Home > manopt > core > getApproxGradient.m

getApproxGradient

PURPOSE ^

Computes an approximation of the gradient of the cost function at x.

SYNOPSIS ^

function approxgrad = getApproxGradient(problem, x, storedb, key)

DESCRIPTION ^

 Computes an approximation of the gradient of the cost function at x.

 function approxgrad = getApproxGradient(problem, x)
 function approxgrad = getApproxGradient(problem, x, storedb)
 function approxgrad = getApproxGradient(problem, x, storedb, key)

 Returns an approximation of the gradient at x for the cost function
 described in the problem structure.

 storedb is a StoreDB object, key is the StoreDB key to point x.

 If no approximate gradient was provided, this call is redirected to
 getGradientFD.
 
 See also: getGradientFD canGetApproxGradient

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function approxgrad = getApproxGradient(problem, x, storedb, key)
0002 % Computes an approximation of the gradient of the cost function at x.
0003 %
0004 % function approxgrad = getApproxGradient(problem, x)
0005 % function approxgrad = getApproxGradient(problem, x, storedb)
0006 % function approxgrad = getApproxGradient(problem, x, storedb, key)
0007 %
0008 % Returns an approximation of the gradient at x for the cost function
0009 % described in the problem structure.
0010 %
0011 % storedb is a StoreDB object, key is the StoreDB key to point x.
0012 %
0013 % If no approximate gradient was provided, this call is redirected to
0014 % getGradientFD.
0015 %
0016 % See also: getGradientFD canGetApproxGradient
0017 
0018 % This file is part of Manopt: www.manopt.org.
0019 % Original author: Nicolas Boumal, Nov. 1, 2016.
0020 % Contributors:
0021 % Change log:
0022 
0023     % Allow omission of the key, and even of storedb.
0024     if ~exist('key', 'var')
0025         if ~exist('storedb', 'var')
0026             storedb = StoreDB();
0027         end
0028         key = storedb.getNewKey();
0029     end
0030 
0031 
0032     if isfield(problem, 'approxgrad')
0033     %% Compute the approximate gradient using approxgrad.
0034         
0035         % Check whether this function wants to deal with storedb or not.
0036         switch nargin(problem.approxgrad);
0037             case 1
0038                 approxgrad = problem.approxgrad(x);
0039             case 2
0040                 % Obtain, pass along, and save the store for x.
0041                 store = storedb.getWithShared(key);
0042                 [approxgrad, store] = problem.approxgrad(x, store);
0043                 storedb.setWithShared(store, key);
0044             case 3
0045                 % Pass along the whole storedb (by reference), with key.
0046                 approxgrad = problem.approxgrad(x, storedb, key);
0047             otherwise
0048                 up = MException('manopt:getApproxGradient:badapproxgrad', ...
0049                     'approxgrad should accept 1, 2 or 3 inputs.');
0050                 throw(up);
0051         end
0052         
0053     else
0054     %% Try to fall back to a standard FD approximation.
0055     
0056         approxgrad = getGradientFD(problem, x, storedb, key);
0057         
0058     end
0059     
0060 end

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