65 lines
2.1 KiB
Mathematica
65 lines
2.1 KiB
Mathematica
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function [Nbegcol,Nlencol,Nrowndx,Nobjcnt,Nobjndx,cJacobian] = jacSparsity(interfacedata)
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linear = setdiff(find(interfacedata.variabletype == 0),interfacedata.evalVariables);
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oJacobian = zeros(length(linear),1);
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variabletype = interfacedata.variabletype;
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c = interfacedata.c;
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F_struc = interfacedata.F_struc;
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m = size(interfacedata.F_struc,1);
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nonlinear = variabletype;
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nonlinear(interfacedata.evalVariables) = 1;
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for i = find(c(:)')%1:length(c)
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% if c(i)
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if nonlinear(i)%variabletype(i) | ismember(i,interfacedata.evalVariables)
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if ismember(i,interfacedata.evalVariables)
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j = find(i == interfacedata.evalVariables);
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variables = interfacedata.evalMap{j}.variableIndex;
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else
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variables = find(interfacedata.monomtable(i,:));
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end
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oJacobian(find(ismember(linear,variables))) = 1;
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end
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% end
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end
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if m > 0
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cJacobian = zeros(m,length(linear));
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for i = 1:size(F_struc,2)-1
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%if nonlinear(i)%variabletype(i) | ismembc(i,interfacedata.evalVariables)
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f = F_struc(:,i+1);
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for j = find(f(:)')%1:size(F_struc,1)
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% if f(j)%F_struc(j,i+1)
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% if variabletype(i) | ismembc(i,interfacedata.evalVariables)
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if ismembc(i,interfacedata.evalVariables)
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k = find(i == interfacedata.evalVariables);
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variables = interfacedata.evalMap{k}.variableIndex;
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elseif nonlinear(i)
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variables = find(interfacedata.monomtable(i,:));
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else
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variables = i;;
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end
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cJacobian(j,find(ismembc(linear,variables))) = 1;
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end
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% else
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% end
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end
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[Nbegcol,Nlencol,Nrowndx] = lindosparse(cJacobian);
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else
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cJacobian = [];
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Nbegcol = [];
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Nrowndx = [];
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Nlencol = [];
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Nbegcol = [Nbegcol sum(Nlencol)];
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end
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oJacobian = double(oJacobian | any(interfacedata.Q(linear,linear),2));
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Nobjndx = find(oJacobian) - 1;
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Nobjcnt = length(Nobjndx);
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if isempty(Nobjndx)
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Nobjndx = [];
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end
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