Difference between revisions of "OptInfo"
(→OptInfo(opt, item, decision, constraint, asRef)) 
(→OptInfo(opt, item, decision, constraint, asRef)) 

Line 14:  Line 14:  
! Type  ! Type  
! Description  ! Description  
+    
+   "All"  
+   LP, QP, QCP, NLP  
+   local .item  
+   ''various''  
+   Returns a comprehensive view inside the optimization, listing most items shown here. This is the same info you get when you double click on the «LP», «NLP», etc., cell in a result window.  
+    
+   "vars"  
+   LP,QP,QCP,NLP  
+   Vars  
+   Text  
+   This lists all scalar decision variable, where each structured decision has been "flattened" to a single vector. This same index is used to index may of the possible [[OptInfo]] results that refer to scalar decisions, e.g., "ObjCoef", "Q", "Lhs", "LhsQ", etc.  
+    
+   "constraints"  
+   LP,QP,QCP,NLP  
+   Constraints  
+   Text  
+   This lists all the scalar constraints, where each structured constraint has been flattened to a single vector. This same index is used to index many of the possible [[OptInfo]] results that refer to scalar constraints, e.g., "Lhs", "LhsQ", "Rhs", "Sense", "constraintLb", "constraintUb", etc.  
    
 "objcoef"   "objcoef"  
−   LP, QP  +   LP, QP, QCP 
 Vars   Vars  
 numeric   numeric  
+   The scalar objective linear coefficients.  
    
 "Q"   "Q"  
−   QP  +   QP, QCP 
 Vars, Vars2   Vars, Vars2  
 numeric   numeric  
+   The scalar quadratic coefficients for the objective. Dense matrix.  
    
 "lhs"   "lhs"  
−   LP, QP  +   LP, QP, QCP 
 Vars, Constraints   Vars, Constraints  
 numeric   numeric  
+   The linear coefficients for all scalar constraints. Dense matrix. You may optionally specify «constraint» to obtain the coefficients for just one constraint, in the intrinsic dimensionality of that constraint but with respect to all scalar decision variables. Or you may specify «decision» to get the coefficients for just one decision, but relative to all scalar constraints. Or you may specify both «decision» and «constraint» to get the coefficients for only one decision and only one constraint, in the dimensionality of each.  
    
 "lhsQ",   "lhsQ",  
−    +   QCP 
 Vars, Vars2, Constraints   Vars, Vars2, Constraints  
 numeric   numeric  
+   The quadratic coefficients for all scalar scalar constraints. Dense matrices, may be too large to fit in memory for some large structured QCPs. You may optionally specify «decision» and/or «constraint» to obtain the quadratic coefficients for just that structured decision and constraint.  
    
 "rhs"   "rhs"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Constraints   Constraints  
 numeric   numeric  
+   The righthand side coefficients for all scalar constraints. You may optionally specify «constraint» to get the coefficients for a single structured constraint, in which case the result will be indexed by the constraint's intrinsic indexes. For a linear or quadratic constraint, the RHS will be the constant term. There is no guarantee of the sign, since it depends on how [[DefineOptimization]] rearranges the constraint when it processes the coefficients. For a nonlinear constraint, rhs will usually be 0. For a range constraint, e.g., <code>a <= f(x) <= b</code>, the far right constant (b) is returned. It is better to use "constraintLb" and "constraintUb" for range constraints.  
    
 "constraintUb"   "constraintUb"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Constraints   Constraints  
 numeric   numeric  
−   Upper bound for each constraint  +   Upper bound for each scalar constraint. You may optionally specify «constraint» to obtain the values for a single structured constraint in the intrinsic dimensionality of the constraint. 
    
 "constraintLb"   "constraintLb"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Constraints   Constraints  
 numeric   numeric  
−   Lower bound for each constraint  +   Lower bound for each scalar constraint. You may optionally specify «constraint» to obtain the values for a single structured constraint in the intrinsic dimensionality of the constraint. 
    
 "sense"   "sense"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Constraints   Constraints  
 '>=','<=', '=', 'R'   '>=','<=', '=', 'R'  
−    +   Inequality for each constraint. 'R' for range (lb & ub). You may optionally specify «constraint» to obtain the sense for a single structured constraint. 
    
 "lb"   "lb"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Vars   Vars  
 numeric   numeric  
−    +   Lower bound for each scalar variable. You may optionally specify «decision» to obtain the value for a single structured decision variable, in terms of the decision's intrinsic indexes. 
    
 "ub"   "ub"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Vars   Vars  
 numeric   numeric  
−    +   Upper bound for each scalar variable. You may optionally specify «decision» to obtain the value for a single structured decision variable, in terms of the decision's intrinsic indexes. 
    
−   "  +   "integer type" 
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 Vars   Vars  
−   '  +   'Continuous', 'Integer', 'Boolean', 'Grouped Integer', or 'SemiContinuous'. 
+   The type of all scalar decision variables. Optionally you may specify «decision» to get the integer type(s) for the indicated structured decision, in terms of the decision's intrinsic indexes.  
    
 "group"   "group"  
−   LP,QP,NLP  +   LP,QP,QCP, NLP 
 Vars   Vars  
 numeric   numeric  
+   Applicable only to a grouped integer variable, returns the group number for each scalar decision variable. You may optionally specify «decision» to obtain the groups for a single structured decision, which will be indexed by the decision's intrinsic indexes.  
    
 "maximize"   "maximize"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 atomic   atomic  
−   True, False  +   True, False, Null 
+   Indicates whether the optimization maximizes or minimizes an objective, or whether there is no objective at all (a find any feasible problem).  
    
 "engine"   "engine"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 atomic   atomic  
 text   text  
+   The name of the engine that will be, or was, used to solve the optimization.  
    
 "setting"   "setting"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 local .Parameter   local .Parameter  
 numeric   numeric  
+   A list of all solver engine control setting values.  
    
 "type"   "type"  
−   LP,QP,NLP  +   LP,QP,QCP,NLP 
 atomic   atomic  
−   "LP","QP", "QCP"  +   "LP","QP", "QCP", "CQCP", "NCQCP", "NLP", "NSP" 
+   The problem type.  
    
−  
−  
−  
−  
−  
−  
−  
−  
−  
}  }  
Revision as of 20:59, 11 February 2011
New to Analytica 4.3. Supercedes the earlier SolverInfo function.
OptInfo(opt, item, decision, constraint, asRef)
Provides access to an «item» in the definition of an optimization problem definition («opt») created by DefineOptimization.
Possible values for the «item» are:
"Item"  Used for  Indexed by  Type  Description 

"All"  LP, QP, QCP, NLP  local .item  various  Returns a comprehensive view inside the optimization, listing most items shown here. This is the same info you get when you double click on the «LP», «NLP», etc., cell in a result window. 
"vars"  LP,QP,QCP,NLP  Vars  Text  This lists all scalar decision variable, where each structured decision has been "flattened" to a single vector. This same index is used to index may of the possible OptInfo results that refer to scalar decisions, e.g., "ObjCoef", "Q", "Lhs", "LhsQ", etc. 
"constraints"  LP,QP,QCP,NLP  Constraints  Text  This lists all the scalar constraints, where each structured constraint has been flattened to a single vector. This same index is used to index many of the possible OptInfo results that refer to scalar constraints, e.g., "Lhs", "LhsQ", "Rhs", "Sense", "constraintLb", "constraintUb", etc. 
"objcoef"  LP, QP, QCP  Vars  numeric  The scalar objective linear coefficients. 
"Q"  QP, QCP  Vars, Vars2  numeric  The scalar quadratic coefficients for the objective. Dense matrix. 
"lhs"  LP, QP, QCP  Vars, Constraints  numeric  The linear coefficients for all scalar constraints. Dense matrix. You may optionally specify «constraint» to obtain the coefficients for just one constraint, in the intrinsic dimensionality of that constraint but with respect to all scalar decision variables. Or you may specify «decision» to get the coefficients for just one decision, but relative to all scalar constraints. Or you may specify both «decision» and «constraint» to get the coefficients for only one decision and only one constraint, in the dimensionality of each. 
"lhsQ",  QCP  Vars, Vars2, Constraints  numeric  The quadratic coefficients for all scalar scalar constraints. Dense matrices, may be too large to fit in memory for some large structured QCPs. You may optionally specify «decision» and/or «constraint» to obtain the quadratic coefficients for just that structured decision and constraint. 
"rhs"  LP,QP,QCP,NLP  Constraints  numeric  The righthand side coefficients for all scalar constraints. You may optionally specify «constraint» to get the coefficients for a single structured constraint, in which case the result will be indexed by the constraint's intrinsic indexes. For a linear or quadratic constraint, the RHS will be the constant term. There is no guarantee of the sign, since it depends on how DefineOptimization rearranges the constraint when it processes the coefficients. For a nonlinear constraint, rhs will usually be 0. For a range constraint, e.g., a <= f(x) <= b , the far right constant (b) is returned. It is better to use "constraintLb" and "constraintUb" for range constraints.

"constraintUb"  LP,QP,QCP,NLP  Constraints  numeric  Upper bound for each scalar constraint. You may optionally specify «constraint» to obtain the values for a single structured constraint in the intrinsic dimensionality of the constraint. 
"constraintLb"  LP,QP,QCP,NLP  Constraints  numeric  Lower bound for each scalar constraint. You may optionally specify «constraint» to obtain the values for a single structured constraint in the intrinsic dimensionality of the constraint. 
"sense"  LP,QP,QCP,NLP  Constraints  '>=','<=', '=', 'R'  Inequality for each constraint. 'R' for range (lb & ub). You may optionally specify «constraint» to obtain the sense for a single structured constraint. 
"lb"  LP,QP,QCP,NLP  Vars  numeric  Lower bound for each scalar variable. You may optionally specify «decision» to obtain the value for a single structured decision variable, in terms of the decision's intrinsic indexes. 
"ub"  LP,QP,QCP,NLP  Vars  numeric  Upper bound for each scalar variable. You may optionally specify «decision» to obtain the value for a single structured decision variable, in terms of the decision's intrinsic indexes. 
"integer type"  LP,QP,QCP,NLP  Vars  'Continuous', 'Integer', 'Boolean', 'Grouped Integer', or 'SemiContinuous'.  The type of all scalar decision variables. Optionally you may specify «decision» to get the integer type(s) for the indicated structured decision, in terms of the decision's intrinsic indexes. 
"group"  LP,QP,QCP, NLP  Vars  numeric  Applicable only to a grouped integer variable, returns the group number for each scalar decision variable. You may optionally specify «decision» to obtain the groups for a single structured decision, which will be indexed by the decision's intrinsic indexes. 
"maximize"  LP,QP,QCP,NLP  atomic  True, False, Null  Indicates whether the optimization maximizes or minimizes an objective, or whether there is no objective at all (a find any feasible problem). 
"engine"  LP,QP,QCP,NLP  atomic  text  The name of the engine that will be, or was, used to solve the optimization. 
"setting"  LP,QP,QCP,NLP  local .Parameter  numeric  A list of all solver engine control setting values. 
"type"  LP,QP,QCP,NLP  atomic  "LP","QP", "QCP", "CQCP", "NCQCP", "NLP", "NSP"  The problem type. 
If you include as a «decision» the identifier of a decision variable passed into the «decisions» parameter of DefineOptimization, it gives results just for that decision. The result is dimensioned by the decision variable's indexes rather than by the .Vars index. The «decision» parameter is relevant to any of the «item»s in the above table that show .Vars in the dimensionality column.
«constraint» is the identifier of a constraint node passed into the «constraints» parameter of DefineOptimization. When this is provided, only the portion of the requested item relevant to that constraint is returned, and the result is dimensioned by the constraint's OptDimensions rather than by the .Constraints index. The «constraint» parameter is relevant to any of the «item»s in the above table that show .Constraints in the dimensionality column.
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