Help in using nonlin_min

[Hitesh Harnal]

hi,

I am new to Octave, having just completed machine learning course on coursera. It's a great tool, thanks for building it! 

I wanted to clarify if I am using the nonlin_min correctly. I have written a trivial example below where the objective is to minimize sum of elements of vector. Constraint is that sum of squares of elements is more than zero.

%========

function [val gradient_val] = f_obj(x)

   val = sum(x);

   grad_val = ones(length(x),1);

end

%========

function [val gradient_val] = constraint(x)

  val = sumsq(x);

  grad_val = x.*2;

end

%========

x_init = ones(10,1);

X_opt = nonlin_min(@(x)f_obj(x), x_init, optimset("inequc", {@(x)constraint(x)}));

Can you please tell if this is the correct syntax for using nonlin_min? In particular will gradients that I have as the second output of f_obj and constraint functions will get used by nonlin_min? 

I have struggled past few days trying to find the right syntax and more examples, so will appreciate the help.

Thanks,

Hitesh