When I run the following 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'
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