When I run the following simple NLOPT example in python :
import numpy as np
import nlopt
n = 2
localopt_feval_max = 10
lb = np.array([-1, -1])
ub = np.array([1, 1])
def myfunc(x, grad):
return -1
opt = nlopt.opt(nlopt.LN_NELDERMEAD, n)
opt.set_lower_bounds(lb)
opt.set_upper_bounds(ub)
opt.set_maxeval(localopt_feval_max)
opt.set_min_objective(myfunc)
opt.set_xtol_rel(1e-8)
x0 = np.array([0,0])
x = opt.optimize(x0)
I get an error:
"ValueError: nlopt invalid argument"
The only suggestion given by the reference here:
http://ab-initio.mit.edu/wiki/index.php/NLopt_Python_Reference
is that the lower bounds might be bigger than the upper bounds, or there is an unknown algorithm (neither of which is the case here). I am running the following versions of Python, NLOPT, and NumPy
>>> sys.version
'3.4.0 (default, Apr 11 2014, 13:05:11) \n[GCC 4.8.2]'
>>> nlopt.__version__
'2.4.2'
>>> np.__version__
'1.8.2'
By changing the function declaration to
def myfunc(x, grad):
return -1.0
everything works. So NLopt can not handle objectives that return python integer
instead of float
I feel like NLopt should be able to cast integer objective function values as float
. If not this, then at least a TypeError
should be raised instead of a ValueError: nlopt invalid argument
.