def test_vectorized(self):
"""Check against the scipy solver."""
model = Group()
x = np.array([[1, 2, -3], [2, -1, 4]])
A = np.array([[5.0, -3.0, 2.0], [1.0, 7.0, -4.0], [1.0, 0.0, 8.0]])
b = np.einsum('jk,ik->ij', A, x)
model.add_subsystem('p1', IndepVarComp('A', A))
model.add_subsystem('p2', IndepVarComp('b', b))
lingrp = model.add_subsystem('lingrp', Group(), promotes=['*'])
lingrp.add_subsystem('lin', LinearSystemComp(size=3, vec_size=2))
model.connect('p1.A', 'lin.A')
model.connect('p2.b', 'lin.b')
prob = Problem(model)
prob.setup()
lingrp.linear_solver = ScipyKrylov()
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, prob['lin.x'], x, .0001)
assert_rel_error(self, prob.model._residuals.get_norm(), 0.0, 1e-10)
model.run_apply_nonlinear()
with model._scaled_context_all():
val = model.lingrp.lin._residuals['x']
assert_rel_error(self, val, np.zeros((2, 3)), tolerance=1e-8)
def test_vectorized_A(self):
"""Check against the scipy solver."""
model = Group()
x = np.array([[1, 2, -3], [2, -1, 4]])
A = np.array([[[5.0, -3.0, 2.0], [1.0, 7.0, -4.0], [1.0, 0.0, 8.0]],
[[2.0, 3.0, 4.0], [1.0, -1.0, -2.0], [3.0, 2.0, -2.0]]])
b = np.einsum('ijk,ik->ij', A, x)
model.add_subsystem('p1', IndepVarComp('A', A))
model.add_subsystem('p2', IndepVarComp('b', b))
lingrp = model.add_subsystem('lingrp', Group(), promotes=['*'])
lingrp.add_subsystem('lin', LinearSystemComp(size=3, vec_size=2, vectorize_A=True))
model.connect('p1.A', 'lin.A')
model.connect('p2.b', 'lin.b')
prob = Problem(model)
prob.setup()
lingrp.linear_solver = ScipyKrylov()
prob.set_solver_print(level=0)
prob.run_model()
assert_rel_error(self, prob['lin.x'], x, .0001)
assert_rel_error(self, prob.model._residuals.get_norm(), 0.0, 1e-10)
model.run_apply_nonlinear()
with model._scaled_context_all():
val = model.lingrp.lin._residuals['x']
assert_rel_error(self, val, np.zeros((2, 3)), tolerance=1e-8)
