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 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, dmi_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 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.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))
# 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_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 + $z * 1.3e9}] '
+ r'0 '
+ r'] ')
# TODO: check the sign of DMI in OOMMF.
field_oommf = compute_dmi_field(mesh, Ms=Ms, init_m0=init_m0, D=-D)
mx0, mx1, mx2 = compare_fields(field_oommf, field)
assert max([mx0, mx1, mx2]) < 1e-12
def test_energy_dmi(Ms=8e5, D=1.32e-3):
mesh = CuboidMesh(nx=40, ny=50, nz=1, dx=2.5, dy=2.5, dz=3, unit_length=1e-9)
sim = Sim(mesh)
sim.Ms = Ms
dmi = DMI(D=D, type='interfacial')
#dmi = DMI(D=D, type='bulk')
sim.add(dmi)
def init_m(pos):
x, y, z = pos
return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 1)
sim.set_m(init_m)
dmi_energy = dmi.compute_energy()
# init_m0="""
# return [list [expr {sin($x*1e9)+$y*1e9+$z*2.3e9}] [expr {cos($x*1e9)+$y*1e9+$z*1.3e9}] 1]
#"""
#field_oommf = compute_dmi_field(mesh, Ms=Ms, init_m0=init_m0, D=D)
dmi_energy_oommf = -4.5665527749090378e-20
print 'dmi energy', dmi_energy
assert abs(dmi_energy - dmi_energy_oommf) / dmi_energy_oommf < 1e-15
def relax_system(mesh):
# Only relaxation
sim = Sim(mesh, name='relax')
# Simulation parameters
sim.driver.set_tols(rtol=1e-8, atol=1e-10)
sim.driver.alpha = 0.5
sim.driver.gamma = 2.211e5
sim.Ms = 8.6e5
sim.do_precession = False
# The initial state passed as a function
sim.set_m(init_m)
# sim.set_m(np.load('m0.npy'))
# Energies
A = 1.3e-11
exch = UniformExchange(A=A)
sim.add(exch)
anis = UniaxialAnisotropy(5e4)
sim.add(anis)
# Start relaxation and save the state in m0.npy
sim.relax(dt=1e-14, stopping_dmdt=0.00001, max_steps=5000,
save_m_steps=None, save_vtk_steps=None)
np.save('m0.npy', sim.spin)
def test_exch_field_oommf(A=1e-11, Ms=2.6e5):
"""
Compare the exchange field from Fidimag with an equivalent
OOMMF simulation. OOMMF field data is taken from an OVF file.
"""
mesh = CuboidMesh(nx=10, ny=3, nz=2, dx=0.5, unit_length=1e-9)
sim = Sim(mesh)
sim.Ms = Ms
exch = UniformExchange(A=A)
sim.add(exch)
def init_m(pos):
x, y, z = pos
return (np.sin(x) + y + 2.3 * z, np.cos(x) + y + 1.3 * z, 0)
sim.set_m(init_m)
field = exch.compute_field()
# An equivalent initial magnetisation for OOMMF
# The spatial variables are rescale since they are in nm
init_m0 = (r'return [list [expr {sin($x * 1e9) + $y * 1e9 + $z * 2.3e9}] '
+ r' [expr {cos($x * 1e9) + $y * 1e9 + $z * 1.3e9}] '
+ r'0 '
+ r'] ')
field_oommf = compute_exch_field(mesh, Ms=Ms, init_m0=init_m0, A=A)
mx0, mx1, mx2 = compare_fields(field_oommf, field)
# Test if the maximum relative errors between both simulations
# is small enough, for every field component
assert max([mx0, mx1, mx2]) < 1e-12
def setup_simulation(mesh, m0, simulation_name, integrator="sundials", use_jac=False):
sim = Sim(mesh, name=simulation_name, integrator=integrator, use_jac)
sim.set_m(m0)
sim.Ms = Ms
sim.alpha = alpha
sim.gamma = gamma
sim.add(UniformExchange(A))
sim.add(Demag())
return sim
def test_with_oommf_spatial_Ms(A=1e-11):
def spatial_Ms(pos):
x, y = pos[0], pos[1]
if x ** 2 + y ** 2 < 5 ** 2:
return 2e4
else:
return 0
init_m0 = (r'return [list [expr {sin($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 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 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
def run(integrator, jacobian):
name = "sim_" + integrator
if integrator == "sundials":
name += "_J1" if jacobian else "_J0"
sim = Sim(mesh, name, integrator, use_jac=jacobian)
sim.Ms = 0.86e6
sim.alpha = 0.5
sim.set_m((1, 0, 1))
sim.add(UniformExchange(A=13e-12))
sim.add(Demag())
ts = np.linspace(0, 3e-10, 61)
for t in ts:
sim.run_until(t)
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 test_zeeman():
mesh = CuboidMesh(nx=5, ny=2, nz=1)
sim = Sim(mesh)
sim.set_m((1, 0, 0))
zeeman = Zeeman(varying_field)
sim.add(zeeman)
field = zeeman.compute_field()
assert field[6] == 1.2 * (2 + 0.5)
assert field[7] == 2.3 * 0.5
def relax_system():
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='relax')
sim.driver.set_tols(rtol=1e-10, atol=1e-10)
sim.driver.alpha = 0.5
sim.set_m((1.0, 0, 0))
sim.add(Zeeman((0, 0, 1e5)))
ts = np.linspace(0, 1e-9, 1001)
for t in ts:
sim.run_until(t)
def run_sim(): mesh = CuboidMesh() sim = Sim(mesh, name='spin') alpha = 0.1 gamma = 2.21e5 sim.alpha = alpha sim.driver.gamma = gamma sim.mu_s = 1.0 sim.set_m((1, 0, 0)) H0 = 1e5 sim.add(Zeeman((0, 0, H0))) sim.driver.run_until(1e-10) sim.driver.run_until(0.5e-10)
def test_sim_pin():
mesh = CuboidMesh(nx=3, ny=2, nz=1)
sim = Sim(mesh)
sim.set_m((0, 0.8, 0.6))
sim.alpha = 0.1
sim.gamma = 1.0
sim.pins = pin_fun
anis = UniaxialAnisotropy(Ku=1, axis=[0, 0, 1], name='Dx')
sim.add(anis)
sim.run_until(1.0)
print sim.spin
assert sim.spin[0] == 0
assert sim.spin[2] != 0
def test_sim_pin():
mesh = CuboidMesh(nx=3, ny=2, nz=1)
sim = Sim(mesh, integrator='sundials_openmp')
sim.set_m((0, 0.8, 0.6))
sim.alpha = 0.1
sim.driver.gamma = 1.0
sim.pins = pin_fun
anis = UniaxialAnisotropy(Ku=1, axis=[0, 0, 1], name='Dx')
sim.add(anis)
sim.driver.run_until(1.0)
print(sim.spin)
assert sim.spin[0] == 0
assert sim.spin[2] != 0
def test_exch_1d(do_plot=False):
# Initiate the 1D mesh and magnetisation as before
mesh = CuboidMesh(nx=100, ny=1, nz=1)
sim = Sim(mesh)
sim.set_m(init_m)
# Simplify the magnetic parameters
mu0 = 4 * np.pi * 1e-7
sim.Ms = 1.0 / mu0
exch = UniformExchange(1)
sim.add(exch)
# Compute the exchange field and reshape it in order
# to leave every row as the [f_x, f_y, f_z] array
# for every spin
field = exch.compute_field()
field.shape = (-1, 3)
# We know that the field in x is always zero ( see the
# analytical calculation at the beginning)
assert max(abs(field[:, 0])) == 0
# These are the analytical values for the exchange field in y,z
# In this case, k=0.1 , then 2 * k^2 evaluates as 0.02
xs = np.linspace(0, 99, 100)
epy = -0.02 * np.sin(0.1 * xs)
epz = -0.02 * np.cos(0.1 * xs)
# Compare the analytical value
# of the y component of the exchange field, with Fidimag's
# result (second column of the reshaped field array)
# WARNING: NOTICE that we are not considering the extremes since
# there is a wrong expression in the border of the exchange field
# with NO PBCs. We must FIX this test!
assert max(abs(epy[1:-1] - field[1:-1, 1])) < 3e-5
if do_plot:
plt.plot(xs, field[:, 1], "-.", label="my", color='DarkGreen')
plt.plot(xs, field[:, 2], "-.", label="mz", color='DarkGreen')
plt.plot(xs, epy, "--", label="analytical", color='b')
plt.plot(xs, epz, "--", color='r')
plt.xlabel("xs")
plt.ylabel("field")
plt.legend()
plt.savefig("exchange_field.pdf")
def test_demag_field_oommf_large(Ms=8e5, A=1.3e-11):
mesh = CuboidMesh(nx=150, ny=50, nz=1, dx=2.5, dy=2.5, dz=3, unit_length=1e-9)
sim = Sim(mesh)
sim.Ms = Ms
exch = UniformExchange(A=A)
sim.add(exch)
demag = Demag()
sim.add(demag)
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)
demag_field = demag.compute_field()
exch_field = exch.compute_field()
#exact = demag.compute_exact()
init_m0 = """
return [list [expr {sin($x*1e9)+$y*1e9+$z*2.3e9}] [expr {cos($x*1e9)+$y*1e9+$z*1.3e9}] 0]
"""
#demag_oommf = compute_demag_field(mesh, Ms=Ms, init_m0=init_m0)
#exch_oommf = compute_exch_field(mesh, Ms=Ms, init_m0=init_m0, A=A)
omf_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),'omfs','test_demag_field_oommf_large_Demag.ohf')
ovf = OMF2(omf_file)
demag_oommf = ovf.get_all_mags()
omf_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),'omfs','test_demag_field_oommf_large_Exchange.ohf')
ovf = OMF2(omf_file)
exch_oommf = ovf.get_all_mags()
mx0, mx1, mx2 = compare_fields(demag_oommf, demag_field)
#print mx0, mx1, mx2
assert max([mx0,mx1,mx2])< 5e-10
mx0, mx1, mx2 = compare_fields(exch_oommf, exch_field)
#print mx0, mx1, mx2
assert max([mx0, mx1, mx2]) < 1e-11
def relax_neb(k, maxst, simname, init_im, interp, save_every=10000):
"""
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
neb = NEB_Sundials(sim,
init_images,
interpolations=interpolations,
spring=k,
name=simname)
neb.relax(max_steps=maxst,
save_vtk_steps=save_every,
save_npy_steps=save_every,
stopping_dmdt=1e-2)
def test_demag_field_oommf(Ms=6e5):
mesh = CuboidMesh(nx=5, ny=2, nz=3, unit_length=1e-9)
sim = Sim(mesh)
sim.Ms = Ms
demag = Demag()
sim.add(demag)
def init_m(pos):
x = pos[0]
if x <= 2:
return (1, 0, 0)
elif x >= 4:
return (0, 0, 1)
else:
return (0, 1, 0)
sim.set_m(init_m)
field = demag.compute_field()
exact = demag.compute_exact()
init_m0 = """
if { $x <=2e-9 } {
return "1 0 0"
} elseif { $x >= 4e-9 } {
return "0 0 1"
} else {
return "0 1 0"
}
"""
field_oommf = compute_demag_field(mesh, Ms=Ms, init_m0=init_m0)
mx0, mx1, mx2 = compare_fields(field_oommf, exact)
print mx0, mx1, mx2
assert max([mx0, mx1, mx2]) < 2e-14
mx0, mx1, mx2 = compare_fields(field_oommf, field)
print mx0, mx1, mx2
assert np.max(abs(field - field_oommf)) < 2e-9
def excite_system(mesh, beta=0.0):
# Specify the stt dynamics in the simulation
sim = Sim(mesh, name='dyn_%g'%beta, driver='llg_stt_cpp')
sim.driver.set_tols(rtol=1e-12, atol=1e-12)
sim.driver.alpha = 0.1
sim.driver.gamma = 2.211e5
sim.Ms = 8.6e5
# 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)
# beta is the parameter in the STT torque
sim.a_J = global_const*1e11
sim.p = (1,0,0)
sim.beta = beta
# The simulation will run for 5 ns and save
# 500 snapshots of the system in the process
ts = np.linspace(0, 0.5e-9, 21)
xs=[]
thetas=[]
for t in ts:
print('time', t)
sim.run_until(t)
spin = sim.spin.copy()
x, theta = extract_dw(spin)
xs.append(x)
thetas.append(theta)
sim.save_vtk()
np.savetxt('dw_%g.txt'%beta,np.transpose(np.array([ts, xs,thetas])))
def relax_system_only_exchange(mesh):
sim = Sim(mesh, name='relax_exchange_only')
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_BP)
A = 1.3e-11
exch = UniformExchange(A=A)
sim.add(exch)
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 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_procession = 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 test_dw_dmi(mesh=mesh, do_plot=False):
Ms = 8.0e5
sim = Sim(mesh, name='relax')
sim.set_m(m_init_dw)
sim.driver.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.driver.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.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(init_m)
# 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):
sim = Sim(mesh, chi=1e-3, name='relax', driver='llbar_full')
sim.driver.set_tols(rtol=1e-7, atol=1e-7)
sim.Ms = 8.0e5
sim.driver.alpha = 0.1
sim.beta = 0
sim.driver.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 apply_field1(mesh):
sim = Sim(mesh, name='dyn')
sim.set_tols(rtol=1e-10, atol=1e-10)
sim.alpha = 0.02
sim.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.run_until(t)
print('sim t=%g' % t)
def relax_system(mesh):
sim = Sim(mesh, name='relax')
sim.driver.set_tols(rtol=1e-6, atol=1e-6)
sim.driver.alpha = 0.5
sim.driver.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 excite_system(mesh, time=5, snaps=501):
# Specify the stt dynamics in the simulation
sim = Sim(mesh, name='dyn', driver='llg_stt')
# Set the simulation parameters
sim.set_tols(rtol=1e-12, atol=1e-14)
sim.alpha = 0.05
sim.gamma = 2.211e5
sim.Ms = 8.6e5
# Load the initial state from the npy file saved
# in the realxation
sim.set_m(np.load('m0.npy'))
# Add the 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)
# Set the current in the x direction, in A / m
# beta is the parameter in the STT torque
sim.jx = -1e12
sim.beta = 1
# The simulation will run for x ns and save
# 'snaps' snapshots of the system in the process
ts = np.linspace(0, time * 1e-9, snaps)
for t in ts:
print 'time', t
sim.run_until(t)
sim.save_vtk()
sim.save_m()
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 = 8.6e5
sim.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)
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 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 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.run_until(t)
print('sim t=%g' % t)
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 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 test_energy_dmi(Ms=8e5, D=1.32e-3):
mesh = CuboidMesh(nx=40,
ny=50,
nz=1,
dx=2.5,
dy=2.5,
dz=3,
unit_length=1e-9)
sim = Sim(mesh)
sim.Ms = Ms
dmi = DMI(D=D, type='interfacial')
#dmi = DMI(D=D, type='bulk')
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, 1)
sim.set_m(init_m)
dmi_energy = dmi.compute_energy()
# init_m0="""
# return [list [expr {sin($x*1e9)+$y*1e9+$z*2.3e9}] [expr {cos($x*1e9)+$y*1e9+$z*1.3e9}] 1]
#"""
#field_oommf = compute_dmi_field(mesh, Ms=Ms, init_m0=init_m0, D=D)
dmi_energy_oommf = -4.5665527749090378e-20
print('dmi energy', dmi_energy)
assert abs(dmi_energy - dmi_energy_oommf) / dmi_energy_oommf < 1e-15
def excite_system(mesh):
# Specify the stt dynamics in the simulation
sim = Sim(mesh, name='dyn2', driver='llg_stt')
sim.driver.set_tols(rtol=1e-12, atol=1e-14)
sim.driver.alpha = 0.2
sim.driver.gamma = 2.211e5
sim.Ms = 8.6e5
# 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)
# Set the current in the x direction, in A / m
# beta is the parameter in the STT torque
sim.driver.jx = -1e12
sim.driver.beta = 0.01
# The simulation will run for 5 ns and save
# 500 snapshots of the system in the process
ts = np.linspace(0, 5e-9, 501)
for t in ts:
print('time', t)
sim.driver.run_until(t)
sim.save_vtk()
sim.save_m()
def relax_system(mesh):
# Only relaxation
sim = Sim(mesh, name='relax')
# Simulation parameters
sim.driver.set_tols(rtol=1e-8, atol=1e-10)
sim.driver.alpha = 0.5
sim.driver.gamma = 2.211e5
sim.Ms = 8.6e5
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
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)
# mT = 795.7747154594767
# ONE_DEGREE_PER_NS = 17453292.52
# Start relaxation and save the state in m0.npy
sim.relax(dt=1e-14,
stopping_dmdt=0.01,
max_steps=5000,
save_m_steps=None,
save_vtk_steps=50)
np.save('m0.npy', sim.spin)
def relax_system_only_exchange(mesh):
sim = Sim(mesh, name='relax_exchange_only')
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_BP)
A = 1.3e-11
exch = UniformExchange(A=A)
sim.add(exch)
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 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_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.driver.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 excite_system(mesh):
sim = Sim(mesh, name='dyn')
sim.driver.set_tols(rtol=1e-10, atol=1e-14)
sim.driver.alpha = 0.01
sim.driver.gamma = 2.211e5
sim.Ms = spatial_Ms
# 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
sigma = 0.08e-9
def gaussian_fun(t):
return np.exp(-0.5 * (t / sigma)**2)
zeeman = TimeZeeman((80 * mT, 0, 0), time_fun=gaussian_fun, name='hx')
#zeeman = Zeeman((100*mT,0,0), name='hx')
sim.add(zeeman, save_field=True)
ts = np.linspace(0, 1e-9, 501)
for t in ts:
print('time', t)
print('length:', sim.spin_length()[0:200])
sim.run_until(t)
sim.save_vtk()
def excite_system(mesh):
sim = Sim(mesh, name='dyn', driver='llg_stt')
sim.set_tols(rtol=1e-8, atol=1e-10)
sim.alpha = 0.5
sim.gamma = 2.211e5
sim.Ms = 8.6e5
sim.set_m(np.load('m0.npy'))
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.jx = -5e12
sim.beta = 0
ts = np.linspace(0, 0.5e-9, 101)
for t in ts:
print 'time', t
sim.run_until(t)
sim.save_vtk()
def relax_neb(mesh, k, maxst, simname, init_im, interp,
save_every=10000, stopping_dYdt=0.01):
"""
Execute a simulation with the NEBM algorithm of the FIDIMAG code
Here we use always the 21x21 Spins Mesh and don't vary the material
parameters. This can be changed adding those parameters as variables.
We create a new Simulation object every time this function is called
since it can be modified in the process
k :: NEBM spring constant
maxst :: Maximum number of iterations
simname :: Simulation name. VTK and NPY files are saved in folders
starting with the 'simname' string
init_im :: A list with magnetisation states (usually loaded from
NPY files or from a function) that will be used as
images in the energy band, e.g. for two states:
[np.load('skyrmion.npy'), np.load('ferromagnet.npy')]
interp :: Array or list with the numbers of interpolations between
every pair of the 'init_im' list. The length of this array
is: len(__init_im) - 1
save_every :: Save VTK and NPY files every 'save_every' number of steps
"""
# Initialise a simulation object and set the default gamma for the LLG
# equation
sim = Sim(mesh, name=simname)
# sim.gamma = const.gamma
# Magnetisation in A/m
sim.Ms = 148367
# Interactions ------------------------------------------------------------
# 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)))
# -------------------------------------------------------------------------
# Set the initial images from the list
init_images = init_im
# The number of interpolations must always be
# equal to 'the number of initial states specified', minus one.
interpolations = interp
# Start a NEB simulation passing the Simulation object and all the NEB
# parameters
neb = NEBM_Geodesic(sim,
init_images,
interpolations=interpolations,
spring_constant=k,
name=simname,
)
# Finally start the energy band relaxation
neb.relax(max_iterations=maxst,
save_vtks_every=save_every,
save_npys_every=save_every,
stopping_dYdt=stopping_dYdt
)
# Produce a file with the data from a cubic interpolation for the band
interp_data = np.zeros((200, 2))
interp_data[:, 0], interp_data[:, 1] = neb.compute_polynomial_approximation(200)
np.savetxt(simname + 'interpolation.dat', interp_data)
dz=dz,
x0=-Lx / 2,
y0=-Ly / 2,
z0=-Lz / 2,
unit_length=1e-9)
sim = Sim(mesh)
Ms = 1.1e6
A = 2e-12
D = 3.9e-3
Ku = 2.5e6
Bz = 1.
sim.set_Ms(Ms)
sim.add(fidimag.micro.UniformExchange(A))
sim.add(fidimag.micro.UniaxialAnisotropy(Ku, axis=(0, 0, 1)))
sim.add(fidimag.micro.Zeeman((0, 0, Bz / C.mu_0)))
# sim.add(fidimag.micro.DMI(D, dmi_type='interfacial'))
# For a C_n material, there is a kind of instability when one of the DM
# constants is larger than approx 0.7 times the other DM constant
sim.add(fidimag.micro.DMI([D, 0.6 * D], dmi_type='C_n'))
sim.set_m(init_m)
sim.driver.do_precession = False
sim.driver.alpha = 0.9
sim.relax()
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 == 'Cartesian':
neb = NEBM_Cartesian(sim,
init_images,
interpolations=interpolations,
spring_constant=k,
name=simname
)
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
)
neb.relax(max_iterations=maxst,
save_vtks_every=save_every,
save_npys_every=save_every,
stopping_dYdt=1e-2)
centre_x = (mesh.coordinates[:, 0].max()
+ mesh.coordinates[:, 0].min()) * 0.5 + mesh.coordinates[:, 0].min()
centre_y = (mesh.coordinates[:, 1].max()
+ mesh.coordinates[:, 1].min()) * 0.5 + mesh.coordinates[:, 1].min()
centre_z = 0.5
# -----------------------------------------------------------------------------
sim = Sim(mesh, name='dynamics')
sim.set_m(np.load('initial_state.npy'))
# -----------------------------------------------------------------------------
sim.Ms = Ms
sim.add(UniformExchange(A))
sim.add(Demag())
# sim.add(UniaxialAnisotropy(Ku, (0, 0, 1)))
# Periodic DMI
sim.add(DMI(D, dmi_type='interfacial'))
# External field along the stripe length
sim.add(Zeeman((0, B0 / mu0, 0)), save_field=True)
# -----------------------------------------------------------------------------
# Dynamics
def spatial_sinc_field(r, x0, y0, z0, h0):
# We define the cylinder with the Magnetisation function
sim = Sim(mesh, name='skyrmion')
sim.Ms = cylinder
# To get a faster relaxation, we tune the LLG equation parameters
sim.do_precession = False
sim.alpha = 0.5
# Initial magnetisation:
sim.set_m(init_m)
# Energies:
# Exchange
sim.add(UniformExchange(A=A))
# Bulk DMI
sim.add(DMI(D=D))
# Relax the system
sim.relax(dt=1e-12,
stopping_dmdt=0.0001,
max_steps=5000,
save_m_steps=None,
save_vtk_steps=None)
# Save the final relaxed state and a vtk file
np.save('sk_up.npy', sim.spin)
sim.save_vtk()
# ----------------------------------------------------------------------------- sim = Sim(mesh) sim.driver.gamma = 2.21e5 sim.set_m((0.1, 0.9, 0)) # ----------------------------------------------------------------------------- A = 13e-12 # J * m**-1 D = 3e-3 # J * m**-2 Ku = 0e6 # J * m**-3 Ms = 0.86e6 # A / m B0 = 0.4 # T sim.Ms = Ms sim.add(UniformExchange(A)) sim.add(Demag()) # sim.add(UniaxialAnisotropy(Ku, (0, 0, 1))) # Periodic DMI sim.add(DMI(D, dmi_type='interfacial')) # External field along the stripe length sim.add(Zeeman((0, B0 / mu0, 0)), save_field=True) # ----------------------------------------------------------------------------- # Relax the system first sim.driver.alpha = 0.9 sim.driver.do_precession = False sim.driver.relax(stopping_dmdt=0.01)
# Initiate Fidimag simulation ---------------------------------------------
sim = Sim(mesh, name=args.sim_name)
# sim.driver.set_tols(rtol=1e-10, atol=1e-14)
sim.driver.alpha = args.alpha
# sim.driver.gamma = 2.211e5
if args.no_precession:
sim.do_precession = False
# Material parameters -----------------------------------------------------
sim.Ms = args.Ms
exch = UniformExchange(A=args.A)
sim.add(exch)
dmi = DMI(D=(args.D * 1e-3), type='interfacial')
sim.add(dmi)
if args.B:
zeeman = Zeeman((0, 0, args.B / mu0))
sim.add(zeeman, save_field=True)
if args.k_u:
# Uniaxial anisotropy along + z-axis
sim.add(UniaxialAnisotropy(args.k_u, axis=(0, 0, 1)))
if args.Demag:
print 'Using Demag!'
sim.add(Demag())
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 = """
return [list [expr {sin($x*1e9)+$y*1e9+$z*2.3e9}] [expr {cos($x*1e9)+$y*1e9+$z*1.3e9}] 0]
"""
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
exch = UniformExchange(A=A)
sim.add(exch)
demag = Demag()
sim.add(demag)
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()
#field_oommf = compute_exch_field(mesh, init_m0=init_m0, A=A, spatial_Ms=init_Ms)
omf_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),'omfs','test_with_oommf_spatial_Ms_Exchange.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
field = demag.compute_field()
#field_oommf = compute_demag_field(mesh, spatial_Ms=init_Ms, init_m0=init_m0)
omf_file = os.path.join(os.path.dirname(os.path.abspath(__file__)),'omfs','test_with_oommf_spatial_Ms_Demag.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-11
