def exercise_pickle():
etm = tst_tardy.get_test_model_by_index(i=5)
assert [body.joint.degrees_of_freedom for body in etm.bodies] \
== [6, 1, 1, 1, 1, 1]
assert etm.potential_obj is not None
etm.assign_random_velocities(e_kin_target=2.34)
etm.dynamics_step(delta_t=0.937)
def etm_as_ftm_with_q_qd():
result = etm_as_ftm(etm=etm)
result.unpack_q(etm.pack_q())
result.unpack_qd(etm.pack_qd())
return result
for protocol in xrange(pickle.HIGHEST_PROTOCOL):
ftm1 = etm_as_ftm_with_q_qd()
s = pickle.dumps(etm_as_ftm_with_q_qd(), protocol)
ftm2 = pickle.loads(s)
assert approx_equal(ftm2.pack_q(), ftm1.pack_q())
assert approx_equal(ftm2.pack_qd(), ftm1.pack_qd())
for delta_t in [0.538, 0.393]:
ftm1.dynamics_step(delta_t=delta_t)
ftm2.dynamics_step(delta_t=delta_t)
assert approx_equal(ftm2.pack_q(), ftm1.pack_q())
assert approx_equal(ftm2.pack_qd(), ftm1.pack_qd())
def run(args):
if (len(args) == 0):
model_index = 1
n_dynamics_steps = 100
delta_t = 0.01
else:
assert len(args) == 3, "model_index, n_dynamics_steps, delta_t"
model_index = int(eval(args[0]))
n_dynamics_steps = int(eval(args[1]))
delta_t = float(eval(args[2]))
tardy_model = tst_tardy.get_test_model_by_index(i=model_index)
tardy_model.assign_random_velocities(e_kin_target=1)
e_pots = flex.double([tardy_model.e_pot()])
e_kins = flex.double([tardy_model.e_kin()])
def show_e_tot():
print "e_tot: %.6g" % (e_pots[-1]+e_kins[-1])
sys.stdout.flush()
for i_step in xrange(n_dynamics_steps):
tardy_model.dynamics_step(delta_t=delta_t)
e_pots.append(tardy_model.e_pot())
e_kins.append(tardy_model.e_kin())
if (i_step % 1000 == 0):
print "i_step:", i_step,
show_e_tot()
print "i_step:", n_dynamics_steps,
show_e_tot()
e_tots = e_pots + e_kins
f = open("e_pot_kin_tot_i=%02d_n=%d_d=%.5f.xy" % (
model_index, n_dynamics_steps, delta_t), "w")
for es in [e_pots, e_kins, e_tots]:
for e in es:
print >> f, e
print >> f, "&"
f.close()
print "OK"
def exercise_fixed_vertices():
etm = tst_tardy.get_test_model_by_index(i=0, fixed_vertex_lists=[[0]])
assert etm.degrees_of_freedom == 0
compare_essence_and_fast_tardy_models(etm=etm)
#
for i_case, etm in enumerate(
tst_tardy.exercise_fixed_vertices_special_cases()):
assert etm.potential_obj is not None
compare_essence_and_fast_tardy_models(etm=etm,
have_singularity=(i_case < 4))
#
for fixed_vertices,expected_dof in \
tst_tardy.test_case_5_fixed_vertices_expected_dof:
etm = tst_tardy.get_test_model_by_index(
i=5, fixed_vertex_lists=[fixed_vertices])
assert etm.degrees_of_freedom == expected_dof
compare_essence_and_fast_tardy_models(etm=etm)
def exercise_fixed_vertices():
etm = tst_tardy.get_test_model_by_index(
i=0, fixed_vertex_lists=[[0]])
assert etm.degrees_of_freedom == 0
compare_essence_and_fast_tardy_models(etm=etm)
#
for i_case,etm in enumerate(
tst_tardy.exercise_fixed_vertices_special_cases()):
assert etm.potential_obj is not None
compare_essence_and_fast_tardy_models(
etm=etm,
have_singularity=(i_case < 4))
#
for fixed_vertices,expected_dof in \
tst_tardy.test_case_5_fixed_vertices_expected_dof:
etm = tst_tardy.get_test_model_by_index(
i=5, fixed_vertex_lists=[fixed_vertices])
assert etm.degrees_of_freedom == expected_dof
compare_essence_and_fast_tardy_models(etm=etm)
def init_view_objects(self):
box = wx.BoxSizer(wx.VERTICAL)
self.view_objects = viewer(self.frame, size=(600, 600))
tardy_model = tst_tardy.get_test_model_by_index(i=self.model_index, fixed_vertex_lists=self.fixed_vertex_lists)
if self.i_seq_labels:
tardy_model.labels = [str(i) for i in xrange(len(tardy_model.labels))]
self.view_objects.set_points_and_lines(
tardy_model=tardy_model,
velocity_scaling=self.velocity_scaling,
e_kin_per_dof=self.e_kin_per_dof,
minimum_covering_sphere_view_scale=self.view_scale,
)
box.Add(self.view_objects, wx.EXPAND, wx.EXPAND)
self.frame.SetSizer(box)
box.SetSizeHints(self.frame)
def init_view_objects(self):
box = wx.BoxSizer(wx.VERTICAL)
self.view_objects = viewer(self.frame, size=(600, 600))
tardy_model = tst_tardy.get_test_model_by_index(
i=self.model_index, fixed_vertex_lists=self.fixed_vertex_lists)
if (self.i_seq_labels):
tardy_model.labels = [
str(i) for i in range(len(tardy_model.labels))
]
self.view_objects.set_points_and_lines(
tardy_model=tardy_model,
velocity_scaling=self.velocity_scaling,
e_kin_per_dof=self.e_kin_per_dof,
minimum_covering_sphere_view_scale=self.view_scale)
box.Add(self.view_objects, wx.EXPAND, wx.EXPAND)
self.frame.SetSizer(box)
box.SetSizeHints(self.frame)
def run(args):
if (len(args) == 0):
model_index = 1
n_dynamics_steps = 100
delta_t = 0.01
else:
assert len(args) == 3, "model_index, n_dynamics_steps, delta_t"
model_index = int(eval(args[0]))
n_dynamics_steps = int(eval(args[1]))
delta_t = float(eval(args[2]))
tardy_model = tst_tardy.get_test_model_by_index(i=model_index)
tardy_model.assign_random_velocities(e_kin_target=1)
e_pots = flex.double([tardy_model.e_pot()])
e_kins = flex.double([tardy_model.e_kin()])
def show_e_tot():
print("e_tot: %.6g" % (e_pots[-1] + e_kins[-1]))
sys.stdout.flush()
for i_step in range(n_dynamics_steps):
tardy_model.dynamics_step(delta_t=delta_t)
e_pots.append(tardy_model.e_pot())
e_kins.append(tardy_model.e_kin())
if (i_step % 1000 == 0):
print("i_step:", i_step, end=' ')
show_e_tot()
print("i_step:", n_dynamics_steps, end=' ')
show_e_tot()
e_tots = e_pots + e_kins
f = open(
"e_pot_kin_tot_i=%02d_n=%d_d=%.5f.xy" %
(model_index, n_dynamics_steps, delta_t), "w")
for es in [e_pots, e_kins, e_tots]:
for e in es:
print(e, file=f)
print("&", file=f)
f.close()
print("OK")
def exercise_pickle():
etm = tst_tardy.get_test_model_by_index(i=5)
assert [body.joint.degrees_of_freedom for body in etm.bodies] \
== [6, 1, 1, 1, 1, 1]
assert etm.potential_obj is not None
etm.assign_random_velocities(e_kin_target=2.34)
etm.dynamics_step(delta_t=0.937)
def etm_as_ftm_with_q_qd():
result = etm_as_ftm(etm=etm)
result.unpack_q(etm.pack_q())
result.unpack_qd(etm.pack_qd())
return result
for protocol in xrange(pickle.HIGHEST_PROTOCOL):
ftm1 = etm_as_ftm_with_q_qd()
s = pickle.dumps(etm_as_ftm_with_q_qd(), protocol)
ftm2 = pickle.loads(s)
assert approx_equal(ftm2.pack_q(), ftm1.pack_q())
assert approx_equal(ftm2.pack_qd(), ftm1.pack_qd())
for delta_t in [0.538, 0.393]:
ftm1.dynamics_step(delta_t=delta_t)
ftm2.dynamics_step(delta_t=delta_t)
assert approx_equal(ftm2.pack_q(), ftm1.pack_q())
assert approx_equal(ftm2.pack_qd(), ftm1.pack_qd())
