1 | %
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2 | % constructor for the linear_equality_constraint class.
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3 | %
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4 | % [lec]=linear_equality_constraint(varargin)
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5 | %
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6 | % where the required varargin are:
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7 | % matrix (double row, variable coefficients, NaN)
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8 | % target (double vector, target values, 0.)
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9 | % and the optional varargin and defaults are:
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10 | % scale_type (char, scaling type, 'none')
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11 | % scale (double, scaling factor, 1.)
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12 | %
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13 | % note that zero arguments constructs a default instance; one
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14 | % argument of the class copies the instance; and two or more
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15 | % arguments constructs a new instance from the arguments.
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16 | %
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17 | % "Copyright 2009, by the California Institute of Technology.
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18 | % ALL RIGHTS RESERVED. United States Government Sponsorship
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19 | % acknowledged. Any commercial use must be negotiated with
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20 | % the Office of Technology Transfer at the California Institute
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21 | % of Technology. (J. Schiermeier, NTR 47078)
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22 | %
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23 | % This software may be subject to U.S. export control laws.
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24 | % By accepting this software, the user agrees to comply with
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25 | % all applicable U.S. export laws and regulations. User has the
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26 | % responsibility to obtain export licenses, or other export
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27 | % authority as may be required before exporting such information
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28 | % to foreign countries or providing access to foreign persons."
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29 | %
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30 | classdef linear_equality_constraint
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31 | properties
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32 | matrix = NaN;
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33 | target = 0.;
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34 | scale_type='none';
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35 | scale = 1.;
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36 | end
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37 |
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38 | methods
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39 | function [lec]=linear_equality_constraint(varargin)
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40 |
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41 | switch nargin
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42 |
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43 | % create a default object
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44 |
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45 | case 0
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46 |
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47 | % copy the object
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48 |
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49 | case 1
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50 | if isa(varargin{1},'linear_equality_constraint')
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51 | lec=varargin{1};
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52 | else
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53 | error('Object ''%s'' is a ''%s'' class object, not ''%s''.',...
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54 | inputname(1),class(varargin{1}),'linear_equality_constraint');
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55 | end
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56 |
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57 | % create the object from the input
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58 |
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59 | otherwise
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60 | if (size(varargin{1},1) == array_numel(varargin{2:min(nargin,4)}) || ...
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61 | size(varargin{1},1) == 1)
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62 | asizec=num2cell(array_size(varargin{2:min(nargin,4)}));
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63 | elseif (array_numel(varargin{2:min(nargin,4)}) == 1)
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64 | asizec=num2cell([size(varargin{1},1) 1]);
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65 | else
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66 | error('Matrix for object of class ''%s'' has inconsistent number of rows.',...
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67 | class(lec));
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68 | end
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69 | lec(asizec{:})=linear_equality_constraint;
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70 | clear asizec
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71 |
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72 | for i=1:numel(lec)
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73 | if (size(varargin{1},1) > 1)
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74 | lec(i).matrix =varargin{1}(i,:);
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75 | else
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76 | lec(i).matrix =varargin{1};
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77 | end
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78 | end
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79 |
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80 | if (nargin >= 2)
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81 | for i=1:numel(lec)
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82 | if (numel(varargin{2}) > 1)
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83 | lec(i).target =varargin{2}(i);
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84 | else
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85 | lec(i).target =varargin{2};
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86 | end
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87 | end
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88 | if (nargin >= 3)
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89 | if ischar(varargin{3})
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90 | varargin{3}=cellstr(varargin{3});
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91 | end
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92 | for i=1:numel(lec)
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93 | if (numel(varargin{3}) > 1)
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94 | lec(i).scale_type=varargin{3}{i};
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95 | else
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96 | lec(i).scale_type=char(varargin{3});
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97 | end
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98 | end
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99 | if (nargin >= 4)
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100 | for i=1:numel(lec)
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101 | if (numel(varargin{4}) > 1)
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102 | lec(i).scale =varargin{4}(i);
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103 | else
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104 | lec(i).scale =varargin{4};
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105 | end
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106 | end
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107 |
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108 | if (nargin > 4)
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109 | warning('linear_equality_constraint:extra_arg',...
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110 | 'Extra arguments for object of class ''%s''.',...
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111 | class(lec));
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112 | end
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113 | end
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114 | end
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115 | end
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116 | end
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117 | end
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118 |
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119 | function []=disp(lec)
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120 |
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121 | % display the object
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122 |
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123 | disp(sprintf('\n'));
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124 | for i=1:numel(lec)
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125 | disp(sprintf('class ''%s'' object ''%s%s'' = \n',...
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126 | class(lec),inputname(1),string_dim(lec,i)));
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127 | disp(sprintf(' matrix: %s' ,string_vec(lec(i).matrix)));
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128 | disp(sprintf(' target: %g' ,lec(i).target));
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129 | disp(sprintf(' scale_type: ''%s''' ,lec(i).scale_type));
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130 | disp(sprintf(' scale: %g\n' ,lec(i).scale));
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131 | end
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132 |
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133 | end
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134 |
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135 | function [matrix]=prop_matrix(lec)
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136 | matrix=zeros(numel(lec),0);
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137 | for i=1:numel(lec)
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138 | matrix(i,1:size(lec(i).matrix,2))=lec(i).matrix(1,:);
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139 | end
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140 | end
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141 | function [lower] =prop_lower(lec)
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142 | lower=[];
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143 | end
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144 | function [upper] =prop_upper(lec)
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145 | upper=[];
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146 | end
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147 | function [target]=prop_target(lec)
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148 | target=zeros(size(lec));
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149 | for i=1:numel(lec)
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150 | target(i)=lec(i).target;
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151 | end
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152 | target=allequal(target,0.);
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153 | end
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154 | function [stype] =prop_stype(lec)
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155 | stype=cell(size(lec));
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156 | for i=1:numel(lec)
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157 | stype(i)=cellstr(lec(i).scale_type);
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158 | end
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159 | stype=allequal(stype,'none');
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160 | end
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161 | function [scale] =prop_scale(lec)
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162 | scale=zeros(size(lec));
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163 | for i=1:numel(lec)
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164 | scale(i)=lec(i).scale;
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165 | end
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166 | scale=allequal(scale,1.);
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167 | end
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168 | end
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169 |
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170 | methods (Static)
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171 | function []=dakota_write(fidi,dvar)
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172 |
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173 | % collect only the variables of the appropriate class
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174 |
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175 | lec=struc_class(dvar,'linear_equality_constraint');
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176 |
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177 | % write constraints
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178 |
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179 | lclist_write(fidi,'linear_equality_constraints','linear_equality',lec);
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180 | end
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181 | end
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182 | end
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