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
