func (c *DemagConvolution) exec3D(outp, inp, vol *data.Slice, Bsat float64) {
padded := c.kernSize
// FW FFT
for i := 0; i < 3; i++ {
zero1(c.fftRBuf[i], c.stream)
in := inp.Comp(i)
copyPadMul(c.fftRBuf[i], in, padded, c.size, vol, Bsat, c.stream)
c.fwPlan.ExecAsync(c.fftRBuf[i], c.fftCBuf[i])
}
// kern mul
N0, N1, N2 := c.fftKernSize[0], c.fftKernSize[1], c.fftKernSize[2] // TODO: rm these
kernMulRSymm3D(c.fftCBuf,
c.gpuFFTKern[0][0], c.gpuFFTKern[1][1], c.gpuFFTKern[2][2],
c.gpuFFTKern[1][2], c.gpuFFTKern[0][2], c.gpuFFTKern[0][1],
N0, N1, N2, c.stream)
// BW FFT
for i := 0; i < 3; i++ {
c.bwPlan.ExecAsync(c.fftCBuf[i], c.fftRBuf[i])
out := outp.Comp(i)
copyPad(out, c.fftRBuf[i], c.size, padded, c.stream)
}
c.stream.Synchronize()
}
func kernMulRSymm2Dx(fftMx, K00 *data.Slice, N1, N2 int, str cu.Stream) {
util.Argument(K00.Len() == (N1/2+1)*N2)
util.Argument(fftMx.NComp() == 1 && K00.NComp() == 1)
cfg := make2DConf(N1, N2)
k_kernmulRSymm2Dx_async(fftMx.DevPtr(0), K00.DevPtr(0), N1, N2, cfg, str)
}
func writeVTKHeader(out io.Writer, q *data.Slice) (err error) {
gridsize := q.Mesh().Size()
_, err = fmt.Fprintln(out, "<?xml version=\"1.0\"?>")
_, err = fmt.Fprintln(out, "<VTKFile type=\"StructuredGrid\" version=\"0.1\" byte_order=\"LittleEndian\">")
_, err = fmt.Fprintf(out, "\t<StructuredGrid WholeExtent=\"0 %d 0 %d 0 %d\">\n", gridsize[Z]-1, gridsize[Y]-1, gridsize[X]-1)
_, err = fmt.Fprintf(out, "\t\t<Piece Extent=\"0 %d 0 %d 0 %d\">\n", gridsize[Z]-1, gridsize[Y]-1, gridsize[X]-1)
return
}
// Adds a constant to each element of the slice.
// dst[comp][index] += cnst[comp]
func AddConst(dst *data.Slice, cnst ...float32) {
util.Argument(len(cnst) == dst.NComp())
N := dst.Len()
cfg := make1DConf(N)
str := stream()
for c := 0; c < dst.NComp(); c++ {
if cnst[c] != 0 {
k_madd2_async(dst.DevPtr(c), dst.DevPtr(c), 1, nil, cnst[c], N, cfg, str)
}
}
syncAndRecycle(str)
}
func scale(f *data.Slice, factor float32) {
a := f.Vectors()
for i := range a[0] {
for j := range a[0][i] {
for k := range a[0][i][j] {
a[0][i][j][k] *= factor
a[1][i][j][k] *= factor
a[2][i][j][k] *= factor
}
}
}
}
func preprocess(f *data.Slice) {
if *flag_normalize {
normalize(f, 1)
}
if *flag_normpeak {
normpeak(f)
}
if *flag_comp != -1 {
*f = *f.Comp(swapIndex(*flag_comp, f.NComp()))
}
if *flag_resize != "" {
resize(f, *flag_resize)
}
//if *flag_scale != 1{
// rescale(f, *flag_scale)
//}
}
func writeVTKPoints(out io.Writer, q *data.Slice, dataformat string) (err error) {
_, err = fmt.Fprintln(out, "\t\t\t<Points>")
fmt.Fprintf(out, "\t\t\t\t<DataArray type=\"Float32\" NumberOfComponents=\"3\" format=\"%s\">\n\t\t\t\t\t", dataformat)
gridsize := q.Mesh().Size()
cellsize := q.Mesh().CellSize()
switch dataformat {
case "ascii":
for k := 0; k < gridsize[X]; k++ {
for j := 0; j < gridsize[Y]; j++ {
for i := 0; i < gridsize[Z]; i++ {
x := (float32)(i) * (float32)(cellsize[Z])
y := (float32)(j) * (float32)(cellsize[Y])
z := (float32)(k) * (float32)(cellsize[X])
_, err = fmt.Fprint(out, x, " ", y, " ", z, " ")
}
}
}
case "binary":
buffer := new(bytes.Buffer)
for k := 0; k < gridsize[X]; k++ {
for j := 0; j < gridsize[Y]; j++ {
for i := 0; i < gridsize[Z]; i++ {
x := (float32)(i) * (float32)(cellsize[Z])
y := (float32)(j) * (float32)(cellsize[Y])
z := (float32)(k) * (float32)(cellsize[X])
binary.Write(buffer, binary.LittleEndian, x)
binary.Write(buffer, binary.LittleEndian, y)
binary.Write(buffer, binary.LittleEndian, z)
}
}
}
b64len := uint32(len(buffer.Bytes()))
bufLen := new(bytes.Buffer)
binary.Write(bufLen, binary.LittleEndian, b64len)
base64out := base64.NewEncoder(base64.StdEncoding, out)
base64out.Write(bufLen.Bytes())
base64out.Write(buffer.Bytes())
base64out.Close()
default:
log.Fatalf("Illegal VTK data format: %v. Options are: ascii, binary", dataformat)
}
_, err = fmt.Fprintln(out, "\n\t\t\t\t</DataArray>")
_, err = fmt.Fprintln(out, "\t\t\t</Points>")
return
}
func dumpGnuplot(out io.Writer, f *data.Slice) (err error) {
buf := bufio.NewWriter(out)
defer buf.Flush()
data := f.Tensors()
gridsize := f.Mesh().Size()
cellsize := f.Mesh().CellSize()
// If no cell size is set, use generic cell index.
if cellsize == [3]float64{0, 0, 0} {
cellsize = [3]float64{1, 1, 1}
}
ncomp := f.NComp()
// Here we loop over X,Y,Z, not Z,Y,X, because
// internal in C-order == external in Fortran-order
for i := 0; i < gridsize[0]; i++ {
x := float64(i) * cellsize[0]
for j := 0; j < gridsize[1]; j++ {
y := float64(j) * cellsize[1]
for k := 0; k < gridsize[2]; k++ {
z := float64(k) * cellsize[2]
_, err = fmt.Fprint(buf, z, " ", y, " ", x, "\t")
for c := 0; c < ncomp; c++ {
_, err = fmt.Fprint(buf, data[swapIndex(c, ncomp)][i][j][k], " ") // converts to user space.
}
_, err = fmt.Fprint(buf, "\n")
}
_, err = fmt.Fprint(buf, "\n")
}
}
return
}
func normpeak(f *data.Slice) {
a := f.Vectors()
maxnorm := 0.
for i := range a[0] {
for j := range a[0][i] {
for k := range a[0][i][j] {
x, y, z := a[0][i][j][k], a[1][i][j][k], a[2][i][j][k]
norm := math.Sqrt(float64(x*x + y*y + z*z))
if norm > maxnorm {
maxnorm = norm
}
}
}
}
scale(f, float32(1/maxnorm))
}
// normalize vector data to given length
func normalize(f *data.Slice, length float64) {
a := f.Vectors()
for i := range a[0] {
for j := range a[0][i] {
for k := range a[0][i][j] {
x, y, z := a[0][i][j][k], a[1][i][j][k], a[2][i][j][k]
norm := math.Sqrt(float64(x*x + y*y + z*z))
invnorm := float32(1)
if norm != 0 {
invnorm = float32(length / norm)
}
a[0][i][j][k] *= invnorm
a[1][i][j][k] *= invnorm
a[2][i][j][k] *= invnorm
}
}
}
}
func writeOvf2Binary4(out io.Writer, array *data.Slice) {
data := array.Tensors()
gridsize := array.Mesh().Size()
var bytes []byte
// OOMMF requires this number to be first to check the format
var controlnumber float32 = OMF_CONTROL_NUMBER
// Conversion form float32 [4]byte in big-endian
// encoding/binary is too slow
// Inlined for performance, terabytes of data will pass here...
bytes = (*[4]byte)(unsafe.Pointer(&controlnumber))[:]
out.Write(bytes)
// Here we loop over X,Y,Z, not Z,Y,X, because
// internal in C-order == external in Fortran-order
ncomp := array.NComp()
for i := 0; i < gridsize[X]; i++ {
for j := 0; j < gridsize[Y]; j++ {
for k := 0; k < gridsize[Z]; k++ {
for c := 0; c < ncomp; c++ {
bytes = (*[4]byte)(unsafe.Pointer(&data[swapIndex(c, ncomp)][i][j][k]))[:]
out.Write(bytes)
}
}
}
}
}
// Memset sets the Slice's components to the specified values.
func Memset(s *data.Slice, val ...float32) {
util.Argument(len(val) == s.NComp())
str := stream()
for c, v := range val {
cu.MemsetD32Async(cu.DevicePtr(s.DevPtr(c)), math.Float32bits(v), int64(s.Len()), str)
}
syncAndRecycle(str)
}
// Writes the OMF header
func writeOmfHeader(out io.Writer, q *data.Slice) (err error) {
gridsize := q.Mesh().Size()
cellsize := q.Mesh().CellSize()
err = hdr(out, "OOMMF", "rectangular mesh v1.0")
hdr(out, "Segment count", "1")
hdr(out, "Begin", "Segment")
hdr(out, "Begin", "Header")
dsc(out, "Time", 0) //q.Time) // TODO !!
hdr(out, "Title", q.Tag())
hdr(out, "meshtype", "rectangular")
hdr(out, "meshunit", "m")
hdr(out, "xbase", cellsize[Z]/2)
hdr(out, "ybase", cellsize[Y]/2)
hdr(out, "zbase", cellsize[X]/2)
hdr(out, "xstepsize", cellsize[Z])
hdr(out, "ystepsize", cellsize[Y])
hdr(out, "zstepsize", cellsize[X])
hdr(out, "xmin", 0)
hdr(out, "ymin", 0)
hdr(out, "zmin", 0)
hdr(out, "xmax", cellsize[Z]*float64(gridsize[Z]))
hdr(out, "ymax", cellsize[Y]*float64(gridsize[Y]))
hdr(out, "zmax", cellsize[X]*float64(gridsize[X]))
hdr(out, "xnodes", gridsize[Z])
hdr(out, "ynodes", gridsize[Y])
hdr(out, "znodes", gridsize[X])
hdr(out, "ValueRangeMinMag", 1e-08) // not so "optional" as the OOMMF manual suggests...
hdr(out, "ValueRangeMaxMag", 1) // TODO
hdr(out, "valueunit", "?")
hdr(out, "valuemultiplier", 1)
hdr(out, "End", "Header")
return
}
// Writes data in OMF Text format
func writeOmfText(out io.Writer, tens *data.Slice) (err error) {
data := tens.Tensors()
gridsize := tens.Mesh().Size()
// Here we loop over X,Y,Z, not Z,Y,X, because
// internal in C-order == external in Fortran-order
for i := 0; i < gridsize[X]; i++ {
for j := 0; j < gridsize[Y]; j++ {
for k := 0; k < gridsize[Z]; k++ {
for c := 0; c < tens.NComp(); c++ {
_, err = fmt.Fprint(out, data[swapIndex(c, tens.NComp())][i][j][k], " ") // converts to user space.
}
_, err = fmt.Fprint(out, "\n")
}
}
}
return
}
func (c *DemagConvolution) exec2D(outp, inp, vol *data.Slice, Bsat float64) {
// Convolution is separated into
// a 1D convolution for x and a 2D convolution for yz.
// So only 2 FFT buffers are needed at the same time.
// FFT x
zero1(c.fftRBuf[0], c.stream)
in := inp.Comp(0)
padded := c.kernSize
copyPadMul(c.fftRBuf[0], in, padded, c.size, vol, Bsat, c.stream)
c.fwPlan.ExecAsync(c.fftRBuf[0], c.fftCBuf[0])
// kern mul X
N1, N2 := c.fftKernSize[1], c.fftKernSize[2] // TODO: rm these
kernMulRSymm2Dx(c.fftCBuf[0], c.gpuFFTKern[0][0], N1, N2, c.stream)
// bw FFT x
c.bwPlan.ExecAsync(c.fftCBuf[0], c.fftRBuf[0])
out := outp.Comp(0)
copyPad(out, c.fftRBuf[0], c.size, padded, c.stream)
// FW FFT yz
for i := 1; i < 3; i++ {
zero1(c.fftRBuf[i], c.stream)
in := inp.Comp(i)
copyPadMul(c.fftRBuf[i], in, padded, c.size, vol, Bsat, c.stream)
c.fwPlan.ExecAsync(c.fftRBuf[i], c.fftCBuf[i])
}
// kern mul yz
kernMulRSymm2Dyz(c.fftCBuf[1], c.fftCBuf[2],
c.gpuFFTKern[1][1], c.gpuFFTKern[2][2], c.gpuFFTKern[1][2],
N1, N2, c.stream)
// BW FFT yz
for i := 1; i < 3; i++ {
c.bwPlan.ExecAsync(c.fftCBuf[i], c.fftRBuf[i])
out := outp.Comp(i)
copyPad(out, c.fftRBuf[i], c.size, padded, c.stream)
}
c.stream.Synchronize()
}
func Image(f *data.Slice, fmin, fmax string) *image.NRGBA {
dim := f.NComp()
switch dim {
default:
log.Fatalf("unsupported number of components: %v", dim)
case 3:
return drawVectors(f.Vectors())
case 1:
min, max := extrema(f.Host()[0])
if fmin != "auto" {
m, err := strconv.ParseFloat(fmin, 32)
util.FatalErr(err)
min = float32(m)
}
if fmax != "auto" {
m, err := strconv.ParseFloat(fmax, 32)
util.FatalErr(err)
max = float32(m)
}
return drawFloats(f.Scalars(), min, max)
}
panic("unreachable")
}
// Add exchange field to Beff with different exchange constant for X,Y,Z direction.
// m must be normalized to unit length.
func AddAnisoExchange(Beff *data.Slice, m *data.Slice, AexX, AexY, AexZ, Msat float64) {
// TODO: size check
mesh := Beff.Mesh()
N := mesh.Size()
c := mesh.CellSize()
w0 := float32(2 * AexX / (Msat * c[0] * c[0]))
w1 := float32(2 * AexY / (Msat * c[1] * c[1]))
w2 := float32(2 * AexZ / (Msat * c[2] * c[2]))
cfg := make2DConfSize(N[2], N[1], STENCIL_BLOCKSIZE)
str := [3]cu.Stream{stream(), stream(), stream()}
for c := 0; c < 3; c++ {
k_addexchange1comp_async(Beff.DevPtr(c), m.DevPtr(c), w0, w1, w2, N[0], N[1], N[2], cfg, str[c])
}
syncAndRecycle(str[0])
syncAndRecycle(str[1])
syncAndRecycle(str[2])
}
func writeOvf2Header(out io.Writer, q *data.Slice, time, tstep float64) {
gridsize := q.Mesh().Size()
cellsize := q.Mesh().CellSize()
fmt.Fprintln(out, "# OOMMF OVF 2.0")
fmt.Fprintln(out, "#")
hdr(out, "Segment count", "1")
fmt.Fprintln(out, "#")
hdr(out, "Begin", "Segment")
hdr(out, "Begin", "Header")
fmt.Fprintln(out, "#")
hdr(out, "Title", q.Tag()) // TODO
hdr(out, "meshtype", "rectangular")
hdr(out, "meshunit", "m")
hdr(out, "xmin", 0)
hdr(out, "ymin", 0)
hdr(out, "zmin", 0)
hdr(out, "xmax", cellsize[Z]*float64(gridsize[Z]))
hdr(out, "ymax", cellsize[Y]*float64(gridsize[Y]))
hdr(out, "zmax", cellsize[X]*float64(gridsize[X]))
name := q.Tag()
var labels []interface{}
if q.NComp() == 1 {
labels = []interface{}{name}
} else {
for i := 0; i < q.NComp(); i++ {
labels = append(labels, name+"_"+string('x'+i))
}
}
hdr(out, "valuedim", q.NComp())
hdr(out, "valuelabels", labels...) // TODO
unit := q.Unit()
if unit == "" {
unit = "1"
}
if q.NComp() == 1 {
hdr(out, "valueunits", unit)
} else {
hdr(out, "valueunits", unit, unit, unit)
}
// We don't really have stages
fmt.Fprintln(out, "# Desc: Stage simulation time: ", tstep, " s")
fmt.Fprintln(out, "# Desc: Total simulation time: ", time, " s")
hdr(out, "xbase", cellsize[Z]/2)
hdr(out, "ybase", cellsize[Y]/2)
hdr(out, "zbase", cellsize[X]/2)
hdr(out, "xnodes", gridsize[Z])
hdr(out, "ynodes", gridsize[Y])
hdr(out, "znodes", gridsize[X])
hdr(out, "xstepsize", cellsize[Z])
hdr(out, "ystepsize", cellsize[Y])
hdr(out, "zstepsize", cellsize[X])
fmt.Fprintln(out, "#")
hdr(out, "End", "Header")
fmt.Fprintln(out, "#")
}
// multiply-add: dst[i] = src1[i] * factor1 + src2[i] * factor2
func Madd2(dst, src1, src2 *data.Slice, factor1, factor2 float32) {
N := dst.Len()
nComp := dst.NComp()
util.Assert(src1.Len() == N && src2.Len() == N)
util.Assert(src1.NComp() == nComp && src2.NComp() == nComp)
cfg := make1DConf(N)
str := stream()
for c := 0; c < nComp; c++ {
k_madd2_async(dst.DevPtr(c), src1.DevPtr(c), factor1,
src2.DevPtr(c), factor2, N, cfg, str)
}
syncAndRecycle(str)
}
// Maximum of the norms of all vectors (x[i], y[i], z[i]).
// max_i sqrt( x[i]*x[i] + y[i]*y[i] + z[i]*z[i] )
func MaxVecNorm(v *data.Slice) float64 {
out := reduceBuf(0)
k_reducemaxvecnorm2(v.DevPtr(0), v.DevPtr(1), v.DevPtr(2), out, 0, v.Len(), reducecfg)
return math.Sqrt(float64(copyback(out)))
}
//// Maximum of the norms of the difference between all vectors (x1,y1,z1) and (x2,y2,z2)
//// (dx, dy, dz) = (x1, y1, z1) - (x2, y2, z2)
//// max_i sqrt( dx[i]*dx[i] + dy[i]*dy[i] + dz[i]*dz[i] )
func MaxVecDiff(x, y *data.Slice) float64 {
util.Argument(x.Len() == y.Len())
out := reduceBuf(0)
k_reducemaxvecdiff2(x.DevPtr(0), x.DevPtr(1), x.DevPtr(2),
y.DevPtr(0), y.DevPtr(1), y.DevPtr(2),
out, 0, x.Len(), reducecfg)
return math.Sqrt(float64(copyback(out)))
}
// Execute the FFT plan, asynchronous.
// src and dst are 3D arrays stored 1D arrays.
func (p *fft3DC2RPlan) ExecAsync(src, dst *data.Slice) {
oksrclen := p.InputLenFloats()
if src.Len() != oksrclen {
panic(fmt.Errorf("fft size mismatch: expecting src len %v, got %v", oksrclen, src.Len()))
}
okdstlen := p.OutputLenFloats()
if dst.Len() != okdstlen {
panic(fmt.Errorf("fft size mismatch: expecting dst len %v, got %v", okdstlen, dst.Len()))
}
p.handle.ExecC2R(cu.DevicePtr(src.DevPtr(0)), cu.DevicePtr(dst.DevPtr(0)))
}
// Maximum of absolute values of all elements.
func MaxAbs(in *data.Slice) float32 {
util.Argument(in.NComp() == 1)
out := reduceBuf(0)
k_reducemaxabs(in.DevPtr(0), out, 0, in.Len(), reducecfg)
return copyback(out)
}
// Normalize the vector field to length mask * norm.
// nil mask interpreted as 1s.
// 0-length vectors are unaffected.
func Normalize(vec *data.Slice) {
N := vec.Len()
cfg := make1DConf(N)
k_normalize(vec.DevPtr(0), vec.DevPtr(1), vec.DevPtr(2), N, cfg)
}
// Landau-Lifshitz torque divided by gamma0:
// - 1/(1+α²) [ m x B + α (m/|m|) x (m x B) ]
// torque in Tesla/s
// m normalized
// B in Tesla
func LLGTorque(torque, m, B *data.Slice, alpha float32) {
// TODO: assert...
N := torque.Len()
cfg := make1DConf(N)
k_llgtorque(torque.DevPtr(0), torque.DevPtr(1), torque.DevPtr(2),
m.DevPtr(0), m.DevPtr(1), m.DevPtr(2),
B.DevPtr(0), B.DevPtr(1), B.DevPtr(2),
alpha, N, cfg)
}
func AddZhangLiTorque(torque, m *data.Slice, j [3]float64, Msat float64, j_MsMap *data.Slice, alpha, xi float64) {
// TODO: assert...
util.Argument(j_MsMap == nil) // not yet supported
c := torque.Mesh().CellSize()
N := torque.Mesh().Size()
cfg := make2DConfSize(N[2], N[1], STENCIL_BLOCKSIZE)
b := MuB / (Qe * Msat * (1 + xi*xi))
ux := float32((j[0] * b) / (Gamma0 * 2 * c[0]))
uy := float32((j[1] * b) / (Gamma0 * 2 * c[1]))
uz := float32((j[2] * b) / (Gamma0 * 2 * c[2]))
k_addzhanglitorque(torque.DevPtr(0), torque.DevPtr(1), torque.DevPtr(2),
m.DevPtr(0), m.DevPtr(1), m.DevPtr(2),
ux, uy, uz,
j_MsMap.DevPtr(0), j_MsMap.DevPtr(1), j_MsMap.DevPtr(2),
float32(alpha), float32(xi),
N[0], N[1], N[2], cfg)
}
// Add uniaxial magnetocrystalline anisotropy field to Beff.
// m: normalized magnetization.
// K: anisotropy axis in J/m³
func AddUniaxialAnisotropy(Beff, m *data.Slice, Kx, Ky, Kz, Msat float64) {
// TODO: size check
N := Beff.Len()
cfg := make1DConf(N)
k_adduniaxialanisotropy(Beff.DevPtr(0), Beff.DevPtr(1), Beff.DevPtr(2),
m.DevPtr(0), m.DevPtr(1), m.DevPtr(2),
float32(Kx/Msat), float32(Ky/Msat), float32(Kz/Msat), N, cfg)
}
func writeVTKCellData(out io.Writer, q *data.Slice, dataformat string) (err error) {
N := q.NComp()
data := q.Tensors()
switch N {
case 1:
fmt.Fprintf(out, "\t\t\t<PointData Scalars=\"%s\">\n", q.Tag())
fmt.Fprintf(out, "\t\t\t\t<DataArray type=\"Float32\" Name=\"%s\" NumberOfComponents=\"%d\" format=\"%s\">\n\t\t\t\t\t", q.Tag(), N, dataformat)
case 3:
fmt.Fprintf(out, "\t\t\t<PointData Vectors=\"%s\">\n", q.Tag())
fmt.Fprintf(out, "\t\t\t\t<DataArray type=\"Float32\" Name=\"%s\" NumberOfComponents=\"%d\" format=\"%s\">\n\t\t\t\t\t", q.Tag(), N, dataformat)
case 6, 9:
fmt.Fprintf(out, "\t\t\t<PointData Tensors=\"%s\">\n", q.Tag())
fmt.Fprintf(out, "\t\t\t\t<DataArray type=\"Float32\" Name=\"%s\" NumberOfComponents=\"%d\" format=\"%s\">\n\t\t\t\t\t", q.Tag(), 9, dataformat) // must be 9!
default:
log.Fatalf("vtk: cannot handle %v components", N)
}
gridsize := q.Mesh().Size()
switch dataformat {
case "ascii":
for i := 0; i < gridsize[X]; i++ {
for j := 0; j < gridsize[Y]; j++ {
for k := 0; k < gridsize[Z]; k++ {
// if symmetric tensor manage it appart to write the full 9 components
if N == 6 {
fmt.Fprint(out, data[swapIndex(0, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(1, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(2, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(1, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(3, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(4, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(2, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(4, 9)][i][j][k], " ")
fmt.Fprint(out, data[swapIndex(5, 9)][i][j][k], " ")
} else {
for c := 0; c < N; c++ {
fmt.Fprint(out, data[swapIndex(c, N)][i][j][k], " ")
}
}
}
}
}
case "binary":
// Inlined for performance, terabytes of data will pass here...
buffer := new(bytes.Buffer)
for i := 0; i < gridsize[X]; i++ {
for j := 0; j < gridsize[Y]; j++ {
for k := 0; k < gridsize[Z]; k++ {
// if symmetric tensor manage it appart to write the full 9 components
if N == 6 {
binary.Write(buffer, binary.LittleEndian, data[swapIndex(0, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(1, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(2, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(1, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(3, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(4, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(2, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(4, 9)][i][j][k])
binary.Write(buffer, binary.LittleEndian, data[swapIndex(5, 9)][i][j][k])
} else {
for c := 0; c < N; c++ {
binary.Write(buffer, binary.LittleEndian, data[swapIndex(c, N)][i][j][k])
}
}
}
}
}
b64len := uint32(len(buffer.Bytes()))
bufLen := new(bytes.Buffer)
binary.Write(bufLen, binary.LittleEndian, b64len)
base64out := base64.NewEncoder(base64.StdEncoding, out)
base64out.Write(bufLen.Bytes())
base64out.Write(buffer.Bytes())
base64out.Close()
default:
panic(fmt.Errorf("vtk: illegal data format " + dataformat + ". Options are: ascii, binary"))
}
fmt.Fprintln(out, "\n\t\t\t\t</DataArray>")
fmt.Fprintln(out, "\t\t\t</PointData>")
return
}
// Add effective field of Dzyaloshinskii-Moriya interaction to Beff (Tesla).
// According to Bagdanov and Röβler, PRL 87, 3, 2001. eq.8 (out-of-plane symmetry breaking).
// m: normalized
// D: J/m²
func AddDMI(Beff *data.Slice, m *data.Slice, D, Msat float64) {
// TODO: size check
mesh := Beff.Mesh()
N := mesh.Size()
c := mesh.CellSize()
dx := float32(D / (Msat * c[0])) // actually (2*D) / (Msat * 2*c), 2*c disappears in kernel.
dy := float32(D / (Msat * c[1]))
dz := float32(D / (Msat * c[2]))
cfg := make2DConf(N[2], N[1])
k_adddmi(Beff.DevPtr(0), Beff.DevPtr(1), Beff.DevPtr(2),
m.DevPtr(0), m.DevPtr(1), m.DevPtr(2),
dx, dy, dz, N[0], N[1], N[2], cfg)
}
// Only the damping term of LLGTorque, with alpha 1. Useful for relaxation.
func DampingTorque(torque, m, B *data.Slice) {
N := torque.Len()
cfg := make1DConf(N)
k_dampingtorque(torque.DevPtr(0), torque.DevPtr(1), torque.DevPtr(2),
m.DevPtr(0), m.DevPtr(1), m.DevPtr(2), B.DevPtr(0), B.DevPtr(1), B.DevPtr(2), N, cfg)
}
