def plot_mesh(pb):
# plot mesh for macro problem
coors = pb.domain.mesh.coors
graph = pb.domain.mesh.get_conn(pb.domain.mesh.descs[0])
fig2 = plt.figure(figsize=(5, 6))
ax = fig2.add_subplot(111, projection='3d')
for e in range(graph.shape[0]):
tupleList = coors[graph[e, :], :]
vertices = [[0, 1, 2, 3], [4, 5, 6, 7], [0, 1, 5, 4], [1, 2, 6, 5],
[2, 3, 7, 6], [3, 0, 4, 7]]
verts = [[
tupleList[vertices[ix][iy]] for iy in range(len(vertices[0]))
] for ix in range(len(vertices))]
pc3d = Poly3DCollection(verts=verts,
facecolors='white',
edgecolors='black',
linewidths=1,
alpha=0.5)
ax.add_collection3d(pc3d)
ax.set_xlim3d(-1.2, 1.2)
ax.set_ylim3d(-1.2, 1.2)
ax.set_zlim3d(-0.01, 3.2)
ax.set_title('3D plot of macro system')
plt.show(fig2)
return None
def plot_gaps(fig_num, plot_rsc, gaps, kinds, freq_range, plot_range, show=False, clear=False, new_axes=False):
"""
Plot band gaps as rectangles.
"""
if plt is None:
return
fig = plt.figure(fig_num)
if clear:
fig.clf()
if new_axes:
ax = fig.add_subplot(111)
else:
ax = fig.gca()
for ii in xrange(len(freq_range) - 1):
f0, f1 = freq_range[[ii, ii + 1]]
gap = gaps[ii]
if isinstance(gap, list):
for ig, (gmin, gmax) in enumerate(gap):
kind, kind_desc = kinds[ii][ig]
plot_gap(ax, ii, f0, f1, kind, kind_desc, gmin, gmax, plot_range, plot_rsc)
else:
gmin, gmax = gap
kind, kind_desc = kinds[ii]
plot_gap(ax, ii, f0, f1, kind, kind_desc, gmin, gmax, plot_range, plot_rsc)
if new_axes:
ax.set_xlim([freq_range[0], freq_range[-1]])
ax.set_ylim(plot_range)
if show:
plt.show()
return fig
def main():
from sfepy.base.base import output
from sfepy.base.conf import ProblemConf, get_standard_keywords
from sfepy.discrete import Problem
from sfepy.base.plotutils import plt
parser = OptionParser(usage=usage, version='%prog')
parser.add_option('-n', '--no-plot',
action="store_true", dest='no_plot',
default=False, help=helps['no_plot'])
options, args = parser.parse_args()
required, other = get_standard_keywords()
# Use this file as the input file.
conf = ProblemConf.from_file(__file__, required, other)
# Create problem instance, but do not set equations.
problem = Problem.from_conf(conf, init_equations=False)
# Solve the problem. Output is ignored, results stored by using the
# step_hook.
u_t = solve_branch(problem, linear_tension)
u_c = solve_branch(problem, linear_compression)
# Get pressure load by calling linear_*() for each time step.
ts = problem.get_timestepper()
load_t = nm.array([linear_tension(ts, nm.array([[0.0]]), 'qp')['val']
for aux in ts.iter_from(0)],
dtype=nm.float64).squeeze()
load_c = nm.array([linear_compression(ts, nm.array([[0.0]]), 'qp')['val']
for aux in ts.iter_from(0)],
dtype=nm.float64).squeeze()
# Join the branches.
displacements = {}
for key in u_t.keys():
displacements[key] = nm.r_[u_c[key][::-1], u_t[key]]
load = nm.r_[load_c[::-1], load_t]
if plt is None:
output('matplotlib cannot be imported, printing raw data!')
output(displacements)
output(load)
else:
legend = []
for key, val in six.iteritems(displacements):
plt.plot(load, val)
legend.append(key)
plt.legend(legend, loc = 2)
plt.xlabel('tension [kPa]')
plt.ylabel('displacement [mm]')
plt.grid(True)
plt.gcf().savefig('pressure_displacement.png')
if not options.no_plot:
plt.show()
def main():
from sfepy.base.conf import ProblemConf, get_standard_keywords
from sfepy.fem import ProblemDefinition
from sfepy.base.plotutils import plt
parser = OptionParser(usage=usage, version='%prog')
parser.add_option('-n', '--no-plot',
action="store_true", dest='no_plot',
default=False, help=helps['no_plot'])
options, args = parser.parse_args()
required, other = get_standard_keywords()
# Use this file as the input file.
conf = ProblemConf.from_file( __file__, required, other )
# Create problem instance, but do not set equations.
problem = ProblemDefinition.from_conf( conf,
init_equations = False )
# Solve the problem. Output is ignored, results stored by using the
# step_hook.
u_t = solve_branch(problem, linear_tension)
u_c = solve_branch(problem, linear_compression)
# Get pressure load by calling linear_*() for each time step.
ts = problem.get_timestepper()
load_t = nm.array([linear_tension(ts, nm.array([[0.0]]), 'qp')['val']
for aux in ts.iter_from( 0 )],
dtype=nm.float64).squeeze()
load_c = nm.array([linear_compression(ts, nm.array([[0.0]]), 'qp')['val']
for aux in ts.iter_from( 0 )],
dtype=nm.float64).squeeze()
# Join the branches.
displacements = {}
for key in u_t.keys():
displacements[key] = nm.r_[u_c[key][::-1], u_t[key]]
load = nm.r_[load_c[::-1], load_t]
if plt is None:
print 'matplotlib cannot be imported, printing raw data!'
print displacements
print load
else:
legend = []
for key, val in displacements.iteritems():
plt.plot( load, val )
legend.append( key )
plt.legend( legend, loc = 2 )
plt.xlabel( 'tension [kPa]' )
plt.ylabel( 'displacement [mm]' )
plt.grid( True )
plt.gcf().savefig( 'pressure_displacement.png' )
if not options.no_plot:
plt.show()
def plot_logs(fig_num, plot_rsc, plot_labels,
freqs, logs, valid, freq_range, plot_range,
draw_eigs=True, show_legend=True, show=False,
clear=False, new_axes=False):
"""
Plot logs of min/middle/max eigs of a mass matrix.
"""
if plt is None: return
fig = plt.figure(fig_num)
if clear:
fig.clf()
if new_axes:
ax = fig.add_subplot(111)
else:
ax = fig.gca()
if draw_eigs:
plot_eigs(fig_num, plot_rsc, plot_labels, valid, freq_range,
plot_range)
for ii, log in enumerate(logs):
l1 = ax.plot(freqs[ii], log[:, -1], **plot_rsc['eig_max'])
if log.shape[1] >= 2:
l2 = ax.plot(freqs[ii], log[:, 0], **plot_rsc['eig_min'])
else:
l2 = None
if log.shape[1] == 3:
l3 = ax.plot(freqs[ii], log[:, 1], **plot_rsc['eig_mid'])
else:
l3 = None
l1[0].set_label(plot_labels['eig_max'])
if l2:
l2[0].set_label(plot_labels['eig_min'])
if l3:
l3[0].set_label(plot_labels['eig_mid'])
fmin, fmax = freqs[0][0], freqs[-1][-1]
ax.plot([fmin, fmax], [0, 0], **plot_rsc['x_axis'])
ax.set_xlabel(plot_labels['x_axis'])
ax.set_ylabel(plot_labels['y_axis'])
if new_axes:
ax.set_xlim([fmin, fmax])
ax.set_ylim(plot_range)
if show_legend:
ax.legend()
if show:
plt.show()
return fig
def main():
from sfepy.base.conf import ProblemConf, get_standard_keywords
from sfepy.fem import ProblemDefinition
from sfepy.base.plotutils import plt
required, other = get_standard_keywords()
# Use this file as the input file.
conf = ProblemConf.from_file( __file__, required, other )
# Create problem instance, but do not set equations.
problem = ProblemDefinition.from_conf( conf,
init_equations = False )
options = Struct( output_filename_trunk = None )
# Solve the problem. Output is ignored, results stored by using the
# step_hook.
u_t = solve_branch( problem, options, linear_tension )
u_c = solve_branch( problem, options, linear_compression )
# Get pressure load by calling linear_*() for each time step.
ts = problem.get_timestepper()
load_t = nm.array([linear_tension(ts, nm.array([[0.0]]), 'qp')['val']
for aux in ts.iter_from( 0 )],
dtype=nm.float64).squeeze()
load_c = nm.array([linear_compression(ts, nm.array([[0.0]]), 'qp')['val']
for aux in ts.iter_from( 0 )],
dtype=nm.float64).squeeze()
# Join the branches.
displacements = {}
for key in u_t.keys():
displacements[key] = nm.r_[u_c[key][::-1], u_t[key]]
load = nm.r_[load_c[::-1], load_t]
if plt is None:
print 'matplotlib cannot be imported, printing raw data!'
print displacements
print load
else:
legend = []
for key, val in displacements.iteritems():
plt.plot( load, val )
legend.append( key )
plt.legend( legend, loc = 2 )
plt.xlabel( 'tension [kPa]' )
plt.ylabel( 'displacement [mm]' )
plt.grid( True )
plt.gcf().savefig( 'pressure_displacement.png' )
plt.show()
def plot_gaps(fig_num,
plot_rsc,
gaps,
kinds,
gap_ranges,
freq_range,
plot_range,
show=False,
clear=False,
new_axes=False):
"""
Plot band gaps as rectangles.
"""
if plt is None: return
fig = plt.figure(fig_num)
if clear:
fig.clf()
if new_axes:
ax = fig.add_subplot(111)
else:
ax = fig.gca()
for ii in range(len(freq_range) - 1):
f0, f1 = freq_range[[ii, ii + 1]]
gap = gaps[ii]
ranges = gap_ranges[ii]
if isinstance(gap, list):
for ig, (gmin, gmax) in enumerate(gap):
kind, kind_desc = kinds[ii][ig]
plot_gap(ax, ranges[ig], kind, kind_desc, plot_range, plot_rsc)
output(ii, gmin[0], gmax[0], '%.8f' % f0, '%.8f' % f1)
output(' -> %s\n %s' % (kind_desc, ranges[ig]))
else:
gmin, gmax = gap
kind, kind_desc = kinds[ii]
plot_gap(ax, ranges, kind, kind_desc, plot_range, plot_rsc)
output(ii, gmin[0], gmax[0], '%.8f' % f0, '%.8f' % f1)
output(' -> %s\n %s' % (kind_desc, ranges))
if new_axes:
ax.set_xlim([freq_range[0], freq_range[-1]])
ax.set_ylim(plot_range)
if show:
plt.show()
return fig
def plot_band_gaps(self, coefs):
opts = self.app_options
bg_keys = [
key for key in coefs.to_dict() if key.startswith('band_gaps')
]
plot_opts = opts.plot_options
plot_rsc = opts.plot_rsc
plt.rcParams.update(plot_rsc['params'])
for ii, key in enumerate(bg_keys):
bg = coefs.get(key)
plot_labels = opts.plot_labels.get(key, opts.plot_labels)
plot_range, teigs = transform_plot_data(bg.logs.eigs,
opts.plot_transform,
self.conf)
fig = plot_gaps(ii,
plot_rsc,
bg.gaps,
bg.kinds,
bg.gap_ranges,
bg.freq_range_margins,
plot_range,
clear=True)
fig = plot_logs(ii,
plot_rsc,
plot_labels,
bg.logs.freqs,
teigs,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range,
show_legend=plot_opts['legend'],
new_axes=True)
plt.tight_layout()
if opts.fig_name is not None:
fig_name = _get_fig_name(self.problem.output_dir,
opts.fig_name, key, 'band_gaps',
opts.fig_suffix)
fig.savefig(fig_name)
if plot_opts['show']:
plt.show()
def plot_eigs(fig_num,
plot_rsc,
plot_labels,
valid,
freq_range,
plot_range,
show=False,
clear=False,
new_axes=False):
"""
Plot resonance/eigen-frequencies.
`valid` must correspond to `freq_range`
resonances : red
masked resonances: dotted red
"""
if plt is None: return
assert_(len(valid) == len(freq_range))
fig = plt.figure(fig_num)
if clear:
fig.clf()
if new_axes:
ax = fig.add_subplot(111)
else:
ax = fig.gca()
l0 = l1 = None
for ii, f in enumerate(freq_range):
if valid[ii]:
l0 = ax.plot([f, f], plot_range, **plot_rsc['resonance'])[0]
else:
l1 = ax.plot([f, f], plot_range, **plot_rsc['masked'])[0]
if l0:
l0.set_label(plot_labels['resonance'])
if l1:
l1.set_label(plot_labels['masked'])
if new_axes:
ax.set_xlim([freq_range[0], freq_range[-1]])
ax.set_ylim(plot_range)
if show:
plt.show()
return fig
def plot_eigs(fig_num, plot_rsc, plot_labels, valid, freq_range, plot_range,
show=False, clear=False, new_axes=False):
"""
Plot resonance/eigen-frequencies.
`valid` must correspond to `freq_range`
resonances : red
masked resonances: dotted red
"""
if plt is None: return
assert_(len(valid) == len(freq_range))
fig = plt.figure(fig_num)
if clear:
fig.clf()
if new_axes:
ax = fig.add_subplot(111)
else:
ax = fig.gca()
l0 = l1 = None
for ii, f in enumerate(freq_range):
if valid[ii]:
l0 = ax.plot([f, f], plot_range, **plot_rsc['resonance'])[0]
else:
l1 = ax.plot([f, f], plot_range, **plot_rsc['masked'])[0]
if l0:
l0.set_label(plot_labels['resonance'])
if l1:
l1.set_label(plot_labels['masked'])
if new_axes:
ax.set_xlim([freq_range[0], freq_range[-1]])
ax.set_ylim(plot_range)
if show:
plt.show()
return fig
def plot_band_gaps(self, coefs):
opts = self.app_options
bg_keys = [key for key in coefs.to_dict()
if key.startswith('band_gaps')]
plot_opts = opts.plot_options
plot_rsc = opts.plot_rsc
plt.rcParams.update(plot_rsc['params'])
for ii, key in enumerate(bg_keys):
bg = coefs.get(key)
plot_labels = opts.plot_labels.get(key, opts.plot_labels)
plot_range, teigs = transform_plot_data(bg.logs.eigs,
opts.plot_transform,
self.conf)
fig = plot_gaps(ii, plot_rsc, bg.gaps, bg.kinds, bg.gap_ranges,
bg.freq_range_margins, plot_range,
clear=True)
fig = plot_logs(ii, plot_rsc, plot_labels, bg.logs.freqs, teigs,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range,
show_legend=plot_opts['legend'],
new_axes=True)
plt.tight_layout()
if opts.fig_name is not None:
fig_name = _get_fig_name(self.problem.output_dir, opts.fig_name,
key, 'band_gaps', opts.fig_suffix)
fig.savefig(fig_name)
if plot_opts['show']:
plt.show()
def plot_dispersion(self, coefs):
opts = self.app_options
bg_keys = [key for key in coefs.to_dict()
if key.startswith('dispersion')]
plot_rsc = opts.plot_rsc
plot_opts = opts.plot_options
plt.rcParams.update(plot_rsc['params'])
plot_labels = opts.plot_labels_angle
for ii, key in enumerate(bg_keys):
pas_key = key.replace('dispersion', 'polarization_angles')
pas = coefs.get(pas_key)
aux = transform_plot_data(pas,
opts.plot_transform_angle,
self.conf)
plot_range, pas = aux
bg = coefs.get(key)
fig = plot_gaps(1, plot_rsc, bg.gaps, bg.kinds,
bg.freq_range_margins, plot_range,
clear=True)
fig = plot_logs(1, plot_rsc, plot_labels, bg.logs.freqs, pas,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range,
show_legend=plot_opts['legend'],
new_axes=True)
fig_name = opts.fig_name_angle
if fig_name is not None:
fig_name = _get_fig_name(self.problem.output_dir, fig_name,
key, 'dispersion', opts.fig_suffix)
fig.savefig(fig_name)
aux = transform_plot_data(bg.logs.eigs,
opts.plot_transform_wave,
self.conf)
plot_range, teigs = aux
plot_labels = opts.plot_labels_wave
fig = plot_gaps(2, plot_rsc, bg.gaps, bg.kinds,
bg.freq_range_margins, plot_range,
clear=True)
fig = plot_logs(2, plot_rsc, plot_labels, bg.logs.freqs, teigs,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range,
show_legend=plot_opts['legend'],
new_axes=True)
fig_name = opts.fig_name_wave
if fig_name is not None:
fig_name = _get_fig_name(self.problem.output_dir, fig_name,
key, 'dispersion', opts.fig_suffix)
fig.savefig(fig_name)
if plot_opts['show']:
plt.show()
def call( self ):
"""In parametric runs, cached data (homogenized coefficients,
Christoffel acoustic tensor and eigenvalue problem solution) are
cleared according to 'clear_cache' aplication options.
Example:
clear_cache = {'cached_christoffel' : True, 'cached_evp' : True}
"""
options = self.options
for key, val in self.app_options.clear_cache.iteritems():
if val and key.startswith('cached_'):
setattr(self, key, None)
if options.phase_velocity:
# No band gaps in this case.
return self.compute_phase_velocity()
evp = self.solve_eigen_problem()
self.fix_eig_range( evp.eigs.shape[0] )
if options.detect_band_gaps:
bg = detect_band_gaps( self.problem, evp.kind,
evp.eigs_rescaled, evp.eig_vectors,
self.app_options, self.conf.funmod )
if options.plot:
plot_range, teigs = transform_plot_data( bg.logs.eigs,
bg.opts.plot_transform,
self.conf.funmod )
plot_rsc = bg.opts.plot_rsc
plot_opts = bg.opts.plot_options
plot_labels = bg.opts.plot_labels
plt.rcParams.update( plot_rsc['params'] )
fig = plot_gaps( 1, plot_rsc, bg.gaps, bg.kinds,
bg.freq_range_margins, plot_range,
clear = True )
fig = plot_logs( 1, plot_rsc, plot_labels, bg.logs.freqs, teigs,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range, False,
show_legend = plot_opts['legend'],
new_axes = True )
fig_name = bg.opts.fig_name
if fig_name is not None:
fig.savefig( fig_name )
if plot_opts['show']:
plt.show()
elif options.analyze_dispersion:
christoffel, iw_dir = self.compute_cat(ret_iw_dir=True)
bg = detect_band_gaps( self.problem, evp.kind,
evp.eigs_rescaled, evp.eig_vectors,
self.app_options, self.conf.funmod,
christoffel = christoffel )
output( 'computing polarization angles...' )
pas = compute_polarization_angles( iw_dir, bg.logs.eig_vectors )
output( '...done' )
bg.polarization_angles = pas
output( 'computing phase velocity...' )
bg.phase_velocity = self.compute_phase_velocity()
output( '...done' )
if options.plot:
plot_rsc = bg.opts.plot_rsc
plot_opts = bg.opts.plot_options
plt.rcParams.update( plot_rsc['params'] )
aux = transform_plot_data( pas,
bg.opts.plot_transform_angle,
self.conf.funmod )
plot_range, pas = aux
plot_labels = bg.opts.plot_labels_angle
fig = plot_gaps( 1, plot_rsc, bg.gaps, bg.kinds,
bg.freq_range_margins, plot_range,
clear = True )
fig = plot_logs( 1, plot_rsc, plot_labels, bg.logs.freqs, pas,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range, False,
show_legend = plot_opts['legend'],
new_axes = True )
fig_name = bg.opts.fig_name_angle
if fig_name is not None:
fig.savefig( fig_name )
aux = transform_plot_data( bg.logs.eigs,
bg.opts.plot_transform_wave,
self.conf.funmod )
plot_range, teigs = aux
plot_labels = bg.opts.plot_labels_wave
fig = plot_gaps( 2, plot_rsc, bg.gaps, bg.kinds,
bg.freq_range_margins, plot_range,
clear = True )
fig = plot_logs( 2, plot_rsc, plot_labels, bg.logs.freqs, teigs,
bg.valid[bg.eig_range],
bg.freq_range_initial,
plot_range, False,
show_legend = plot_opts['legend'],
new_axes = True )
fig_name = bg.opts.fig_name_wave
if fig_name is not None:
fig.savefig( fig_name )
if plot_opts['show']:
plt.show()
else:
bg = None
return evp, bg
