Python Sim.relax方法代码示例

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh):

    sim=Sim(mesh,name='relax')
    sim.set_options(rtol=1e-12,atol=1e-14)
    sim.do_precession = False
    sim.alpha = 0.5
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.18
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0,0e-3,2e-2],name='H')
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-8, max_steps=10000, save_m_steps=None, save_vtk_steps=100)

    np.save('m0.npy',sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh):

    # Only relaxation
    sim = Sim(mesh, name='relax')

    # Simulation parameters
    sim.driver.set_tols(rtol=1e-8, atol=1e-10)
    sim.alpha = 0.5
    sim.driver.gamma = 2.211e5 / mu0
    sim.mu_s = 1e-27 / mu0
    sim.driver.do_precession = False

    # The initial state passed as a function
    sim.set_m(init_m)
    # sim.set_m(np.load('m0.npy'))

    # Energies
    exch = UniformExchange(J=2e-20)
    sim.add(exch)

    anis = Anisotropy(0.01*2e-20, axis=(0, 0, 1))
    sim.add(anis)

    # dmi = DMI(D=8e-4)
    # sim.add(dmi)

    # Start relaxation and save the state in m0.npy
    sim.relax(dt=1e-14, stopping_dmdt=1e4, max_steps=5000,
              save_m_steps=None, save_vtk_steps=None)

    np.save('m0.npy', sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    sim.set_default_options(gamma=const.gamma)
    sim.driver.alpha = 0.5
    sim.mu_s = const.mu_s_1

    sim.set_m(init_m)

    J = 50.0 * const.k_B
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.5 * J
    dmi = DMI(D)
    sim.add(dmi)

    Hz = 0.2 * J / const.mu_s_1
    zeeman = Zeeman([0, 0, Hz])
    sim.add(zeeman)

    ONE_DEGREE_PER_NS = 17453292.52

    sim.relax(dt=1e-13, stopping_dmdt=0.01 * ONE_DEGREE_PER_NS,
              max_steps=1000, save_m_steps=100, save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def test_skx_num():

    mesh = CuboidMesh(nx=120, ny=120, nz=1, periodicity=(True, True, False))

    sim = Sim(mesh, name='skx_num')
    sim.set_tols(rtol=1e-6, atol=1e-6)
    sim.alpha = 1.0
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)

    sim.do_procession = False

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.09
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0, 5e-3])
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-2, max_steps=1000,
              save_m_steps=None, save_vtk_steps=None)

    skn = sim.skyrmion_number()
    print 'skx_number', skn
    assert skn > -1 and skn < -0.99

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    # sim.set_options(rtol=1e-10,atol=1e-14)
    sim.alpha = 1.0
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)
    # sim.set_m(random_m)
    # sim.set_m(np.load('m_10000.npy'))

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.09
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0, 3.75e-3])
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-6, max_steps=1000,
              save_m_steps=100, save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh, Hy=0):

    sim = Sim(mesh, name="relax")
    sim.set_options(rtol=1e-10, atol=1e-12)
    sim.alpha = 0.5
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.do_precession = False

    sim.set_m(init_m)
    # sim.set_m(random_m)
    # sim.set_m(np.load('m_10000.npy'))

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.18
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, Hy, 2e-2], name="H")
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-8, max_steps=10000, save_m_steps=100, save_vtk_steps=50)

    np.save("m0.npy", sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system_stage1():

    mesh = CuboidMesh(nx=140 , ny=140, nz=1)

    sim = Sim(mesh, name='relax', driver='llg')
    #sim.set_options(dt=1e-14, gamma=const.gamma, k_B=const.k_B)
    sim.alpha = 0.5
    sim.do_precession = False
    sim.gamma = const.gamma
    sim.mu_s = spatial_mu

    sim.set_m(init_m)

    J = 50 * const.k_B
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.27 * J
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman(spatial_H)
    sim.add(zeeman)

    sim.relax(dt=1e-14, stopping_dmdt=1e10, max_steps=1000,
              save_m_steps=100, save_vtk_steps=10)

    np.save('skx.npy', sim.spin)
    plot_m(mesh, 'skx.npy', comp='z')

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def test_skx_num_atomistic():
    """
    Test the *finite spin chirality* or skyrmion number for
    a discrete spins simulation in a two dimensional lattice

    The expression is (PRL 108, 017601 (2012)) :

    Q =     S_i \dot ( S_{i+1}  X  S_{j+1} )
         +  S_i \dot ( S_{i-1}  X  S_{j-1} )

    which measures the chirality taking two triangles of spins
    per lattice site i:
        S_{i} , S_{i + x} , S_{i + y}    and
        S_{i} , S_{i - x} , S_{i - y}

    The area of the two triangles cover a unit cell, thus the sum
    cover the whole area of the atomic lattice

    This test generate a skyrmion pointing down with unrealistic
    paremeters.

    """

    mesh = CuboidMesh(nx=120, ny=120, nz=1,
                      periodicity=(True, True, False))

    sim = Sim(mesh, name='skx_num')
    sim.set_tols(rtol=1e-6, atol=1e-6)
    sim.alpha = 1.0
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(lambda pos: init_m(pos, 60, 60, 20))

    sim.do_precession = False

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.09
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0, 5e-3])
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-2, max_steps=1000,
              save_m_steps=None, save_vtk_steps=None)

    skn = sim.skyrmion_number()
    print('skx_number', skn)
    assert skn > -1 and skn < -0.99

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system():

    # 1D chain of 50 spins with a lattice constant of 0.27 A
    mesh = CuboidMesh(nx=nx,
                  dx=dx,
                  unit_length=1e-9,
                  # pbc='1d'
                  )

    # Initiate the simulation. PBCs are specified in the mesh
    sim = Sim(mesh, name=sim_name)
    sim.gamma = const.gamma

    # magnetisation in units of Bohr's magneton
    sim.mu_s = 2. * const.mu_B

    # sim.set_options(gamma=const.gamma, k_B=const.k_B)

    # Initial magnetisation profile
    sim.set_m((0, 0, 1))

    # Exchange constant in Joules: E = Sum J_{ij} S_i S_j
    J = 12. * const.meV
    exch = UniformExchange(J)
    sim.add(exch)

    # DMI constant in Joules: E = Sum D_{ij} S_i x S_j
    D = 2. * const.meV
    dmi = DMI(D, dmi_type='interfacial')
    sim.add(dmi)

    # Anisotropy along +z axis
    ku = Anisotropy(Ku=0.5 * const.meV,
                    axis=[0, 0, 1],
                    name='ku')
    sim.add(ku)

    # Faster convergence
    sim.alpha = 0.5
    sim.do_precession = False

    sim.relax(dt=1e-13, stopping_dmdt=0.05,
              max_steps=700,
              save_m_steps=1000, save_vtk_steps=1000)

    # Save the last relaxed state
    np.save(sim_name + '.npy', sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def test_dw_dmi_atomistic(do_plot=False):

    mesh = CuboidMesh(nx=300, ny=1, nz=1)

    sim = Sim(mesh, name='relax')
    sim.set_default_options(gamma=const.gamma)
    sim.alpha = 0.5
    sim.mu_s = const.mu_s_1
    sim.do_procession = False

    sim.set_m(m_init_dw)

    J = 50.0 * const.k_B
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.01 * J
    dmi = DMI(D)
    sim.add(dmi)

    K = 0.005 * J
    anis = Anisotropy(K, axis=[1,0,0])
    sim.add(anis)

    ONE_DEGREE_PER_NS = 17453292.52

    sim.relax(dt=1e-13, stopping_dmdt=0.01 * ONE_DEGREE_PER_NS,
              max_steps=1000, save_m_steps=100, save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

    xs = np.array([p[0] for p in mesh.coordinates]) - 150

    mx, my, mz = analytical(xs, A=J/2.0, D=-D, K=K)
    mxyz = sim.spin.copy()
    mxyz = mxyz.reshape(-1, 3).T

    assert max(abs(mxyz[0, :] - mx)) < 0.001
    assert max(abs(mxyz[1, :] - my)) < 0.001
    assert max(abs(mxyz[2, :] - mz)) < 0.0006

    if do_plot:

        save_plot(xs, mxyz, mx, my, mz)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    # sim.set_options(rtol=1e-10,atol=1e-14)
    sim.alpha = 1.0
    sim.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(init_m)
    # sim.set_m(random_m)
    # sim.set_m(np.load('m_10000.npy'))

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    Kx = Anisotropy(Ku=0.005, axis=(1, 0, 0), name='Kx')
    sim.add(Kx)

    sim.relax(dt=2.0, stopping_dmdt=1e-6, max_steps=1000,
              save_m_steps=100, save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def relax_system(mesh):

    sim = Sim(mesh, name='relax')
    sim.set_default_options(gamma=constant.gamma)
    sim.driver.alpha = 0.5
    sim.mu_s = constant.mu_s_1
    sim.do_precession = False

    sim.set_m(m_init_dw)

    J = 50.0 * constant.k_B
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.1 * J
    dmi = DMI(D, dmi_type = 'interfacial')
    sim.add(dmi)

    K = 0.02 * J
    anis = Anisotropy(K, axis=[0,0,1])
    sim.add(anis)

    ONE_DEGREE_PER_NS = 17453292.52

    sim.relax(dt=1e-13, stopping_dmdt=0.01 * ONE_DEGREE_PER_NS,
              max_steps=1000, save_m_steps=100, save_vtk_steps=50)

    np.save('m0.npy', sim.spin)

    xs = np.array([p[0] for p in mesh.pos]) - 150

    mx, my, mz = analytical(xs, A=J/2.0, D=-D, K=K)
    mxyz = sim.spin.copy()
    mxyz.shape = (3, -1)

    save_plot(xs, mxyz, mx, my, mz)

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def test_skx_num_atomistic():
    """
    Test the *finite spin chirality* or skyrmion number for
    a discrete spins simulation in a two dimensional lattice

    The expression is (PRL 108, 017601 (2012)) :

    Q =     S_i \dot ( S_{i+1}  X  S_{j+1} )
         +  S_i \dot ( S_{i-1}  X  S_{j-1} )

    which measures the chirality taking two triangles of spins
    per lattice site i:
        S_{i} , S_{i + x} , S_{i + y}    and
        S_{i} , S_{i - x} , S_{i - y}

    The area of the two triangles cover a unit cell, thus the sum
    cover the whole area of the atomic lattice

    We also test the Berg and Luscher definition for a topological
    charge (see the hexagonal mesh test for details) in a
    square lattice.

    This test generate a skyrmion pointing down with unrealistic
    paremeters.

    """

    mesh = CuboidMesh(nx=120, ny=120, nz=1,
                      periodicity=(True, True, False))

    sim = Sim(mesh, name='skx_num')
    sim.driver.set_tols(rtol=1e-6, atol=1e-6)
    sim.driver.alpha = 1.0
    sim.driver.gamma = 1.0
    sim.mu_s = 1.0

    sim.set_m(lambda pos: init_m(pos, 60, 60, 20))

    sim.do_precession = False

    J = 1.0
    exch = UniformExchange(J)
    sim.add(exch)

    D = 0.09
    dmi = DMI(D)
    sim.add(dmi)

    zeeman = Zeeman([0, 0, 5e-3])
    sim.add(zeeman)

    sim.relax(dt=2.0, stopping_dmdt=1e-2, max_steps=1000,
              save_m_steps=None, save_vtk_steps=None)

    skn = sim.skyrmion_number()
    print('skx_number', skn)

    skn_BL = sim.skyrmion_number(method='BergLuscher')
    print('skx_number_BergLuscher', skn_BL)

    # Test the finite chirality method
    assert skn > -1 and skn < -0.99

    # Test the Berg-Luscher method
    assert np.abs(skn_BL - (-1)) < 1e-4 and np.sign(skn_BL) < 0

    # Test guiding center
    Rx, Ry = compute_RxRy(mesh, sim.spin)
    print('Rx=%g, Ry=%g'%(Rx, Ry))
    assert Rx<60 and Rx>58
    assert Ry<60 and Ry>58

# 需要导入模块: from fidimag.atomistic import Sim [as 别名]
# 或者: from fidimag.atomistic.Sim import relax [as 别名]
def test_skx_num_atomistic_hexagonal():
    """

    Test the topological charge or skyrmion number for a discrete spins
    simulation in a two dimensional hexagonal lattice, using Berg and Luscher
    definition in [Nucl Phys B 190, 412 (1981)] and simplified in [PRB 93,
    174403 (2016)], which maps a triangulated lattice (using triangles of
    neighbouring spins) area into a unit sphere.

    The areas of two triangles per lattice site cover a unit cell, thus the sum
    cover the whole area of the atomic lattice

    This test generates a skyrmion pointing down and two skyrmions pointing up
    in a PdFe sample using magnetic parameters from: PRL 114, 177203 (2015)

    """

    mesh = HexagonalMesh(0.2715, 41, 41, periodicity=(True, True))

    sim = Sim(mesh, name='skx_number_hexagonal')
    sim.driver.set_tols(rtol=1e-6, atol=1e-6)
    sim.driver.alpha = 1.0
    sim.driver.gamma = 1.0
    sim.mu_s = 3 * const.mu_B

    sim.set_m(lambda pos: init_m(pos, 16.1, 10, 2))

    sim.driver.do_precession = False

    J = 5.881 * const.meV
    exch = UniformExchange(J)
    sim.add(exch)

    D = 1.557 * const.meV
    dmi = DMI(D, dmi_type='interfacial')
    sim.add(dmi)

    sim.add(Anisotropy(0.406 * const.meV, axis=[0, 0, 1]))

    zeeman = Zeeman([0, 0, 2.5])
    sim.add(zeeman)

    sim.relax(dt=1e-13, stopping_dmdt=1e-2, max_steps=2000,
              save_m_steps=None, save_vtk_steps=100)

    skn_single = sim.skyrmion_number(method='BergLuscher')
    print('skx_number_hexagonal', skn_single)

    # Now we generate two skyrmions pointing up
    sim.driver.reset_integrator()
    sim.set_m(lambda pos: init_m_multiple_sks(pos, 1,
                                              sk_pos=[(9, 6), (18, 12)]
                                              )
              )
    sim.get_interaction('Zeeman').update_field([0, 0, -2.5])
    sim.relax(dt=1e-13, stopping_dmdt=1e-2, max_steps=2000,
              save_m_steps=None, save_vtk_steps=None)

    skn_two = sim.skyrmion_number(method='BergLuscher')
    print('skx_number_hexagonal_two', skn_two)

    # Check that we get a right sk number
    assert np.abs(skn_single - (-1)) < 1e-4 and np.sign(skn_single) < 0
    assert np.abs(skn_two - (2)) < 1e-4 and np.sign(skn_two) > 0