本文整理汇总了Python中sfepy.discrete.Problem.create_state方法的典型用法代码示例。如果您正苦于以下问题：Python Problem.create_state方法的具体用法？Python Problem.create_state怎么用？Python Problem.create_state使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类sfepy.discrete.Problem的用法示例。
在下文中一共展示了Problem.create_state方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: main
# 需要导入模块: from sfepy.discrete import Problem [as 别名]
# 或者: from sfepy.discrete.Problem import create_state [as 别名]
#.........这里部分代码省略.........
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
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)