(x) function
// x : station where dfdx has to be calculated
// fx : f @ x
// w : workspace with size == n == len(x)
// RETURNS:
// J : dfdx @ x [must be pre-allocated]
func Jacobian(J *la.Triplet, ffcn Cb_f, x, fx, w []float64) (err error) {
ndim := len(x)
start, endp1 := 0, ndim
if J.Max() == 0 {
J.Init(ndim, ndim, ndim*ndim)
}
J.Start()
var df float64
for col := 0; col < ndim; col++ {
xsafe := x[col]
delta := math.Sqrt(EPS * max(CTE1, math.Abs(xsafe)))
x[col] = xsafe + delta
err = ffcn(w, x) // w := f(x+δx[col])
if err != nil {
return
}
for row := start; row < endp1; row++ {
df = w[row] - fx[row]
J.Put(row, col, df/delta)
}
x[col] = xsafe
}
return
}示例5: main
func main() {
mpi.Start(false)
defer func() {
mpi.Stop(false)
}()
if mpi.Rank() == 0 {
chk.PrintTitle("Test ODE 04b (MPI)")
io.Pfcyan("Hairer-Wanner VII-p376 Transistor Amplifier (MPI)\n")
io.Pfcyan("(from E Hairer's website, not the system in the book)\n")
}
if mpi.Size() != 3 {
chk.Panic(">> error: this test requires 3 MPI processors\n")
return
}
// RIGHT-HAND SIDE OF THE AMPLIFIER PROBLEM
w := make([]float64, 8) // workspace
fcn := func(f []float64, x float64, y []float64, args ...interface{}) error {
d := args[0].(*HWtransData)
UET := d.UE * math.Sin(d.W*x)
FAC1 := d.BETA * (math.Exp((y[3]-y[2])/d.UF) - 1.0)
FAC2 := d.BETA * (math.Exp((y[6]-y[5])/d.UF) - 1.0)
la.VecFill(f, 0)
switch mpi.Rank() {
case 0:
f[0] = y[0] / d.R9
case 1:
f[1] = (y[1]-d.UB)/d.R8 + d.ALPHA*FAC1
f[2] = y[2]/d.R7 - FAC1
case 2:
f[3] = y[3]/d.R5 + (y[3]-d.UB)/d.R6 + (1.0-d.ALPHA)*FAC1
f[4] = (y[4]-d.UB)/d.R4 + d.ALPHA*FAC2
f[5] = y[5]/d.R3 - FAC2
f[6] = y[6]/d.R1 + (y[6]-d.UB)/d.R2 + (1.0-d.ALPHA)*FAC2
f[7] = (y[7] - UET) / d.R0
}
mpi.AllReduceSum(f, w)
return nil
}
// JACOBIAN OF THE AMPLIFIER PROBLEM
jac := func(dfdy *la.Triplet, x float64, y []float64, args ...interface{}) error {
d := args[0].(*HWtransData)
FAC14 := d.BETA * math.Exp((y[3]-y[2])/d.UF) / d.UF
FAC27 := d.BETA * math.Exp((y[6]-y[5])/d.UF) / d.UF
if dfdy.Max() == 0 {
dfdy.Init(8, 8, 16)
}
NU := 2
dfdy.Start()
switch mpi.Rank() {
case 0:
dfdy.Put(2+0-NU, 0, 1.0/d.R9)
dfdy.Put(2+1-NU, 1, 1.0/d.R8)
dfdy.Put(1+2-NU, 2, -d.ALPHA*FAC14)
dfdy.Put(0+3-NU, 3, d.ALPHA*FAC14)
dfdy.Put(2+2-NU, 2, 1.0/d.R7+FAC14)
case 1:
dfdy.Put(1+3-NU, 3, -FAC14)
dfdy.Put(2+3-NU, 3, 1.0/d.R5+1.0/d.R6+(1.0-d.ALPHA)*FAC14)
dfdy.Put(3+2-NU, 2, -(1.0-d.ALPHA)*FAC14)
dfdy.Put(2+4-NU, 4, 1.0/d.R4)
dfdy.Put(1+5-NU, 5, -d.ALPHA*FAC27)
case 2:
dfdy.Put(0+6-NU, 6, d.ALPHA*FAC27)
dfdy.Put(2+5-NU, 5, 1.0/d.R3+FAC27)
dfdy.Put(1+6-NU, 6, -FAC27)
dfdy.Put(2+6-NU, 6, 1.0/d.R1+1.0/d.R2+(1.0-d.ALPHA)*FAC27)
dfdy.Put(3+5-NU, 5, -(1.0-d.ALPHA)*FAC27)
dfdy.Put(2+7-NU, 7, 1.0/d.R0)
}
return nil
}
// MATRIX "M"
c1, c2, c3, c4, c5 := 1.0e-6, 2.0e-6, 3.0e-6, 4.0e-6, 5.0e-6
var M la.Triplet
M.Init(8, 8, 14)
M.Start()
NU := 1
switch mpi.Rank() {
case 0:
M.Put(1+0-NU, 0, -c5)
M.Put(0+1-NU, 1, c5)
M.Put(2+0-NU, 0, c5)
M.Put(1+1-NU, 1, -c5)
M.Put(1+2-NU, 2, -c4)
M.Put(1+3-NU, 3, -c3)
case 1:
M.Put(0+4-NU, 4, c3)
M.Put(2+3-NU, 3, c3)
M.Put(1+4-NU, 4, -c3)
case 2:
M.Put(1+5-NU, 5, -c2)
M.Put(1+6-NU, 6, -c1)
M.Put(0+7-NU, 7, c1)
M.Put(2+6-NU, 6, c1)
M.Put(1+7-NU, 7, -c1)
//.........这里部分代码省略.........
示例6: main
func main() {
mpi.Start(false)
defer func() {
mpi.Stop(false)
}()
if mpi.Rank() == 0 {
chk.PrintTitle("ode04: Hairer-Wanner VII-p376 Transistor Amplifier\n")
}
if mpi.Size() != 3 {
chk.Panic(">> error: this test requires 3 MPI processors\n")
return
}
// data
UE, UB, UF, ALPHA, BETA := 0.1, 6.0, 0.026, 0.99, 1.0e-6
R0, R1, R2, R3, R4, R5 := 1000.0, 9000.0, 9000.0, 9000.0, 9000.0, 9000.0
R6, R7, R8, R9 := 9000.0, 9000.0, 9000.0, 9000.0
W := 2.0 * 3.141592654 * 100.0
// initial values
xa := 0.0
ya := []float64{0.0,
UB,
UB / (R6/R5 + 1.0),
UB / (R6/R5 + 1.0),
UB,
UB / (R2/R1 + 1.0),
UB / (R2/R1 + 1.0),
0.0}
// endpoint of integration
xb := 0.05
//xb = 0.0123 // OK
//xb = 0.01235 // !OK
// right-hand side of the amplifier problem
w := make([]float64, 8) // workspace
fcn := func(f []float64, dx, x float64, y []float64, args ...interface{}) error {
UET := UE * math.Sin(W*x)
FAC1 := BETA * (math.Exp((y[3]-y[2])/UF) - 1.0)
FAC2 := BETA * (math.Exp((y[6]-y[5])/UF) - 1.0)
la.VecFill(f, 0)
switch mpi.Rank() {
case 0:
f[0] = y[0] / R9
case 1:
f[1] = (y[1]-UB)/R8 + ALPHA*FAC1
f[2] = y[2]/R7 - FAC1
case 2:
f[3] = y[3]/R5 + (y[3]-UB)/R6 + (1.0-ALPHA)*FAC1
f[4] = (y[4]-UB)/R4 + ALPHA*FAC2
f[5] = y[5]/R3 - FAC2
f[6] = y[6]/R1 + (y[6]-UB)/R2 + (1.0-ALPHA)*FAC2
f[7] = (y[7] - UET) / R0
}
mpi.AllReduceSum(f, w)
return nil
}
// Jacobian of the amplifier problem
jac := func(dfdy *la.Triplet, dx, x float64, y []float64, args ...interface{}) error {
FAC14 := BETA * math.Exp((y[3]-y[2])/UF) / UF
FAC27 := BETA * math.Exp((y[6]-y[5])/UF) / UF
if dfdy.Max() == 0 {
dfdy.Init(8, 8, 16)
}
NU := 2
dfdy.Start()
switch mpi.Rank() {
case 0:
dfdy.Put(2+0-NU, 0, 1.0/R9)
dfdy.Put(2+1-NU, 1, 1.0/R8)
dfdy.Put(1+2-NU, 2, -ALPHA*FAC14)
dfdy.Put(0+3-NU, 3, ALPHA*FAC14)
dfdy.Put(2+2-NU, 2, 1.0/R7+FAC14)
case 1:
dfdy.Put(1+3-NU, 3, -FAC14)
dfdy.Put(2+3-NU, 3, 1.0/R5+1.0/R6+(1.0-ALPHA)*FAC14)
dfdy.Put(3+2-NU, 2, -(1.0-ALPHA)*FAC14)
dfdy.Put(2+4-NU, 4, 1.0/R4)
dfdy.Put(1+5-NU, 5, -ALPHA*FAC27)
case 2:
dfdy.Put(0+6-NU, 6, ALPHA*FAC27)
dfdy.Put(2+5-NU, 5, 1.0/R3+FAC27)
dfdy.Put(1+6-NU, 6, -FAC27)
dfdy.Put(2+6-NU, 6, 1.0/R1+1.0/R2+(1.0-ALPHA)*FAC27)
dfdy.Put(3+5-NU, 5, -(1.0-ALPHA)*FAC27)
dfdy.Put(2+7-NU, 7, 1.0/R0)
}
return nil
}
// matrix "M"
c1, c2, c3, c4, c5 := 1.0e-6, 2.0e-6, 3.0e-6, 4.0e-6, 5.0e-6
var M la.Triplet
M.Init(8, 8, 14)
M.Start()
NU := 1
//.........这里部分代码省略.........