Error: Not enough input arguments.

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Ba Ba Black Sheep!
评论： Walter Roberson 2017-1-3
The following code works fine.
See the inline function fungrad.
function [x, fval, eflag, iter, fcount] =
Optimization_With_Analytic_Gradient(start_point)
x0 = start_point;
% inline function defitions
fungrad = @(x)deal(fun(x),grad(x));
% options setup
options = optimoptions( 'fminunc', ...
'Display','off',...
'OutputFcn',@bananaout,...
'Algorithm','trust-region', ...
'GradObj','on');
% calling fminunc
[x,fval,eflag,output] = fminunc(fungrad,x0,options);
iter = output.iterations;
fcount = output.funcCount;
% plot window title
title 'Rosenbrock solution via fminunc with gradient'
disp('Optimization_With_Analytic_Gradient...');
end
But, when I call it using the following code,
function out = fungrad(x)
out = deal(fun(x),grad(x));
end
It displays the following error:
Error using fungrad (line 2)
Not enough input arguments.
Error in Optimization_With_Analytic_Gradient (line 24)
[x,fval,eflag,output] = fminunc(fungrad,x0,options);
Error in main (line 48)
[x, fval, eflag, iter, fcount] =
Optimization_With_Analytic_Gradient(starting_point);
Rest of the code:
function out = fun(x)
out = 100*(x(2) - x(1)^2)^2 + (1 - x(1))^2;
end
function out = grad( x )
out = [-400*(x(2) - x(1)^2)*x(1) - 2*(1 - x(1));
200*(x(2) - x(1)^2)];
end

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采纳的回答

Walter Roberson
Walter Roberson 2017-1-3
[x,fval,eflag,output] = fminunc(@fungrad,x0,options);
However, your code will not work. Your objective function must return the gradient information only when nargout > 1. Your use of deal() always returns two outputs, and that is going to fail.
Refer to http://www.mathworks.com/matlabcentral/answers/318706-problem-running-fmincon-input-arguments-to-function-include-colon-operator#comment_417378
  2 个评论
Ba Ba Black Sheep!
Ba Ba Black Sheep! 2017-1-3
编辑：Ba Ba Black Sheep! 2017-1-3
Your objective function must return the gradient information
only when nargout > 1.
which one? banana? or, fungrad?
_
N.B. Sorry! I am absolutely new.
Walter Roberson
Walter Roberson 2017-1-3
You have
fungrad = @(x)deal(fun(x),grad(x));
so your fungrad is always returning two outputs. fungrad is being used as your objective function for fminunc . The objective function must only assign the gradient when it is asked to do so. See the example https://www.mathworks.com/help/optim/ug/fminunc.html#butzm_r-1 and notice that it tests nargout

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