GETV Returns initial value, lower bound and upper bound for opt variables.
[V0, VL, VU] = GETV(OM)
[V0, VL, VU] = GETV(OM, NAME)
[V0, VL, VU] = GETV(OM, NAME, IDX)
[V0, VL, VU, VT] = GETV(...)
Returns the initial value V0, lower bound VL and upper bound VU for
the full optimization variable vector, or for a specific named or named
and indexed variable set. Optionally also returns a corresponding char
vector VT of variable types, where 'C', 'I' and 'B' represent continuous
integer and binary variables, respectively.
Examples:
[x, xmin, xmax] = getv(om);
[Pg, Pmin, Pmax] = getv(om, 'Pg');
[zij0, zijmin, zijmax, ztype] = getv(om, 'z', {i, j});
See also OPT_MODEL.0001 function [v0, vl, vu, vt] = getv(om, name, idx) 0002 %GETV Returns initial value, lower bound and upper bound for opt variables. 0003 % [V0, VL, VU] = GETV(OM) 0004 % [V0, VL, VU] = GETV(OM, NAME) 0005 % [V0, VL, VU] = GETV(OM, NAME, IDX) 0006 % [V0, VL, VU, VT] = GETV(...) 0007 % Returns the initial value V0, lower bound VL and upper bound VU for 0008 % the full optimization variable vector, or for a specific named or named 0009 % and indexed variable set. Optionally also returns a corresponding char 0010 % vector VT of variable types, where 'C', 'I' and 'B' represent continuous 0011 % integer and binary variables, respectively. 0012 % 0013 % Examples: 0014 % [x, xmin, xmax] = getv(om); 0015 % [Pg, Pmin, Pmax] = getv(om, 'Pg'); 0016 % [zij0, zijmin, zijmax, ztype] = getv(om, 'z', {i, j}); 0017 % 0018 % See also OPT_MODEL. 0019 0020 % MATPOWER 0021 % Copyright (c) 2008-2015 by Power System Engineering Research Center (PSERC) 0022 % by Ray Zimmerman, PSERC Cornell 0023 % 0024 % $Id: getv.m 2644 2015-03-11 19:34:22Z ray $ 0025 % 0026 % This file is part of MATPOWER. 0027 % Covered by the 3-clause BSD License (see LICENSE file for details). 0028 % See http://www.pserc.cornell.edu/matpower/ for more info. 0029 0030 if nargout > 3 0031 have_vt = 1; 0032 else 0033 have_vt = 0; 0034 end 0035 if nargin < 2 0036 v0 = []; vl = []; vu = []; vt = char([]); 0037 s1 = struct('type', {'.', '{}'}, 'subs', {'', 1}); 0038 for k = 1:om.var.NS 0039 name = om.var.order(k).name; 0040 idx = om.var.order(k).idx; 0041 if isempty(idx) 0042 v0 = [ v0; om.var.data.v0.(name) ]; 0043 vl = [ vl; om.var.data.vl.(name) ]; 0044 vu = [ vu; om.var.data.vu.(name) ]; 0045 if have_vt 0046 N = om.var.idx.N.(name); 0047 vt0 = om.var.data.vt.(name); 0048 if isscalar(vt0) && N > 1 0049 vt = [ vt char(vt0 * ones(1, N)) ]; 0050 else 0051 vt = [ vt vt0 ]; 0052 end 0053 end 0054 else 0055 % (calls to substruct() are relatively expensive ... 0056 % s1 = substruct('.', name, '{}', idx); 0057 % ... so replace it with these more efficient lines) 0058 s1(1).subs = name; 0059 s1(2).subs = idx; 0060 v0 = [ v0; subsref(om.var.data.v0, s1) ]; 0061 vl = [ vl; subsref(om.var.data.vl, s1) ]; 0062 vu = [ vu; subsref(om.var.data.vu, s1) ]; 0063 if have_vt 0064 % (calls to substruct() are relatively expensive ... 0065 % s2 = substruct('.', name, '()', idx); 0066 % ... so replace it with these more efficient lines) 0067 s2 = s1; 0068 s2(2).type = '()'; 0069 N = subsref(om.var.idx.N, s2); 0070 vt0 = subsref(om.var.data.vt, s1); 0071 if isscalar(vt0) && N > 1 0072 vt = [ vt char(vt0 * ones(1, N)) ]; 0073 else 0074 vt = [ vt vt0 ]; 0075 end 0076 end 0077 end 0078 end 0079 else 0080 if isfield(om.var.idx.N, name) 0081 if nargin < 3 0082 v0 = om.var.data.v0.(name); 0083 vl = om.var.data.vl.(name); 0084 vu = om.var.data.vu.(name); 0085 if have_vt 0086 N = om.var.idx.N.(name); 0087 vt0 = om.var.data.vt.(name); 0088 if isscalar(vt0) && N > 1 0089 vt = char(vt0 * ones(1, N)); 0090 else 0091 vt = vt0; 0092 end 0093 end 0094 else 0095 % (calls to substruct() are relatively expensive ... 0096 % s1 = substruct('.', name, '{}', idx); 0097 % ... so replace it with these more efficient lines) 0098 s1 = struct('type', {'.', '{}'}, 'subs', {name, idx}); 0099 v0 = subsref(om.var.data.v0, s1); 0100 vl = subsref(om.var.data.vl, s1); 0101 vu = subsref(om.var.data.vu, s1); 0102 if have_vt 0103 % (calls to substruct() are relatively expensive ... 0104 % s2 = substruct('.', name, '()', idx); 0105 % ... so replace it with these more efficient lines) 0106 s2 = s1; 0107 s2(2).type = '()'; 0108 N = subsref(om.var.idx.N, s2); 0109 vt0 = subsref(om.var.data.vt, s1); 0110 if isscalar(vt0) && N > 1 0111 vt = char(vt0 * ones(1, N)); 0112 else 0113 vt = vt0; 0114 end 0115 end 0116 end 0117 else 0118 v0 = []; 0119 vl = []; 0120 vu = []; 0121 if have_vt 0122 vt = []; 0123 end 0124 end 0125 end