Home > matpower7.1 > mp-opt-model > lib > @opt_model > params_var.m

params_var

PURPOSE ^

PARAMS_VAR Returns initial value, lower bound and upper bound for opt variables.

SYNOPSIS ^

function [v0, vl, vu, vt] = params_var(om, name, idx)

DESCRIPTION ^

PARAMS_VAR  Returns initial value, lower bound and upper bound for opt variables.
   [V0, VL, VU] = OM.PARAMS_VAR()
   [V0, VL, VU] = OM.PARAMS_VAR(NAME)
   [V0, VL, VU] = OM.PARAMS_VAR(NAME, IDX_LIST)
   [V0, VL, VU, VT] = PARAMS_VAR(...)
   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:
       [x0, xmin, xmax] = om.params_var();
       [Pg0, Pmin, Pmax] = om.params_var('Pg');
       [zij0, zijmin, zijmax, ztype] = om.params_var('z', {i, j});
   
   See also OPT_MODEL.

CROSS-REFERENCE INFORMATION ^

This function calls: This function is called by:

SOURCE CODE ^

0001 function [v0, vl, vu, vt] = params_var(om, name, idx)
0002 %PARAMS_VAR  Returns initial value, lower bound and upper bound for opt variables.
0003 %   [V0, VL, VU] = OM.PARAMS_VAR()
0004 %   [V0, VL, VU] = OM.PARAMS_VAR(NAME)
0005 %   [V0, VL, VU] = OM.PARAMS_VAR(NAME, IDX_LIST)
0006 %   [V0, VL, VU, VT] = PARAMS_VAR(...)
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 %       [x0, xmin, xmax] = om.params_var();
0015 %       [Pg0, Pmin, Pmax] = om.params_var('Pg');
0016 %       [zij0, zijmin, zijmax, ztype] = om.params_var('z', {i, j});
0017 %
0018 %   See also OPT_MODEL.
0019 
0020 %   MP-Opt-Model
0021 %   Copyright (c) 2008-2020, Power Systems Engineering Research Center (PSERC)
0022 %   by Ray Zimmerman, PSERC Cornell
0023 %
0024 %   This file is part of MP-Opt-Model.
0025 %   Covered by the 3-clause BSD License (see LICENSE file for details).
0026 %   See https://github.com/MATPOWER/mp-opt-model for more info.
0027 
0028 if nargout > 3
0029     have_vt = 1;
0030 else
0031     have_vt = 0;
0032 end
0033 if nargin < 2
0034     v0 = []; vl = []; vu = []; vt = char([]);
0035     %% calls to substruct() are relatively expensive, so we pre-build the
0036     %% structs for addressing cell and numeric array fields, updating only
0037     %% the subscripts before use
0038     sc = struct('type', {'.', '{}'}, 'subs', {'', 1});  %% cell array field
0039     for k = 1:om.var.NS
0040         name = om.var.order(k).name;
0041         idx = om.var.order(k).idx;
0042         if isempty(idx)
0043             v0 = [ v0; om.var.data.v0.(name) ];
0044             vl = [ vl; om.var.data.vl.(name) ];
0045             vu = [ vu; om.var.data.vu.(name) ];
0046             if have_vt
0047                 N = om.var.idx.N.(name);
0048                 vt0 = om.var.data.vt.(name);
0049                 if isscalar(vt0) && N > 1 
0050                     vt = [ vt char(vt0 * ones(1, N)) ];
0051                 else
0052                     vt = [ vt vt0 ];
0053                 end
0054             end
0055         else
0056             % (calls to substruct() are relatively expensive ...
0057             % sc = substruct('.', name, '{}', idx);
0058             % ... so replace it with these more efficient lines)
0059             sc(1).subs = name;
0060             sc(2).subs = idx;
0061             v0 = [ v0; subsref(om.var.data.v0, sc) ];
0062             vl = [ vl; subsref(om.var.data.vl, sc) ];
0063             vu = [ vu; subsref(om.var.data.vu, sc) ];
0064             if have_vt
0065                 % (calls to substruct() are relatively expensive ...
0066                 % sn = substruct('.', name, '()', idx);
0067                 % ... so replace it with these more efficient lines)
0068                 sn = sc; sn(2).type = '()';
0069                 N = subsref(om.var.idx.N, sn);
0070                 vt0 = subsref(om.var.data.vt, sc);
0071                 if isscalar(vt0) && N > 1 
0072                     vt = [ vt char(vt0 * ones(1, N)) ];
0073                 else
0074                     if ~isempty(vt0)
0075                         vt = [ vt vt0 ];
0076                     end
0077                 end
0078             end
0079         end
0080     end
0081 else
0082     if isfield(om.var.idx.N, name)
0083         if nargin < 3 || isempty(idx)
0084             v0 = om.var.data.v0.(name);
0085             vl = om.var.data.vl.(name);
0086             vu = om.var.data.vu.(name);
0087             if have_vt
0088                 N = om.var.idx.N.(name);
0089                 vt0 = om.var.data.vt.(name);
0090                 if isscalar(vt0) && N > 1 
0091                     vt = char(vt0 * ones(1, N));
0092                 else
0093                     vt = vt0;
0094                 end
0095             end
0096         else
0097             % (calls to substruct() are relatively expensive ...
0098             % sc = substruct('.', name, '{}', idx);
0099             % ... so replace it with these more efficient lines)
0100             sc = struct('type', {'.', '{}'}, 'subs', {name, idx});
0101             v0 = subsref(om.var.data.v0, sc);
0102             vl = subsref(om.var.data.vl, sc);
0103             vu = subsref(om.var.data.vu, sc);
0104             if have_vt
0105                 % (calls to substruct() are relatively expensive ...
0106                 % sn = substruct('.', name, '()', idx);
0107                 % ... so replace it with these more efficient lines)
0108                 sn = sc; sn(2).type = '()';
0109                 N = subsref(om.var.idx.N, sn);
0110                 vt0 = subsref(om.var.data.vt, sc);
0111                 if isscalar(vt0) && N > 1 
0112                     vt = char(vt0 * ones(1, N));
0113                 else
0114                     vt = vt0;
0115                 end
0116             end
0117         end
0118     else
0119         v0 = [];
0120         vl = [];
0121         vu = [];
0122         if have_vt
0123             vt = [];
0124         end
0125     end
0126 end

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