📄 gradchek.m
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function [gradient, delta] = gradchek(w, func, grad, varargin)
%GRADCHEK Checks a user-defined gradient function using finite differences.
%
% Description
% This function is intended as a utility for other netlab functions
% (particularly optimisation functions) to use. It enables the user to
% check whether a gradient calculation has been correctly implmented
% for a given function. GRADCHEK(W, FUNC, GRAD) checks how accurate the
% gradient GRAD of a function FUNC is at a parameter vector X. A
% central difference formula with step size 1.0e-6 is used, and the
% results for both gradient function and finite difference
% approximation are printed. The optional return value GRADIENT is the
% gradient calculated using the function GRAD and the return value
% DELTA is the difference between the functional and finite difference
% methods of calculating the graident.
%
% GRADCHEK(X, FUNC, GRAD, P1, P2, ...) allows additional arguments to
% be passed to FUNC and GRAD.
%
% See also
% CONJGRAD, GRADDESC, HMC, OLGD, QUASINEW, SCG
%
% Copyright (c) Ian T Nabney (1996-2001)
% Reasonable value for step size
epsilon = 1.0e-6;
func = fcnchk(func, length(varargin));
grad = fcnchk(grad, length(varargin));
% Treat
nparams = length(w);
deltaf = zeros(1, nparams);
step = zeros(1, nparams);
for i = 1:nparams
% Move a small way in the ith coordinate of w
step(i) = 1.0;
fplus = feval('linef', epsilon, func, w, step, varargin{:});
fminus = feval('linef', -epsilon, func, w, step, varargin{:});
% Use central difference formula for approximation
deltaf(i) = 0.5*(fplus - fminus)/epsilon;
step(i) = 0.0;
end
gradient = feval(grad, w, varargin{:});
fprintf(1, 'Checking gradient ...\n\n');
delta = gradient - deltaf;
fprintf(1, ' analytic diffs delta\n\n');
disp([gradient', deltaf', delta'])
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