GET_IDX Returns the idx struct for vars, lin/nonlin constraints, costs.
VV = OM.GET_IDX()
[VV, LL] = OM.GET_IDX()
[VV, LL, NNE] = OM.GET_IDX()
[VV, LL, NNE, NNI] = OM.GET_IDX()
[VV, LL, NNE, NNI, CC] = OM.GET_IDX()
Returns a structure for each with the beginning and ending
index value and the number of elements for each named block.
The 'i1' field (that's a one) is a struct with all of the
starting indices, 'iN' contains all the ending indices and
'N' contains all the sizes. Each is a struct whose fields are
the named blocks.
Alternatively, you can specify the type of named set(s) directly
as inputs ...
[IDX1, IDX2, ...] = OM.GET_IDX(SET_TYPE1, SET_TYPE2, ...);
[CC, VV] = OM.GET_IDX('cost', 'var');
[LL, NNE, NNI] = OM.GET_IDX('lin', 'nle', 'nli');
The specific type of named set being referenced is
given by the SET_TYPE inputs, with the following valid options:
SET_TYPE = 'var' => variable set
SET_TYPE = 'lin' => linear constraint set
SET_TYPE = 'nle' => nonlinear equality constraint set
SET_TYPE = 'nli' => nonlinear inequality constraint set
SET_TYPE = 'cost' => cost set
Examples:
[vv, ll, nne] = om.get_idx();
[vv, ll, cc] = om.get_idx('var', 'lin', 'cost');
For a variable block named 'z' we have ...
vv.i1.z - starting index for 'z' in optimization vector x
vv.iN.z - ending index for 'z' in optimization vector x
vv.N.z - number of elements in 'z'
To extract a 'z' variable from x:
z = x(vv.i1.z:vv.iN.z);
To extract the multipliers on a linear constraint set
named 'foo', where mu_l and mu_u are the full set of
linear constraint multipliers:
mu_l_foo = mu_l(ll.i1.foo:ll.iN.foo);
mu_u_foo = mu_u(ll.i1.foo:ll.iN.foo);
The number of nonlinear equality constraints in a set named 'bar':
nbar = nne.N.bar;
(note: the following is preferable ...
nbar = om.getN('nle', 'bar');
... if you haven't already called get_idx to get nne.)
If 'z', 'foo' and 'bar' are indexed sets, then you can
replace them with something like 'z(i,j)', 'foo(i,j,k)'
or 'bar(i)' in the examples above.
See also OPT_MODEL, ADD_VAR, ADD_LIN_CONSTRAINT, ADD_NLN_CONSTRAINT,
ADD_QUAD_COST, ADD_NLN_COST and ADD_LEGACY_COST.0001 function varargout = get_idx(om, varargin) 0002 %GET_IDX Returns the idx struct for vars, lin/nonlin constraints, costs. 0003 % VV = OM.GET_IDX() 0004 % [VV, LL] = OM.GET_IDX() 0005 % [VV, LL, NNE] = OM.GET_IDX() 0006 % [VV, LL, NNE, NNI] = OM.GET_IDX() 0007 % [VV, LL, NNE, NNI, CC] = OM.GET_IDX() 0008 % 0009 % Returns a structure for each with the beginning and ending 0010 % index value and the number of elements for each named block. 0011 % The 'i1' field (that's a one) is a struct with all of the 0012 % starting indices, 'iN' contains all the ending indices and 0013 % 'N' contains all the sizes. Each is a struct whose fields are 0014 % the named blocks. 0015 % 0016 % Alternatively, you can specify the type of named set(s) directly 0017 % as inputs ... 0018 % 0019 % [IDX1, IDX2, ...] = OM.GET_IDX(SET_TYPE1, SET_TYPE2, ...); 0020 % [CC, VV] = OM.GET_IDX('cost', 'var'); 0021 % [LL, NNE, NNI] = OM.GET_IDX('lin', 'nle', 'nli'); 0022 % 0023 % The specific type of named set being referenced is 0024 % given by the SET_TYPE inputs, with the following valid options: 0025 % SET_TYPE = 'var' => variable set 0026 % SET_TYPE = 'lin' => linear constraint set 0027 % SET_TYPE = 'nle' => nonlinear equality constraint set 0028 % SET_TYPE = 'nli' => nonlinear inequality constraint set 0029 % SET_TYPE = 'cost' => cost set 0030 % 0031 % Examples: 0032 % [vv, ll, nne] = om.get_idx(); 0033 % [vv, ll, cc] = om.get_idx('var', 'lin', 'cost'); 0034 % 0035 % For a variable block named 'z' we have ... 0036 % vv.i1.z - starting index for 'z' in optimization vector x 0037 % vv.iN.z - ending index for 'z' in optimization vector x 0038 % vv.N.z - number of elements in 'z' 0039 % 0040 % To extract a 'z' variable from x: 0041 % z = x(vv.i1.z:vv.iN.z); 0042 % 0043 % To extract the multipliers on a linear constraint set 0044 % named 'foo', where mu_l and mu_u are the full set of 0045 % linear constraint multipliers: 0046 % mu_l_foo = mu_l(ll.i1.foo:ll.iN.foo); 0047 % mu_u_foo = mu_u(ll.i1.foo:ll.iN.foo); 0048 % 0049 % The number of nonlinear equality constraints in a set named 'bar': 0050 % nbar = nne.N.bar; 0051 % (note: the following is preferable ... 0052 % nbar = om.getN('nle', 'bar'); 0053 % ... if you haven't already called get_idx to get nne.) 0054 % 0055 % If 'z', 'foo' and 'bar' are indexed sets, then you can 0056 % replace them with something like 'z(i,j)', 'foo(i,j,k)' 0057 % or 'bar(i)' in the examples above. 0058 % 0059 % See also OPT_MODEL, ADD_VAR, ADD_LIN_CONSTRAINT, ADD_NLN_CONSTRAINT, 0060 % ADD_QUAD_COST, ADD_NLN_COST and ADD_LEGACY_COST. 0061 0062 % MATPOWER 0063 % Copyright (c) 2008-2017, Power Systems Engineering Research Center (PSERC) 0064 % by Ray Zimmerman, PSERC Cornell 0065 % 0066 % This file is part of MATPOWER. 0067 % Covered by the 3-clause BSD License (see LICENSE file for details). 0068 % See https://matpower.org for more info. 0069 0070 if nargin == 1 0071 varargout{1} = om.var.idx; 0072 if nargout > 1 0073 varargout{2} = om.lin.idx; 0074 if nargout > 2 0075 varargout{3} = om.nle.idx; 0076 if nargout > 3 0077 varargout{4} = om.nli.idx; 0078 if nargout > 4 0079 varargout{5} = om.cost.idx; 0080 end 0081 end 0082 end 0083 end 0084 else 0085 for k = nargout:-1:1 0086 varargout{k} = om.(varargin{k}).idx; 0087 end 0088 end