export.m

matlab波形优化算法经常要用到的matlab toolbox工具箱:yalmip

function [model,recoverdata,diagnostic,interfacedata] = export(varargin)
%EXPORT  Exports YALMIP problem to solver specific format
%
%   [MODEL,RECOVERYMODEL,DIAGNOSTIC,INTERNAL] = EXPORT(F,h,options) is the common command to
%   export optimization problems of the following kind
%
%    min        h
%    subject to
%            F >(=) 0
%
%
%   The MODEL is exported in the format defined by the solver chosen
%   in the options structure, or automatically chosen by YALMIP.
%
%   If the solver format not is support by EXPORT,the YALMIP model used to
%   call the solver is returned)
%
%   If YALMIP by some reason failed to generate a model, the DIAGNOSTIC 
%   variable will be non-empty.
%
%   The fourth output is the internal model used by YALMIP to communicate
%   with the generalized solver interfaces.
%
%   The RECOVERYMODEL is used to relate a solution of the exported model
%   to the original variables in YALMIP.

% Arrrgh, new format with logdet much better, but we have to
% take care of old code, requires some testing...
varargin = combatible({varargin{:}});
nargin = length(varargin);
% *********************************
% CHECK INPUT
% *********************************
if nargin<1
    help export
    return
else
    F = varargin{1};
    % Check for wrong syntax
    if ~isempty(F) & ~isa(F,'lmi') & ~isa(F,'constraint')
        error('First argument should be a SET object')
    end

    if isa(F,'constraint')
        F = set(F);
    end
end

model = [];
recoverdata = [];
diagnostic = [];
interfacedata = [];

if nargin>=2
    h = varargin{2};
    if isa(h,'double')
        h = [];
    end
    if ~(isempty(h) | isa(h,'sdpvar') | isa(h,'logdet'))
        error('Second argument (the objective function h) should be an sdpvar or logdet object (or empty).');
    end
    if isa(h,'logdet')
        logdetStruct.P  = getP(h);
        logdetStruct.gain  = getgain(h);
        if any(logdetStruct.gain>0)
            warning('Perhaps you mean -logdet(P)...')
            diagnostic.yalmiptime = etime(clock,yalmiptime);
            diagnostic.solvertime = 0;
            diagnostic.info = yalmiperror(-2,'YALMIP');
            diagnostic.problem = -2;
            return
        end
        h = getcx(h);       
        if isempty(F)
           F = set([]);
        end
        
    else
      logdetStruct = [];
    end
else
    h = [];
    logdetStruct = [];
end

if nargin>=3
    options = varargin{3};
    if ~(isempty(options) | isa(options,'struct'))
        error('Third argument (options) should be an sdpsettings struct (or empty).');
    end
    if isempty(options)
        options = sdpsettings;
    end
else
    options = sdpsettings;
end
options.solver = lower(options.solver);

if nargin<6
    if isequal(options.solver,'')
        findallsolvers = 1;
    else
        findallsolvers = 0;
    end
else
    findallsolvers = varargin{6};
end

% Just for safety
if isempty(F) & isempty(logdetStruct)
    F = lmi;
end

% ******************************************
% COMPILE IN GENERALIZED YALMIP FORMAT
% ******************************************
if ~isempty(F) & any(is(F,'parametric'))
    % Special code, do not mix with standard case, in case there is some
    % bug (this has not been tested)
    [interfacedata,recoverdata,solver,diagnostic,F] = compileinterfacedata(F,[],logdetStruct,h,options,findallsolvers,1);
else
    [interfacedata,recoverdata,solver,diagnostic,F] = compileinterfacedata(F,[],logdetStruct,h,options,findallsolvers);
end

if ~isempty(diagnostic)   
    model = [];
    recoverdata = [];
    return
end

% Not official yet
if nargin == 5
    model=interfacedata;
    return
end

% ******************************************
% CONVERT
% ******************************************
switch lower(solver.tag)
    
    case {'mosek-socp','mosek-lp/qp','mosek-geometric'}
        model.prob = yalmip2mosek(interfacedata);
                
    case 'quadprog'
        [model.Q,model.c,model.A,model.b,model.Aeq,model.beq,model.lb,model.ub,model.ops] = yalmip2quadprog(interfacedata);
        
    case {'sedumi-1.05','sedumi-1.1'}        
        model = yalmip2sedumi(interfacedata);
        
    case 'csdp'        
        model = yalmip2csdp(interfacedata);       
        
    case 'dsdp-5'  
        model = yalmip2dsdp(interfacedata);

    case 'sdpa-m'        
        model = yalmip2sdpa(interfacedata);
                        
    case {'sdpt3-3.1','sdpt3-4'}
        % Convert from internal (sedumi-like) format
        if isequal(interfacedata.K.m,0)
           model = yalmip2sdpt3(interfacedata);
        else
            error('MAXDET models still not supported in SDPT3 export')
        end

    case 'glpk-glpkmex'        
        model = yalmip2glpkmex(interfacedata);
                
    case 'pensdp-penopt'        
        model = yalmip2pensdp(interfacedata);
                
    case 'mpt'
        interfacedata.parametric_variables = find(ismember(recoverdata.used_variables,getvariables(F(find(is(F,'parametric'))))));
        interfacedata.requested_variables = [];
        model = yalmip2mpt(interfacedata);
                
    case 'penbmi-penopt'        
        model.penstruct = sedumi2penbmi(interfacedata.F_struc,interfacedata.c,interfacedata.Q,interfacedata.K,interfacedata.monomtable,interfacedata.options,interfacedata.x0);
               
    otherwise
        model = [];
end



function newinputformat = combatible(varargin)

varargin = varargin{1};

classification = 0;
% 0 : Ambigious
% 1 : Old
% 2 : New

% Try some fast methods to determine...
m = length(varargin);
if m==1
    classification = 2;
elseif m>=3 & isstruct(varargin{3})
    classification = 2;
elseif m>=4 & isstruct(varargin{4})
    classification = 1;
elseif m>=2 & isa(varargin{2},'lmi')
    classification = 1;
elseif m>=3 & isa(varargin{3},'sdpvar')
    classification = 1;
elseif m>=2 & isa(varargin{2},'sdpvar') & min(size(varargin{2}))==1
    classification = 2;
elseif m>=2 & isa(varargin{2},'sdpvar') & prod(size(varargin{2}))>=1
    classification = 1;
elseif m>=2 & isa(varargin{2},'logdet')
    classification = 2;
elseif m==2 & isempty(varargin{2})
    classification = 2;
end

if classification==0
    warning('I might have interpreted this problem wrong due to the new input format in version 3. To get rid of this warning, use an options structure');
    classification = 2;
end

if classification==2
    newinputformat = varargin;
else
    newinputformat = varargin;
    P = varargin{2};
    % 99.9% of the cases....
    if isempty(P)
        newinputformat = {newinputformat{[1 3:end]}};
    else
        if isa(P,'lmi')
            P = sdpvar(P);
        end
        if m>=3
            cxP = newinputformat{3}-logdet(P);
            newinputformat{3}=cxP;
        else
            cxP = -logdet(P);
            newinputformat{3}=cxP;
        end
        newinputformat = {newinputformat{[1 3:end]}};
    end
end