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"""Component has a pass_by_obj=True parameter connected to the driver""" | |
from __future__ import print_function | |
from openmdao.api import IndepVarComp, Component, Problem, Group, Driver | |
import numpy | |
import itertools | |
import six | |
from openmdao.util.record_util import create_local_meta, update_local_meta | |
class DummyDriver(Driver): | |
def __init__(self, *args, **kwargs): | |
super(DummyDriver, self).__init__(*args, **kwargs) | |
def run(self, problem): | |
self.set_desvar('p1.x', u'var_x') | |
self.set_desvar('p2.y', 123.0) | |
metadata = create_local_meta(None, 'Driver') | |
problem.root.solve_nonlinear(metadata=metadata) | |
#self.recorders.record_iteration(problem.root, metadata) | |
class PassByObjParaboloid(Component): | |
""" Evaluates the equation f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 """ | |
def __init__(self): | |
super(PassByObjParaboloid, self).__init__() | |
self.add_param('x', val=u'var_x', pass_by_obj=True) | |
self.add_param('y', val=0.0) | |
self.add_output('f_xy', val=0.0) | |
def solve_nonlinear(self, params, unknowns, resids): | |
"""f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 | |
Optimal solution (minimum): x = 6.6667; y = -7.3333 | |
""" | |
x = hash(params['x']) | |
y = params['y'] | |
unknowns['f_xy'] = (x-3.0)**2 + x*y + (y+4.0)**2 - 3.0 | |
def linearize(self, params, unknowns, resids): | |
""" Jacobian for our paraboloid.""" | |
x = hash(params['x']) | |
y = params['y'] | |
J = {} | |
J['f_xy', 'x'] = 2.0*x - 6.0 + y | |
J['f_xy', 'y'] = 2.0*y + 8.0 + x | |
return J | |
if __name__ == "__main__": | |
top = Problem() | |
root = top.root = Group() | |
root.add('p1', IndepVarComp('x', u'var_x', pass_by_obj=True)) | |
root.add('p2', IndepVarComp('y', -4.0)) | |
root.add('p', PassByObjParaboloid()) | |
root.connect('p1.x', 'p.x') | |
root.connect('p2.y', 'p.y') | |
top.driver = DummyDriver() | |
top.driver.add_desvar('p1.x') | |
top.driver.add_desvar('p2.y') | |
top.driver.add_objective('p.f_xy') | |
top.setup() | |
top.run() | |
# print(root.p.unknowns['f_xy']) |
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