1 | function sys = sdpvar(varargin) |
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2 | %SDPVAR Create symbolic decision variable |
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3 | % |
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4 | % You can create a sdpvar variable by: |
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5 | % X = SDPVAR(n) Symmetric nxn matrix |
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6 | % X = SDPVAR(n,n) Symmetric nxn matrix |
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7 | % X = SDPVAR(n,m) Full nxm matrix (n~=m) |
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8 | % |
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9 | % Definition of multiple scalars can be simplified |
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10 | % SDPVAR x y z w |
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11 | % |
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12 | % The parametrizations supported are |
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13 | % X = SDPVAR(n,n,'full') Full nxn matrix |
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14 | % X = SDPVAR(n,n,'symmetric') Symmetric nxn matrix |
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15 | % X = SDPVAR(n,n,'toeplitz') Symmetric Toeplitz |
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16 | % X = SDPVAR(n,n,'hankel') Symmetric Hankel |
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17 | % X = SDPVAR(n,n,'skew') Skew-symmetric |
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18 | % |
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19 | % The letters 'sy','f','ha', 't' and 'sk' are searched for in the third argument |
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20 | % hence sdpvar(n,n,'toeplitz') gives the same result as sdpvar(n,n,'t') |
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21 | % |
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22 | % Only square Toeplitz and Hankel matries are supported |
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23 | % |
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24 | % A scalar is defined as a 1x1 matrix |
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25 | % |
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26 | % Higher-dimensional matrices are also supported, although this currently |
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27 | % is an experimental feature with limited use. The type flag applies to |
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28 | % the lowest level slice. |
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29 | % |
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30 | % X = SDPVAR(n,n,n,'full') Full nxnxn matrix |
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31 | % |
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32 | % In addition to the matrix type, a fourth argument |
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33 | % can be used to obtain a complex matrix. All the |
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34 | % matrix types above apply to a complex matrix, and |
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35 | % in addition a Hermitian type is added |
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36 | % |
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37 | % X = SDPVAR(n,n,'hermitian','complex') Complex Hermitian nxn matrix (X=X'=conj(X.')) |
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38 | % |
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39 | % The other types are obtained as above |
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40 | % X = SDPVAR(n,n,'symmetric','complex') Complex symmetric nxn matrix (X=X.') |
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41 | % X = SDPVAR(n,n,'full','complex') Complex full nxn matrix |
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42 | % ... and the same for Toeplitz, Hankel and skew-symmetric |
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43 | % |
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44 | % See also @SDPVAR/SET, INTVAR, BINVAR, methods('sdpvar'), SEE |
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45 | |
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46 | % Author Johan Löfberg |
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47 | % $Id: ncvar.m,v 1.4 2006/08/28 13:48:38 joloef Exp $ |
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48 | |
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49 | superiorto('sdpvar'); |
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50 | if nargin==0 |
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51 | return |
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52 | end |
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53 | |
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54 | if isstruct(varargin{1}) |
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55 | sys = class(varargin{1},'ncvar'); |
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56 | return |
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57 | end |
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58 | |
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59 | % To speed up dualization, we keep track of primal SDP cones |
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60 | % [0 0] : Nothing known (cleared in some operator, or none-cone to start with) |
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61 | % [1 0] : Primal cone |
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62 | % [1 1] : Primal cone + DOUBLE |
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63 | % [1 2 x] : Primal cone + SDPVAR |
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64 | % [-1 1] : -Primal cone + DOUBLE |
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65 | % [-1 2 x] : -Primal cone + SDPVAR |
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66 | |
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67 | conicinfo = [0 0]; |
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68 | |
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69 | if ischar(varargin{1}) |
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70 | switch varargin{1} |
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71 | case 'clear' |
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72 | disp('Obsolete comand'); |
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73 | return |
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74 | case 'nvars' |
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75 | sys = yalmip('nvars');%THIS IS OBSAOLETE AND SHOULD NOT BE USED |
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76 | return |
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77 | otherwise |
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78 | n = length(varargin); |
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79 | varnames = varargin; |
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80 | for k = 1:n |
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81 | varcmd{k}='(1,1)'; |
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82 | lp=findstr(varargin{k},'('); |
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83 | rp=findstr(varargin{k},')'); |
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84 | if isempty(lp) & isempty(rp) |
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85 | if ~isvarname(varargin{k}) |
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86 | error('Not a valid variable name.') |
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87 | end |
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88 | else |
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89 | if (~isempty(lp))&(~isempty(rp)) |
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90 | if min(lp)<max(rp) |
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91 | varnames{k} = varargin{k}(1:lp-1); |
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92 | varcmd{k}=varargin{k}(lp:rp); |
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93 | else |
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94 | error('Not a valid variable name.') |
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95 | end |
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96 | else |
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97 | error('Not a valid variable name.') |
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98 | end |
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99 | end |
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100 | end |
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101 | for k = 1:n |
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102 | if isequal(varnames{k},'i') | isequal(varnames{k},'j') |
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103 | if length(dbstack) == 1 |
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104 | assignin('caller',varnames{k},eval(['sdpvar' varcmd{k}])); |
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105 | else |
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106 | error(['Due to a bug in MATLAB, use ' varnames{k} ' = sdpvar' varcmd{k} ' instead.']); |
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107 | end |
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108 | else |
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109 | assignin('caller',varnames{k},eval(['ncvar' varcmd{k}])); |
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110 | end |
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111 | end |
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112 | return |
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113 | end |
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114 | end |
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115 | |
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116 | % ************************************************************************* |
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117 | % Maybe new NDSDPVAR syntax |
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118 | % ************************************************************************* |
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119 | if nargin > 2 & isa(varargin{3},'double') & ~isempty(varargin{3}) |
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120 | sys = ndsdpvar(varargin{:}); |
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121 | return |
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122 | end |
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123 | |
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124 | |
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125 | % Supported matrix types |
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126 | % - symm |
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127 | % - full |
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128 | % - skew |
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129 | % - hank |
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130 | % - toep |
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131 | switch nargin |
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132 | case 1 %Bug in MATLAB 5.3!! sdpvar called from horzcat!!!!???? |
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133 | if isempty(varargin{1}) |
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134 | sys = varargin{1}; |
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135 | return |
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136 | end |
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137 | if isa(varargin{1},'sdpvar') |
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138 | sys = varargin{1}; |
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139 | sys.typeflag = 0; |
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140 | return |
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141 | end |
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142 | n = varargin{1}; |
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143 | m = varargin{1}; |
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144 | if sum(n.*m)==0 |
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145 | sys = zeros(n,m); |
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146 | return |
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147 | end |
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148 | if (n==m) |
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149 | matrix_type = 'symm'; |
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150 | nvar = sum(n.*(n+1)/2); |
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151 | conicinfo = [1 0]; |
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152 | else |
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153 | matrix_type = 'full'; |
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154 | nvar = sum(n.*m); |
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155 | end |
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156 | case 2 |
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157 | n = varargin{1}; |
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158 | m = varargin{2}; |
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159 | if length(n)~=length(m) |
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160 | error('The dimensions must have the same lengths') |
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161 | end |
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162 | if sum(n.*m)==0 |
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163 | sys = zeros(n,m); |
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164 | return |
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165 | end |
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166 | if (n==m) |
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167 | matrix_type = 'symm'; |
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168 | nvar = sum(n.*(n+1)/2); |
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169 | conicinfo = [1 0]; |
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170 | else |
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171 | matrix_type = 'full'; |
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172 | nvar = sum(n.*m); |
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173 | end |
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174 | case {3,4} |
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175 | n = varargin{1}; |
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176 | m = varargin{2}; |
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177 | if sum(n.*m)==0 |
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178 | sys = zeros(n,m); |
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179 | return |
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180 | end |
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181 | |
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182 | % Check for complex or real |
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183 | if (nargin == 4) |
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184 | if isempty(varargin{4}) |
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185 | varargin{4} = 'real'; |
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186 | else |
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187 | if ~ischar(varargin{4}) |
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188 | help sdpvar |
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189 | error('Fourth argument should be ''complex'' or ''real''') |
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190 | end |
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191 | end |
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192 | index_cmrl = strmatch(varargin{4},{'real','complex'}); |
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193 | if isempty(index_cmrl) |
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194 | error('Fourth argument should be ''complex'' or ''real''. See help above') |
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195 | end |
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196 | else |
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197 | if ~ischar(varargin{3}) |
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198 | help sdpvar |
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199 | error('Third argument should be ''symmetric'', ''full'', ''hermitian'',...See help above') |
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200 | end |
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201 | index_cmrl = 1; |
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202 | end; |
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203 | |
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204 | if isempty(varargin{3}) |
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205 | if n==m |
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206 | index_type = 7; %Default symmetric |
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207 | else |
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208 | index_type = 4; |
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209 | end |
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210 | else |
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211 | if ~isempty(strmatch(varargin{3},{'complex','real'})) |
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212 | % User had third argument as complex or real |
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213 | error(['Third argument should be ''symmetric'', ''full'', ''toeplitz''... Maybe you meant sdpvar(n,n,''full'',''' varargin{3} ''')']) |
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214 | end |
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215 | index_type = strmatch(varargin{3},{'toeplitz','hankel','symmetric','full','rhankel','skew','hermitian'}); |
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216 | end |
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217 | |
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218 | if isempty(index_type) |
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219 | error(['Matrix type "' varargin{3} '" not supported']) |
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220 | else |
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221 | switch index_type+100*(index_cmrl-1) |
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222 | case 1 |
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223 | if n~=m |
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224 | error('Toeplitz matrix must be square') |
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225 | else |
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226 | matrix_type = 'toep'; |
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227 | nvar = n; |
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228 | end |
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229 | |
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230 | case 2 |
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231 | if n~=m |
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232 | error('Hankel matrix must be square') |
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233 | else |
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234 | matrix_type = 'hank'; |
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235 | nvar = n; |
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236 | end |
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237 | |
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238 | case 3 |
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239 | if n~=m |
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240 | error('Symmetric matrix must be square') |
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241 | else |
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242 | matrix_type = 'symm'; |
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243 | nvar = sum(n.*(n+1)/2); |
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244 | end |
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245 | |
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246 | case 4 |
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247 | matrix_type = 'full'; |
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248 | nvar = sum(n.*m); |
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249 | if nvar==1 |
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250 | matrix_type = 'symm'; |
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251 | end |
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252 | |
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253 | case 5 |
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254 | if n~=m |
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255 | error('Hankel matrix must be square') |
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256 | else |
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257 | matrix_type = 'rhankel'; |
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258 | nvar = 2*n-1; |
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259 | end |
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260 | |
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261 | case 6 |
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262 | if n~=m |
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263 | error('Skew symmetric matrix must be square') |
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264 | else |
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265 | matrix_type = 'skew'; |
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266 | nvar = (n*(n+1)/2)-n; |
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267 | end |
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268 | |
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269 | case 7 |
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270 | if n~=m |
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271 | error('Symmetric matrix must be square') |
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272 | else |
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273 | matrix_type = 'symm'; |
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274 | nvar = n*(n+1)/2; |
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275 | end |
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276 | |
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277 | case 101 |
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278 | if n~=m |
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279 | error('Toeplitz matrix must be square') |
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280 | else |
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281 | matrix_type = 'toep complex'; |
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282 | nvar = 2*n; |
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283 | end |
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284 | |
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285 | case 102 |
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286 | if n~=m |
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287 | error('Hankel matrix must be square') |
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288 | else |
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289 | matrix_type = 'hank complex'; |
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290 | nvar = (2*n); |
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291 | end |
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292 | |
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293 | case 103 |
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294 | if n~=m |
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295 | error('Symmetric matrix must be square') |
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296 | else |
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297 | matrix_type = 'symm complex'; |
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298 | nvar = 2*n*(n+1)/2; |
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299 | end |
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300 | |
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301 | case 104 |
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302 | matrix_type = 'full complex'; |
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303 | nvar = 2*n*m; |
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304 | if nvar==1 |
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305 | matrix_type = 'symm complex'; |
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306 | end |
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307 | |
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308 | case 105 |
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309 | if n~=m |
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310 | error('Hankel matrix must be square') |
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311 | else |
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312 | matrix_type = 'rhankel complex'; |
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313 | nvar = 2*(2*n-1); |
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314 | end |
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315 | |
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316 | case 106 |
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317 | if n~=m |
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318 | error('Skew symmetric matrix must be square') |
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319 | else |
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320 | matrix_type = 'skew complex'; |
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321 | nvar = 2*((n*(n+1)/2)-n); |
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322 | end |
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323 | |
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324 | case 107 |
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325 | if n~=m |
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326 | error('Hermitian matrix must be square') |
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327 | else |
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328 | matrix_type = 'herm complex'; |
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329 | nvar = n*(n+1)/2+(n*(n+1)/2-n); |
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330 | end |
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331 | |
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332 | |
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333 | otherwise |
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334 | error('Bug! Report!'); |
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335 | end |
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336 | |
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337 | end |
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338 | |
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339 | case 5 % Fast version for internal use |
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340 | sys.basis = varargin{5}; |
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341 | sys.lmi_variables=varargin{4}; |
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342 | sys.dim(1) = varargin{1}; |
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343 | sys.dim(2) = varargin{2}; |
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344 | sys.typeflag = 0; |
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345 | sys.savedata = []; |
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346 | sys.extra = []; |
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347 | sys.extra.expanded = []; |
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348 | sys.conicinfo = 0; |
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349 | % Find zero-variables |
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350 | constants = find(sys.lmi_variables==0); |
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351 | if ~isempty(constants); |
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352 | sys.lmi_variables(constants)=[]; |
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353 | sys.basis(:,1) = sys.basis(:,1) + sum(sys.basis(:,1+constants),2); |
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354 | sys.basis(:,1+constants)=[]; |
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355 | end |
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356 | if isempty(sys.lmi_variables) |
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357 | sys = full(reshape(sys.basis(:,1),sys.dim(1),sys.dim(2))); |
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358 | else |
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359 | sys = class(sys,'sdpvar'); |
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360 | end |
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361 | return |
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362 | case 6 % Fast version for internal use |
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363 | sys.basis = varargin{5}; |
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364 | sys.lmi_variables=varargin{4}; |
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365 | sys.dim(1) = varargin{1}; |
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366 | sys.dim(2) = varargin{2}; |
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367 | sys.typeflag = varargin{6}; |
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368 | sys.savedata = []; |
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369 | sys.extra = []; |
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370 | sys.extra.expanded = []; |
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371 | sys.conicinfo = 0; |
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372 | % Find zero-variables |
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373 | constants = find(sys.lmi_variables==0); |
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374 | if ~isempty(constants); |
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375 | sys.lmi_variables(constants)=[]; |
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376 | sys.basis(:,1) = sys.basis(:,1) + sum(sys.basis(:,1+constants),2); |
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377 | sys.basis(:,1+constants)=[]; |
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378 | end |
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379 | if isempty(sys.lmi_variables) |
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380 | sys = full(reshape(sys.basis(:,1),sys.dim(1),sys.dim(2))); |
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381 | else |
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382 | sys = class(sys,'sdpvar'); |
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383 | end |
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384 | return |
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385 | case 7 % Fast version for internal use |
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386 | sys.basis = varargin{5}; |
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387 | sys.lmi_variables=varargin{4}; |
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388 | sys.dim(1) = varargin{1}; |
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389 | sys.dim(2) = varargin{2}; |
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390 | sys.typeflag = varargin{6}; |
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391 | sys.savedata = []; |
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392 | sys.extra = varargin{7}; |
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393 | sys.extra.expanded = []; |
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394 | sys.conicinfo = varargin{7}; |
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395 | % Find zero-variables |
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396 | constants = find(sys.lmi_variables==0); |
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397 | if ~isempty(constants); |
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398 | sys.lmi_variables(constants)=[]; |
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399 | sys.basis(:,1) = sys.basis(:,1) + sum(sys.basis(:,1+constants),2); |
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400 | sys.basis(:,1+constants)=[]; |
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401 | end |
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402 | if isempty(sys.lmi_variables) |
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403 | sys = full(reshape(sys.basis(:,1),sys.dim(1),sys.dim(2))); |
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404 | else |
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405 | sys = class(sys,'sdpvar'); |
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406 | end |
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407 | return |
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408 | |
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409 | otherwise |
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410 | error('Wrong number of arguments in sdpvar creation'); |
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411 | end |
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412 | |
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413 | if isempty(n) | isempty(m) |
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414 | error('Size must be integer valued') |
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415 | end; |
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416 | if ~((abs((n-ceil(n)))+ abs((m-ceil(m))))==0) |
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417 | error('Size must be integer valued') |
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418 | end |
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419 | |
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420 | nonCommutingTable = yalmip('nonCommutingTable'); |
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421 | [monomtable,variabletype] = yalmip('monomtable'); |
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422 | lmi_variables = (1:nvar)+max(size(nonCommutingTable,1),size(monomtable,1)); |
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423 | |
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424 | for blk = 1:length(n) |
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425 | switch matrix_type |
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426 | |
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427 | case 'full' |
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428 | basis{blk} = [spalloc(n(blk)*m(blk),1,0) speye(n(blk)*m(blk))];%speye(nvar)]; |
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429 | |
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430 | case 'full complex' |
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431 | basis = [spalloc(n*m,1,0) speye(nvar/2) speye(nvar/2)*sqrt(-1)]; |
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432 | |
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433 | case 'symm' |
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434 | if 0 |
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435 | basis = spalloc(n^2,1+nvar,n^2); |
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436 | l = 2; |
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437 | an_empty = spalloc(n,n,2); |
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438 | for i=1:n |
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439 | temp = an_empty; |
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440 | temp(i,i)=1; |
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441 | basis(:,l)=temp(:); |
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442 | l = l+1; |
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443 | for j=i+1:n, |
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444 | temp = an_empty; |
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445 | temp(i,j)=1; |
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446 | temp(j,i)=1; |
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447 | basis(:,l)=temp(:); |
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448 | l = l+1; |
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449 | end |
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450 | end |
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451 | else |
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452 | % Hrm...fast but completely f*d up |
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453 | |
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454 | Y = reshape(1:n(blk)^2,n(blk),n(blk)); |
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455 | Y = tril(Y); |
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456 | Y = (Y+Y')-diag(sparse(diag(Y))); |
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457 | [uu,oo,pp] = unique(Y(:)); |
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458 | if 1 |
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459 | basis{blk} = sparse(1:n(blk)^2,pp+1,1); |
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460 | else |
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461 | basis{blk} = lazybasis(n^2,1+(n*(n+1)/2),1:n(blk)^2,pp+1,ones(n(blk)^2,1)); |
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462 | end |
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463 | |
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464 | end |
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465 | |
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466 | case 'symm complex' |
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467 | basis = spalloc(n^2,1+nvar,2); |
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468 | l = 2; |
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469 | an_empty = spalloc(n,n,2); |
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470 | for i=1:n |
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471 | temp = an_empty; |
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472 | temp(i,i)=1; |
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473 | basis(:,l)=temp(:); |
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474 | l = l+1; |
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475 | for j=i+1:n, |
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476 | temp = an_empty; |
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477 | temp(i,j)=1; |
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478 | temp(j,i)=1; |
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479 | basis(:,l)=temp(:); |
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480 | l = l+1; |
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481 | end |
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482 | end |
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483 | for i=1:n |
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484 | temp = an_empty; |
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485 | temp(i,i)=sqrt(-1); |
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486 | basis(:,l)=temp(:); |
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487 | l = l+1; |
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488 | for j=i+1:n, |
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489 | temp = an_empty; |
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490 | temp(i,j)=sqrt(-1); |
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491 | temp(j,i)=sqrt(-1); |
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492 | basis(:,l)=temp(:); |
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493 | l = l+1; |
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494 | end |
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495 | end |
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496 | |
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497 | case 'herm complex' |
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498 | basis = spalloc(n^2,1+nvar,2); |
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499 | l = 2; |
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500 | an_empty = spalloc(n,n,2); |
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501 | for i=1:n |
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502 | temp = an_empty; |
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503 | temp(i,i)=1; |
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504 | basis(:,l)=temp(:); |
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505 | l = l+1; |
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506 | for j=i+1:n, |
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507 | temp = an_empty; |
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508 | temp(i,j)=1; |
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509 | temp(j,i)=1; |
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510 | basis(:,l)=temp(:); |
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511 | l = l+1; |
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512 | end |
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513 | end |
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514 | for i=1:n |
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515 | for j=i+1:n, |
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516 | temp = an_empty; |
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517 | temp(i,j)=sqrt(-1); |
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518 | temp(j,i)=-sqrt(-1); |
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519 | basis(:,l)=temp(:); |
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520 | l = l+1; |
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521 | end |
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522 | end |
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523 | |
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524 | case 'skew' |
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525 | basis = spalloc(n^2,1+nvar,2); |
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526 | l = 2; |
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527 | an_empty = spalloc(n,n,2); |
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528 | for i=1:n |
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529 | for j=i+1:n, |
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530 | temp = an_empty; |
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531 | temp(i,j)=1; |
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532 | temp(j,i)=-1; |
---|
533 | basis(:,l)=temp(:); |
---|
534 | l = l+1; |
---|
535 | end |
---|
536 | end |
---|
537 | |
---|
538 | case 'skew complex' |
---|
539 | basis = spalloc(n^2,1+nvar,2); |
---|
540 | l = 2; |
---|
541 | an_empty = spalloc(n,n,2); |
---|
542 | for i=1:n |
---|
543 | for j=i+1:n, |
---|
544 | temp = an_empty; |
---|
545 | temp(i,j)=1; |
---|
546 | temp(j,i)=-1; |
---|
547 | basis(:,l)=temp(:); |
---|
548 | l = l+1; |
---|
549 | end |
---|
550 | end |
---|
551 | for i=1:n |
---|
552 | for j=i+1:n, |
---|
553 | temp = an_empty; |
---|
554 | temp(i,j)=sqrt(-1); |
---|
555 | temp(j,i)=-sqrt(-1); |
---|
556 | basis(:,l)=temp(:); |
---|
557 | l = l+1; |
---|
558 | end |
---|
559 | end |
---|
560 | |
---|
561 | case 'toep' |
---|
562 | basis = spalloc(n^2,1+nvar,2); |
---|
563 | an_empty = spalloc(n,1,1); |
---|
564 | for i=1:n, |
---|
565 | v = an_empty; |
---|
566 | v(i)=1; |
---|
567 | temp = sparse(toeplitz(v)); |
---|
568 | basis(:,i+1) = temp(:); |
---|
569 | end |
---|
570 | |
---|
571 | % Notice, complex Toeplitz not Hermitian |
---|
572 | case 'toep complex' |
---|
573 | basis = spalloc(n^2,1+nvar,2); |
---|
574 | an_empty = spalloc(n,1,1); |
---|
575 | for i=1:n, |
---|
576 | v = an_empty; |
---|
577 | v(i)=1; |
---|
578 | temp = sparse(toeplitz(v)); |
---|
579 | basis(:,i+1) = temp(:); |
---|
580 | end |
---|
581 | for i=1:n, |
---|
582 | v = an_empty; |
---|
583 | v(i)=sqrt(-1); |
---|
584 | temp = sparse(toeplitz(v)); |
---|
585 | basis(:,n+i+1) = temp(:); |
---|
586 | end |
---|
587 | |
---|
588 | case 'hank' |
---|
589 | basis = spalloc(n^2,1+nvar,2); |
---|
590 | an_empty = spalloc(n,1,1); |
---|
591 | for i=1:n, |
---|
592 | v = an_empty; |
---|
593 | v(i)=1; |
---|
594 | temp = sparse(hankel(v)); |
---|
595 | basis(:,i+1) = temp(:); |
---|
596 | end |
---|
597 | |
---|
598 | case 'hank complex' |
---|
599 | basis = spalloc(n^2,1+nvar,2); |
---|
600 | an_empty = spalloc(n,1,1); |
---|
601 | for i=1:n, |
---|
602 | v = an_empty; |
---|
603 | v(i)=1; |
---|
604 | temp = sparse(hankel(v)); |
---|
605 | basis(:,i+1) = temp(:); |
---|
606 | end |
---|
607 | for i=1:n, |
---|
608 | v = an_empty; |
---|
609 | v(i)=sqrt(-1); |
---|
610 | temp = sparse(hankel(v)); |
---|
611 | basis(:,n+i+1) = temp(:); |
---|
612 | end |
---|
613 | |
---|
614 | case 'rhankel' |
---|
615 | basis = spalloc(n^2,1+nvar,2); |
---|
616 | an_empty = spalloc(2*n-1,1,1); |
---|
617 | for i=1:nvar, |
---|
618 | v = an_empty; |
---|
619 | v(i)=1; |
---|
620 | temp = sparse(hankel(v(1:n),[v(n);v(n+1:2*n-1)])); |
---|
621 | basis(:,i+1) = temp(:); |
---|
622 | end |
---|
623 | |
---|
624 | case 'rhankel complex' |
---|
625 | basis = spalloc(n^2,1+nvar,2); |
---|
626 | an_empty = spalloc(2*n-1,1,1); |
---|
627 | for i=1:nvar/2, |
---|
628 | v = an_empty; |
---|
629 | v(i)=1; |
---|
630 | temp = sparse(hankel(v(1:n),[v(n);v(n+1:2*n-1)])); |
---|
631 | basis(:,i+1) = temp(:); |
---|
632 | end |
---|
633 | for i=1:nvar/2, |
---|
634 | v = an_empty; |
---|
635 | v(i)=sqrt(-1); |
---|
636 | temp = sparse(hankel(v(1:n),[v(n);v(n+1:2*n-1)])); |
---|
637 | basis(:,nvar/2+i+1) = temp(:); |
---|
638 | end |
---|
639 | |
---|
640 | otherwise |
---|
641 | error('Bug! Report') |
---|
642 | end |
---|
643 | |
---|
644 | end |
---|
645 | |
---|
646 | % Update noncommuting table and monomtables |
---|
647 | nonCommutingTable(lmi_variables,1) = nan; |
---|
648 | nonCommutingTable(lmi_variables,2) = lmi_variables; |
---|
649 | yalmip('nonCommutingTable',nonCommutingTable); |
---|
650 | variabletype(lmi_variables) = 0; |
---|
651 | monomtable(lmi_variables(end),lmi_variables(end)) = 0; |
---|
652 | yalmip('setmonomtable',monomtable,variabletype); |
---|
653 | |
---|
654 | |
---|
655 | % Create an object |
---|
656 | if isa(basis,'cell') |
---|
657 | top = 1; |
---|
658 | for blk = 1:length(n) |
---|
659 | sys{blk}.basis=basis{blk}; |
---|
660 | nn = size(sys{blk}.basis,2)-1; |
---|
661 | sys{blk}.lmi_variables = lmi_variables(top:top+nn-1); |
---|
662 | top = top + nn; |
---|
663 | sys{blk}.dim(1) = n(blk); |
---|
664 | sys{blk}.dim(2) = m(blk); |
---|
665 | sys{blk}.typeflag = 0; |
---|
666 | sys{blk}.savedata = []; |
---|
667 | sys{blk}.extra = []; |
---|
668 | sys{blk}.extra.expanded = []; |
---|
669 | sys{blk}.conicinfo = conicinfo; |
---|
670 | sys{blk} = class(sys{blk},'ncvar'); |
---|
671 | end |
---|
672 | if length(n)==1 |
---|
673 | sys = sys{1}; |
---|
674 | end |
---|
675 | else |
---|
676 | sys.basis=basis; |
---|
677 | sys.lmi_variables = lmi_variables; |
---|
678 | sys.dim(1) = n; |
---|
679 | sys.dim(2) = m; |
---|
680 | sys.typeflag = 0; |
---|
681 | sys.savedata = []; |
---|
682 | sys.extra = []; |
---|
683 | sys.extra.expanded = []; |
---|
684 | sys.conicinfo = conicinfo; |
---|
685 | sys = class(sys,'ncvar'); |
---|
686 | if ~isreal(basis) |
---|
687 | % Add internal information about complex pairs |
---|
688 | complex_elements = find(any(imag(basis),2)); |
---|
689 | complex_pairs = []; |
---|
690 | for i = 1:length(complex_elements) |
---|
691 | complex_pairs = [complex_pairs;lmi_variables(find(basis(complex_elements(i),:))-1)]; |
---|
692 | end |
---|
693 | complex_pairs = uniquesafe(complex_pairs,'rows'); |
---|
694 | yalmip('addcomplexpair',complex_pairs); |
---|
695 | end |
---|
696 | end |
---|