Reputation: 87
I have a component that has an input that is an int so I am setting pass_by_obj = True. However, when I check derivatives with check_partial_derivatives(), it throws this error:
data = prob.check_partial_derivatives(out_stream=sys.stdout)
File "/usr/local/lib/python2.7/site-packages/openmdao/core/problem.py", line 1711, in check_partial_derivatives
jac_rev[(u_name, p_name)][idx, :] = dinputs._dat[p_name].val
TypeError: float() argument must be a string or a number
It appears to be trying to take the derivative even though it cannot. Here is a simple example:
import sys
from openmdao.api import IndepVarComp, Problem, Group, Component
class Comp(Component):
def __init__(self):
super(Comp, self).__init__()
self.add_param('x', val=0.0)
self.add_param('y', val=3, pass_by_obj=True)
self.add_output('z', val=0.0)
def solve_nonlinear(self, params, unknowns, resids):
unknowns['z'] = params['y']*params['x']
def linearize(self, params, unknowns, resids):
J = {}
J['z', 'x'] = params['y']
return J
prob = Problem()
prob.root = Group()
prob.root.add('comp', Comp(), promotes=['*'])
prob.root.add('p1', IndepVarComp('x', 0.0), promotes=['x'])
prob.root.add('p2', IndepVarComp('y', 3, pass_by_obj=True), promotes=['y'])
prob.setup(check=False)
prob['x'] = 2.0
prob['y'] = 3
prob.run()
print prob['z']
data = prob.check_partial_derivatives(out_stream=sys.stdout)
It is possible to use the check_partial_derivatives() method with components that have inputs that are specified as pass_by_obj? I don't care about the derivatives for the inputs that are specified as pass_by_obj, but I care about the other inputs.
Upvotes: 0
Views: 64
Reputation: 2202
Thanks for the report and test. This was a bug where we weren't excluding the design variables that were declared pass_by_obj. I've got a pull request up on the OpenMDAO repo with a fix. It'll probably be merged to master within a day.
EDIT -- The fix is merged. https://github.com/OpenMDAO/OpenMDAO/commit/b123b284e46aac7e15fa9bce3751f9ad9bb63b95
Upvotes: 2