def main():
parser = ArgumentParser(description=__doc__,
formatter_class=RawDescriptionHelpFormatter)
parser.add_argument('--version', action='version', version='%(prog)s')
parser.add_argument('-d',
'--dims',
metavar='dims',
action='store',
dest='dims',
default='[1.0, 1.0]',
help=helps['dims'])
parser.add_argument('-c',
'--centre',
metavar='centre',
action='store',
dest='centre',
default='[0.0, 0.0]',
help=helps['centre'])
parser.add_argument('-s',
'--shape',
metavar='shape',
action='store',
dest='shape',
default='[11, 11]',
help=helps['shape'])
parser.add_argument('--show',
action="store_true",
dest='show',
default=False,
help=helps['show'])
options = parser.parse_args()
dims = nm.array(eval(options.dims), dtype=nm.float64)
centre = nm.array(eval(options.centre), dtype=nm.float64)
shape = nm.array(eval(options.shape), dtype=nm.int32)
output('dimensions:', dims)
output('centre: ', centre)
output('shape: ', shape)
mesh = gen_block_mesh(dims, shape, centre, name='block-fem')
fe_domain = FEDomain('domain', mesh)
pb, state = run(fe_domain, 1)
pb.save_state('laplace_shifted_periodic.vtk', state)
if options.show:
from sfepy.postprocess.viewer import Viewer
from sfepy.postprocess.domain_specific import DomainSpecificPlot
view = Viewer('laplace_shifted_periodic.vtk')
view(rel_scaling=1,
domain_specific={
'u': DomainSpecificPlot('plot_warp_scalar', ['rel_scaling=1'])
},
is_scalar_bar=True,
is_wireframe=True,
opacity=0.3)
def __call__(self, parser, namespace, value, option_string=None):
if value is not None:
print(value)
out = {}
confs = value.split(':')
for conf in confs:
aux = conf.split(',')
var_name, fun_name = aux[:2]
args = aux[2:]
out[var_name] = DomainSpecificPlot(fun_name, args)
setattr(namespace, self.dest, out)
def parse_domain_specific(option, opt, value, parser):
if value is not None:
print value
out = {}
confs = value.split(':')
for conf in confs:
aux = conf.split(',')
var_name, fun_name = aux[:2]
args = aux[2:]
out[var_name] = DomainSpecificPlot(fun_name, args)
setattr(parser.values, option.dest, out)
def main():
parser = ArgumentParser(description=__doc__.rstrip(),
formatter_class=RawDescriptionHelpFormatter)
parser.add_argument('output_dir', help=helps['output_dir'])
parser.add_argument('-d', '--dims', metavar='l,w,t',
action='store', dest='dims',
default='0.2,0.01,0.001', help=helps['dims'])
parser.add_argument('-n', '--nx', metavar='start,stop,step',
action='store', dest='nx',
default='2,103,10', help=helps['nx'])
parser.add_argument('-t', '--transform', choices=['none', 'bend', 'twist'],
action='store', dest='transform',
default='none', help=helps['transform'])
parser.add_argument('--young', metavar='float', type=float,
action='store', dest='young',
default=210e9, help=helps['young'])
parser.add_argument('--poisson', metavar='float', type=float,
action='store', dest='poisson',
default=0.3, help=helps['poisson'])
parser.add_argument('--force', metavar='float', type=float,
action='store', dest='force',
default=-1.0, help=helps['force'])
parser.add_argument('-p', '--plot',
action="store_true", dest='plot',
default=False, help=helps['plot'])
parser.add_argument('--u-scaling', metavar='float', type=float,
action='store', dest='scaling',
default=1.0, help=helps['scaling'])
parser.add_argument('-s', '--show',
action="store_true", dest='show',
default=False, help=helps['show'])
parser.add_argument('--silent',
action='store_true', dest='silent',
default=False, help=helps['silent'])
options = parser.parse_args()
dims = nm.array([float(ii) for ii in options.dims.split(',')],
dtype=nm.float64)
nxs = tuple([int(ii) for ii in options.nx.split(',')])
young = options.young
poisson = options.poisson
force = options.force
output_dir = options.output_dir
odir = lambda filename: os.path.join(output_dir, filename)
filename = odir('output_log.txt')
ensure_path(filename)
output.set_output(filename=filename, combined=options.silent == False)
output('output directory:', output_dir)
output('using values:')
output(" dimensions:", dims)
output(" nx range:", nxs)
output(" Young's modulus:", options.young)
output(" Poisson's ratio:", options.poisson)
output(' force:', options.force)
output(' transform:', options.transform)
if options.transform == 'none':
options.transform = None
u_exact = get_analytical_displacement(dims, young, force,
transform=options.transform)
if options.transform is None:
ilog = 2
labels = ['u_3']
elif options.transform == 'bend':
ilog = 0
labels = ['u_1']
elif options.transform == 'twist':
ilog = [0, 1, 2]
labels = ['u_1', 'u_2', 'u_3']
label = ', '.join(labels)
log = []
for nx in range(*nxs):
shape = (nx, 2)
pb, state, u, gamma2 = solve_problem(shape, dims, young, poisson, force,
transform=options.transform)
dofs = u.get_state_in_region(gamma2)
output('DOFs along the loaded edge:')
output('\n%s' % dofs)
log.append([nx - 1] + nm.array(dofs[0, ilog], ndmin=1).tolist())
pb.save_state(odir('shell10x_cantilever.vtk'), state)
log = nm.array(log)
output('max. %s displacement w.r.t. number of cells:' % label)
output('\n%s' % log)
output('analytical value:', u_exact)
if options.plot:
import matplotlib.pyplot as plt
plt.rcParams.update({
'lines.linewidth' : 3,
'font.size' : 16,
})
fig, ax1 = plt.subplots()
fig.suptitle('max. $%s$ displacement' % label)
for ic in range(log.shape[1] - 1):
ax1.plot(log[:, 0], log[:, ic + 1], label=r'$%s$' % labels[ic])
ax1.set_xlabel('# of cells')
ax1.set_ylabel(r'$%s$' % label)
ax1.grid(which='both')
lines1, labels1 = ax1.get_legend_handles_labels()
if u_exact is not None:
ax1.hlines(u_exact, log[0, 0], log[-1, 0],
'r', 'dotted', label=r'$%s^{analytical}$' % label)
ax2 = ax1.twinx()
# Assume single log column.
ax2.semilogy(log[:, 0], nm.abs(log[:, 1] - u_exact), 'g',
label=r'$|%s - %s^{analytical}|$' % (label, label))
ax2.set_ylabel(r'$|%s - %s^{analytical}|$' % (label, label))
lines2, labels2 = ax2.get_legend_handles_labels()
else:
lines2, labels2 = [], []
ax1.legend(lines1 + lines2, labels1 + labels2, loc='best')
plt.tight_layout()
ax1.set_xlim([log[0, 0] - 2, log[-1, 0] + 2])
suffix = {None: 'straight',
'bend' : 'bent', 'twist' : 'twisted'}[options.transform]
fig.savefig(odir('shell10x_cantilever_convergence_%s.png' % suffix))
plt.show()
if options.show:
from sfepy.postprocess.viewer import Viewer
from sfepy.postprocess.domain_specific import DomainSpecificPlot
ds = {'u_disp' :
DomainSpecificPlot('plot_displacements',
['rel_scaling=%f' % options.scaling])}
view = Viewer(odir('shell10x_cantilever.vtk'))
view(domain_specific=ds, is_scalar_bar=True, is_wireframe=True,
opacity={'wireframe' : 0.5})
'vibro_acoustic3d_mid.py',
'linear_elastic_mM.py',
'time_poisson_explicit.py',
'__init__.py',
]
omit_dirs = [
re.compile('.*output.*/').match,
]
custom = {
'diffusion/sinbc.py' : {
'_t' : {
'is_wireframe' : True,
'domain_specific' : {
't' : DomainSpecificPlot('plot_warp_scalar',
['rel_scaling=1']),
},
'view' : (-160, 33, 4, [0.5, 1.22, 0.05]),
'roll' : 68,
'opacity' : {'wireframe' : 0.3},
},
'_grad' : {
'opacity' : {'surface' : 0.3},
'view' : (-160, 33, 4, [0.5, 1.22, 0.05]),
'roll' : 68,
},
},
'acoustics/acoustics3d.py' : {
'_p_1' : {
'view' : (-53, 120, 0.225, [0.021, 0.018, 0.066]),
'roll' : -177,
'roll': -120,
},
'_w': {
'view': (0.0, 0.0, 0.86, [0.0, 0.0, 0.1]),
'roll': 0,
},
'_g0': {
'view': (0.0, 0.0, 0.86, [0.0, 0.0, 0.1]),
'roll': 0,
},
},
'diffusion/laplace_1d.py': {
'': {
'is_wireframe': True,
'domain_specific': {
't': DomainSpecificPlot('plot_warp_scalar', ['rel_scaling=1']),
},
'view': (-90, 90, 1.5, [0, 0, 0]),
'roll': 0,
'opacity': {
'wireframe': 0.3
},
},
},
'diffusion/laplace_coupling_lcbcs.py': {
'': {
'is_wireframe': True,
'domain_specific': {
'u1': DomainSpecificPlot('plot_warp_scalar',
['rel_scaling=1']),
'u2': DomainSpecificPlot('plot_warp_scalar',
omits = [
'linear_elastic_mM.py',
'time_poisson_explicit.py',
'__init__.py',
]
omit_dirs = [
re.compile('.*output.*/').match,
]
custom = {
'diffusion/sinbc.py' : {
'_t' : {
'is_wireframe' : True,
'domain_specific' : {
't' : DomainSpecificPlot('plot_warp_scalar',
['rel_scaling=1']),
},
'view' : (-160, 33, 4, [0.5, 1.22, 0.05]),
'roll' : 68,
'opacity' : {'wireframe' : 0.3},
},
'_grad' : {
'opacity' : {'surface' : 0.3},
'view' : (-160, 33, 4, [0.5, 1.22, 0.05]),
'roll' : 68,
},
},
}
def _omit(filename):
omit = False
def main():
parser = ArgumentParser(description=__doc__,
formatter_class=RawDescriptionHelpFormatter)
parser.add_argument('--version', action='version', version='%(prog)s')
parser.add_argument('-d',
'--dims',
metavar='dims',
action='store',
dest='dims',
default='[1.0, 1.0]',
help=helps['dims'])
parser.add_argument('-c',
'--centre',
metavar='centre',
action='store',
dest='centre',
default='[0.0, 0.0]',
help=helps['centre'])
parser.add_argument('-s',
'--shape',
metavar='shape',
action='store',
dest='shape',
default='[11, 11]',
help=helps['shape'])
parser.add_argument('-b',
'--bc-kind',
metavar='kind',
action='store',
dest='bc_kind',
choices=['free', 'cantilever', 'fixed'],
default='free',
help=helps['bc_kind'])
parser.add_argument('-a',
'--axis',
metavar='0, ..., dim, or -1',
type=int,
action='store',
dest='axis',
default=-1,
help=helps['axis'])
parser.add_argument('--young',
metavar='float',
type=float,
action='store',
dest='young',
default=200e+9,
help=helps['young'])
parser.add_argument('--poisson',
metavar='float',
type=float,
action='store',
dest='poisson',
default=0.3,
help=helps['poisson'])
parser.add_argument('--density',
metavar='float',
type=float,
action='store',
dest='density',
default=7800.0,
help=helps['density'])
parser.add_argument('--order',
metavar='int',
type=int,
action='store',
dest='order',
default=1,
help=helps['order'])
parser.add_argument('-n',
'--n-eigs',
metavar='int',
type=int,
action='store',
dest='n_eigs',
default=6,
help=helps['n_eigs'])
parser.add_argument('-i',
'--ignore',
metavar='int',
type=int,
action='store',
dest='ignore',
default=None,
help=helps['ignore'])
parser.add_argument('--solver', metavar='solver', action='store',
dest='solver',
default= \
"eig.scipy,method:'eigh',tol:1e-5,maxiter:1000",
help=helps['solver'])
parser.add_argument('--show',
action="store_true",
dest='show',
default=False,
help=helps['show'])
#parser.add_argument('filename', nargs='?', default=None)
#read block.mesh
#parser.add_argument('filename', nargs='?', default="platehexat200mm.mesh")
parser.add_argument('filename', nargs='?', default="block_1m.mesh")
options = parser.parse_args()
aux = options.solver.split(',')
kwargs = {}
for option in aux[1:]:
key, val = option.split(':')
kwargs[key.strip()] = eval(val)
eig_conf = Struct(name='evp', kind=aux[0], **kwargs)
output('using values:')
output(" Young's modulus:", options.young)
output(" Poisson's ratio:", options.poisson)
output(' density:', options.density)
output('displacement field approximation order:', options.order)
output('requested %d eigenvalues' % options.n_eigs)
output('using eigenvalue problem solver:', eig_conf.kind)
output.level += 1
for key, val in six.iteritems(kwargs):
output('%s: %r' % (key, val))
output.level -= 1
assert_((0.0 < options.poisson < 0.5),
"Poisson's ratio must be in ]0, 0.5[!")
assert_((0 < options.order),
'displacement approximation order must be at least 1!')
filename = options.filename
if filename is not None:
mesh = Mesh.from_file(filename)
dim = mesh.dim
dims = nm.diff(mesh.get_bounding_box(), axis=0)
else:
dims = nm.array(eval(options.dims), dtype=nm.float64)
dim = len(dims)
centre = nm.array(eval(options.centre), dtype=nm.float64)[:dim]
shape = nm.array(eval(options.shape), dtype=nm.int32)[:dim]
output('dimensions:', dims)
output('centre: ', centre)
output('shape: ', shape)
mesh = gen_block_mesh(dims, shape, centre, name='mesh')
output('axis: ', options.axis)
assert_((-dim <= options.axis < dim), 'invalid axis value!')
eig_solver = Solver.any_from_conf(eig_conf)
# Build the problem definition.
domain = FEDomain('domain', mesh)
bbox = domain.get_mesh_bounding_box()
min_coor, max_coor = bbox[:, options.axis]
eps = 1e-8 * (max_coor - min_coor)
ax = 'xyz'[:dim][options.axis]
omega = domain.create_region('Omega', 'all')
"""
bottom = domain.create_region('Bottom',
'vertices in (%s < %.10f)'
% (ax, min_coor + eps),
'facet')
bottom_top = domain.create_region('BottomTop',
'r.Bottom +v vertices in (%s > %.10f)'
% (ax, max_coor - eps),
'facet')
"""
#import pdb; pdb.set_trace()
left = domain.create_region('left', 'vertices in (x < -0.49)', 'facet')
field = Field.from_args('fu',
nm.float64,
'vector',
omega,
approx_order=options.order)
u = FieldVariable('u', 'unknown', field)
v = FieldVariable('v', 'test', field, primary_var_name='u')
mtx_d = stiffness_from_youngpoisson(dim, options.young, options.poisson)
m = Material('m', D=mtx_d, rho=options.density)
integral = Integral('i', order=2 * options.order)
t1 = Term.new('dw_lin_elastic(m.D, v, u)', integral, omega, m=m, v=v, u=u)
t2 = Term.new('dw_volume_dot(m.rho, v, u)', integral, omega, m=m, v=v, u=u)
eq1 = Equation('stiffness', t1)
eq2 = Equation('mass', t2)
lhs_eqs = Equations([eq1, eq2])
pb = Problem('modal', equations=lhs_eqs)
"""
if options.bc_kind == 'free':
pb.time_update()
n_rbm = dim * (dim + 1) // 2
elif options.bc_kind == 'cantilever':
fixed = EssentialBC('Fixed', bottom, {'u.all' : 0.0})
pb.time_update(ebcs=Conditions([fixed]))
n_rbm = 0
elif options.bc_kind == 'fixed':
fixed = EssentialBC('Fixed', bottom_top, {'u.all' : 0.0})
pb.time_update(ebcs=Conditions([fixed]))
n_rbm = 0
else:
raise ValueError('unsupported BC kind! (%s)' % options.bc_kind)
if options.ignore is not None:
n_rbm = options.ignore
"""
fixed = EssentialBC('Fixed', left, {'u.all': 0.0})
pb.time_update(ebcs=Conditions([fixed]))
n_rbm = 0
pb.update_materials()
# Assemble stiffness and mass matrices.
mtx_k = eq1.evaluate(mode='weak', dw_mode='matrix', asm_obj=pb.mtx_a)
mtx_m = mtx_k.copy()
mtx_m.data[:] = 0.0
mtx_m = eq2.evaluate(mode='weak', dw_mode='matrix', asm_obj=mtx_m)
try:
eigs, svecs = eig_solver(mtx_k,
mtx_m,
options.n_eigs + n_rbm,
eigenvectors=True)
except sla.ArpackNoConvergence as ee:
eigs = ee.eigenvalues
svecs = ee.eigenvectors
output('only %d eigenvalues converged!' % len(eigs))
output('%d eigenvalues converged (%d ignored as rigid body modes)' %
(len(eigs), n_rbm))
eigs = eigs[n_rbm:]
svecs = svecs[:, n_rbm:]
omegas = nm.sqrt(eigs)
freqs = omegas / (2 * nm.pi)
output('number | eigenvalue | angular frequency '
'| frequency')
for ii, eig in enumerate(eigs):
output('%6d | %17.12e | %17.12e | %17.12e' %
(ii + 1, eig, omegas[ii], freqs[ii]))
# Make full eigenvectors (add DOFs fixed by boundary conditions).
variables = pb.get_variables()
vecs = nm.empty((variables.di.ptr[-1], svecs.shape[1]), dtype=nm.float64)
for ii in range(svecs.shape[1]):
vecs[:, ii] = variables.make_full_vec(svecs[:, ii])
# Save the eigenvectors.
out = {}
state = pb.create_state()
for ii in range(eigs.shape[0]):
state.set_full(vecs[:, ii])
aux = state.create_output_dict()
strain = pb.evaluate('ev_cauchy_strain.i.Omega(u)',
integrals=Integrals([integral]),
mode='el_avg',
verbose=False)
out['u%03d' % ii] = aux.popitem()[1]
out['strain%03d' % ii] = Struct(mode='cell', data=strain)
pb.save_state('eigenshapes.vtk', out=out)
pb.save_regions_as_groups('regions')
if len(eigs) and options.show:
# Show the solution. If the approximation order is greater than 1, the
# extra DOFs are simply thrown away.
from sfepy.postprocess.viewer import Viewer
from sfepy.postprocess.domain_specific import DomainSpecificPlot
scaling = 0.05 * dims.max() / nm.abs(vecs).max()
ds = {}
for ii in range(eigs.shape[0]):
pd = DomainSpecificPlot('plot_displacements', [
'rel_scaling=%s' % scaling, 'color_kind="tensors"',
'color_name="strain%03d"' % ii
])
ds['u%03d' % ii] = pd
view = Viewer('eigenshapes.vtk')
view(domain_specific=ds,
only_names=sorted(ds.keys()),
is_scalar_bar=False,
is_wireframe=True)
def main():
parser = OptionParser(usage=usage, version='%prog')
parser.add_option('-d',
'--dims',
metavar='dims',
action='store',
dest='dims',
default='[1.0, 1.0]',
help=helps['dims'])
parser.add_option('-c',
'--centre',
metavar='centre',
action='store',
dest='centre',
default='[0.0, 0.0]',
help=helps['centre'])
parser.add_option('-s',
'--shape',
metavar='shape',
action='store',
dest='shape',
default='[11, 11]',
help=helps['shape'])
parser.add_option('-b',
'--bc-kind',
metavar='kind',
action='store',
dest='bc_kind',
choices=['free', 'clamped'],
default='free',
help=helps['bc_kind'])
parser.add_option('--young',
metavar='float',
type=float,
action='store',
dest='young',
default=6.80e+10,
help=helps['young'])
parser.add_option('--poisson',
metavar='float',
type=float,
action='store',
dest='poisson',
default=0.36,
help=helps['poisson'])
parser.add_option('--density',
metavar='float',
type=float,
action='store',
dest='density',
default=2700.0,
help=helps['density'])
parser.add_option('--order',
metavar='int',
type=int,
action='store',
dest='order',
default=1,
help=helps['order'])
parser.add_option('-n',
'--n-eigs',
metavar='int',
type=int,
action='store',
dest='n_eigs',
default=6,
help=helps['order'])
parser.add_option('',
'--show',
action="store_true",
dest='show',
default=False,
help=helps['show'])
options, args = parser.parse_args()
assert_((0.0 < options.poisson < 0.5),
"Poisson's ratio must be in ]0, 0.5[!")
assert_((0 < options.order),
'displacement approximation order must be at least 1!')
dims = nm.array(eval(options.dims), dtype=nm.float64)
dim = len(dims)
centre = nm.array(eval(options.centre), dtype=nm.float64)[:dim]
shape = nm.array(eval(options.shape), dtype=nm.int32)[:dim]
output('dimensions:', dims)
output('centre: ', centre)
output('shape: ', shape)
output('using values:')
output(" Young's modulus:", options.young)
output(" Poisson's ratio:", options.poisson)
output(' density:', options.density)
# Build the problem definition.
mesh = gen_block_mesh(dims, shape, centre, name='mesh')
domain = FEDomain('domain', mesh)
bbox = domain.get_mesh_bounding_box()
min_y, max_y = bbox[:, 1]
eps = 1e-8 * (max_y - min_y)
omega = domain.create_region('Omega', 'all')
bottom = domain.create_region('Bottom',
'vertices in (y < %.10f)' % (min_y + eps),
'facet')
field = Field.from_args('fu',
nm.float64,
'vector',
omega,
approx_order=options.order)
u = FieldVariable('u', 'unknown', field)
v = FieldVariable('v', 'test', field, primary_var_name='u')
mtx_d = stiffness_from_youngpoisson(dim, options.young, options.poisson)
m = Material('m', D=mtx_d, rho=options.density)
integral = Integral('i', order=2 * options.order)
t1 = Term.new('dw_lin_elastic(m.D, v, u)', integral, omega, m=m, v=v, u=u)
t2 = Term.new('dw_volume_dot(m.rho, v, u)', integral, omega, m=m, v=v, u=u)
eq1 = Equation('stiffness', t1)
eq2 = Equation('mass', t2)
lhs_eqs = Equations([eq1, eq2])
pb = Problem('modal', equations=lhs_eqs)
if options.bc_kind == 'free':
pb.time_update()
n_rbm = dim * (dim + 1) / 2
else:
fixed_b = EssentialBC('FixedB', bottom, {'u.all': 0.0})
pb.time_update(ebcs=Conditions([fixed_b]))
n_rbm = 0
pb.update_materials()
# Assemble stiffness and mass matrices.
mtx_k = eq1.evaluate(mode='weak', dw_mode='matrix', asm_obj=pb.mtx_a)
mtx_m = mtx_k.copy()
mtx_m.data[:] = 0.0
mtx_m = eq2.evaluate(mode='weak', dw_mode='matrix', asm_obj=mtx_m)
try:
eigs, svecs = sla.eigsh(mtx_k,
k=options.n_eigs + n_rbm,
M=mtx_m,
which='SM',
tol=1e-5,
maxiter=10000)
except sla.ArpackNoConvergence as ee:
eigs = ee.eigenvalues
svecs = ee.eigenvectors
output('only %d eigenvalues converged!' % len(eigs))
eigs = eigs[n_rbm:]
svecs = svecs[:, n_rbm:]
output('eigenvalues:', eigs)
output('eigen-frequencies:', nm.sqrt(eigs))
# Make full eigenvectors (add DOFs fixed by boundary conditions).
variables = pb.get_variables()
vecs = nm.empty((variables.di.ptr[-1], svecs.shape[1]), dtype=nm.float64)
for ii in xrange(svecs.shape[1]):
vecs[:, ii] = variables.make_full_vec(svecs[:, ii])
# Save the eigenvectors.
out = {}
state = pb.create_state()
for ii in xrange(eigs.shape[0]):
state.set_full(vecs[:, ii])
aux = state.create_output_dict()
strain = pb.evaluate('ev_cauchy_strain.i.Omega(u)',
integrals=Integrals([integral]),
mode='el_avg',
verbose=False)
out['u%03d' % ii] = aux.popitem()[1]
out['strain%03d' % ii] = Struct(mode='cell', data=strain)
pb.save_state('eigenshapes.vtk', out=out)
pb.save_regions_as_groups('regions')
if options.show:
# Show the solution. If the approximation order is greater than 1, the
# extra DOFs are simply thrown away.
from sfepy.postprocess.viewer import Viewer
from sfepy.postprocess.domain_specific import DomainSpecificPlot
scaling = 0.05 * dims.max() / nm.abs(vecs).max()
ds = {}
for ii in xrange(eigs.shape[0]):
pd = DomainSpecificPlot('plot_displacements', [
'rel_scaling=%s' % scaling, 'color_kind="tensors"',
'color_name="strain%03d"' % ii
])
ds['u%03d' % ii] = pd
view = Viewer('eigenshapes.vtk')
view(domain_specific=ds,
only_names=sorted(ds.keys()),
is_scalar_bar=False,
is_wireframe=True)
