def test_resume_withscaling(self):
_test_recursion_cache(
self, lambda: map(
types.frozenarray,
solver.impliciteuler('dofs',
residual=self.residual,
inertia=self.inertia,
lhs0=self.lhs0,
timestep=100)))
def test_iters(self):
it = iter(
solver.impliciteuler(
'dofs',
residual=self.residual,
inertia=self.inertia,
lhs0=self.lhs0,
timestep=100)) # involves 2-level timestep scaling
assert numpy.equal(next(it), self.lhs0).all()
self.assertAlmostEqual64(
next(it),
'eNpzNBA1NjHuNHQ3FDsTfCbAuNz4nUGZgeyZiDOZxlONmQwU9W3OFJ/pNQAADZIOPA=='
)
def main(
nelems: 'number of elements' = 20,
degree: 'polynomial degree' = 1,
timescale: 'time scale (timestep=timescale/nelems)' = .5,
tol: 'solver tolerance' = 1e-5,
ndims: 'spatial dimension' = 1,
endtime: 'end time, 0 for no end time' = 0,
withplots: 'create plots' = True,
):
# construct mesh, basis
ns = function.Namespace()
domain, ns.x = mesh.rectilinear([numpy.linspace(0, 1, nelems + 1)] * ndims,
periodic=range(ndims))
ns.basis = domain.basis('discont', degree=degree)
ns.u = 'basis_n ?lhs_n'
# construct initial condition (centered gaussian)
lhs0 = domain.project('exp(-?y_i ?y_i) | ?y_i = 5 (x_i - 0.5_i)' @ ns,
onto=ns.basis,
geometry=ns.x,
degree=5)
# prepare residual
ns.f = '.5 u^2'
ns.C = 1
res = domain.integral('-basis_n,0 f' @ ns, geometry=ns.x, degree=5)
res += domain.interfaces.integral(
'-[basis_n] n_0 ({f} - .5 C [u] n_0)' @ ns, geometry=ns.x, degree=5)
inertia = domain.integral('basis_n u' @ ns, geometry=ns.x, degree=5)
# prepare plotting
makeplots = MakePlots(domain, video=withplots
== 'video') if withplots else lambda ns: None
# start time stepping
timestep = timescale / nelems
for itime, lhs in log.enumerate(
'timestep',
solver.impliciteuler('lhs',
res,
inertia,
timestep,
lhs0,
newtontol=tol)):
makeplots(ns | dict(lhs=lhs))
if endtime and itime * timestep >= endtime:
break
return res.eval(arguments=dict(lhs=lhs)), lhs
def main(
nelems: 'number of elements' = 20,
degree: 'polynomial degree' = 1,
timescale: 'time scale (timestep=timescale/nelems)' = .5,
tol: 'solver tolerance' = 1e-5,
ndims: 'spatial dimension' = 1,
endtime: 'end time, 0 for no end time' = 0,
withplots: 'create plots' = True,
):
# construct mesh, basis
ns = function.Namespace()
domain, ns.x = mesh.rectilinear([numpy.linspace(0,1,nelems+1)]*ndims, periodic=range(ndims))
ns.basis = domain.basis('discont', degree=degree)
ns.u = 'basis_n ?lhs_n'
# construct initial condition (centered gaussian)
lhs0 = domain.project('exp(-?y_i ?y_i) | ?y_i = 5 (x_i - 0.5_i)' @ ns, onto=ns.basis, geometry=ns.x, degree=5)
# prepare residual
ns.f = '.5 u^2'
ns.C = 1
res = domain.integral('-basis_n,0 f' @ ns, geometry=ns.x, degree=5)
res += domain.interfaces.integral('-[basis_n] n_0 ({f} - .5 C [u] n_0)' @ ns, geometry=ns.x, degree=5)
inertia = domain.integral('basis_n u' @ ns, geometry=ns.x, degree=5)
# prepare plotting
makeplots = MakePlots(domain, video=withplots=='video') if withplots else lambda ns: None
# start time stepping
timestep = timescale/nelems
for itime, lhs in log.enumerate('timestep', solver.impliciteuler('lhs', res, inertia, timestep, lhs0, newtontol=tol)):
makeplots(ns | dict(lhs=lhs))
if endtime and itime * timestep >= endtime:
break
return res.eval(arguments=dict(lhs=lhs)), lhs
def main(nelems: int, degree: int, reynolds: float, rotation: float,
timestep: float, maxradius: float, seed: int, endtime: float):
'''
Flow around a cylinder.
.. arguments::
nelems [24]
Element size expressed in number of elements along the cylinder wall.
All elements have similar shape with approximately unit aspect ratio,
with elements away from the cylinder wall growing exponentially.
degree [3]
Polynomial degree for velocity space; the pressure space is one degree
less.
reynolds [1000]
Reynolds number, taking the cylinder radius as characteristic length.
rotation [0]
Cylinder rotation speed.
timestep [.04]
Time step
maxradius [25]
Target exterior radius; the actual domain size is subject to integer
multiples of the configured element size.
seed [0]
Random seed for small velocity noise in the intial condition.
endtime [inf]
Stopping time.
'''
elemangle = 2 * numpy.pi / nelems
melems = int(numpy.log(2 * maxradius) / elemangle + .5)
treelog.info('creating {}x{} mesh, outer radius {:.2f}'.format(
melems, nelems, .5 * numpy.exp(elemangle * melems)))
domain, geom = mesh.rectilinear([melems, nelems], periodic=(1, ))
domain = domain.withboundary(inner='left', outer='right')
ns = function.Namespace()
ns.uinf = 1, 0
ns.r = .5 * function.exp(elemangle * geom[0])
ns.Re = reynolds
ns.phi = geom[1] * elemangle # add small angle to break element symmetry
ns.x_i = 'r <cos(phi), sin(phi)>_i'
ns.J = ns.x.grad(geom)
ns.unbasis, ns.utbasis, ns.pbasis = function.chain([ # compatible spaces
domain.basis(
'spline', degree=(degree, degree - 1), removedofs=((0, ), None)),
domain.basis('spline', degree=(degree - 1, degree)),
domain.basis('spline', degree=degree - 1),
]) / function.determinant(ns.J)
ns.ubasis_ni = 'unbasis_n J_i0 + utbasis_n J_i1' # piola transformation
ns.u_i = 'ubasis_ni ?lhs_n'
ns.p = 'pbasis_n ?lhs_n'
ns.sigma_ij = '(u_i,j + u_j,i) / Re - p δ_ij'
ns.h = .5 * elemangle
ns.N = 5 * degree / ns.h
ns.rotation = rotation
ns.uwall_i = '0.5 rotation <-sin(phi), cos(phi)>_i'
inflow = domain.boundary['outer'].select(
-ns.uinf.dotnorm(ns.x),
ischeme='gauss1') # upstream half of the exterior boundary
sqr = inflow.integral('(u_i - uinf_i) (u_i - uinf_i)' @ ns,
degree=degree * 2)
cons = solver.optimize(
'lhs', sqr, droptol=1e-15) # constrain inflow semicircle to uinf
sqr = domain.integral('(u_i - uinf_i) (u_i - uinf_i) + p^2' @ ns,
degree=degree * 2)
lhs0 = solver.optimize('lhs', sqr) # set initial condition to u=uinf, p=0
numpy.random.seed(seed)
lhs0 *= numpy.random.normal(1, .1, lhs0.shape) # add small velocity noise
res = domain.integral(
'(ubasis_ni u_i,j u_j + ubasis_ni,j sigma_ij + pbasis_n u_k,k) d:x'
@ ns,
degree=9)
res += domain.boundary['inner'].integral(
'(N ubasis_ni - (ubasis_ni,j + ubasis_nj,i) n_j) (u_i - uwall_i) d:x / Re'
@ ns,
degree=9)
inertia = domain.integral('ubasis_ni u_i d:x' @ ns, degree=9)
bbox = numpy.array(
[[-2, 46 / 9],
[-2, 2]]) # bounding box for figure based on 16x9 aspect ratio
bezier0 = domain.sample('bezier', 5)
bezier = bezier0.subset((bezier0.eval(
(ns.x - bbox[:, 0]) * (bbox[:, 1] - ns.x)) > 0).all(axis=1))
interpolate = util.tri_interpolator(
bezier.tri, bezier.eval(ns.x),
mergetol=1e-5) # interpolator for quivers
spacing = .05 # initial quiver spacing
xgrd = util.regularize(bbox, spacing)
with treelog.iter.plain(
'timestep',
solver.impliciteuler('lhs',
residual=res,
inertia=inertia,
lhs0=lhs0,
timestep=timestep,
constrain=cons,
newtontol=1e-10)) as steps:
for istep, lhs in enumerate(steps):
t = istep * timestep
x, u, normu, p = bezier.eval(
['x_i', 'u_i', 'sqrt(u_k u_k)', 'p'] @ ns, lhs=lhs)
ugrd = interpolate[xgrd](u)
with export.mplfigure('flow.png', figsize=(12.8, 7.2)) as fig:
ax = fig.add_axes([0, 0, 1, 1],
yticks=[],
xticks=[],
frame_on=False,
xlim=bbox[0],
ylim=bbox[1])
im = ax.tripcolor(x[:, 0],
x[:, 1],
bezier.tri,
p,
shading='gouraud',
cmap='jet')
import matplotlib.collections
ax.add_collection(
matplotlib.collections.LineCollection(x[bezier.hull],
colors='k',
linewidths=.1,
alpha=.5))
ax.quiver(xgrd[:, 0],
xgrd[:, 1],
ugrd[:, 0],
ugrd[:, 1],
angles='xy',
width=1e-3,
headwidth=3e3,
headlength=5e3,
headaxislength=2e3,
zorder=9,
alpha=.5)
ax.plot(0,
0,
'k',
marker=(3, 2, t * rotation * 180 / numpy.pi - 90),
markersize=20)
cax = fig.add_axes([0.9, 0.1, 0.01, 0.8])
cax.tick_params(labelsize='large')
fig.colorbar(im, cax=cax)
if t >= endtime:
break
xgrd = util.regularize(bbox, spacing, xgrd + ugrd * timestep)
return lhs0, lhs
def main(nelems: int, ndims: int, degree: int, timescale: float,
newtontol: float, endtime: float):
'''
Burgers equation on a 1D or 2D periodic domain.
.. arguments::
nelems [20]
Number of elements along a single dimension.
ndims [1]
Number of spatial dimensions.
degree [1]
Polynomial degree for discontinuous basis functions.
timescale [.5]
Fraction of timestep and element size: timestep=timescale/nelems.
newtontol [1e-5]
Newton tolerance.
endtime [inf]
Stopping time.
'''
domain, geom = mesh.rectilinear([numpy.linspace(0, 1, nelems + 1)] * ndims,
periodic=range(ndims))
ns = function.Namespace()
ns.x = geom
ns.basis = domain.basis('discont', degree=degree)
ns.u = 'basis_n ?lhs_n'
ns.f = '.5 u^2'
ns.C = 1
res = domain.integral('-basis_n,0 f d:x' @ ns, degree=5)
res += domain.interfaces.integral(
'-[basis_n] n_0 ({f} - .5 C [u] n_0) d:x' @ ns, degree=degree * 2)
inertia = domain.integral('basis_n u d:x' @ ns, degree=5)
sqr = domain.integral(
'(u - exp(-?y_i ?y_i)(y_i = 5 (x_i - 0.5_i)))^2 d:x' @ ns, degree=5)
lhs0 = solver.optimize('lhs', sqr)
timestep = timescale / nelems
bezier = domain.sample('bezier', 7)
with treelog.iter.plain(
'timestep',
solver.impliciteuler('lhs',
res,
inertia,
timestep=timestep,
lhs0=lhs0,
newtontol=newtontol)) as steps:
for itime, lhs in enumerate(steps):
x, u = bezier.eval(['x_i', 'u'] @ ns, lhs=lhs)
export.triplot('solution.png',
x,
u,
tri=bezier.tri,
hull=bezier.hull,
clim=(0, 1))
if itime * timestep >= endtime:
break
return lhs
def main(
nelems: 'number of elements' = 12,
viscosity: 'fluid viscosity' = 1e-2,
density: 'fluid density' = 1,
tol: 'solver tolerance' = 1e-12,
rotation: 'cylinder rotation speed' = 0,
timestep: 'time step' = 1/24,
maxradius: 'approximate domain size' = 25,
tmax: 'end time' = numpy.inf,
degree: 'polynomial degree' = 2,
withplots: 'create plots' = True,
):
log.user('reynolds number: {:.1f}'.format(density / viscosity)) # based on unit length and velocity
# create namespace
ns = function.Namespace()
ns.uinf = 1, 0
ns.density = density
ns.viscosity = viscosity
# construct mesh
rscale = numpy.pi / nelems
melems = numpy.ceil(numpy.log(2*maxradius) / rscale).astype(int)
log.info('creating {}x{} mesh, outer radius {:.2f}'.format(melems, 2*nelems, .5*numpy.exp(rscale*melems)))
domain, x0 = mesh.rectilinear([range(melems+1),numpy.linspace(0,2*numpy.pi,2*nelems+1)], periodic=(1,))
rho, phi = x0
phi += 1e-3 # tiny nudge (0.057 deg) to break element symmetry
radius = .5 * function.exp(rscale * rho)
ns.x = radius * function.trigtangent(phi)
domain = domain.withboundary(inner='left', inflow=domain.boundary['right'].select(-ns.uinf.dotnorm(ns.x), ischeme='gauss1'))
# prepare bases (using piola transformation to maintain u/p compatibility)
J = ns.x.grad(x0)
detJ = function.determinant(J)
ns.unbasis, ns.utbasis, ns.pbasis = function.chain([ # compatible spaces using piola transformation
domain.basis('spline', degree=(degree+1,degree), removedofs=((0,),None))[:,_] * J[:,0] / detJ,
domain.basis('spline', degree=(degree,degree+1))[:,_] * J[:,1] / detJ,
domain.basis('spline', degree=degree) / detJ,
])
ns.ubasis_ni = 'unbasis_ni + utbasis_ni'
# populate namespace
ns.u_i = 'ubasis_ni ?lhs_n'
ns.p = 'pbasis_n ?lhs_n'
ns.sigma_ij = 'viscosity (u_i,j + u_j,i) - p δ_ij'
ns.hinner = 2 * numpy.pi / nelems
ns.c = 5 * (degree+1) / ns.hinner
ns.nietzsche_ni = 'viscosity (c ubasis_ni - (ubasis_ni,j + ubasis_nj,i) n_j)'
ns.ucyl = -.5 * rotation * function.trignormal(phi)
# create residual vector components
res = domain.integral('ubasis_ni,j sigma_ij + pbasis_n u_k,k' @ ns, geometry=ns.x, degree=2*(degree+1))
res += domain.boundary['inner'].integral('nietzsche_ni (u_i - ucyl_i)' @ ns, geometry=ns.x, degree=2*(degree+1))
oseen = domain.integral('density ubasis_ni u_i,j uinf_j' @ ns, geometry=ns.x, degree=2*(degree+1))
convec = domain.integral('density ubasis_ni u_i,j u_j' @ ns, geometry=ns.x, degree=3*(degree+1))
inertia = domain.integral('density ubasis_ni u_i' @ ns, geometry=ns.x, degree=2*(degree+1))
# constrain full velocity vector at inflow
sqr = domain.boundary['inflow'].integral('(u_i - uinf_i) (u_i - uinf_i)' @ ns, geometry=ns.x, degree=9)
cons = solver.optimize('lhs', sqr, droptol=1e-15)
# solve unsteady navier-stokes equations, starting from stationary oseen flow
lhs0 = solver.solve_linear('lhs', res+oseen, constrain=cons)
makeplots = MakePlots(domain, ns, timestep=timestep, rotation=rotation) if withplots else lambda *args: None
for istep, lhs in log.enumerate('timestep', solver.impliciteuler('lhs', residual=res+convec, inertia=inertia, lhs0=lhs0, timestep=timestep, constrain=cons, newtontol=1e-10)):
makeplots(lhs)
if istep * timestep >= tmax:
break
return lhs0, lhs
def main(
nelems: 'number of elements' = 20,
epsilon: 'epsilon, 0 for automatic (based on nelems)' = 0,
timestep: 'time step' = .01,
maxtime: 'end time' = 1.,
theta: 'contact angle (degrees)' = 90,
init: 'initial condition (random/bubbles)' = 'random',
figures: 'create figures' = True,
):
mineps = 1. / nelems
if not epsilon:
log.info('setting epsilon={}'.format(mineps))
epsilon = mineps
elif epsilon < mineps:
log.warning('epsilon under crititical threshold: {} < {}'.format(
epsilon, mineps))
# create namespace
ns = function.Namespace()
ns.epsilon = epsilon
ns.ewall = .5 * numpy.cos(theta * numpy.pi / 180)
# construct mesh
xnodes = ynodes = numpy.linspace(0, 1, nelems + 1)
domain, ns.x = mesh.rectilinear([xnodes, ynodes])
# prepare bases
ns.cbasis, ns.mubasis = function.chain(
[domain.basis('spline', degree=2),
domain.basis('spline', degree=2)])
# polulate namespace
ns.c = 'cbasis_n ?lhs_n'
ns.c0 = 'cbasis_n ?lhs0_n'
ns.mu = 'mubasis_n ?lhs_n'
ns.f = '(6 c0 - 2 c0^3 - 4 c) / epsilon^2'
# construct initial condition
if init == 'random':
numpy.random.seed(0)
lhs0 = numpy.random.normal(0, .5, ns.cbasis.shape)
elif init == 'bubbles':
R1 = .25
R2 = numpy.sqrt(.5) * R1 # area2 = .5 * area1
ns.cbubble1 = function.tanh(
(R1 - function.norm2(ns.x -
(.5 + R2 / numpy.sqrt(2) + .8 * ns.epsilon)))
/ ns.epsilon)
ns.cbubble2 = function.tanh(
(R2 - function.norm2(ns.x -
(.5 - R1 / numpy.sqrt(2) - .8 * ns.epsilon)))
/ ns.epsilon)
sqr = domain.integral('(c - cbubble1 - cbubble2 - 1)^2 + mu^2' @ ns,
geometry=ns.x,
degree=4)
lhs0 = solver.optimize('lhs', sqr)
else:
raise Exception('unknown init %r' % init)
# construct residual
res = domain.integral(
'epsilon^2 cbasis_n,k mu_,k + mubasis_n (mu + f) - mubasis_n,k c_,k'
@ ns,
geometry=ns.x,
degree=4)
res -= domain.boundary.integral('mubasis_n ewall' @ ns,
geometry=ns.x,
degree=4)
inertia = domain.integral('cbasis_n c' @ ns, geometry=ns.x, degree=4)
# solve time dependent problem
nsteps = numeric.round(maxtime / timestep)
makeplots = MakePlots(domain, nsteps,
ns) if figures else lambda *args: None
for istep, lhs in log.enumerate(
'timestep',
solver.impliciteuler('lhs',
target0='lhs0',
residual=res,
inertia=inertia,
timestep=timestep,
lhs0=lhs0)):
makeplots(lhs)
if istep == nsteps:
break
return lhs0, lhs
def test_resume_withscaling(self):
_test_recursion_cache(self, lambda: map(types.frozenarray, solver.impliciteuler('dofs', residual=self.residual, inertia=self.inertia, lhs0=self.lhs0, timestep=100)))
def test_iters(self):
it = iter(solver.impliciteuler('dofs', residual=self.residual, inertia=self.inertia, lhs0=self.lhs0, timestep=100)) # involves 2-level timestep scaling
assert numpy.equal(next(it), self.lhs0).all()
numeric.assert_allclose64(next(it), 'eNpzNBA1NjHuNHQ3FDsTfCbAuNz4nUGZgeyZiDOZxlONmQwU9W3OFJ/pNQAADZIOPA==')
def main(
nelems: 'number of elements' = 12,
viscosity: 'fluid viscosity' = 1e-2,
density: 'fluid density' = 1,
tol: 'solver tolerance' = 1e-12,
rotation: 'cylinder rotation speed' = 0,
timestep: 'time step' = 1/24,
maxradius: 'approximate domain size' = 25,
tmax: 'end time' = numpy.inf,
degree: 'polynomial degree' = 2,
figures: 'create figures' = True,
):
log.user('reynolds number: {:.1f}'.format(density / viscosity)) # based on unit length and velocity
# create namespace
ns = function.Namespace()
ns.uinf = 1, 0
ns.density = density
ns.viscosity = viscosity
# construct mesh
rscale = numpy.pi / nelems
melems = numpy.ceil(numpy.log(2*maxradius) / rscale).astype(int)
log.info('creating {}x{} mesh, outer radius {:.2f}'.format(melems, 2*nelems, .5*numpy.exp(rscale*melems)))
domain, x0 = mesh.rectilinear([range(melems+1),numpy.linspace(0,2*numpy.pi,2*nelems+1)], periodic=(1,))
rho, phi = x0
phi += 1e-3 # tiny nudge (0.057 deg) to break element symmetry
radius = .5 * function.exp(rscale * rho)
ns.x = radius * function.trigtangent(phi)
domain = domain.withboundary(inner='left', inflow=domain.boundary['right'].select(-ns.uinf.dotnorm(ns.x), ischeme='gauss1'))
# prepare bases (using piola transformation to maintain u/p compatibility)
J = ns.x.grad(x0)
detJ = function.determinant(J)
ns.unbasis, ns.utbasis, ns.pbasis = function.chain([ # compatible spaces using piola transformation
domain.basis('spline', degree=(degree+1,degree), removedofs=((0,),None))[:,_] * J[:,0] / detJ,
domain.basis('spline', degree=(degree,degree+1))[:,_] * J[:,1] / detJ,
domain.basis('spline', degree=degree) / detJ,
])
ns.ubasis_ni = 'unbasis_ni + utbasis_ni'
# populate namespace
ns.u_i = 'ubasis_ni ?lhs_n'
ns.p = 'pbasis_n ?lhs_n'
ns.sigma_ij = 'viscosity (u_i,j + u_j,i) - p δ_ij'
ns.hinner = 2 * numpy.pi / nelems
ns.c = 5 * (degree+1) / ns.hinner
ns.nietzsche_ni = 'viscosity (c ubasis_ni - (ubasis_ni,j + ubasis_nj,i) n_j)'
ns.ucyl = -.5 * rotation * function.trignormal(phi)
# create residual vector components
res = domain.integral('ubasis_ni,j sigma_ij + pbasis_n u_k,k' @ ns, geometry=ns.x, degree=2*(degree+1))
res += domain.boundary['inner'].integral('nietzsche_ni (u_i - ucyl_i)' @ ns, geometry=ns.x, degree=2*(degree+1))
oseen = domain.integral('density ubasis_ni u_i,j uinf_j' @ ns, geometry=ns.x, degree=2*(degree+1))
convec = domain.integral('density ubasis_ni u_i,j u_j' @ ns, geometry=ns.x, degree=3*(degree+1))
inertia = domain.integral('density ubasis_ni u_i' @ ns, geometry=ns.x, degree=2*(degree+1))
# constrain full velocity vector at inflow
sqr = domain.boundary['inflow'].integral('(u_i - uinf_i) (u_i - uinf_i)' @ ns, geometry=ns.x, degree=9)
cons = solver.optimize('lhs', sqr, droptol=1e-15)
# solve unsteady navier-stokes equations, starting from stationary oseen flow
lhs0 = solver.solve_linear('lhs', res+oseen, constrain=cons)
makeplots = MakePlots(domain, ns, timestep=timestep, rotation=rotation) if figures else lambda *args: None
for istep, lhs in log.enumerate('timestep', solver.impliciteuler('lhs', residual=res+convec, inertia=inertia, lhs0=lhs0, timestep=timestep, constrain=cons, newtontol=1e-10)):
makeplots(lhs)
if istep * timestep >= tmax:
break
return lhs0, lhs
def main(
nelems: 'number of elements' = 20,
epsilon: 'epsilon, 0 for automatic (based on nelems)' = 0,
timestep: 'time step' = .01,
maxtime: 'end time' = 1.,
theta: 'contact angle (degrees)' = 90,
init: 'initial condition (random/bubbles)' = 'random',
withplots: 'create plots' = True,
):
mineps = 1./nelems
if not epsilon:
log.info('setting epsilon={}'.format(mineps))
epsilon = mineps
elif epsilon < mineps:
log.warning('epsilon under crititical threshold: {} < {}'.format(epsilon, mineps))
# create namespace
ns = function.Namespace()
ns.epsilon = epsilon
ns.ewall = .5 * numpy.cos( theta * numpy.pi / 180 )
# construct mesh
xnodes = ynodes = numpy.linspace(0,1,nelems+1)
domain, ns.x = mesh.rectilinear( [ xnodes, ynodes ] )
# prepare bases
ns.cbasis, ns.mubasis = function.chain([
domain.basis('spline', degree=2),
domain.basis('spline', degree=2)
])
# polulate namespace
ns.c = 'cbasis_n ?lhs_n'
ns.c0 = 'cbasis_n ?lhs0_n'
ns.mu = 'mubasis_n ?lhs_n'
ns.f = '(6 c0 - 2 c0^3 - 4 c) / epsilon^2'
# construct initial condition
if init == 'random':
numpy.random.seed(0)
lhs0 = numpy.random.normal(0, .5, ns.cbasis.shape)
elif init == 'bubbles':
R1 = .25
R2 = numpy.sqrt(.5) * R1 # area2 = .5 * area1
ns.cbubble1 = function.tanh((R1-function.norm2(ns.x-(.5+R2/numpy.sqrt(2)+.8*ns.epsilon)))/ns.epsilon)
ns.cbubble2 = function.tanh((R2-function.norm2(ns.x-(.5-R1/numpy.sqrt(2)-.8*ns.epsilon)))/ns.epsilon)
sqr = domain.integral('(c - cbubble1 - cbubble2 - 1)^2 + mu^2' @ ns, geometry=ns.x, degree=4)
lhs0 = solver.optimize('lhs', sqr)
else:
raise Exception( 'unknown init %r' % init )
# construct residual
res = domain.integral('epsilon^2 cbasis_n,k mu_,k + mubasis_n (mu + f) - mubasis_n,k c_,k' @ ns, geometry=ns.x, degree=4)
res -= domain.boundary.integral('mubasis_n ewall' @ ns, geometry=ns.x, degree=4)
inertia = domain.integral('cbasis_n c' @ ns, geometry=ns.x, degree=4)
# solve time dependent problem
nsteps = numeric.round(maxtime/timestep)
makeplots = MakePlots(domain, nsteps, ns) if withplots else lambda *args: None
for istep, lhs in log.enumerate('timestep', solver.impliciteuler('lhs', target0='lhs0', residual=res, inertia=inertia, timestep=timestep, lhs0=lhs0)):
makeplots(lhs)
if istep == nsteps:
break
return lhs0, lhs
