if dof_name == "m_Fe2":
return m
else:
return [-mi for mi in m]
H_direction = [0.0, 0.0, 1.0] # The direction of the applied field
# The list of values taken by the norm of the applied field
H_norms = [0.05, 0.1, [], 1.0, 1.1, [], 2.0, 2.2, [],
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [], 5.0]
# Selected norms for the second part of the simulation
H_norms = [0]
selected_H_norms = [0.5, 1.0, 1.5, 2.0, 3.0, 3.2, [], 5.0]
selected_H_norms = [0]
H_scale = 1
H_norms = sets.float_set(H_norms, H_scale)
selected_H_norms = sets.float_set(selected_H_norms, H_scale)
H_unit = T/mu0 # The unit for these values is T (Tesla)
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=H_direction,
norm_list=H_norms)
# A small deviation to avoid points of unstable equilibrium
H_dev = [0.0001, 0.0001, 0.0001]
new_Hs = []
for H in Hs:
new_Hs.append([Hi+H_devi for Hi, H_devi in zip(H, H_dev)])
new_Hs.append(H)
def m0_Dy(r):
return directions['m_Dy']
def m0_Fe(r):
return directions['m_Fe2']
#--------------------------------------------
B_direction = [0.0, 0.0, -1.0] # The direction of the applied field
#The list of values taken by the norm of the applied field
B_unit = Tesla # The unit for these values
B_norms = \
sets.float_set([0.0, 0.1, [], 2.0, 2.25, [],
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [],
5.0, 5.5, [], 12.0])
selected_B_norms = \
sets.float_set([0.0, 0.5, [], 3.5, 3.8, 3.9, 4.0, 4.1, 4.5, 5.0, [], 12.0])
delta_B = [0.002, 0.002, 0.002] # Tilt vector in T
#tilted_B_norms = [B_norm + delta_B for B_norm in B_norms]
#selected_B_norms = [B_norm + delta_B for B_norm in selected_B_norms]
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = []
delta_H = [dBi*B_unit/mu0 for dBi in delta_B]
for H in sets.vector_set(direction=B_direction,
norm_list=B_norms,
This file generates the meshes geometries (netgen) for the 2nd mumag
standard problem.
All distances here are measured in nanometers.
"""
import material
from nmag import simulation_units as su
from nmag import SI
import nsim.sets as sets
# This is the list of values for d/l_ex.
# For each of these value a mesh geometry specification file .geo
# will be generated. This file can be used with netgen to obtain
# the meshes. Unfortunately it seems one has to do it manually
# Then use 'make convert' to pass from neu to h5 mesh file format.
d_list = sets.float_set([5, 10, "...", 30]) # values of d/lex
def create_mesh(d, file_name, rod=None):
L, d, t = material.bar_size(d)
if rod == None:
rod = t
else:
rod = min(rod, t)
s = "algebraic3d\nsolid cube = plane (0, 0, 0; 0, 0, -1)\n"
s += " and plane (0, 0, 0; 0, -1, 0)\n and plane (0, 0, 0; -1, 0, 0)\n"
s += " and plane (%f, %f, %f; 0, 0, 1)\n" % (L, d, t)
s += " and plane (%f, %f, %f; 0, 1, 0)\n" % (L, d, t)
s += " and plane (%f, %f, %f; 1, 0, 0) -maxh = %f;\ntlo cube;\n" % (L, d, t, rod)
f = open(file_name, "w")
f.write(s)
f.close()
if header and os.path.exists(file): return
f = open(file, "a")
f.write(line)
f.close()
out("# d/l_ex Hc/Ms Mr_x/Ms Mr_y/Ms\n", header=True)
args = []
if len(sys.argv) > 1:
# We take only arguments which do not contain '-'
# (just to avoid considering '-ldebug' and other options)
for arg in sys.argv[1:]:
if not('-' in arg): args.append(arg)
if len(args) != 0:
d_list = sets.float_set(args)
else:
d_list = sets.float_set([5]) #, 6, "...", 10])
for d in d_list:
mesh_file, mesh_unit = meshes.better_mesh(d)
r = mumag2_simulation(mesh_file, mesh_unit*SI(1e-9, "m"), Hs, m0)
#ocaml.sys_check_heap()
out("# d=%f, mesh='%s', scaling=%f\n" % (d, mesh_file, mesh_unit))
out("%f %f %f %f\n" % (d, r["hc"], r["mrx"], r["mry"]))
m_out = open("m_d%03.0f.dat" % d, "w")
for h_par, m_par, (mx, my, mz), t in zip(r["h_pars"], r["m_pars"], r["ms"], r["ts"]):
m_out.write("%g %g %g %g %g %g\n" % (h_par, m_par, mx, my, mz, t))
m_out.close()
return directions['m_Fe3O4']
def m0_CoFe2O4(r):
return directions['m_CoFe2O4']
# The direction of the applied field
B_direction = [0.0, 1.0, 0.0]
#The list of values taken by the norm of the applied field
B_norms = [-5.0, -4.9, [], 5.0]
B_unit = Tesla # The unit for these values
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=B_direction,
norm_list=sets.float_set(B_norms),
units=B_unit/mu0) # remember that H = B/mu0
# A small deviation to avoid points of unstable equilibrium
H_dev = [SI(0.005e6, "A/m")]*3
Hs = [[Hi+H_devi for Hi, H_devi in zip(H, H_dev)]
for H in Hs]
#--------------------------------------------
## Here we set up the simulation
# Create the simulation object
sim = nmag.Simulation("run", do_demag=False, adjust_tolerances=False)
# Set the coupling between the two magnetisations
Fe3O4_CoFe2O4_lc = Fe3O4_CoFe2O4_sup_lc*mesh_unit*discretization
directions = {'m_Dy':[0,1,0], 'm_Fe2':[0,-1,0]}
def m0_Dy(r):
return directions['m_Dy']
def m0_Fe(r):
return directions['m_Fe2']
B_direction = [0.0, 1.0, 0.0] # The direction of the applied field
#The list of values taken by the norm of the applied field
B_norms = [0.1, 0.2, [], 1.0, 1.1, [], 2.0, 2.2, [],
3.8, 3.82, [], 4.2, 4.25, [], 4.5, 4.6, [],
5.0, 5.5, [], 8.0]
selected_B_norms = [3.6, 4.0, 4.2]
B_norms = sets.float_set(B_norms, B_scale)
selected_B_norms = sets.float_set(selected_B_norms, B_scale)
layers = [(scale*left, scale*right) for (left, right) in layers]
B_unit = Tesla # The unit for these values
delta_B = 0.0*Tesla
# From the norms and the direction (which is constant) we derive
# all the values that the applied field will take during the simulation
Hs = sets.vector_set(direction=B_direction,
norm_list=B_norms,
units=B_unit/mu0) # remember that H = B/mu0
# A small deviation to avoid points of unstable equilibrium
H_dev = [SI(0.005e6, "A/m"), 0, SI(0.005e6, "A/m")]
