def __init__(self, mesh, spin, Ms, field, pins,
interactions,
name,
data_saver,
integrator='sundials',
use_jac=False
):
super(MicroDriver, self).__init__()
# These are (ideally) references to arrays taken from the Simulation
# class. Variables with underscore are arrays changed by a property in
# the simulation class
self.mesh = mesh
self.spin = spin
self._Ms = Ms
# Only for LLG STT: (??)
self.Ms_const = 0
self.field = field
self._pins = pins
self.interactions = interactions
# Strings are not referenced, this is a copy:
self.name = name
# The following are proper of the driver class: (see DriverBase) ------
# See also the set_default_options() function
self.n = self.mesh.n
self.n_nonzero = self.mesh.n # number of spins that are not zero
# We check this in the set_Ms function
self.initiate_variables(self.n)
self.set_default_options()
# Integrator options --------------------------------------------------
# Here we set up the CVODE integrator from Sundials to evolve a
# specific micromagnetic equation. The equations are specified in the
# sundials_rhs function from any of the micromagnetic drivers in the
# micromagnetic folder (LLG, LLG_STT, etc.)
if integrator == "sundials" and use_jac:
self.integrator = CvodeSolver(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag":
self.integrator = CvodeSolver(self.spin, self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials":
self.integrator = CvodeSolver(self.spin, self.sundials_rhs)
elif integrator == "euler" or integrator == "rk4":
self.integrator = CvodeSolver(self.spin, self.step_rhs,
integrator)
elif integrator == "sundials_openmp" and use_jac:
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs)
elif integrator == "euler_openmp" or integrator == "rk4_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.step_rhs,
integrator)
else:
raise NotImplemented("integrator must be sundials, euler or rk4")
# Savers --------------------------------------------------------------
# VTK saver for the magnetisation/spin field
self.VTK = VTK(self.mesh,
directory='{}_vtks'.format(self.name),
filename='m'
)
# Initialise the table for the data file with the simulation
# information:
self.data_saver = data_saver
# This should not be necessary:
# self.data_saver.entities['skx_num'] = {
# 'unit': '<>',
# 'get': lambda sim: sim.skyrmion_number(),
# 'header': 'skx_num'}
self.data_saver.entities['rhs_evals'] = {
'unit': '<>',
'get': lambda sim: self.integrator.rhs_evals(),
'header': 'rhs_evals'}
self.data_saver.entities['real_time'] = {
'unit': '<s>',
'get': lambda _: time.time(), # seconds since epoch
'header': 'real_time'}
self.data_saver.update_entity_order()
# ---------------------------------------------------------------------
# OOMMF convention is to check if the spins have moved by ~1 degree in
# a nanosecond in order to stop a simulation, so we set this scale for
# dm/dt
# ONE_DEGREE_PER_NANOSECOND:
self._dmdt_factor = (2 * np.pi / 360) / 1e-9
def set_integrator(self, integrator, use_jac):
# Integrator options --------------------------------------------------
# Here we set up the CVODE integrator from Sundials to evolve a
# specific micromagnetic equation. The equations are specified in the
# sundials_rhs function from any of the micromagnetic drivers in the
# micromagnetic folder (LLG, LLG_STT, etc.)
if integrator == "sundials" and use_jac:
self.integrator = CvodeSolver(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag":
self.integrator = CvodeSolver(self.spin,
self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials":
self.integrator = CvodeSolver(self.spin, self.sundials_rhs)
elif integrator == "euler" or integrator == "rk4":
self.integrator = StepIntegrator(self.spin, self.step_rhs)
elif integrator == "scipy":
self.integrator = ScipyIntegrator(self.spin, self.step_rhs)
elif integrator == "sundials_openmp" and use_jac:
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin,
self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs)
elif integrator == "euler_openmp" or integrator == "rk4_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.step_rhs,
integrator)
else:
raise NotImplemented("integrator must be sundials, euler or rk4")
class MicroDriver(DriverBase):
"""
A class with shared methods and properties for different drivers to solve
the Landau-Lifshitz-Gilbert equation
Variables that are proper of the driver class:
* alpha (damping)
* Ms_const
* t
* spin_last
* dm_dt
* integrator_tolerances_set
* step
* n (from mesh)
* n_nonzero (from mesh and set_Ms method in Simulation)
* gamma
* do_precession
* default_c (correction factor to keep the magnetisation normalised
during the LLG equation integration. See the
fidimag/atomistic/lib/llg.c file for more details)
TODO: Check default_c units in the micromagnetic
context
From DriverBase: t, spin_last, dm_dt, integrator_tolerances_set, step
"""
def __init__(self, mesh, spin, Ms, field, pins,
interactions,
name,
data_saver,
integrator='sundials',
use_jac=False
):
super(MicroDriver, self).__init__()
# These are (ideally) references to arrays taken from the Simulation
# class. Variables with underscore are arrays changed by a property in
# the simulation class
self.mesh = mesh
self.spin = spin
self._Ms = Ms
# Only for LLG STT: (??)
self.Ms_const = 0
self.field = field
self._pins = pins
self.interactions = interactions
# Strings are not referenced, this is a copy:
self.name = name
# The following are proper of the driver class: (see DriverBase) ------
# See also the set_default_options() function
self.n = self.mesh.n
self.n_nonzero = self.mesh.n # number of spins that are not zero
# We check this in the set_Ms function
self.initiate_variables(self.n)
self.set_default_options()
# Integrator options --------------------------------------------------
# Here we set up the CVODE integrator from Sundials to evolve a
# specific micromagnetic equation. The equations are specified in the
# sundials_rhs function from any of the micromagnetic drivers in the
# micromagnetic folder (LLG, LLG_STT, etc.)
if integrator == "sundials" and use_jac:
self.integrator = CvodeSolver(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag":
self.integrator = CvodeSolver(self.spin, self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials":
self.integrator = CvodeSolver(self.spin, self.sundials_rhs)
elif integrator == "euler" or integrator == "rk4":
self.integrator = CvodeSolver(self.spin, self.step_rhs,
integrator)
elif integrator == "sundials_openmp" and use_jac:
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs)
elif integrator == "euler_openmp" or integrator == "rk4_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.step_rhs,
integrator)
else:
raise NotImplemented("integrator must be sundials, euler or rk4")
# Savers --------------------------------------------------------------
# VTK saver for the magnetisation/spin field
self.VTK = VTK(self.mesh,
directory='{}_vtks'.format(self.name),
filename='m'
)
# Initialise the table for the data file with the simulation
# information:
self.data_saver = data_saver
# This should not be necessary:
# self.data_saver.entities['skx_num'] = {
# 'unit': '<>',
# 'get': lambda sim: sim.skyrmion_number(),
# 'header': 'skx_num'}
self.data_saver.entities['rhs_evals'] = {
'unit': '<>',
'get': lambda sim: self.integrator.rhs_evals(),
'header': 'rhs_evals'}
self.data_saver.entities['real_time'] = {
'unit': '<s>',
'get': lambda _: time.time(), # seconds since epoch
'header': 'real_time'}
self.data_saver.update_entity_order()
# ---------------------------------------------------------------------
# OOMMF convention is to check if the spins have moved by ~1 degree in
# a nanosecond in order to stop a simulation, so we set this scale for
# dm/dt
# ONE_DEGREE_PER_NANOSECOND:
self._dmdt_factor = (2 * np.pi / 360) / 1e-9
def set_default_options(self, gamma=2.21e5, Ms=8.0e5, alpha=0.1):
"""
Default option for the integrator
Default gamma is for a free electron
"""
self.default_c = 1e11
self._alpha[:] = alpha
# When we create the simulation, Ms is set to the default value. This
# is overriden when calling the set_Ms method from the Siulation class
# or when setting Ms directly (property)
self._Ms[:] = Ms
self.gamma = gamma
self.do_precession = True
def sundials_rhs(self, t, y, ydot):
"""
Defined in the corresponding driver class
"""
pass
def set_tols(self, rtol=1e-8, atol=1e-10, max_ord=None, reset=True):
"""
Set the relative and absolute tolerances for the CVODE integrator
"""
if max_ord is not None:
self.integrator.set_options(rtol=rtol, atol=atol, max_ord=max_ord)
else:
# not all integrators have max_ord (only VODE does)
# and we don't want to encode a default value here either
self.integrator.set_options(rtol=rtol, atol=atol)
if reset:
self.reset_integrator(self.t)
# -------------------------------------------------------------------------
# Save functions ----------------------------------------------------------
# -------------------------------------------------------------------------
def save_vtk(self):
"""
Save a VTK file with the magnetisation vector field (vector data)
and the saturation magnetisation values (scalar data) as
cell data
"""
self.VTK.reset_data()
# Here we save both Ms and spins as cell data
self.VTK.save_scalar(self._Ms, name='mu_s')
self.VTK.save_vector(self.spin.reshape(-1, 3), name='spins')
self.VTK.write_file(step=self.step)
class DriverBase(object):
"""
Common methods for the micromagnetic and atomistic driver classes
"""
def __init__(self):
pass
# -------------------------------------------------------------------------
def initiate_variables(self, n_spins):
"""
Common variables for both micro and atomistic drivers
"""
self._alpha = np.zeros(n_spins, dtype=np.float)
self.t = 0
self.spin_last = np.ones(3 * n_spins, dtype=np.float)
self.dm_dt = np.zeros(3 * n_spins, dtype=np.float)
self.integrator_tolerances_set = False
self.step = 0
def get_alpha(self):
"""
Returns the array with the spatially dependent Gilbert damping
per mesh/lattice site
"""
return self._alpha
def set_alpha(self, value):
"""
Set the Gilbert damping of the system as a uniform or spatially
dependent scalar field
ARGUMENTS:
value :: * For a uniform damping across the whole sample, just
specify a float ranging from 0 to 1
* In addition, you can specify a function that returns
values ranging from 0 to 1, which depends on the spatial
coordinates. For example, a damping that increases
linearly in the x direction:
def alpha_profile(r):
for r[0] <= 10:
return r[0] / 10.
else:
return 0
* You can also manually specify an array with n values
ranging from 0 to 1 with the damping values, in the same
order than the mesh coordinates array.
* Alternatively, if you previously saved the damping
field array to a numpy file, you can load it using
numpy.load(my_array)
"""
self._alpha[:] = helper.init_scalar(value, self.mesh)
alpha = property(get_alpha, set_alpha)
def set_integrator(self, integrator, use_jac):
# Integrator options --------------------------------------------------
# Here we set up the CVODE integrator from Sundials to evolve a
# specific micromagnetic equation. The equations are specified in the
# sundials_rhs function from any of the micromagnetic drivers in the
# micromagnetic folder (LLG, LLG_STT, etc.)
if integrator == "sundials" and use_jac:
self.integrator = CvodeSolver(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag":
self.integrator = CvodeSolver(self.spin,
self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials":
self.integrator = CvodeSolver(self.spin, self.sundials_rhs)
elif integrator == "euler" or integrator == "rk4":
self.integrator = StepIntegrator(self.spin, self.step_rhs)
elif integrator == "scipy":
self.integrator = ScipyIntegrator(self.spin, self.step_rhs)
elif integrator == "sundials_openmp" and use_jac:
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs,
self.sundials_jtimes)
elif integrator == "sundials_diag_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin,
self.sundials_rhs,
linear_solver="diag")
elif integrator == "sundials_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.sundials_rhs)
elif integrator == "euler_openmp" or integrator == "rk4_openmp":
self.integrator = CvodeSolver_OpenMP(self.spin, self.step_rhs,
integrator)
else:
raise NotImplemented("integrator must be sundials, euler or rk4")
# ------------------------------------------------------------------------
def stat(self):
return self.integrator.stat()
def set_default_options(self):
pass
def reset_integrator(self, t=0):
"""
Reset the CVODE integrator and set the simulation time to `t`
The simulation step is reset to zero
"""
self.integrator.reset(self.spin, t)
self.t = t # also reinitialise the simulation time and step
self.step = 0
def set_tols(self, rtol=1e-8, atol=1e-10):
"""
Set the relative and absolute tolerances for the CVODE integrator
"""
self.integrator.set_options(rtol, atol)
def compute_effective_field(self, t):
"""
Compute the effective field from the simulation interactions,
calling the method from the corresponding Energy class
"""
# self.spin[:] = y[:]
self.field[:] = 0
for obj in self.interactions:
self.field += obj.compute_field(t)
def compute_effective_field_jac(self, t, spin):
self.field[:] = 0
for obj in self.interactions:
if obj.jac:
self.field += obj.compute_field(t, spin=spin)
def compute_dmdt(self, dt):
m0 = self.spin_last
m1 = self.spin
dm = (m1 - m0).reshape((3, -1))
max_dm = np.max(np.sqrt(np.sum(dm**2, axis=0)))
max_dmdt = max_dm / dt
return max_dmdt
def run_until(self, t):
"""
Evolve the system with a micromagnetic driver (LLG, LLG_STT, etc.)
until a specific time `t`, using the specified integrator.
The integrator was specified with the right hand side of the
driver equation
"""
if t <= self.t:
if t == self.t and self.t == 0.0:
self.compute_effective_field(t)
self.data_saver.save()
return
else:
raise ValueError("t must be >= sim.t")
ode = self.integrator
self.spin_last[:] = self.spin[:]
flag = ode.run_until(t)
if flag < 0:
raise Exception("Run cython run_until failed!!!")
self.spin[:] = ode.y[:]
self.t = t
self.step += 1
# Update field before saving data
self.compute_effective_field(t)
self.data_saver.save()
def relax(self,
dt=10e-12,
stopping_dmdt=0.01,
max_steps=1000,
save_m_steps=100,
save_vtk_steps=100):
"""
Evolve the system until meeting the `dmdt` < `stopping_dmdt` criteria.
The magnetisation dynamics will be checked a maximum of `max_steps`
times at an interval of at least `dt` and compared to `stopping_dmdt`
which is given in units of degrees per nanosecond.
With `save_m_steps` and `save_vtk_steps` the magnetisation will be
saved every given number of integrator steps to npy resp. vtk files.
"""
while self.step < max_steps:
_dt = max(dt, self.integrator.get_current_step())
self.run_until(self.t + _dt)
# Explanation: For very small integrator steps, there is no use in
# checking for relaxation at every step and `dt` will provide the lower
# boundary of what is acceptable (every 10 picoseconds per default).
# On the other hand, when the integrator steps get larger than `dt`
# we might as well let the integrator do its work uninterrupted.
if (save_vtk_steps is not None) and (self.step % save_vtk_steps
== 0):
self.save_vtk()
if (save_m_steps is not None) and (self.step % save_m_steps == 0):
self.save_m()
dmdt = self.compute_dmdt(_dt)
print("#{:<4} t={:<8.3g} dt={:.3g} max_dmdt={:.3g}".format(
self.step, # incremented in self.run_until (called above)
self.t,
_dt,
dmdt / self._dmdt_factor))
if dmdt < stopping_dmdt * self._dmdt_factor:
break
if save_m_steps is not None:
self.save_m()
if save_vtk_steps is not None:
self.save_vtk()
# -------------------------------------------------------------------------
# Save functions ----------------------------------------------------------
# -------------------------------------------------------------------------
def save_vtk(self):
pass
def save_m(self, ZIP=False):
"""
Save the magnetisation/spin vector field as a numpy array in
a NPY file. The files are saved in the `{name}_npys` folder, where
`{name}` is the simulation name, with the file name `m_{step}.npy`
where `{step}` is the simulation step (from the integrator)
"""
if not os.path.exists('%s_npys' % self.name):
os.makedirs('%s_npys' % self.name)
name = '%s_npys/m_%g.npy' % (self.name, self.step)
np.save(name, self.spin)
if ZIP:
with zipfile.ZipFile('%s_m.zip' % self.name, 'a') as myzip:
myzip.write(name)
try:
os.remove(name)
except OSError:
pass
def save_skx(self):
"""
Save the skyrmion number density (sk number per mesh site)
as a numpy array in a NPY file.
The files are saved in the `{name}_skx_npys` folder, where
`{name}` is the simulation name, with the file name `skx_{step}.npy`
where `{step}` is the simulation step (from the integrator)
"""
if not os.path.exists('%s_skx_npys' % self.name):
os.makedirs('%s_skx_npys' % self.name)
name = '%s_skx_npys/m_%g.npy' % (self.name, self.step)
# The _skx_number array is defined in the SimBase class in Common
np.save(name, self._skx_number)
