128 lines
4.0 KiB
Matlab
Executable File
128 lines
4.0 KiB
Matlab
Executable File
function [properties,F,arguments,fcn]=model(X,method,options,extstruct,w)
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%MODEL Internal function to extracts nonlinear operator models
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%
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% [properties,F] = model(x)
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%
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% MODEL returns the constraints needed to model a variable related to an
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% extended operator such as min, max, abs, norm, geomean, ...
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%
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% Examples :
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%
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% sdpvar x y;
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% t = min(x,y);
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% [properties,F] = model(t)
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% Gives F = [t<=x, t<=y]
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extvar = getvariables(X);
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arguments = cell(1,length(extvar));
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properties = cell(1,length(extvar));
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if nargin<2
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method = 'graph';
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end
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if nargin < 3
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options = [];
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end
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if nargin < 5
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% Not used
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w = [];
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end
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if nargin<4
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extstruct = yalmip('extstruct',extvar);
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elseif isempty(extstruct)
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extstruct = yalmip('extstruct',extvar);
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end
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if isempty(extstruct)
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error('This is not a nonlinear operator variable');
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end
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fcn = extstruct.fcn;
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try
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n = yalmip('nvars');
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[F,properties,arguments] = feval(fcn,method,extstruct.var,extstruct.arg{1:end-1});
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if isa(F,'constraint')
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F = lmi(F);
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end
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newAux = n+1:yalmip('nvars');
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involved = getvariables(extstruct.arg{1});
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for i = 2:length(extstruct.arg)-1
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vars = getvariables(extstruct.arg{i});
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if ~isempty(vars)
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involved = union(involved,vars);
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end
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end
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if ~isempty(options)
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if ~(strcmp(options.robust.auxreduce,'none'))
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% This info is only needed when we do advanced Robust optimization
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yalmip('setdependence',[getvariables(extstruct.var) newAux],involved);
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yalmip('setdependence',[getvariables(extstruct.var)],newAux);
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end
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end
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catch
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error(['Failed when trying to create a model for the "' extstruct.fcn '" operator']);
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end
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% Make sure all operators have these properties
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if ~isempty(properties)
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if ~iscell(properties)
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properties = {properties};
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end
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for i = 1:length(properties)
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properties{i}.name = fcn;
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properties{i} = assertProperty(properties{i},'definiteness','none');
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properties{i} = assertProperty(properties{i},'convexity','none');
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properties{i} = assertProperty(properties{i},'monotonicity','none');
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properties{i} = assertProperty(properties{i},'derivative',[]);
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properties{i} = assertProperty(properties{i},'inverse',[]);
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properties{i} = assertProperty(properties{i},'models',getvariables(extstruct.var));
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properties{i} = assertProperty(properties{i},'convexhull',[]);
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properties{i} = assertProperty(properties{i},'bounds',[]);
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properties{i} = assertProperty(properties{i},'domain',[-inf inf]);
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switch properties{i}.definiteness
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case 'positive'
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properties{i} = assertProperty(properties{i},'range',[0 inf]);
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case 'negative'
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properties{i} = assertProperty(properties{i},'range',[-inf 0]);
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otherwise
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properties{i} = assertProperty(properties{i},'range',[-inf inf]);
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end
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properties{i} = assertProperty(properties{i},'model','unspecified');
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end
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end
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% Normalize the callback expression and check for some obsoleted stuff
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if ~isempty(properties)
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if isequal(properties{1}.model,'callback')
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F_normalizing = NormalizeCallback(method,extstruct.var,extstruct.arg{:},options.usex0);
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F = F + F_normalizing;
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end
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if length(extstruct.computes)>1
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for i = 1:length(properties)
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properties{i}.models = extstruct.computes;
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end
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end
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for i = 1:length(properties)
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if ~any(strcmpi(properties{i}.convexity,{'convex','concave','none'}))
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disp('More cleaning, strange convextiy returned...Report bug in model.m')
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error('More cleaning, strange convextiy returned...Report bug in model.m')
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end
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end
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end
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% This is useful in MPT
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if ~isempty(F)
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F = tag(F,['Expansion of ' extstruct.fcn]);
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end
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if ~isempty(properties)
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% properties = properties{1};
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end
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function properties = assertProperty(properties,checkfor,default);
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if ~isfield(properties,checkfor)
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properties = setfield(properties,checkfor,default);
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end |