48 lines
1.6 KiB
Mathematica
48 lines
1.6 KiB
Mathematica
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function varargout = sosmodel(varargin)
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%SOSMODEL Derive sum-of-squares model without solving it
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%
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% [F,obj,m] = sosmodel(F,h,options,params,monomials) compiles the SOS
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% problem (i.e., derives the SDP model) without actually solving it
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%
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% Inputs
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% F : The model involving SOS constraints
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% h : Objective function (function of params) [optional]
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% options : SDPSETTINGS structure [optional]
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% params : Parametric variables in model [optional]
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% monomials : Prespecified monomials to be used [optional]
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%
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% Outputs
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% F : Constraints defining the problem
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% h : Objective function
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% m : Monomials used in the decomposition
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%
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%
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% NOTE: If you do not specify any options structure or specify sos.model
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% as default 0 an image model representation will be used (sos.model = 2).
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% With this, the compiled model is expressed in terms of the original
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% variables (with kernel model, a dual problem is derived, and thus no
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% original variables are used)
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%
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% See also SOLVESOS, OPTIMIZE, SOS, OPTIMIZER
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% When sosmodel is used, default is to return a model expressed in the
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% original variables, i.e., image space model
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if nargin > 3
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ops = varargin{3};
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if isempty(ops)
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ops = sdpsettings('sos.model',2);
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varargin{3} = ops;
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else
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try
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if isequal(ops.sos.model,0)
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ops.sos.model = 2;
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end
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varargin{3} = ops;
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catch
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end
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end
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else
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ops = sdpsettings('sos.model',2);
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varargin{3} = ops;
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end
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[varargout{1:nargout}] = compilesos(varargin{:});
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