def test_linearGS_simul_element_and_full_connection(self):
# Added because of a bug with array slices for Linear GS
top = Assembly()
top.add('comp1', ArrayComp2D())
top.add('comp2', ArrayComp2D())
top.add('driver', SimpleDriver())
top.driver.workflow.add(['comp1', 'comp2'])
top.connect('comp1.y', 'comp2.x')
top.driver.add_parameter('comp1.x[0][0]', low=-10, high=10)
top.driver.add_objective('comp1.y[0][0]')
top.driver.add_constraint('comp2.y[0][1] < 0')
top.driver.gradient_options.lin_solver = 'linear_gs'
top.driver.gradient_options.maxiter = 1
top.run()
J = top.driver.calc_gradient(mode='forward')
assert_rel_error(self, J[0, 0], 2.0, .000001)
assert_rel_error(self, J[1, 0], 39.0, .000001)
J = top.driver.calc_gradient(mode='adjoint')
assert_rel_error(self, J[0, 0], 2.0, .000001)
assert_rel_error(self, J[1, 0], 39.0, .000001)
def test_nested_2Darray_simul_element_and_full_connection2(self):
# Slightly different config
top = Assembly()
top.add('nest', Assembly())
top.nest.add('comp1', ArrayComp2D())
top.nest.add('comp2', ArrayComp2D())
top.driver.gradient_options.lin_solver = 'petsc_ksp'
top.nest.driver.gradient_options.lin_solver = 'petsc_ksp'
top.nest.driver.workflow.add(['comp1', 'comp2'])
top.nest.connect('comp1.y', 'comp2.x')
top.nest.create_passthrough('comp1.x')
top.nest.create_passthrough('comp1.y')
top.nest.add('yy', Array(iotype='out'))
top.nest.connect('comp2.y', 'yy')
top.add('driver', SimpleDriver())
top.driver.workflow.add(['nest'])
top.driver.add_parameter('nest.x[0][0]', low=-10, high=10)
top.driver.add_objective('nest.yy[0][0]')
top.driver.add_constraint('nest.y[0][1] < 0')
top.run()
J = top.driver.calc_gradient(mode='forward')
assert_rel_error(self, J[0, 0], 24.0, .000001)
assert_rel_error(self, J[1, 0], 4.0, .000001)
J = top.driver.calc_gradient(mode='adjoint')
assert_rel_error(self, J[0, 0], 24.0, .000001)
assert_rel_error(self, J[1, 0], 4.0, .000001)
J = top.driver.calc_gradient(mode='fd')
assert_rel_error(self, J[0, 0], 24.0, .000001)
assert_rel_error(self, J[1, 0], 4.0, .000001)
def test_PA_slices(self):
top = set_as_top(Assembly())
top.add('comp', ArrayComp2D())
top.add('driver', SimpleDriver())
top.driver.workflow.add('comp')
top.comp.force_fd = True
top.driver.gradient_options.directional_fd = True
top.driver.add_parameter('comp.x', low=-100, high=100)
top.driver.add_constraint('comp.y[0][-1] < 1.0')
top.driver.add_constraint('sum(comp.y) < 4.0')
top.run()
J = top.driver.workflow.calc_gradient(mode='forward')
assert_rel_error(self, J[0, 0], 4.0, 0.001)
assert_rel_error(self, J[0, 1], 2.0, 0.001)
assert_rel_error(self, J[0, 2], 6.0, 0.001)
assert_rel_error(self, J[0, 3], 5.0, 0.001)
def test_array(self):
top = set_as_top(Assembly())
nest = top.add('nest', Assembly())
top.driver.workflow.add('nest')
top.driver.gradient_options.lin_solver = 'petsc_ksp'
nest.add('comp', ArrayComp2D())
nest.driver.workflow.add('comp')
nest.create_passthrough('comp.x')
nest.create_passthrough('comp.y')
top.run()
J = top.driver.calc_gradient(inputs = ['nest.x'], outputs=['nest.y'])
diff = J - top.nest.comp.J
assert_rel_error(self, diff.max(), 0.0, .000001)
J = top.driver.calc_gradient(inputs = ['nest.x'], outputs=['nest.y'], mode='adjoint')
diff = J - top.nest.comp.J
assert_rel_error(self, diff.max(), 0.0, .000001)
def test_nested_2Darray(self):
top = Assembly()
top.add('nest', Assembly())
top.nest.add('comp', ArrayComp2D())
top.driver.workflow.add(['nest'])
top.nest.driver.workflow.add(['comp'])
top.nest.create_passthrough('comp.x')
top.nest.create_passthrough('comp.y')
top.run()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x',
],
outputs=['nest.y'],
mode='forward')
diff = J - top.nest.comp.J
assert_rel_error(self, diff.max(), 0.0, .000001)
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[0, 0]',
],
outputs=['nest.y[0, 0]'],
mode='forward')
diff = J - top.nest.comp.J[0, 0]
assert_rel_error(self, diff.max(), 0.0, .000001)
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[0, 1]',
],
outputs=['nest.y[1, 0]'],
mode='forward')
diff = J - top.nest.comp.J[1, 2]
assert_rel_error(self, diff.max(), 0.0, .000001)
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[0, 1]',
],
outputs=['nest.y[1, 0]'],
mode='fd')
diff = J - top.nest.comp.J[1, 2]
assert_rel_error(self, diff.max(), 0.0, .000001)
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[0, -1]',
],
outputs=['nest.y[-1, 0]'],
mode='forward')
diff = J - top.nest.comp.J[1, 2]
assert_rel_error(self, diff.max(), 0.0, .000001)
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[0, -1]',
],
outputs=['nest.y[-1, 0]'],
mode='fd')
diff = J - top.nest.comp.J[1, 2]
assert_rel_error(self, diff.max(), 0.0, .000001)
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
Jsub = top.nest.comp.J[2:3, 2:3]
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[1][:]',
],
outputs=['nest.y[1][:]'],
mode='forward')
diff = J - Jsub
top.run()
top.driver.workflow.config_changed()
top.nest.driver.workflow.config_changed()
J = top.driver.workflow.calc_gradient(inputs=[
'nest.x[1][:]',
],
outputs=['nest.y[1][:]'],
mode='fd')
diff = J - Jsub
def test_nested_array_full_and_partial_passthrough(self):
top = Assembly()
top.add('nest', Assembly())
top.nest.add('comp1', ArrayComp2D())
top.nest.add('comp2', ArrayComp2D())
top.driver.gradient_options.lin_solver = 'petsc_ksp'
top.nest.driver.gradient_options.lin_solver = 'petsc_ksp'
top.nest.driver.workflow.add(['comp1', 'comp2'])
top.nest.create_passthrough('comp1.x', 'x')
top.nest.create_passthrough('comp1.y', 'y1')
top.nest.create_passthrough('comp2.y', 'y2')
top.nest.connect('x[-1, -1]', 'comp2.x[-1, -1]')
top.add('driver', SimpleDriver())
top.driver.workflow.add(['nest'])
top.run()
Jbase = top.nest.comp1.provideJ()
J = top.driver.calc_gradient(inputs=['nest.x'],
outputs=['nest.y1', 'nest.y2'],
mode='fd')
diff = abs(J[0:4, :] - Jbase)
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = abs(J[0:4, -1] - Jbase[:, -1])
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = abs(J[4:, :-1])
assert_rel_error(self, diff.max(), 0.0, .00001)
J = top.driver.calc_gradient(inputs=['nest.x'],
outputs=['nest.y1', 'nest.y2'],
mode='forward')
diff = abs(J[0:4, :] - Jbase)
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = abs(J[0:4, -1] - Jbase[:, -1])
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = abs(J[4:, :-1])
assert_rel_error(self, diff.max(), 0.0, .00001)
Jdict = top.driver.calc_gradient(inputs=['nest.x'],
outputs=['nest.y1', 'nest.y2'],
mode='forward',
return_format='dict')
diff = Jdict['nest.y1']['nest.x'] - Jbase
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = Jdict['nest.y2']['nest.x'] - J[4:, :]
assert_rel_error(self, diff.max(), 0.0, .00001)
J = top.driver.calc_gradient(inputs=['nest.x'],
outputs=['nest.y1', 'nest.y2'],
mode='adjoint')
diff = abs(J[0:4, :] - Jbase)
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = abs(J[0:4, -1] - Jbase[:, -1])
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = abs(J[4:, :-1])
assert_rel_error(self, diff.max(), 0.0, .00001)
Jdict = top.driver.calc_gradient(inputs=['nest.x'],
outputs=['nest.y1', 'nest.y2'],
mode='adjoint',
return_format='dict')
diff = Jdict['nest.y1']['nest.x'] - Jbase
assert_rel_error(self, diff.max(), 0.0, .00001)
diff = Jdict['nest.y2']['nest.x'] - J[4:, :]
assert_rel_error(self, diff.max(), 0.0, .00001)