Problem using ExternalCodeComp in Openmdao - openmdao

Question

I am trying out the example problem for ExternalCodeComp as given in openmdao docs.
The optimization code is
import openmdao.api as om
from openmdao.components.tests.test_external_code_comp import ParaboloidExternalCodeCompFD
prob = om.Problem()
model = prob.model
model.add_subsystem('p', ParaboloidExternalCodeCompFD(), promotes_inputs=['x', 'y'])
# find optimal solution with SciPy optimize
# solution (minimum): x = 6.6667; y = -7.3333
prob.driver = om.ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'SLSQP'
prob.model.add_design_var('p.x', lower=-50, upper=50)
prob.model.add_design_var('p.y', lower=-50, upper=50)
prob.model.add_objective('p.f_xy')
prob.driver.options['tol'] = 1e-9
prob.driver.options['disp'] = True
prob.setup()
# Set input values
prob.set_val('p.x', 3.0)
prob.set_val('p.y', -4.0)
prob.run_driver()
print(prob.get_val('p.x'))
print(prob.get_val('p.y'))
However, I get the following error at prob.setup().
Exception has occurred: RuntimeError
Group (<model>): Output not found for design variable 'p.x'.
What does this mean ? I dont know if I am missing something basic. The problem only occurs when I try to optimize it. There is no problem when I just use the external code in a model (as given in the docs).

Answer 1

In this line you promoted the inputs x and y
model.add_subsystem('p', ParaboloidExternalCodeCompFD(), promotes_inputs=['x', 'y'])
Notice that you did not promote the output f_xy
so from the top level of the model the correct paths are:
p.f_xy for the output, but x and y for the inputs.
Thus the correct way to add the design variables and set the values was to use x and y.
import openmdao.api as om
from openmdao.components.tests.test_external_code_comp import ParaboloidExternalCodeCompFD
prob = om.Problem()
model = prob.model
model.add_subsystem('p', ParaboloidExternalCodeCompFD(), promotes_inputs=['x', 'y'])
# find optimal solution with SciPy optimize
# solution (minimum): x = 6.6667; y = -7.3333
prob.driver = om.ScipyOptimizeDriver()
prob.driver.options['optimizer'] = 'SLSQP'
prob.model.add_design_var('x', lower=-50, upper=50)
prob.model.add_design_var('y', lower=-50, upper=50)
prob.model.add_objective('p.f_xy')
prob.driver.options['tol'] = 1e-9
prob.driver.options['disp'] = True
prob.setup()
# Set input values
prob.set_val('x', 3.0)
prob.set_val('y', -4.0)
prob.run_driver()
print(prob.get_val('x'))
print(prob.get_val('y'))