Source code for openmdao.test_suite.components.paraboloid

""" Definition of the Paraboloid component, which evaluates the equation
(x-3)^2 + xy + (y+4)^2 = 3
"""
from __future__ import division, print_function

import openmdao.api as om


[docs]class Paraboloid(om.ExplicitComponent): """ Evaluates the equation f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3. """
[docs] def setup(self): self.add_input('x', val=0.0) self.add_input('y', val=0.0) self.add_output('f_xy', val=0.0) self.declare_partials('*', '*')
[docs] def compute(self, inputs, outputs): """ f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 Optimal solution (minimum): x = 6.6667; y = -7.3333 """ x = inputs['x'] y = inputs['y'] outputs['f_xy'] = (x-3.0)**2 + x*y + (y+4.0)**2 - 3.0
[docs] def compute_partials(self, inputs, partials): """ Jacobian for our paraboloid. """ x = inputs['x'] y = inputs['y'] partials['f_xy', 'x'] = 2.0*x - 6.0 + y partials['f_xy', 'y'] = 2.0*y + 8.0 + x
if __name__ == "__main__": model = om.Group() ivc = om.IndepVarComp() ivc.add_output('x', 3.0) ivc.add_output('y', -4.0) model.add_subsystem('des_vars', ivc) model.add_subsystem('parab_comp', Paraboloid()) model.connect('des_vars.x', 'parab_comp.x') model.connect('des_vars.y', 'parab_comp.y') prob = om.Problem(model) prob.driver = om.ScipyOptimizeDriver() # so 'openmdao cite' will report it for cite docs prob.setup() prob.run_model() print(prob['parab_comp.f_xy']) prob['des_vars.x'] = 5.0 prob['des_vars.y'] = -2.0 prob.run_model() print(prob['parab_comp.f_xy'])