1 | function [C,A,b,blk] = dsdpdata(F,h) |
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2 | %DSDPDATA Internal function create DSDP data |
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3 | |
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4 | % Author Johan Löfberg |
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5 | % $Id: dsdpdata.m,v 1.3 2004/11/24 09:13:05 johanl Exp $ |
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6 | |
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7 | if ~(isempty(F) | isa(F,'lmi')) |
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8 | help lmi |
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9 | error('First argument (F) should be an lmi object. See help text above'); |
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10 | end |
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11 | |
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12 | if ~(isempty(h) | isa(h,'sdpvar')) |
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13 | help solvesdp |
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14 | error('Third argument (the objective function h) should be an sdpvar object (or empty). See help text above'); |
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15 | end |
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16 | |
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17 | [ProblemString,real_data] = catsdp(F); |
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18 | if (real_data == 0) |
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19 | error('DSDP does not support complex data') |
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20 | end |
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21 | |
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22 | % This one is used a lot |
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23 | nvars = sdpvar('nvars'); |
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24 | |
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25 | % Convert the objective |
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26 | onlyfeasible = 0; |
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27 | if isempty(h) |
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28 | c=zeros(nvars,1); |
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29 | else |
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30 | [n,m]=size(h); |
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31 | if ~((n==1) & (m==1)) |
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32 | error('Scalar expression to minimize please.'); |
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33 | else |
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34 | lmi_variables = getvariables(h); |
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35 | c = zeros(nvars,1); |
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36 | for i=1:length(lmi_variables) |
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37 | c(lmi_variables(i))=getbasematrix(h,lmi_variables(i)); |
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38 | end; |
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39 | end |
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40 | end |
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41 | |
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42 | [F_struc,K,F_blksz] = lmi2spstruct(F); |
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43 | |
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44 | % Which sdpvar variables are actually in the problem |
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45 | used_variables_LMI = find(any(F_struc(:,2:end),1)); |
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46 | used_variables_obj = find(any(c',1)); |
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47 | used_variables = uniquestripped([used_variables_LMI used_variables_obj]); |
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48 | |
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49 | % Check for unbounded variables |
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50 | unbounded_variables = setdiff(used_variables_obj,used_variables_LMI); |
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51 | if ~isempty(unbounded_variables) |
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52 | % Remove unbounded variable from problem |
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53 | used_variables = setdiff(used_variables,unbounded_variables); |
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54 | end |
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55 | |
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56 | % Pick out the necessary rows |
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57 | if length(used_variables)<nvars |
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58 | c = c(used_variables); |
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59 | F_struc = sparse(F_struc(:,[1 1+[used_variables]])); |
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60 | end |
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61 | |
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62 | |
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63 | if (K.f>0) |
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64 | % Extract the inequalities |
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65 | A_equ = F_struc(1:K.f,2:end); |
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66 | b_equ = -F_struc(1:K.f,1); |
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67 | |
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68 | % Find feasible (turn off annoying warning on PC) |
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69 | % Using method from Nocedal-Wright book |
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70 | showprogress('Solving equalities',options.ShowProgress); |
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71 | [Q,R] = qr(A_equ'); |
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72 | n = size(R,2); |
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73 | Q1 = Q(:,1:n); |
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74 | R = R(1:n,:); |
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75 | x_equ = Q1*(R'\b_equ); |
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76 | % Exit if no consistent solution exist |
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77 | if (norm(A_equ*x_equ-b_equ)>sqrt(eps)) |
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78 | error('Linear constraints inconsistent.'); |
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79 | return |
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80 | end |
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81 | % We dont need the rows for equalities anymore |
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82 | F_struc = F_struc(K.f+1:end,:); |
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83 | K.f = 0; |
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84 | |
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85 | % We found a new basis |
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86 | H = Q(:,n+1:end); % New basis |
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87 | |
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88 | % objective in new basis |
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89 | c = H'*c; |
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90 | % LMI in new basis |
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91 | F_struc = [F_struc*[1;x_equ] F_struc(:,2:end)*H]; |
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92 | else |
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93 | % For simpliciy we introduce a dummy coordinate change |
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94 | x_equ = 0; |
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95 | H = 1; |
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96 | end |
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97 | |
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98 | % Convert from SP format (same format as SDPT3-2.3) |
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99 | [C,A,b,blk] = sp2sdpt323(F_struc,F_blksz,c); |
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