def compute_field(): mesh = CuboidMesh(nx=1, ny=1, nz=1, dx=2.0, dy=2.0, dz=2.0, unit_length=1e-9, periodicity=(True, True, False)) sim = Sim(mesh, name='relax') sim.driver.set_tols(rtol=1e-10, atol=1e-14) sim.driver.alpha = 0.5 sim.driver.gamma = 2.211e5 sim.Ms = 8.6e5 sim.do_precession = False sim.set_m((0, 0, 1)) # sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) demag = Demag(pbc_2d=True) sim.add(demag) field = demag.compute_field() print(field) np.save('m0.npy', sim.spin)
def test_dw_dmi(mesh=mesh, do_plot=False): Ms = 8.0e5 sim = Sim(mesh, name='relax') sim.set_m(m_init_dw) sim.set_tols(rtol=1e-8, atol=1e-12) sim.Ms = Ms sim.alpha = 0.5 sim.do_precession = False A = 1.3e-11 D = 4e-4 Kx = 8e4 Kp = -6e5 sim.add(UniformExchange(A)) sim.add(DMI(D)) sim.add(UniaxialAnisotropy(Kx, axis=[1, 0, 0], name='Kx')) sim.relax(stopping_dmdt=0.01) xs = np.array([p[0] for p in mesh.coordinates]) mx, my, mz = analytical(xs, A=A, D=D, K=Kx) mxyz = sim.spin.copy() mxyz = mxyz.reshape(-1, 3) assert max(abs(mxyz[:, 0] - mx)) < 0.002 assert max(abs(mxyz[:, 1] - my)) < 0.002 assert max(abs(mxyz[:, 2] - mz)) < 0.0006 if do_plot: save_plot(mxyz, mx, my, mz)
def relax_system(mesh): sim = Sim(mesh, name='relax') sim.driver.set_tols(rtol=1e-10, atol=1e-14) sim.driver.alpha = 0.5 sim.driver.gamma = 2.211e5 sim.Ms = spatial_Ms sim.driver.do_precession = False sim.set_m(init_m) # sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) demag = Demag(pbc_2d=True) sim.add(demag) mT = 795.7747154594767 ONE_DEGREE_PER_NS = 17453292.52 sim.relax(dt=1e-13, stopping_dmdt=0.01, max_steps=5000, save_m_steps=100, save_vtk_steps=50) np.save('m0.npy', sim.spin)
def test_compute_field(): """In an infinite film, we expect the demag tensor to be (0, 0, -1), and thus the magnetisation, if aligned in 0, 0, 1 direction, to create a demag field pointing with equal strength in the opposite direction. """ mesh = CuboidMesh(nx=1, ny=1, nz=1, dx=2.0, dy=2.0, dz=2.0, unit_length=1e-9, periodicity=(True, True, False)) sim = Sim(mesh, name='relax') sim.set_tols(rtol=1e-10, atol=1e-14) sim.alpha = 0.5 sim.gamma = 2.211e5 sim.Ms = 8.6e5 sim.do_precession = False sim.set_m((0, 0, 1)) demag = Demag(pbc_2d=True) sim.add(demag) field = demag.compute_field() print((1 + field[2] / 8.6e5)) assert abs(1 + field[2] / 8.6e5) < 1e-10
def test_zeeman_energy(): mu0 = 4 * np.pi * 1e-7 # A system of 8 cells ( not using nm units) mesh = CuboidMesh(dx=2, dy=2, dz=2, nx=2, ny=2, nz=2 ) sim = Sim(mesh) Ms = 1e5 sim.set_Ms(Ms) sim.set_m((0, 0, 1)) H = 0.1 / mu0 zeeman = Zeeman((0, 0, H)) sim.add(zeeman) field = zeeman.compute_field() zf = sim.get_interaction('Zeeman') # -> -> # Expected energy: Int ( -mu0 M * H ) dV # Since we have 8 cells with the same M, we just sum their contrib exp_energy = 8 * (-mu0 * H * Ms * mesh.dx * mesh.dy * mesh.dz) assert np.abs(zf.compute_energy() - exp_energy) < 1e-10
def relax_system(mesh): sim = Sim(mesh, name='relax') sim.set_tols(rtol=1e-10, atol=1e-14) sim.alpha = 0.5 sim.gamma = 2.211e5 sim.Ms = 8.6e5 sim.do_precession = False sim.set_m((1,1,1)) # sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) dmi = DMI(D=1e-3) sim.add(dmi) zeeman = Zeeman((0, 0, 2e4)) sim.add(zeeman, save_field=True) sim.relax(dt=1e-13, stopping_dmdt=0.01, max_steps=5000, save_m_steps=None, save_vtk_steps=50) np.save('m0.npy', sim.spin)
def relax_system(mesh): # Only relaxation sim = Sim(mesh, name='relax') # Simulation parameters sim.set_tols(rtol=1e-8, atol=1e-10) sim.alpha = 0.5 sim.gamma = 2.211e5 sim.Ms = 8.6e5 sim.do_procession = False # The initial state passed as a function sim.set_m(init_m) # sim.set_m(np.load('m0.npy')) # Energies A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) anis = UniaxialAnisotropy(5e4) 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=0.00001, max_steps=5000, save_m_steps=None, save_vtk_steps=None) np.save('m0.npy', sim.spin)
def excite_system(mesh): # Specify the stt dynamics in the simulation sim = Sim(mesh, name='fidimag', driver='llg_stt') sim.driver.set_tols(rtol=1e-8, atol=1e-8) sim.driver.alpha = 0.1 sim.driver.gamma = 2.211e5 sim.Ms = 8.0e5 sim.driver.p = 1 sim.set_m(np.load('npys/m0_cpu.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) sim.add(Demag()) sim.driver.jx = -1e12 sim.driver.beta = 0.05 ts = np.linspace(0, 8e-9, 801) for t in ts: print('time', t) sim.driver.run_until(t)
def test_dmi_field_oommf(D=4.1e-3, Ms=2.6e5): mesh = CuboidMesh(nx=10, ny=3, nz=2, dx=0.5, unit_length=1e-9) sim = Sim(mesh) sim.Ms = Ms dmi = DMI(D=D, type='interfacial') sim.add(dmi) def init_m(pos): x, y, z = pos return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 0) sim.set_m(init_m) field = dmi.compute_field() init_m0 = """ return [list [expr {sin($x*1e9)+$y*1e9+$z*2.3e9}] [expr {cos($x*1e9)+$y*1e9+$z*1.3e9}] 0] """ # TODO: check the sign of DMI in OOMMF. #field_oommf = compute_dmi_field(mesh, Ms=Ms, init_m0=init_m0, D=-D) omf_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),'omfs','test_dmi_field_oommf.ohf') ovf = OMF2(omf_file) field_oommf = ovf.get_all_mags() mx0, mx1, mx2 = compare_fields(field_oommf, field) assert max([mx0, mx1, mx2]) < 1e-12
def relax_system(mesh): sim = Sim(mesh, name='relax') sim.driver.set_tols(rtol=1e-10, atol=1e-10) sim.driver.alpha = 0.5 sim.driver.gamma = 2.211e5 sim.Ms = 8.0e5 sim.do_precession = False sim.set_m((1, 0.25, 0.1)) # sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) demag = Demag() sim.add(demag) sim.relax(dt=1e-13, stopping_dmdt=0.01, max_steps=5000, save_m_steps=100, save_vtk_steps=50) np.save('m0.npy', sim.spin)
def test_exch_field_oommf(A=1e-11, Ms=2.6e5): """ Compare the exchange field from Fidimag with an equivalent OOMMF simulation. OOMMF field data is taken from an OVF file. """ mesh = CuboidMesh(nx=10, ny=3, nz=2, dx=0.5, unit_length=1e-9) sim = Sim(mesh) sim.Ms = Ms exch = UniformExchange(A=A) sim.add(exch) def init_m(pos): x, y, z = pos return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 0) sim.set_m(init_m) field = exch.compute_field() # An equivalent initial magnetisation for OOMMF # The spatial variables are rescale since they are in nm init_m0 = ( r'return [list [expr {sin($x * 1e9) + $y * 1e9 + $z * 2.3e9}] ' + r' [expr {cos($x * 1e9) + $y * 1e9 + $z * 1.3e9}] ' + r'0 ' + r'] ') field_oommf = compute_exch_field(mesh, Ms=Ms, init_m0=init_m0, A=A) mx0, mx1, mx2 = compare_fields(field_oommf, field) # Test if the maximum relative errors between both simulations # is small enough, for every field component assert max([mx0, mx1, mx2]) < 1e-12
def create_simulation(mesh, simname): # Initiate a simulation object. PBCs are specified in the mesh sim = Sim(mesh, name=simname) # Use default gamma value # sim.gamma = const.gamma # Magnetisation in A/m sim.Ms = 148367 # We could change the parameters using this option # sim.set_options(gamma=const.gamma) # Initial magnetisation profile from the function sim.set_m((0, 0.2, 0.8)) # Exchange constant A = 1.602e-12 exch = UniformExchange(A) sim.add(exch) # DMI constant D = 3.84e-3 dmi = DMI(D, dmi_type='interfacial') sim.add(dmi) # Zeeman field sim.add(Zeeman((0, 0, 25. / c.mu_0))) # Tune the damping for faster convergence sim.driver.alpha = 0.5 # Remove precession sim.driver.do_precession = False sim.driver.set_tols(rtol=1e-12, atol=1e-12) return sim
def test_dmi_field_oommf(D=4.1e-3, Ms=2.6e5): mesh = CuboidMesh(nx=10, ny=3, nz=2, dx=0.5, unit_length=1e-9) sim = Sim(mesh) sim.Ms = Ms dmi = DMI(D=D, type='interfacial') sim.add(dmi) def init_m(pos): x, y, z = pos return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 0) sim.set_m(init_m) field = dmi.compute_field() init_m0 = ( r'return [list [expr {sin($x * 1e9) + $y * 1e9 + $z * 2.3e9}] ' + r' [expr {cos($x * 1e9) + $y * 1e9 + $z * 1.3e9}] ' + r'0 ' + r'] ') # TODO: check the sign of DMI in OOMMF. field_oommf = compute_dmi_field(mesh, Ms=Ms, init_m0=init_m0, D=-D) mx0, mx1, mx2 = compare_fields(field_oommf, field) assert max([mx0, mx1, mx2]) < 1e-12
def relax_system(mesh): sim = Sim(mesh, name='relax') sim.set_tols(rtol=1e-6, atol=1e-6) sim.alpha = 0.5 sim.gamma = 2.211e5 sim.Ms = 8.6e5 sim.do_precession = False sim.set_m(init_m) #sim.set_m((0,0.1,1)) #sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) dmi = DMI(D=1.3e-3) sim.add(dmi) anis = UniaxialAnisotropy(-3.25e4, axis=(0, 0, 1)) sim.add(anis) zeeman = Zeeman((0, 0, 6.014576e4)) sim.add(zeeman, save_field=True) sim.relax(dt=1e-13, stopping_dmdt=0.5, max_steps=5000, save_m_steps=None, save_vtk_steps=50) np.save('m0.npy', sim.spin)
def run_fidimag(mesh): mu0 = 4 * np.pi * 1e-7 Ms = 8.6e5 A = 16e-12 D = -3.6e-3 K = 510e3 sim = Sim(mesh) sim.set_tols(rtol=1e-10, atol=1e-10) sim.alpha = 0.5 sim.gamma = 2.211e5 sim.Ms = Ms sim.do_precession = False sim.set_m((0, 0, 1)) sim.add(UniformExchange(A)) sim.add(DMI(D, type='interfacial')) sim.add(UniaxialAnisotropy(K, axis=(0, 0, 1))) sim.relax(dt=1e-13, stopping_dmdt=0.01, max_steps=5000, save_m_steps=None, save_vtk_steps=50) m = sim.spin return m.copy()
def test_exch_field_oommf(A=1e-11, Ms=2.6e5): mesh = CuboidMesh(nx=10, ny=3, nz=2, dx=0.5, unit_length=1e-9) sim = Sim(mesh) sim.Ms = Ms exch = UniformExchange(A=A) sim.add(exch) def init_m(pos): x, y, z = pos return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 0) sim.set_m(init_m) field = exch.compute_field() init_m0 = """ return [list [expr {sin($x*1e9)+$y*1e9+$z*2.3e9}] [expr {cos($x*1e9)+$y*1e9+$z*1.3e9}] 0] """ omf_file = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'omfs', 'test_exch_field_oommf.ohf' ) ovf = OMF2(omf_file) field_oommf = ovf.get_all_mags() #field_oommf = compute_exch_field(mesh, Ms=Ms, init_m0=init_m0, A=A) mx0, mx1, mx2 = compare_fields(field_oommf, field) assert max([mx0, mx1, mx2]) < 1e-12
def relax_system(mesh): sim = Sim(mesh, name='relax') sim.set_tols(rtol=1e-6, atol=1e-6) sim.alpha = 0.5 sim.gamma = 2.211e5 sim.Ms = 8.6e5 sim.do_precession = False sim.set_m(init_m) exch = UniformExchange(A=1.3e-11) sim.add(exch) dmi = DMI(D=-4e-3) sim.add(dmi) zeeman = Zeeman((0, 0, 4e5)) sim.add(zeeman, save_field=True) sim.relax(dt=1e-13, stopping_dmdt=1e-2, save_m_steps=None, save_vtk_steps=50) np.save('m0.npy', sim.spin)
def relax_system(mesh): sim = Sim(mesh, chi=1e-3, name='relax', driver='llbar_full') sim.set_tols(rtol=1e-7, atol=1e-7) sim.Ms = 8.0e5 sim.alpha = 0.1 sim.beta = 0 sim.gamma = 2.211e5 sim.set_m((1, 0.25, 0.1)) # sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) mT = 795.7747154594767 zeeman = Zeeman([-100 * mT, 4.3 * mT, 0], name='H') sim.add(zeeman, save_field=True) demag = Demag() sim.add(demag) ONE_DEGREE_PER_NS = 17453292.52 sim.relax(dt=1e-12, stopping_dmdt=0.01, max_steps=5000, save_m_steps=100, save_vtk_steps=50) np.save('m0.npy', sim.spin)
def test_sim_init_m(): mesh = CuboidMesh(nx=3, ny=4, nz=5) sim = Sim(mesh) sim.set_m((0, 1, 0)) sim.spin.shape = (-1, 3) spin_y = sim.spin[:, 1] assert (spin_y.any() == 1)
def apply_field1(mesh): sim = Sim(mesh, name='dyn') sim.driver.set_tols(rtol=1e-10, atol=1e-10) sim.driver.alpha = 0.02 sim.driver.gamma = 2.211e5 sim.Ms = 8.0e5 sim.set_m(np.load('m0.npy')) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) demag = Demag() sim.add(demag) mT = 0.001 / mu0 print("Applied field = {}".format(mT)) zeeman = Zeeman([-24.6 * mT, 4.3 * mT, 0], name='H') sim.add(zeeman, save_field=True) ts = np.linspace(0, 1e-9, 201) for t in ts: sim.driver.run_until(t) print('sim t=%g' % t)
def relax_neb(k, maxst, simname, init_im, interp, save_every=10000, coordinates='Cartesian'): """ Execute a simulation with the NEB function of the FIDIMAG code, for an elongated particle (long cylinder) The simulations are made for a specific spring constant 'k' (a float), number of images 'init_im', interpolations between images 'interp' (an array) and a maximum of 'maxst' steps. 'simname' is the name of the simulation, to distinguish the output files. --> vtks and npys are saved in files starting with the 'simname' string """ # Prepare simulation # We define the cylinder with the Magnetisation function sim = Sim(mesh) sim.Ms = two_part # sim.add(UniformExchange(A=A)) # Uniaxial anisotropy along x-axis sim.add(UniaxialAnisotropy(Kx, axis=(1, 0, 0))) # Define many initial states close to one extreme. We want to check # if the images in the last step, are placed mostly in equally positions init_images = init_im # Number of images between each state specified before (here we need only # two, one for the states between the initial and intermediate state # and another one for the images between the intermediate and final # states). Thus, the number of interpolations must always be # equal to 'the number of initial states specified', minus one. interpolations = interp if coordinates == 'Spherical': neb = NEBM_Spherical(sim, init_images, interpolations=interpolations, spring_constant=k, name=simname ) if coordinates == 'Geodesic': neb = NEBM_Geodesic(sim, init_images, interpolations=interpolations, spring_constant=k, name=simname, integrator='sundials' ) neb.relax(max_iterations=2000, save_vtks_every=save_every, save_npys_every=save_every, stopping_dYdt=1e-4, dt=1e-6 )
def elongated_part_sim(): sim = Sim(mesh) sim.Ms = lambda r: cylinder(r, centre, 8) sim.add(UniformExchange(A=A)) sim.add(UniaxialAnisotropy(Kx, axis=(0, 1, 0))) # Anisotropy along y sim.add(Demag()) return sim
def relax_system(mesh): sim = Sim(mesh, name='relax') sim.driver.set_tols(rtol=1e-10, atol=1e-10) sim.driver.alpha = 0.1 sim.driver.gamma = 2.211e5 sim.Ms = spatial_Ms print(sim.Ms) sim.set_m(init_m) A = 1.3e-11 exch = UniformExchange(A=A) sim.add(exch) demag = Demag() sim.add(demag) dmi = DMI(D=4e-3) sim.add(dmi) dmi2 = DMI(D=2e-3, dmi_type="interfacial") sim.add(dmi2) anis = UniaxialAnisotropy(-3e4, axis=(0, 0, 1)) sim.add(anis) sim.relax(dt=1e-13, stopping_dmdt=5e4, max_steps=5000, save_m_steps=100, save_vtk_steps=50) #np.save('m0.npy', sim.spin) fd = demag.compute_field(sim.spin) fe = exch.compute_field(sim.spin) fdmi = dmi.compute_field(sim.spin) fdmi2 = dmi2.compute_field(sim.spin) fanis = anis.compute_field(sim.spin) np.savetxt( "test_fields.txt", np.transpose([ np.concatenate((sim.Ms, sim.Ms, sim.Ms, [0.0])), np.concatenate((sim.spin, [100])), np.concatenate((fd, [demag.compute_energy()])), np.concatenate((fe, [exch.compute_energy()])), np.concatenate((fdmi, [dmi.compute_energy()])), np.concatenate((fdmi2, [dmi2.compute_energy()])), np.concatenate((fanis, [anis.compute_energy()])) ]), header= "Generated by Fidimag. Size=20x5x3, 2.5nm x 2.5nm x 3nm, Ms=8.0e5A/m, A=1.3e-11 J/m," + " D=4e-3 J/m^2, D_int=2e-3 J/m^2, Ku=-3e4 J/m^3 axis=(0,0,1).\n Ms " + "".ljust(20) + " m0 " + "".ljust(20) + "demag" + "".ljust(20) + "exch" + "".ljust(22) + "dmi" + "".ljust(22) + "dmi_interfacial" + "".ljust(22) + "anis")
def test_with_oommf_spatial_Ms(A=1e-11): def spatial_Ms(pos): x, y = pos[0], pos[1] if x**2 + y**2 < 5**2: return 2e4 else: return 0 init_m0 = ( r'return [list [expr {sin($x * 1e9) + $y * 1e9 + $z * 2.3e9}] ' + r' [expr {cos($x * 1e9) + $y * 1e9 + $z * 1.3e9}] ' + r'0 ' + r'] ') init_Ms = """ if { ($x * $x + $y * $y) < 5e-9 * 5e-9 } { return 2e4 } else { return 0 } """ mesh = CuboidMesh(nx=12, ny=10, nz=2, dx=0.5, unit_length=1e-9) sim = Sim(mesh) sim.Ms = spatial_Ms def init_m(pos): x, y, z = pos return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 0) sim.set_m(init_m) exch = UniformExchange(A=A) sim.add(exch) demag = Demag() sim.add(demag) field = exch.compute_field() field_oommf = compute_exch_field(mesh, init_m0=init_m0, A=A, spatial_Ms=init_Ms) mx0, mx1, mx2 = compare_fields(field_oommf, field) assert max([mx0, mx1, mx2]) < 1e-12 field = demag.compute_field() field_oommf = compute_demag_field(mesh, spatial_Ms=init_Ms, init_m0=init_m0) mx0, mx1, mx2 = compare_fields(field_oommf, field) assert max([mx0, mx1, mx2]) < 1e-11
def test_sim_single_spin(do_plot=False): mesh = CuboidMesh(nx=1, ny=1, nz=1) sim = Sim(mesh, name='spin') alpha = 0.1 gamma = 2.21e5 sim.alpha = alpha sim.gamma = gamma sim.mu_s = 1.0 sim.set_m((1, 0, 0)) H0 = 1e5 sim.add(Zeeman((0, 0, H0))) ts = np.linspace(0, 1e-9, 101) mx = [] my = [] mz = [] real_ts = [] for t in ts: sim.run_until(t) real_ts.append(sim.t) print(sim.t, abs(sim.spin_length()[0] - 1)) mx.append(sim.spin[0]) my.append(sim.spin[1]) mz.append(sim.spin[2]) mz = np.array(mz) # print mz a_mx, a_my, a_mz = single_spin(alpha, gamma, H0, ts) print(sim.stat()) if do_plot: ts_ns = np.array(real_ts) * 1e9 plt.plot(ts_ns, mx, ".", label="mx", color='DarkGreen') plt.plot(ts_ns, my, ".", label="my", color='darkslateblue') plt.plot(ts_ns, mz, ".", label="mz", color='m') plt.plot(ts_ns, a_mx, "--", label="analytical", color='b') plt.plot(ts_ns, a_my, "--", color='b') plt.plot(ts_ns, a_mz, "--", color='b') plt.xlabel("time (ns)") plt.ylabel("m") plt.title("integrating a macrospin") plt.legend() plt.savefig("single_spin.pdf") print(("Max Deviation = {0}".format( np.max(np.abs(mz - a_mz))))) assert np.max(np.abs(mz - a_mz)) < 5e-7
def test_sim_init_m_fun(): mesh = CuboidMesh(nx=3, ny=4, nz=5) sim = Sim(mesh) sim.set_m(init_m, normalise=False) print(sim.spin.reshape(-1, 3).shape) print(sim.mesh.index(1, 2, 3)) assert (sim.spin_at(1, 2, 3)[0] == 1) assert (sim.spin_at(1, 2, 3)[1] == 2) assert (sim.spin_at(1, 2, 3)[2] == 3)
def relax_neb(k, maxst, simname, init_im, interp, save_every=10000): """ Execute a simulation with the NEB function of the FIDIMAG code, for a nano disk The simulations are made for a specific spring constant 'k' (a float), number of images 'init_im', interpolations between images 'interp' (an array) and a maximum of 'maxst' steps. 'simname' is the name of the simulation, to distinguish the output files. --> vtks and npys are saved in folders starting with the 'simname' """ # Prepare simulation # We define the small cylinder with the Magnetisation function sim = Sim(mesh) sim.Ms = cylinder # Energies # Exchange sim.add(UniformExchange(A=A)) # Bulk DMI --> This produces a Bloch DW - like skyrmion sim.add(DMI(D=D)) # No Demag, but this could have some effect # Demagnetization energy # sim.add(Demag()) # Initial images (npy files or functions) init_images = init_im # Number of images between each state specified before (here we need only # two, one for the states between the initial and intermediate state # and another one for the images between the intermediate and final # states). Thus, the number of interpolations must always be # equal to 'the number of initial states specified', minus one. interpolations = interp # Initiate the NEB algorithm driver neb = NEB_Sundials(sim, init_images, interpolations=interpolations, spring=k, name=simname) # Start the relaxation neb.relax(max_steps=maxst, save_vtk_steps=save_every, save_npy_steps=save_every, stopping_dmdt=1)
def setup_domain_wall_cobalt(node_count=NODE_COUNT, A=A_Co, Ms=Ms_Co, K1=K1_Co, length=LENGTH, do_precession=True, unit_length=UNIT_LENGTH): a = length / node_count # cell size mesh = CuboidMesh(dx=a, dy=a, dz=a, nx=node_count, ny=1, nz=1, unit_length=unit_length) sim = Sim(mesh, "dw_cobalt") sim.Ms = Ms sim.set_m(lambda r: initial_m(r, length)) sim.do_precession = do_precession sim.add(UniformExchange(A)) sim.add(UniaxialAnisotropy(K1, (0, 0, 1))) sim.pins = lambda r: 1 if (r[0] < a or r[0] > LENGTH - a) else 0 return sim
def test_init(): """ This tests (mx, my, mx) for the first 2 spins """ mesh = CuboidMesh(nx=100, ny=1, nz=1) sim = Sim(mesh) sim.set_m(init_m) expected = np.array([0, 0, 1, 0, np.sin(0.1), np.cos(0.1)]) assert max(abs(sim.spin[:6] - expected)) < 1e-15
def create_simulation(mesh): sim = Sim(mesh) sim.Ms = 8.6e5 sim.set_m((1, 0, 0)) sim.add(UniformExchange(A=1.3e-11)) # sim.add(Demag()) #sim.add(UniaxialAnisotropy(Kx, (1, 0, 0), name='Kx')) anis = UniaxialAnisotropy(1e5, axis=(1, 0, 0)) sim.add(anis) return sim