def test_thin_film_demag_against_real_demag():
sim = Sim(
df.BoxMesh(df.Point(0, 0, 0), df.Point(500e-9, 500e-9, 1e-9), 50, 50,
1), Ms)
sim.set_m((0, 0, 1))
tfdemag = ThinFilmDemag()
sim.add(tfdemag)
H_tfdemag = tfdemag.compute_field().view().reshape((3, -1)).mean(1)
demag = Demag()
sim.add(demag)
H_demag = demag.compute_field().view().reshape((3, -1)).mean(1)
diff = np.abs(H_tfdemag - H_demag) / Ms
print "Standard Demag:\n", H_demag
print "ThinFilmDemag:\n", H_tfdemag
print "Difference relative to Ms:\n", diff
assert np.allclose(H_tfdemag, H_demag, atol=0.05 * Ms) # 5% of Ms
sim.set_m((1, 0, 0))
H_tfdemag = tfdemag.compute_field().view().reshape((3, -1)).mean(1)
H_demag = demag.compute_field().view().reshape((3, -1)).mean(1)
print "Running again, changed m in the meantime."
diff = np.abs(H_tfdemag - H_demag) / Ms
print "Standard Demag:\n", H_demag
print "ThinFilmDemag:\n", H_tfdemag
print "Difference relative to Ms:\n", diff
assert np.allclose(H_tfdemag, H_demag, atol=0.005 * Ms) # 0.5% of Ms
def run_demag(repetitions, params, m, Ms, unit_length, bem=None, b2g_map=None):
demag = Demag("FK")
demag.parameters["phi_1_solver"] = params[0]
demag.parameters["phi_1_preconditioner"] = params[1]
demag.parameters["phi_2_solver"] = params[2]
demag.parameters["phi_2_preconditioner"] = params[3]
if bem is not None:
demag.precomputed_bem(bem, b2g_map)
demag.setup(m, Ms, unit_length)
start = now()
for j in xrange(repetitions):
H = demag.compute_field()
runtime = (now() - start) / repetitions
return H, runtime
def relax_system():
Ms = 8.6e5
sim = Simulation(mesh, Ms, unit_length=1e-9, name='dy', pbc='1d')
sim.alpha = 0.01
sim.set_m((0.8, 0.6, 1))
sim.set_tol(1e-8, 1e-8)
A = 1.3e-11
sim.add(Exchange(A))
parameters = {
'absolute_tolerance': 1e-10,
'relative_tolerance': 1e-10,
'maximum_iterations': int(1e5)
}
Ts = []
for i in range(-9, 10):
Ts.append((10 * i, 0, 0))
demag = Demag(solver='Treecode')
demag.parameters['phi_1'] = parameters
demag.parameters['phi_2'] = parameters
sim.add(demag)
demag.compute_field()
sim.schedule('save_ndt', every=2e-12)
#sim.schedule('save_vtk', every=2e-12, filename='vtks/m.pvd')
#sim.schedule('save_m', every=2e-12, filename='npys/m.pvd')
sim.run_until(0.2e-9)
def setup_finmag():
mesh = from_geofile(os.path.join(MODULE_DIR, "sphere.geo"))
S3 = df.VectorFunctionSpace(mesh, "Lagrange", 1)
m = Field(S3)
m.set(df.Constant((1, 0, 0)))
Ms = 1
demag = Demag()
demag.setup(m,
Field(df.FunctionSpace(mesh, 'DG', 0), Ms),
unit_length=1e-9)
H = demag.compute_field()
return dict(m=m, H=H, Ms=Ms, S3=S3, table=start_table())
def uniformly_magnetised_sphere():
Ms = 1
mesh = sphere(r=1, maxh=0.25)
S3 = df.VectorFunctionSpace(mesh, "CG", 1)
m = Field(S3)
m.set(df.Constant((1, 0, 0)))
solutions = []
for solver in solvers:
demag = Demag(solver)
demag.setup(m,
Field(df.FunctionSpace(mesh, 'DG', 0), Ms),
unit_length=1e-9)
demag.H = demag.compute_field()
solutions.append(demag)
return solutions
def test_field():
"""
Test the demag field.
H_demag should be equal to -1/3 M, and with m = (1, 0 ,0)
and Ms = 1,this should give H_demag = (-1/3, 0, 0).
"""
# Using mesh with radius 10 nm (nmag ex. 1)
mesh = from_geofile(os.path.join(MODULE_DIR, "sphere1.geo"))
S3 = df.VectorFunctionSpace(mesh, "Lagrange", 1)
m_function = df.interpolate(df.Constant((1, 0, 0)), S3)
m = Field(S3, m_function)
demag = Demag()
demag.setup(m,
Field(df.FunctionSpace(mesh, 'DG', 0), Ms),
unit_length=1e-9)
# Compute demag field
H_demag = demag.compute_field()
H_demag.shape = (3, -1)
x, y, z = H_demag[0], H_demag[1], H_demag[2]
print "Max values in direction:"
print "x: %g, y: %g, z: %g" % (max(x), max(y), max(z))
print "Min values in direction:"
print "x: %g, y: %g, z: %g" % (min(x), min(y), min(z))
x, y, z = average(x), average(y), average(z)
print "Average values in direction"
print "x: %g, y: %g, z: %g" % (x, y, z)
# Compute relative erros
x = abs((x + 1. / 3 * Ms) / Ms)
y = abs(y / Ms)
z = abs(z / Ms)
print "Relative error:"
print "x: %g, y: %g, z: %g" % (x, y, z)
assert x < TOL, "x-average is %g, should be -1/3." % x
assert y < TOL, "y-average is %g, should be zero." % y
assert z < TOL, "z-average is %g, should be zero." % z
def run_benchmark(solver):
radius = 10.0
maxh = 0.5
unit_length = 1e-9
mesh = sphere(r=radius, maxh=maxh, directory="meshes")
S3 = df.VectorFunctionSpace(mesh, "Lagrange", 1)
Ms = 1
m_0 = (1, 0, 0)
m = df.Function(S3)
m.assign(df.Constant(m_0))
H_ref = np.array((-Ms / 3.0, 0, 0))
if solver == "krylov":
parameters = {}
parameters["phi_1_solver"] = "default"
parameters["phi_1_preconditioner"] = "default"
parameters["phi_2_solver"] = "default"
parameters["phi_2_preconditioner"] = "default"
demag = Demag("FK", solver_type="Krylov", parameters=parameters)
elif solver == "lu":
demag = Demag("FK", solver_type="LU")
else:
import sys
print "Unknown solver {}.".format(solver)
sys.exit(1)
demag.setup(S3, m, Ms, unit_length)
REPETITIONS = 10
start = time.time()
for j in xrange(REPETITIONS):
H = demag.compute_field()
elapsed = (time.time() - start) / REPETITIONS
H = H.reshape((3, -1))
spread = abs(H[0].max() - H[0].min())
error = abs(H.mean(axis=1)[0] - H_ref[0]) / abs(H_ref[0])
print elapsed, error, spread
if solver == "FK":
if i == 0:
demag.parameters["phi_1_solver"] = "default"
demag.parameters["phi_1_preconditioner"] = "default"
demag.parameters["phi_2_solver"] = "default"
demag.parameters["phi_2_preconditioner"] = "default"
if i == 1:
demag.parameters["phi_1_solver"] = "cg"
demag.parameters["phi_1_preconditioner"] = "ilu"
demag.parameters["phi_2_solver"] = "cg"
demag.parameters["phi_2_preconditioner"] = "ilu"
demag.setup(m, Ms, unit_length)
start = time.time()
for j in xrange(10):
H = demag.compute_field()
elapsed = (time.time() - start) / 10.0
H = H.reshape((3, -1)).mean(axis=1)
error = abs(H[0] - H_ref[0]) / abs(H_ref[0])
timings[i].append(elapsed)
errors[i].append(error)
fig = plt.figure()
ax = fig.add_subplot(211)
ax.set_title("Runtime")
for i, solver in enumerate(solvers):
ax.plot(vertices, timings[i], label=solvers_label[i])
ax.legend(loc=2)
ax.set_xlabel("vertices")
ax.set_ylabel("time (s)")
