76 lines
1.7 KiB
Mathematica
76 lines
1.7 KiB
Mathematica
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function assign(X,value,ls)
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%ASSIGN Assigns a numerical value to an sdpvar
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%
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% ASSIGN(X,value) Tries to set the free variables in X so that
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% double(X)=value. Notice that other variables
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% sharing the same free variables will be affected.
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% If the assignment is infeasible, an error message
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% will be issued.
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%
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% ASSIGN(X,value,1) Least square assignment.
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%
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% After assigning values to decision variables, these can be communicated
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% to the solver as an initial guess by turning on the option 'usex0' in the
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% options structure sent to optimize.
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if nargin<3
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ls = 0;
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end
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if ~isa(X,'sdpvar')
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error('First argument should be an SDPVAR object.');
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end
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if isa(value,'logical')
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value = double(value);
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end
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if ~isnumeric(value)
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error('Second argument should be NUMERIC.');
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end
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if prod(size(value)) == 1
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value = repmat(value,size(X));
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end
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if isempty(value)
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return
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end
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if ~isequal(size(X),size(value))
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error('Both arguments must have same size')
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end
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if ~isa(X,'sdpvar')
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error('First arguments must be an sdpvar object')
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end
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if is(X,'complex')
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assign(real(X),real(value));
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assign(imag(X),imag(value));
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return
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end
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x_lmi_variables = X.lmi_variables;
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b = value(:)-X.basis(:,1);
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A = X.basis(:,2:end);
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feas_var = A\b;
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% Improve
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e = A*feas_var-b;
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de = A\e;
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feas_var = feas_var-de;
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if ~ls
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if norm(A*feas_var-b)>sqrt(eps)
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error('Inconsistent assignment')
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end
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end
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sol = yalmip('getsolution');
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keep_these = find(~ismember(sol.variables,x_lmi_variables));
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sol.optvar = [sol.optvar(keep_these);feas_var(:)];
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sol.variables = [sol.variables(keep_these);x_lmi_variables(:)];
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yalmip('setallsolution',sol);
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