def create_gu():
cp = CreasePatternState(X=[[0, 0.5, -0.5],
[1, 0, 0],
[1, 1, 0],
[2, 0.5, -0.5],
],
L=[[0, 1], [1, 2], [2, 0], [1, 3],
[2, 3]],
F=[[0, 1, 2], [1, 3, 2]]
)
cp_factory = CustomCPFactory(formed_object=cp)
# begin
from oricreate.gu import GuPsiConstraints
# Link the crease factory it with the constraint client
gu_dof_constraints = \
GuPsiConstraints(forming_task=cp_factory,
psi_constraints=[([(0, 1.0)], 0),
])
cp = cp_factory.formed_object
print(cp.iL)
print(cp.iL_psi)
print('gu:', gu_dof_constraints.get_G(1.0))
print('g_du:\n', gu_dof_constraints.get_G_du(1.0))
# end
return gu_dof_constraints
def create_gu():
cp = CreasePatternState(X=[[0, 0.5, -0.5],
[1, 0, 0],
[1, 1, 0],
[2, 0.5, -0.5],
],
L=[[0, 1], [1, 2], [2, 0], [1, 3],
[2, 3]],
F=[[0, 1, 2], [1, 3, 2]]
)
cp_factory = CustomCPFactory(formed_object=cp)
# begin
from oricreate.gu import GuPsiConstraints
# Link the crease factory it with the constraint client
gu_dof_constraints = \
GuPsiConstraints(forming_task=cp_factory,
psi_constraints=[([(0, 1.0)], 0),
])
cp = cp_factory.formed_object
print cp.iL
print cp.iL_psi
print 'gu:', gu_dof_constraints.get_G(1.0)
print 'g_du:\n', gu_dof_constraints.get_G_du(1.0)
# end
return gu_dof_constraints
def _get_load_task(self):
self.fold_task.x_1
fat = self.factory_task
fixed_corner_n = fat.N_grid[(0, 0, -1, -1), (1, -2, 1, -2)].flatten()
fixed_n = fat.N_grid[(0, 0), (1, -2)].flatten()
slide_z = fix(fat.N_grid[-1, -2], [2], lambda t: -0.8 * self.L_x * t)
slide_x = fix(fat.N_grid[-1, -2], [0], lambda t: 0.1 * self.L_y * t)
loaded_n = fat.N_grid[self.n_x / 2, self.n_y / 2]
fixed_nodes_xyz = fix(fixed_n, (0, 2)) + slide_z
#fixed_nodes_xyz = fix(fixed_corner_n, (0, 1, 2))
dof_constraints = fixed_nodes_xyz
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
gu_constant_length = GuConstantLength()
diag_psi_mask = np.ones_like(fat.L_d_grid, dtype=np.bool_)
diag_psi_mask[1:-1, 1:-1] = False
diag_lines = fat.L_d_grid[diag_psi_mask].flatten()
diag_psi_constraints = [([(i, 1.0)], 0) for i in diag_lines]
gu_psi_constraints = \
GuPsiConstraints(forming_task=fat,
psi_constraints=diag_psi_constraints)
sim_config = SimulationConfig(
goal_function_type='total potential energy',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5,
MAX_ITER=1000,
debug_level=0)
def FN(F):
return lambda t: t * F
P = 0.0 * 30.5 * self.load_factor
F_ext_list = [(loaded_n, 2, FN(-P))]
fu_tot_poteng = FuPotEngTotal(kappa=np.array([1.0]),
F_ext_list=F_ext_list,
thickness=1,
exclude_lines=diag_lines)
sim_config._fu = fu_tot_poteng
st = SimulationTask(previous_task=self.fold_task,
config=sim_config,
n_steps=self.n_load_steps)
fu_tot_poteng.forming_task = st
cp = st.formed_object
cp.x_0 = self.fold_task.x_1
cp.u[:, :] = 0.0
return st
def _get_fold_task(self):
# Link the crease factory it with the constraint client
fat = self.factory_task
gu_constant_length = GuConstantLength()
nx2 = 1
ny2 = 2
dof_constraints = fix(fat.N_grid[nx2 - 1, ny2], [1]) \
+ fix(fat.N_grid[nx2, ny2], [0, 1, 2]) \
+ fix(fat.N_grid[nx2, (ny2 - 1, ny2 + 1)], [2])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
psi_max = np.pi * 0.4
diag_psi_mask = np.ones_like(fat.L_d_grid, dtype=np.bool_)
diag_psi_mask[1:-1, 1:-1] = False
diag_psi_constraints = [([(i, 1.0)], 0)
for i in fat.L_d_grid[diag_psi_mask].flatten()]
gu_psi_constraints = \
GuPsiConstraints(forming_task=fat,
psi_constraints=diag_psi_constraints +
[([(fat.L_h_grid[nx2, ny2], 1.0)],
lambda t: psi_max * t),
])
sim_config = SimulationConfig(goal_function_type='none',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-8,
MAX_ITER=200)
sim_task = SimulationTask(previous_task=fat,
config=sim_config,
n_steps=20)
cp = sim_task.formed_object
cp.u[fat.N_grid[::2, :].flatten(), 2] = -0.1
cp.u[fat.N_grid[0, ::2].flatten(), 2] = -0.2
return sim_task
cp.plot_mpl(ax, facets=True)
plt.tight_layout()
plt.show()
# Link the crease factory it with the constraint client
gu_constant_length = GuConstantLength()
dof_constraints = fix(cpf.N_grid[0, 1], [1]) \
+ fix(cpf.N_grid[1, 1], [0, 1, 2]) \
+ fix(cpf.N_grid[1, (0, -1)], [2])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
psi_max = np.pi / 4.0
diag_psi_constraints = [([(i, 1.0)], 0) for i in cpf.L_d_grid.flatten()]
gu_psi_constraints = \
GuPsiConstraints(forming_task=cpf,
psi_constraints=diag_psi_constraints +
[([(cpf.L_h_grid[1, 1], 1.0)],
lambda t: -psi_max * t),
])
sim_config = SimulationConfig(goal_function_type='none',
gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5,
MAX_ITER=10)
sim_task = SimulationTask(previous_task=cpf, config=sim_config, n_steps=5)
cp = sim_task.formed_object
cp.u[cpf.N_grid[(0, -1), 1], 2] = -1.0
import mayavi.mlab as m
import pylab as p
cp_factory_task = create_cp_factory()
cp = cp_factory_task.formed_object
ax = p.axes()
cp.plot_mpl(ax)
p.show()
# Link the crease factory it with the constraint client
gu_constant_length = GuConstantLength()
dof_constraints = fix([0], [0, 1, 2]) + fix([1], [1, 2]) + fix([4], [2])
gu_dof_constraints = GuDofConstraints(dof_constraints=dof_constraints)
psi_max = np.pi / 4.0
gu_psi_constraints = \
GuPsiConstraints(forming_task=cp_factory_task,
psi_constraints=[([(5, 1.0)], lambda t: psi_max * t),
([(7, 1.0)], 0),
([(8, 1.0)], 0),
])
sim_config = SimulationConfig(gu={
'cl': gu_constant_length,
'dofs': gu_dof_constraints,
'psi': gu_psi_constraints
},
acc=1e-5,
MAX_ITER=10)
sim_step = SimulationStep(forming_task=cp_factory_task, config=sim_config)
sim_step._solve_nr()
m.figure(bgcolor=(1.0, 1.0, 1.0), fgcolor=(0.6, 0.6, 0.6))
cpf = create_cp_factory()
cp = cpf.formed_object
import matplotlib.pyplot as plt
fig, ax = plt.subplots()
cp.plot_mpl(ax, facets=True)
plt.tight_layout()
plt.show()
gu_constant_length = GuConstantLength()
psi_max = np.pi / 4.0
diag_psi_constraints = [([(i, 1.0)], 0) for i in cpf.L_d_grid.flatten()]
gu_psi_constraints = \
GuPsiConstraints(forming_task=cpf,
psi_constraints=diag_psi_constraints
)
fu_psi_target_value = \
FuTargetPsiValue(forming_task=cpf,
psi_value=(cpf.L_h_grid[1, 1], lambda t: -psi_max * t)
)
hu_psi_constraints = \
HuPsiConstraints(forming_task=cpf,
psi_constraints=[(cpf.L_h_grid[0, 1], True),
(cpf.L_v_grid[1, 0], True),
(cpf.L_v_grid[1, 1], True),
])
sim_config = SimulationConfig(goal_function_type='total potential energy',
gu={'cl': gu_constant_length,
'psi': gu_psi_constraints},
hu={'mv': hu_psi_constraints},