manoptsolve

 Gateway helper function to call a Manopt solver, chosen in the options.

 function [x, cost, info, options] = manoptsolve(problem)
 function [x, cost, info, options] = manoptsolve(problem, x0)
 function [x, cost, info, options] = manoptsolve(problem, x0, options)
 function [x, cost, info, options] = manoptsolve(problem, [], options)

 Depending on what is available in the Manopt problem structure, one of
 the Manopt solvers will be called and the outputs passed along. It is
 also possible to force the choice of a solver by specifying it in the
 options structure. For example:

    options.solver = @trustregions;

 Simply specify a function handle to a Manopt solver.

 See also: trustregions conjugategradient steepestdescent

0001 function [x, cost, info, options] = manoptsolve(problem, x0, options)
0002 % Gateway helper function to call a Manopt solver, chosen in the options.
0003 %
0004 % function [x, cost, info, options] = manoptsolve(problem)
0005 % function [x, cost, info, options] = manoptsolve(problem, x0)
0006 % function [x, cost, info, options] = manoptsolve(problem, x0, options)
0007 % function [x, cost, info, options] = manoptsolve(problem, [], options)
0008 %
0009 % Depending on what is available in the Manopt problem structure, one of
0010 % the Manopt solvers will be called and the outputs passed along. It is
0011 % also possible to force the choice of a solver by specifying it in the
0012 % options structure. For example:
0013 %
0014 %    options.solver = @trustregions;
0015 %
0016 % Simply specify a function handle to a Manopt solver.
0017 %
0018 % See also: trustregions conjugategradient steepestdescent
0019 
0020 % This file is part of Manopt: www.manopt.org.
0021 % Original author: Nicolas Boumal, Aug. 13, 2014.
0022 % Contributors:
0023 % Change log:
0024 
0025     % At the very least, we need a cost function.
0026     if ~canGetCost(problem)
0027         error('The problem structure must specify a cost function.');
0028     end
0029     
0030     % Depending on the number of differentials available, pick a different
0031     % default solver.
0032     if ~canGetGradient(problem)
0033         localdefaults.solver = @neldermead;
0034     elseif ~canGetHessian(problem)
0035         localdefaults.solver = @conjugategradient;
0036     else
0037         localdefaults.solver = @trustregions;
0038     end
0039     
0040     % Merge local defaults with user options, if any.
0041     if ~exist('options', 'var') || isempty(options)
0042         options = struct();
0043     end
0044     options = mergeOptions(localdefaults, options);
0045     
0046     % If no initial guess was specified, prepare the empty one.
0047     if ~exist('x0', 'var')
0048         x0 = [];
0049     end
0050     
0051     % Issue the actual call.
0052     [x, cost, info, options] = options.solver(problem, x0, options);
0053     
0054 end