Golang Slice.Len方法代碼示例

// 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)
}

// 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)
}

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)
}

// Does not yet use Y mirror symmetry!!
// Even though it is implemented partially in kernel
func kernMulRSymm3D(fftM [3]*data.Slice, K00, K11, K22, K12, K02, K01 *data.Slice, N0, N1, N2 int, str cu.Stream) {
	util.Argument(K00.Len() == N0*(N1)*N2) // no symmetry yet
	util.Argument(fftM[0].NComp() == 1 && K00.NComp() == 1)

	cfg := make2DConf(N1, N2)

	k_kernmulRSymm3D_async(fftM[0].DevPtr(0), fftM[1].DevPtr(0), fftM[2].DevPtr(0),
		K00.DevPtr(0), K11.DevPtr(0), K22.DevPtr(0), K12.DevPtr(0), K02.DevPtr(0), K01.DevPtr(0),
		N0, N1, N2, cfg, str)
}

func kernMulRSymm2Dyz(fftMy, fftMz, K11, K22, K12 *data.Slice, N1, N2 int, str cu.Stream) {
	util.Argument(K11.Len() == (N1/2+1)*N2)
	util.Argument(fftMy.NComp() == 1 && K11.NComp() == 1)

	cfg := make2DConf(N1, N2)

	k_kernmulRSymm2Dyz_async(fftMy.DevPtr(0), fftMz.DevPtr(0),
		K11.DevPtr(0), K22.DevPtr(0), K12.DevPtr(0),
		N1, N2, cfg, str)
}

// 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)
}

// 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)
}

// 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)
}

// Copies src into dst, which is larger or smaller.
// The remainder of dst is not filled with zeros.
func copyPad(dst, src *data.Slice, dstsize, srcsize [3]int, str cu.Stream) {
	util.Argument(dst.NComp() == 1 && src.NComp() == 1)
	util.Assert(dst.Len() == prod(dstsize))
	util.Assert(src.Len() == prod(srcsize))

	N0 := iMin(dstsize[1], srcsize[1])
	N1 := iMin(dstsize[2], srcsize[2])
	cfg := make2DConf(N0, N1)

	k_copypad_async(dst.DevPtr(0), dstsize[0], dstsize[1], dstsize[2],
		src.DevPtr(0), srcsize[0], srcsize[1], srcsize[2], cfg, str)
}

// Copies src into dst, which is larger or smaller, and multiplies by vol*Bsat.
// The remainder of dst is not filled with zeros.
func copyPadMul(dst, src *data.Slice, dstsize, srcsize [3]int, vol *data.Slice, Bsat float64, str cu.Stream) {
	util.Argument(dst.NComp() == 1)
	util.Argument(src.NComp() == 1)
	util.Argument(vol.NComp() == 1)
	util.Assert(dst.Len() == prod(dstsize) && src.Len() == prod(srcsize))
	util.Assert(vol.Mesh().Size() == srcsize)

	N0 := iMin(dstsize[1], srcsize[1])
	N1 := iMin(dstsize[2], srcsize[2])
	cfg := make2DConf(N0, N1)

	k_copypadmul_async(dst.DevPtr(0), dstsize[0], dstsize[1], dstsize[2],
		src.DevPtr(0), srcsize[0], srcsize[1], srcsize[2],
		vol.DevPtr(0), float32(Bsat), cfg, str)
}

// 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)))
}

// Execute the FFT plan, asynchronous.
// src and dst are 3D arrays stored 1D arrays.
func (p *fft3DR2CPlan) ExecAsync(src, dst *data.Slice) {
	util.Argument(src.NComp() == 1 && dst.NComp() == 1)
	oksrclen := p.InputLen()
	if src.Len() != oksrclen {
		log.Panicf("fft size mismatch: expecting src len %v, got %v", oksrclen, src.Len())
	}
	okdstlen := p.OutputLen()
	if dst.Len() != okdstlen {
		log.Panicf("fft size mismatch: expecting dst len %v, got %v", okdstlen, dst.Len())
	}
	p.handle.ExecR2C(cu.DevicePtr(src.DevPtr(0)), cu.DevicePtr(dst.DevPtr(0)))
}

// multiply-add: dst[i] = src1[i] * factor1 + src2[i] * factor2 + src3 * factor3
func Madd3(dst, src1, src2, src3 *data.Slice, factor1, factor2, factor3 float32) {
	N := dst.Len()
	nComp := dst.NComp()
	util.Assert(src1.Len() == N && src2.Len() == N && src3.Len() == N)
	util.Assert(src1.NComp() == nComp && src2.NComp() == nComp && src3.NComp() == nComp)
	cfg := make1DConf(N)
	str := stream()
	for c := 0; c < nComp; c++ {
		k_madd3_async(dst.DevPtr(c), src1.DevPtr(c), factor1,
			src2.DevPtr(c), factor2, src3.DevPtr(c), factor3, N, cfg, str)
	}
	syncAndRecycle(str)
}

// Extract real parts, copy them from src to dst.
// In the meanwhile, check if imaginary parts are nearly zero
// and scale the kernel to compensate for unnormalized FFTs.
func scaleRealParts(dst, src *data.Slice, scale float32) {
	util.Argument(2*dst.Len() == src.Len())
	util.Argument(dst.NComp() == 1 && src.NComp() == 1)

	srcList := src.HostCopy().Host()[0]
	dstList := dst.Host()[0]

	// Normally, the FFT'ed kernel is purely real because of symmetry,
	// so we only store the real parts...
	maximg := float32(0.)
	maxreal := float32(0.)
	for i := 0; i < src.Len()/2; i++ {
		dstList[i] = srcList[2*i] * scale
		if fabs(srcList[2*i+0]) > maxreal {
			maxreal = fabs(srcList[2*i+0])
		}
		if fabs(srcList[2*i+1]) > maximg {
			maximg = fabs(srcList[2*i+1])
		}
	}
	// ...however, we check that the imaginary parts are nearly zero,
	// just to be sure we did not make a mistake during kernel creation.
	if maximg/maxreal > FFT_IMAG_TOLERANCE {
		log.Fatalf("Too large FFT kernel imaginary/real part: %v", maximg/maxreal)
	}
}

//// 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)))
}