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 = 0.1
sim.set_m((0, 0, 1))
sim.add(Zeeman((0, 0, 1e5)))
w0 = 2 * np.pi * 1e9
def sin_fun(t):
return np.sin(w0 * t)
h0 = 1e3
theta = np.pi / 20
hx = h0 * np.sin(theta)
hz = h0 * np.cos(theta)
hx = TimeZeeman([hx, 0, hz], sin_fun, name='h')
sim.add(hx, save_field=True)
ts = np.linspace(0, 5e-9, 5001)
for t in ts:
sim.run_until(t)
def relax_system():
mesh = CuboidMesh(nx=1, ny=1, nz=1)
sim = Sim(mesh, name='relax')
sim.set_tols(rtol=1e-10, atol=1e-10)
sim.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)
for t in ts:
print 'time', t
sim.run_until(t)
sim.save_vtk()
sim.save_m()
if __name__ == '__main__':
# We will crate a mesh with 1000 elements of elements
# in the x direction, and 1 along y and z
# (so we have a 1D system)
mesh = CuboidMesh(nx=1000,
ny=1,
nz=1,
dx=2,
dy=2,
dz=2.0,
unit_length=1e-9)
# Relax the initial state
relax_system(mesh)
deal_plot([['m0.npy', 'mx']], 'initial_state.pdf')
# Now we excite the system with the current
excite_system(mesh)
# Plot the dynamics of a single spin
# deal_plot_dynamics()
# We can plot the m_z component for a number snapshots
# 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=1e-2, max_steps=5000,
save_m_steps=None, save_vtk_steps=50)
np.save('m0.npy', sim.spin)
if __name__ == '__main__':
mesh = CuboidMesh(
nx=501, ny=501, nz=1, dx=2.0, dy=2.0, dz=2.0, unit_length=1e-9, periodicity=(True, True, False))
relax_system(mesh)
# apply_field1(mesh)
# deal_plot()
plt.plot(ts, mx, '--', label='m_fidimag', dashes=(2, 2))
plt.plot(ts, my, '--', label='', dashes=(2, 2))
plt.plot(ts, mz, '--', label='', dashes=(2, 2))
plt.plot(ts2, mx2, '--', label='m_oommf')
plt.plot(ts2, my2, '--', label='')
plt.plot(ts2, mz2, '--', label='')
plt.title('std4')
plt.legend()
#plt.xlim([0, 0.012])
#plt.ylim([-5, 100])
plt.xlabel(r'Ts (ns)')
# plt.ylabel('Susceptibility')
plt.savefig('cmp.pdf')
if __name__ == '__main__':
mesh = CuboidMesh(nx=200,
ny=50,
nz=1,
dx=2.5,
dy=2.5,
dz=3,
unit_length=1e-9)
relax_system(mesh)
apply_field1(mesh)
deal_plot()
def test_prb88_184422():
mu0 = 4 * np.pi * 1e-7
Ms = 8.6e5
A = 16e-12
D = 3.6e-3
K = 510e3
mesh = CuboidMesh(nx=100, dx=1, unit_length=1e-9)
sim = Sim(mesh)
sim.driver.set_tols(rtol=1e-10, atol=1e-14)
sim.driver.alpha = 0.5
sim.driver.gamma = 2.211e5
sim.Ms = Ms
sim.do_precession = False
sim.set_m((0, 0, 1))
sim.add(UniformExchange(A=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
mx, my, mz = np.split(m, 3)
x_array = np.linspace(-49.5, 49.5, 100)
#plt.plot(x_array, mx)
#plt.plot(x_array, my)
#plt.plot(x_array, mz)
mesh = df.IntervalMesh(100, -50, 50)
Delta = np.sqrt(A / K)
xi = 2 * A / D
Delta_s = Delta * 1e9
V = df.FunctionSpace(mesh, "Lagrange", 1)
u = df.TrialFunction(V)
v = df.TestFunction(V)
u_ = df.Function(V)
F = -df.inner(df.nabla_grad(u), df.nabla_grad(v)) * df.dx - \
(0.5 / Delta_s**2) * df.sin(2 * u) * v * df.dx
F = df.action(F, u_)
J = df.derivative(F, u_, u)
# the boundary condition is from equation (8)
theta0 = np.arcsin(Delta / xi)
ss = 'x[0]<0? %g: %g ' % (-theta0, theta0)
u0 = df.Expression(ss)
def u0_boundary(x, on_boundary):
return on_boundary
bc = df.DirichletBC(V, u0, u0_boundary)
problem = df.NonlinearVariationalProblem(F, u_, bcs=bc, J=J)
solver = df.NonlinearVariationalSolver(problem)
solver.solve()
u_array = u_.vector().array()
mx_df = []
for x in x_array:
mx_df.append(u_(x))
#plt.plot(x_array, mx_df)
assert abs(np.max(mx - mx_df)) < 0.05
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=1e-2,
max_steps=5000,
save_m_steps=None,
save_vtk_steps=50)
np.save('m0.npy', sim.spin)
if __name__ == '__main__':
mesh = CuboidMesh(nx=501,
ny=501,
nz=1,
dx=2.0,
dy=2.0,
dz=2.0,
unit_length=1e-9,
pbc='xy')
relax_system(mesh)
# apply_field1(mesh)
# deal_plot()
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()
if __name__ == '__main__':
mesh = CuboidMesh(nx=80,
ny=80,
nz=2,
dx=2.5,
dy=2.5,
dz=5.0,
unit_length=1e-9)
# relax_system(mesh)
excite_system(mesh)
# apply_field1(mesh)
# deal_plot()
import matplotlib as mpl
mpl.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
from micro import Sim
from common import CuboidMesh
from micro import Zeeman
from fidimag.common.fileio import DataReader
from util.omf import OMF2
mesh = CuboidMesh(nx=100, dx=1, unit_length=1e-9)
def plot_all():
font = {'family': 'serif',
'weight': 'normal',
'size': 12,
}
plt.rc('font', **font)
Ms = 8.6e5
omf = OMF2('oommf/dmi-Oxs_TimeDriver-Magnetization-00-0000963.omf')
mx = omf.get_all_mag(comp='x') / Ms
my = omf.get_all_mag(comp='y') / Ms
mz = omf.get_all_mag(comp='z') / Ms
xs = np.linspace(0.5, 100 - 0.5, 100)
"""
n=20
for i in range(1,n):
theta = i*np.pi/n
mx = -np.cos(theta)
my = np.sin(theta)
init_images.append((mx,my,0))
"""
# init_images.append(np.load('m_final.npy'))
init_images = [(-1, 0, 0), init_dw, (1, 0, 0)]
neb = NEB_Sundials(
sim, init_images, interpolations=[6, 6], name='neb', spring=1e8)
# neb.add_noise(0.1)
neb.relax(dt=1e-8, max_steps=5000, save_vtk_steps=500,
save_npy_steps=500, stopping_dmdt=100)
if __name__ == "__main__":
mesh = CuboidMesh(nx=160, ny=1, nz=1, dx=4.0, dy=4.0, dz=4.0, unit_length=1e-9)
sim = create_simulation(mesh)
# relax_two_state(mesh)
relax_system(sim)
plot_energy_2d('neb')
plot_energy_3d('neb')