Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/netlab3.3/gradchek.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 function [gradient, delta] = gradchek(w, func, grad, varargin) | |
2 %GRADCHEK Checks a user-defined gradient function using finite differences. | |
3 % | |
4 % Description | |
5 % This function is intended as a utility for other netlab functions | |
6 % (particularly optimisation functions) to use. It enables the user to | |
7 % check whether a gradient calculation has been correctly implmented | |
8 % for a given function. GRADCHEK(W, FUNC, GRAD) checks how accurate the | |
9 % gradient GRAD of a function FUNC is at a parameter vector X. A | |
10 % central difference formula with step size 1.0e-6 is used, and the | |
11 % results for both gradient function and finite difference | |
12 % approximation are printed. The optional return value GRADIENT is the | |
13 % gradient calculated using the function GRAD and the return value | |
14 % DELTA is the difference between the functional and finite difference | |
15 % methods of calculating the graident. | |
16 % | |
17 % GRADCHEK(X, FUNC, GRAD, P1, P2, ...) allows additional arguments to | |
18 % be passed to FUNC and GRAD. | |
19 % | |
20 % See also | |
21 % CONJGRAD, GRADDESC, HMC, OLGD, QUASINEW, SCG | |
22 % | |
23 | |
24 % Copyright (c) Ian T Nabney (1996-2001) | |
25 | |
26 % Reasonable value for step size | |
27 epsilon = 1.0e-6; | |
28 | |
29 func = fcnchk(func, length(varargin)); | |
30 grad = fcnchk(grad, length(varargin)); | |
31 | |
32 % Treat | |
33 nparams = length(w); | |
34 deltaf = zeros(1, nparams); | |
35 step = zeros(1, nparams); | |
36 for i = 1:nparams | |
37 % Move a small way in the ith coordinate of w | |
38 step(i) = 1.0; | |
39 fplus = feval('linef', epsilon, func, w, step, varargin{:}); | |
40 fminus = feval('linef', -epsilon, func, w, step, varargin{:}); | |
41 % Use central difference formula for approximation | |
42 deltaf(i) = 0.5*(fplus - fminus)/epsilon; | |
43 step(i) = 0.0; | |
44 end | |
45 gradient = feval(grad, w, varargin{:}); | |
46 fprintf(1, 'Checking gradient ...\n\n'); | |
47 delta = gradient - deltaf; | |
48 fprintf(1, ' analytic diffs delta\n\n'); | |
49 disp([gradient', deltaf', delta']) |