def post_process(out, problem, state, extend=False):
"""
This will be called after the problem is solved.
Parameters
----------
out : dict
The output dictionary, where this function will store additional data.
problem : Problem instance
The current Problem instance.
state : State instance
The computed state, containing FE coefficients of all the unknown
variables.
extend : bool
The flag indicating whether to extend the output data to the whole
domain. It can be ignored if the problem is solved on the whole domain
already.
Returns
-------
out : dict
The updated output dictionary.
"""
# Cauchy strain averaged in elements.
strain = problem.evaluate('ev_cauchy_strain.i.Omega( u )',
mode='el_avg')
out['cauchy_strain'] = Struct(name='output_data',
mode='cell', data=strain,
dofs=None)
# Cauchy stress averaged in elements.
stress = problem.evaluate('ev_cauchy_stress.i.Omega( solid.D, u )',
mode='el_avg')
out['cauchy_stress'] = Struct(name='output_data',
mode='cell', data=stress,
dofs=None)
# Define three line probes in axial directions.
mesh = problem.domain.mesh
bbox = mesh.get_bounding_box()
cx, cy, cz = 0.5 * bbox.sum(axis=0)
labels = []
probe_names = []
probe = Probe(out, mesh)
# line probe
labels.append('line probe - x direction')
probe_names.append('line')
probe.add_line_probe('line',
[bbox[0,0], cy, cz],
[bbox[1,0], cy, cz],
30)
# circle probe
labels.append('circle probe')
probe_names.append('circle')
probe.add_circle_probe('circle',
[cx, cy, cz],
[0, 0, 1],
0.015,
30)
# ray probe
labels.append('ray probe - y direction')
probe_names.append('ray')
probe.add_ray_probe('ray',
[cx, bbox[0,1], cz],
[0, 1, 0],
par_fun, 20)
# Gnerate matplotlib figures with the probe plot.
for probe_name, label in zip(probe_names, labels):
fig = plt.figure()
plt.clf()
fig.subplots_adjust(hspace=0.4)
plt.subplot(311)
pars, vals = probe(probe_name, 'u')
for ic in range(vals.shape[1]):
plt.plot(pars, vals[:,ic], label=r'$u_{%d}$' % (ic + 1),
lw=1, ls='-', marker='+', ms=3)
plt.ylabel('displacements')
plt.xlabel('probe %s' % label, fontsize=8)
plt.legend(loc='best', prop=fm.FontProperties(size=10))
sym_indices = [0, 4, 8, 1, 2, 5]
sym_labels = ['11', '22', '33', '12', '13', '23']
plt.subplot(312)
pars, vals = probe(probe_name, 'cauchy_strain')
for ii, ic in enumerate(sym_indices):
plt.plot(pars, vals[:,ic], label=r'$e_{%s}$' % sym_labels[ii],
lw=1, ls='-', marker='+', ms=3)
plt.ylabel('Cauchy strain')
plt.xlabel('probe %s' % label, fontsize=8)
plt.legend(loc='best', prop=fm.FontProperties(size=8))
plt.subplot(313)
pars, vals = probe(probe_name, 'cauchy_stress')
for ii, ic in enumerate(sym_indices):
plt.plot(pars, vals[:,ic], label=r'$\tau_{%s}$' % sym_labels[ii],
lw=1, ls='-', marker='+', ms=3)
plt.ylabel('Cauchy stress')
plt.xlabel('probe %s' % label, fontsize=8)
plt.legend(loc='best', prop=fm.FontProperties(size=8))
opts = problem.conf.options
filename_results = os.path.join(opts.get('output_dir'),
'cylinder_probe_%s.png' % probe_name)
fig.savefig(filename_results)
return out
def stress_strain(out, pb, state, extend=False):
"""
Calculate and output strain and stress for given displacements.
"""
from sfepy.base.base import Struct
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm
ev = pb.evaluate
strain = ev('ev_cauchy_strain.2.Omega(u)', mode='el_avg')
stress = ev('ev_cauchy_stress.2.Omega(Asphalt.D, u)', mode='el_avg')
out['cauchy_strain'] = Struct(name='output_data', mode='cell',
data=strain, dofs=None)
out['cauchy_stress'] = Struct(name='output_data', mode='cell',
data=stress, dofs=None)
probe = Probe(out, pb.domain.mesh, probe_view=True)
ps0 = [[0.0, 0.0, 0.0], [ 0.0, 0.0, 0.0]]
ps1 = [[75.0, 0.0, 0.0], [ 0.0, 75.0, 0.0]]
n_point = 10
labels = ['%s -> %s' % (p0, p1) for p0, p1 in zip(ps0, ps1)]
probes = []
for ip in xrange(len(ps0)):
p0, p1 = ps0[ip], ps1[ip]
probes.append('line%d' % ip)
probe.add_line_probe('line%d' % ip, p0, p1, n_point)
for ip, label in zip(probes, labels):
fig = plt.figure()
plt.clf()
fig.subplots_adjust(hspace=0.4)
plt.subplot(311)
pars, vals = probe(ip, 'u')
for ic in range(vals.shape[1] - 1):
plt.plot(pars, vals[:,ic], label=r'$u_{%d}$' % (ic + 1),
lw=1, ls='-', marker='+', ms=3)
plt.ylabel('displacements')
plt.xlabel('probe %s' % label, fontsize=8)
plt.legend(loc='best', prop=fm.FontProperties(size=10))
sym_indices = [0, 4, 1]
sym_labels = ['11', '22', '12']
plt.subplot(312)
pars, vals = probe(ip, 'cauchy_strain')
for ii, ic in enumerate(sym_indices):
plt.plot(pars, vals[:,ic], label=r'$e_{%s}$' % sym_labels[ii],
lw=1, ls='-', marker='+', ms=3)
plt.ylabel('Cauchy strain')
plt.xlabel('probe %s' % label, fontsize=8)
plt.legend(loc='best', prop=fm.FontProperties(size=8))
plt.subplot(313)
pars, vals = probe(ip, 'cauchy_stress')
for ii, ic in enumerate(sym_indices):
plt.plot(pars, vals[:,ic], label=r'$\sigma_{%s}$' % sym_labels[ii],
lw=1, ls='-', marker='+', ms=3)
plt.ylabel('Cauchy stress')
plt.xlabel('probe %s' % label, fontsize=8)
plt.legend(loc='best', prop=fm.FontProperties(size=8))
opts = pb.conf.options
filename_results = os.path.join(opts.get('output_dir'),
'its2D_probe_%s.png' % ip)
fig.savefig(filename_results)
return out
