scip_nlp.c

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/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
/*                                                                           */
/*                  This file is part of the program and library             */
/*         SCIP --- Solving Constraint Integer Programs                      */
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/*  Copyright (c) 2002-2024 Zuse Institute Berlin (ZIB)                      */
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/**@file   scip_nlp.c
 * @ingroup OTHER_CFILES
 * @brief  public methods for nonlinear relaxation
 * @author Thorsten Gellermann
 * @author Stefan Vigerske
 *
 * @todo check all SCIP_STAGE_* switches, and include the new stages TRANSFORMED and INITSOLVE
 */
 
/*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
 
#include "blockmemshell/memory.h"
#include "scip/nlpi.h"
#include "scip/debug.h"
#include "scip/nlp.h"
#include "scip/pub_message.h"
#include "scip/pub_misc.h"
#include "scip/pub_nlp.h"
#include "scip/pub_paramset.h"
#include "scip/scip_mem.h"
#include "scip/scip_nlp.h"
#include "scip/scip_param.h"
#include "scip/scip_sol.h"
#include "scip/set.h"
#include "scip/struct_mem.h"
#include "scip/struct_prob.h"
#include "scip/struct_scip.h"
#include "scip/struct_set.h"
#include "scip/struct_var.h"
 
/**@addtogroup PublicNLPMethods
 * @{
 */
 
/** returns whether the NLP relaxation has been enabled
 *
 *  If the NLP relaxation is enabled, then SCIP will construct the NLP relaxation when the solving process is about to begin.
 *  To check whether an NLP is existing, use SCIPisNLPConstructed().
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITPRESOLVE
 *       - \ref SCIP_STAGE_PRESOLVING
 *       - \ref SCIP_STAGE_EXITPRESOLVE
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 *
 *  @see SCIPenableNLP
 */
SCIP_Bool SCIPisNLPEnabled(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPisNLPEnabled", FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   return scip->transprob->nlpenabled;
}
 
/** notifies SCIP that the NLP relaxation should be initialized in INITSOLVE
 *
 *  This method is typically called by a constraint handler that handles constraints that have a nonlinear representation as nonlinear rows, e.g., cons_nonlinear.
 *
 *  The function should be called before the branch-and-bound process is initialized, e.g., when presolve is exiting.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITPRESOLVE
 *       - \ref SCIP_STAGE_PRESOLVING
 *       - \ref SCIP_STAGE_EXITPRESOLVE
 *       - \ref SCIP_STAGE_PRESOLVED
 */
void SCIPenableNLP(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPenableNLP", FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE) );
 
   scip->transprob->nlpenabled = TRUE;
}
 
/** returns, whether an NLP has been constructed
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_Bool SCIPisNLPConstructed(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPisNLPConstructed", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   return (scip->nlp != NULL);
}
 
/** checks whether the NLP has a continuous variable in a nonlinear term
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPhasNLPContinuousNonlinearity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_Bool*            result              /**< buffer to store result */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPhasNLPContinuousNonlinearity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been not constructed.\n");
      return SCIP_ERROR;
   }
 
   SCIP_CALL( SCIPnlpHasContinuousNonlinearity(scip->nlp, scip->mem->probmem, scip->set, scip->stat, result) );
 
   return SCIP_OKAY;
}
 
/** gets current NLP variables along with the current number of NLP variables
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNLPVarsData(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_VAR***           vars,               /**< pointer to store the array of NLP variables, or NULL */
   int*                  nvars               /**< pointer to store the number of NLP variables, or NULL */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNLPVarsData", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp != NULL )
   {
      if( vars != NULL )
         *vars = SCIPnlpGetVars(scip->nlp);
      if( nvars != NULL )
         *nvars = SCIPnlpGetNVars(scip->nlp);
   }
   else
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   return SCIP_OKAY;
}
 
/** gets array with variables of the NLP
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_VAR** SCIPgetNLPVars(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPVars", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return NULL; /*lint !e527*/
   }
 
   return SCIPnlpGetVars(scip->nlp);
}
 
/** gets current number of variables in NLP
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
int SCIPgetNNLPVars(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNNLPVars", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return 0; /*lint !e527*/
   }
 
   return SCIPnlpGetNVars(scip->nlp);
}
 
/** computes for each variables the number of NLP rows in which the variable appears in the nonlinear part
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNLPVarsNonlinearity(
   SCIP*                 scip,               /**< SCIP data structure */
   int*                  nlcount             /**< an array of length at least SCIPnlpGetNVars() to store nonlinearity counts of variables */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNLPVarsNonlinearity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpGetVarsNonlinearity(scip->nlp, scip->mem->probmem, scip->set, scip->stat, nlcount) );
 
   return SCIP_OKAY;
}
 
/** returns dual solution values associated with lower bounds of NLP variables
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_Real* SCIPgetNLPVarsLbDualsol(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPVarsLbDualsol", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return NULL; /*lint !e527*/
   }
 
   return SCIPnlpGetVarsLbDualsol(scip->nlp);
}
 
/** returns dual solution values associated with upper bounds of NLP variables
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_Real* SCIPgetNLPVarsUbDualsol(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPVarsUbDualsol", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return NULL; /*lint !e527*/
   }
 
   return SCIPnlpGetVarsUbDualsol(scip->nlp);
}
 
/** gets current NLP nonlinear rows along with the current number of NLP nonlinear rows
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNLPNlRowsData(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW***         nlrows,             /**< pointer to store the array of NLP nonlinear rows, or NULL */
   int*                  nnlrows             /**< pointer to store the number of NLP nonlinear rows, or NULL */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNLPNlRowsData", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   if( nlrows != NULL )
      *nlrows = SCIPnlpGetNlRows(scip->nlp);
   if( nnlrows != NULL )
      *nnlrows = SCIPnlpGetNNlRows(scip->nlp);
 
   return SCIP_OKAY;
}
 
/** gets array with nonlinear rows of the NLP
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_NLROW** SCIPgetNLPNlRows(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPNlRows", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return NULL; /*lint !e527*/
   }
 
   return SCIPnlpGetNlRows(scip->nlp);
}
 
/** gets current number of nonlinear rows in NLP
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
int SCIPgetNNLPNlRows(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNNLPNlRows", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return 0; /*lint !e527*/
   }
 
   return SCIPnlpGetNNlRows(scip->nlp);
}
 
/** gets statistics on convexity of rows in NLP
 *
 *  Reports counts on the current number of linear rows, convex inequalities, nonconvex inequalities, and nonlinear equalities or ranged rows.
 *  - A nonlinear inequality with infinity left-hand-side is accounted as convex if its expression has been marked as convex.
 *  - A nonlinear inequality with infinity right-hand-side is accounted as convex if its expression has been marked as concave.
 *  - Other nonlinear rows are accounted as nonconvex. Note that convexity for a nonlinear row may just not have been detected.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 *       - \ref SCIP_STAGE_SOLVED
 */
SCIP_RETCODE SCIPgetNLPNlRowsStat(
   SCIP*                 scip,               /**< SCIP data structure */
   int*                  nlinear,            /**< buffer to store number of linear rows in NLP, or NULL */
   int*                  nconvexineq,        /**< buffer to store number of convex inequalities in NLP, or NULL */
   int*                  nnonconvexineq,     /**< buffer to store number of nonconvex inequalities in NLP, or NULL */
   int*                  nnonlineareq        /**< buffer to store number of nonlinear equalities or ranged rows in NLP, or NULL */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPnlpGetNlRowsStat", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_ERROR;
   }
 
   SCIPnlpGetNlRowsStat(scip->nlp, nlinear, nconvexineq, nnonconvexineq, nnonlineareq);
 
   return SCIP_OKAY;
}
 
/** adds a nonlinear row to the NLP. This row is captured by the NLP.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPaddNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow               /**< nonlinear row to add to NLP */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPaddNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpAddNlRow(scip->nlp, SCIPblkmem(scip), scip->set, scip->stat, nlrow) );
 
   return SCIP_OKAY;
}
 
/** removes a nonlinear row from the NLP
 *
 *  This row is released in the NLP.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 *       - \ref SCIP_STAGE_SOLVED
 *       - \ref SCIP_STAGE_EXITSOLVE
 */
SCIP_RETCODE SCIPdelNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow               /**< nonlinear row to add to NLP */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPdelNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpDelNlRow(scip->nlp, SCIPblkmem(scip), scip->set, scip->stat, nlrow) );
 
   return SCIP_OKAY;
}
 
/** makes sure that the NLP of the current node is flushed
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPflushNLP(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPflushNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpFlush(scip->nlp, scip->mem->probmem, scip->set, scip->stat) );
 
   return SCIP_OKAY;
}
 
/** sets or clears initial primal guess for NLP solution (start point for NLP solver)
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPsetNLPInitialGuess(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_Real*            initialguess        /**< values of initial guess (corresponding to variables from SCIPgetNLPVarsData), or NULL to use no start point */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPsetNLPInitialGuess", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpSetInitialGuess(scip->set, scip->nlp, SCIPblkmem(scip), initialguess) );
 
   return SCIP_OKAY;
}
 
/** sets initial primal guess for NLP solution (start point for NLP solver)
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPsetNLPInitialGuessSol(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_SOL*             sol                 /**< solution which values should be taken as initial guess, or NULL for LP solution */
   )
{
   SCIP_Real* vals;
 
   SCIP_CALL( SCIPcheckStage(scip, "SCIPsetNLPInitialGuessSol", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPallocBufferArray(scip, &vals, SCIPnlpGetNVars(scip->nlp)) );
   SCIP_CALL( SCIPgetSolVals(scip, sol, SCIPnlpGetNVars(scip->nlp), SCIPnlpGetVars(scip->nlp), vals) );
   SCIP_CALL( SCIPnlpSetInitialGuess(scip->set, scip->nlp, SCIPblkmem(scip), vals) );
   SCIPfreeBufferArray(scip, &vals);
 
   return SCIP_OKAY;
}
 
/** solves the current NLP (or diving NLP if in diving mode) with given parameters
 *
 *  Typical use is
 *
 *      SCIP_NLPPARAM nlparam = { SCIP_NLPPARAM_DEFAULT(scip); }
 *      nlpparam.iterlimit = 42;
 *      SCIP_CALL( SCIPsolveNLPParam(scip, nlpparam) );
 *
 *  or, in one line:
 *
 *      SCIP_CALL( SCIPsolveNLPParam(scip, (SCIP_NLPPARAM){ SCIP_NLPPARAM_DEFAULT(scip), .iterlimit = 42 }) );
 *
 *  To get the latter, also \ref SCIPsolveNLP can be used.
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPsolveNLPParam(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLPPARAM         param               /**< NLP solve parameters */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPsolveNLPParam", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpSolve(scip->nlp, SCIPblkmem(scip), scip->set, scip->messagehdlr, scip->stat, scip->primal, scip->tree, &param) );
 
   return SCIP_OKAY;
}
 
#if defined(_MSC_VER) && _MSC_VER < 1800
/* warn that SCIPsolveNLP() macro isn't perfect with ancient MSVC */
#pragma message ( "Warning: designated initializers not supported by this version of MSVC. Parameters given to NLP solves may be ignored." )
#endif
 
/** gets solution status of current NLP
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_NLPSOLSTAT SCIPgetNLPSolstat(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPSolstat", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return SCIP_NLPSOLSTAT_UNKNOWN; /*lint !e527*/
   }
 
   return SCIPnlpGetSolstat(scip->nlp);
}
 
/** gets termination status of last NLP solve
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_NLPTERMSTAT SCIPgetNLPTermstat(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPTermstat", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return SCIP_NLPTERMSTAT_OTHER; /*lint !e527*/
   }
 
   return SCIPnlpGetTermstat(scip->nlp);
}
 
/** gives statistics (number of iterations, solving time, ...) of last NLP solve
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNLPStatistics(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLPSTATISTICS*   statistics          /**< pointer to store statistics */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNLPStatistics", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpGetStatistics(scip->set, scip->nlp, statistics) );
 
   return SCIP_OKAY;
}
 
/** gets objective value of current NLP
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_Real SCIPgetNLPObjval(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPgetNLPObjval", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp != NULL )
   {
      return SCIPnlpGetObjval(scip->nlp);
   }
   else
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALID;
   }
}
 
/** indicates whether a solution for the current NLP is available
 *
 * The solution may be optimal, feasible, or infeasible.
 * Thus, returns whether the NLP solution status is at most \ref SCIP_NLPSOLSTAT_LOCINFEASIBLE.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_Bool SCIPhasNLPSolution(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL_ABORT( SCIPcheckStage(scip, "SCIPhasNLPSolution", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      SCIPABORT();
      return FALSE; /*lint !e527*/
   }
 
   return SCIPnlpHasSolution(scip->nlp);
}
 
/** gets fractional variables of last NLP solution along with solution values and fractionalities
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNLPFracVars(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_VAR***           fracvars,           /**< pointer to store the array of NLP fractional variables, or NULL */
   SCIP_Real**           fracvarssol,        /**< pointer to store the array of NLP fractional variables solution values, or NULL */
   SCIP_Real**           fracvarsfrac,       /**< pointer to store the array of NLP fractional variables fractionalities, or NULL */
   int*                  nfracvars,          /**< pointer to store the number of NLP fractional variables , or NULL */
   int*                  npriofracvars       /**< pointer to store the number of NLP fractional variables with maximal branching priority, or NULL */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNLPFracVars", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpGetFracVars(scip->nlp, SCIPblkmem(scip), scip->set, scip->stat, fracvars, fracvarssol, fracvarsfrac, nfracvars, npriofracvars) );
 
   return SCIP_OKAY;
}
 
/** writes current NLP to a file
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPwriteNLP(
   SCIP*                 scip,               /**< SCIP data structure */
   const char*           filename            /**< file name */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPwriteNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpWrite(scip->nlp, scip->mem->probmem, scip->set, scip->stat, scip->messagehdlr, filename) );
 
   return SCIP_OKAY;
}
 
/** gets the NLP interface and problem used by the SCIP NLP
 *
 *  @warning With the NLPI and its problem, all methods defined in \ref scip_nlpi.h and \ref pub_nlpi.h can be used.
 *           It needs to be ensured that the full internal state of the NLPI does not change or is recovered completely
 *           after the end of the method that uses the NLPI. In particular, if the NLP or its solution is manipulated
 *           (e.g. by calling one of the SCIPaddNlpi...() or the SCIPsolveNlpi() method), one has to check in advance
 *           whether the NLP is currently solved.  If this is the case, one has to make sure that the internal solution
 *           status is recovered completely again. Additionally one has to resolve the NLP with
 *           SCIPsolveNlpi() in order to reinstall the internal solution status.
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNLPI(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLPI**           nlpi,               /**< pointer to store the NLP solver interface */
   SCIP_NLPIPROBLEM**    nlpiproblem         /**< pointer to store the NLP solver interface problem */
   )
{
   assert(nlpi != NULL);
   assert(nlpiproblem != NULL);
 
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNLPI", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   *nlpi = SCIPnlpGetNLPI(scip->nlp);
   *nlpiproblem = SCIPnlpGetNLPIProblem(scip->nlp);
 
   return SCIP_OKAY;
}
 
/** @} */
 
/**@addtogroup PublicNLPDiveMethods
 * @{ */
 
/** initiates NLP diving
 *
 *  Makes functions SCIPchgVarObjDiveNLP(), SCIPchgVarBoundsDiveNLP() and SCIPchgVarsBoundsDiveNLP() available.
 *  Further, SCIPsolveNLP() can be used to solve the diving NLP.
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPstartDiveNLP(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPstartDiveNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpStartDive(scip->nlp, SCIPblkmem(scip), scip->set, scip->stat) );
 
   return SCIP_OKAY;
}
 
/** ends NLP diving
 *
 *  Resets changes made by SCIPchgVarObjDiveNLP(), SCIPchgVarBoundsDiveNLP(), and SCIPchgVarsBoundsDiveNLP().
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPendDiveNLP(
   SCIP*                 scip                /**< SCIP data structure */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPendDiveNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpEndDive(scip->nlp, SCIPblkmem(scip), scip->set, scip->stat) );
 
   return SCIP_OKAY;
}
 
/** changes linear objective coefficient of a variable in diving NLP
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgVarObjDiveNLP(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_VAR*             var,                /**< variable which coefficient to change */
   SCIP_Real             coef                /**< new value for coefficient */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgVarObjDiveNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   assert( var->scip == scip );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpChgVarObjDive(scip->nlp, SCIPblkmem(scip), scip->set, scip->stat, var, coef) );
 
   return SCIP_OKAY;
}
 
/** changes bounds of a variable in diving NLP
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgVarBoundsDiveNLP(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_VAR*             var,                /**< variable which bounds to change */
   SCIP_Real             lb,                 /**< new lower bound */
   SCIP_Real             ub                  /**< new upper bound */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgVarBoundsDiveNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   assert( var->scip == scip );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpChgVarBoundsDive(scip->set, scip->nlp, var, lb, ub) );
 
   return SCIP_OKAY;
}
 
/** changes bounds of a set of variables in diving NLP
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgVarsBoundsDiveNLP(
   SCIP*                 scip,               /**< SCIP data structure */
   int                   nvars,              /**< number of variables which bounds to changes */
   SCIP_VAR**            vars,               /**< variables which bounds to change */
   SCIP_Real*            lbs,                /**< new lower bounds */
   SCIP_Real*            ubs                 /**< new upper bounds */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgVarsBoundsDiveNLP", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("NLP has not been constructed.\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlpChgVarsBoundsDive(scip->nlp, scip->set, nvars, vars, lbs, ubs) );
 
   return SCIP_OKAY;
}
 
/** @} */
 
/**@addtogroup PublicNLRowMethods
 * @{
 */
 
/** creates and captures a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPcreateNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW**          nlrow,              /**< buffer to store pointer to nonlinear row */
   const char*           name,               /**< name of nonlinear row */
   SCIP_Real             constant,           /**< constant */
   int                   nlinvars,           /**< number of linear variables */
   SCIP_VAR**            linvars,            /**< linear variables, or NULL if nlinvars == 0 */
   SCIP_Real*            lincoefs,           /**< linear coefficients, or NULL if nlinvars == 0 */
   SCIP_EXPR*            expr,               /**< nonlinear expression, or NULL */
   SCIP_Real             lhs,                /**< left hand side */
   SCIP_Real             rhs,                /**< right hand side */
   SCIP_EXPRCURV         curvature           /**< curvature of the nonlinear row */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPcreateNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowCreate(nlrow, scip->mem->probmem, scip->set, scip->stat,
         name, constant, nlinvars, linvars, lincoefs, expr, lhs, rhs, curvature) );
 
   return SCIP_OKAY;
}
 
/** creates and captures a nonlinear row without any coefficients
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPcreateEmptyNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW**          nlrow,              /**< pointer to nonlinear row */
   const char*           name,               /**< name of nonlinear row */
   SCIP_Real             lhs,                /**< left hand side */
   SCIP_Real             rhs                 /**< right hand side */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPcreateEmptyNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowCreate(nlrow, scip->mem->probmem, scip->set, scip->stat,
         name, 0.0, 0, NULL, NULL, NULL, lhs, rhs, SCIP_EXPRCURV_UNKNOWN) );
 
   return SCIP_OKAY;
}
 
/** creates and captures a nonlinear row from a linear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPcreateNlRowFromRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW**          nlrow,              /**< pointer to nonlinear row */
   SCIP_ROW*             row                 /**< the linear row to copy */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPcreateNlRowFromRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowCreateFromRow(nlrow, scip->mem->probmem, scip->set, scip->stat, row) );
 
   return SCIP_OKAY;
}
 
/** increases usage counter of a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPcaptureNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow               /**< nonlinear row to capture */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPcaptureNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIPnlrowCapture(nlrow);
 
   return SCIP_OKAY;
}
 
/** decreases usage counter of a nonlinear row, and frees memory if necessary
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 *       - \ref SCIP_STAGE_EXITSOLVE
 */
SCIP_RETCODE SCIPreleaseNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW**          nlrow               /**< pointer to nonlinear row */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPreleaseNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, TRUE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowRelease(nlrow, scip->mem->probmem, scip->set, scip->stat) );
 
   return SCIP_OKAY;
}
 
/** changes left hand side of a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgNlRowLhs(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real             lhs                 /**< new left hand side */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgNlRowLhs", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowChgLhs(nlrow, scip->set, scip->stat, scip->nlp, lhs) );
 
   return SCIP_OKAY;
}
 
/** changes right hand side of a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgNlRowRhs(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real             rhs                 /**< new right hand side */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgNlRowRhs", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowChgRhs(nlrow, scip->set, scip->stat, scip->nlp, rhs) );
 
   return SCIP_OKAY;
}
 
/** changes constant of a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgNlRowConstant(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   SCIP_Real             constant            /**< new value for constant */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgNlRowConstant", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowChgConstant(nlrow, scip->set, scip->stat, scip->nlp, constant) );
 
   return SCIP_OKAY;
}
 
/** set curvature of a nonlinear row */
void SCIPsetNlRowCurvature(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   SCIP_EXPRCURV         curvature           /**< curvature of NLP row */
   )
{
   assert(scip != NULL);
 
   SCIPnlrowSetCurvature(scip->nlp, scip->set, nlrow, curvature);
}
 
/** adds variable with a linear coefficient to a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPaddLinearCoefToNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   SCIP_VAR*             var,                /**< problem variable */
   SCIP_Real             val                 /**< value of coefficient in linear part of row */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPaddLinearCoefToNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowAddLinearCoef(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->nlp, var, val) );
 
   return SCIP_OKAY;
}
 
/** adds variables with linear coefficients to a row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPaddLinearCoefsToNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   int                   nvars,              /**< number of variables to add to the row */
   SCIP_VAR**            vars,               /**< problem variables to add */
   SCIP_Real*            vals                /**< values of coefficients in linear part of row */
   )
{
   int v;
 
   assert(nvars == 0 || vars != NULL);
   assert(nvars == 0 || vals != NULL);
 
   SCIP_CALL( SCIPcheckStage(scip, "SCIPaddLinearCoefsToNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   /* add the variables to the row */
   for( v = 0; v < nvars; ++v )
   {
      SCIP_CALL( SCIPnlrowAddLinearCoef(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->nlp, vars[v], vals[v]) );
   }
 
   return SCIP_OKAY;
}
 
/** changes linear coefficient of a variables in a nonlinear row
 *
 *  Setting the coefficient to 0.0 means that it is removed from the row.
 *  The variable does not need to exists before.
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPchgNlRowLinearCoef(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   SCIP_VAR*             var,                /**< variable */
   SCIP_Real             coef                /**< new value of coefficient */
   )
{
   assert(var != NULL);
 
   SCIP_CALL( SCIPcheckStage(scip, "SCIPchgNlRowLinearCoef", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowChgLinearCoef(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->nlp, var, coef) );
 
   return SCIP_OKAY;
}
 
/** sets or deletes expression in a nonlinear row
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPsetNlRowExpr(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   SCIP_EXPR*            expr                /**< expression, or NULL */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPsetNlRowExpr", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowChgExpr(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->nlp, expr) );
 
   /* invalidate curvature */
   SCIPnlrowSetCurvature(scip->nlp, scip->set, nlrow, SCIP_EXPRCURV_UNKNOWN);
 
   return SCIP_OKAY;
}
 
/** recalculates the activity of a nonlinear row in the last NLP solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPrecalcNlRowNLPActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow               /**< NLP nonlinear row */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPrecalcNlRowNLPActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("do not have NLP for computing NLP activity\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlrowRecalcNLPActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp) );
 
   return SCIP_OKAY;
}
 
/** returns the activity of a nonlinear row in the last NLP solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowNLPActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real*            activity            /**< pointer to store activity value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowNLPActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("do not have NLP for computing NLP activity\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlrowGetNLPActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp, activity) );
 
   return SCIP_OKAY;
}
 
/** gives the feasibility of a nonlinear row in the last NLP solution: negative value means infeasibility
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowNLPFeasibility(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real*            feasibility         /**< pointer to store feasibility value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowNLPFeasibility", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp == NULL )
   {
      SCIPerrorMessage("do not have NLP for computing NLP feasibility\n");
      return SCIP_INVALIDCALL;
   }
 
   SCIP_CALL( SCIPnlrowGetNLPFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp, feasibility) );
 
   return SCIP_OKAY;
}
 
/** recalculates the activity of a nonlinear row for the current pseudo solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPrecalcNlRowPseudoActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow               /**< NLP nonlinear row */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPrecalcNlRowPseudoActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowRecalcPseudoActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp) );
 
   return SCIP_OKAY;
}
 
/** gives the activity of a nonlinear row for the current pseudo solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowPseudoActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real*            pseudoactivity      /**< pointer to store pseudo activity value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowPseudoActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowGetPseudoActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp, pseudoactivity) );
 
   return SCIP_OKAY;
}
 
/** gives the feasibility of a nonlinear row for the current pseudo solution: negative value means infeasibility
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowPseudoFeasibility(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real*            pseudofeasibility   /**< pointer to store pseudo feasibility value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowPseudoFeasibility", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowGetPseudoFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp, pseudofeasibility) );
 
   return SCIP_OKAY;
}
 
/** recalculates the activity of a nonlinear row in the last NLP or pseudo solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPrecalcNlRowActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow               /**< NLP nonlinear row */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPrecalcNlRowActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp != NULL && SCIPnlpHasCurrentNodeNLP(scip->nlp) && SCIPnlpHasSolution(scip->nlp) )
   {
      SCIP_CALL( SCIPnlrowRecalcNLPActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp) );
   }
   else
   {
      SCIP_CALL( SCIPnlrowRecalcPseudoActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp) );
   }
 
   return SCIP_OKAY;
}
 
/** gives the activity of a nonlinear row in the last NLP or pseudo solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real*            activity            /**< pointer to store activity value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp != NULL && SCIPnlpHasCurrentNodeNLP(scip->nlp) && SCIPnlpHasSolution(scip->nlp) )
   {
      SCIP_CALL( SCIPnlrowGetNLPActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp, activity) );
   }
   else
   {
      SCIP_CALL( SCIPnlrowGetPseudoActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp, activity) );
   }
 
   return SCIP_OKAY;
}
 
/** gives the feasibility of a nonlinear row in the last NLP or pseudo solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowFeasibility(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_Real*            feasibility         /**< pointer to store feasibility value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowFeasibility", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( scip->nlp != NULL && SCIPnlpHasCurrentNodeNLP(scip->nlp) && SCIPnlpHasSolution(scip->nlp) )
   {
      SCIP_CALL( SCIPnlrowGetNLPFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp, feasibility) );
   }
   else
   {
      SCIP_CALL( SCIPnlrowGetPseudoFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp, feasibility) );
   }
 
   return SCIP_OKAY;
}
 
/** gives the activity of a nonlinear row for the given primal solution or NLP solution or pseudo solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowSolActivity(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_SOL*             sol,                /**< primal CIP solution, or NULL for NLP solution of pseudo solution */
   SCIP_Real*            activity            /**< pointer to store activity value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowSolActivity", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( sol != NULL )
   {
      SCIP_CALL( SCIPnlrowGetSolActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, sol, activity) );
   }
   else if( scip->nlp != NULL && SCIPnlpHasCurrentNodeNLP(scip->nlp) && SCIPnlpHasSolution(scip->nlp) )
   {
      SCIP_CALL( SCIPnlrowGetNLPActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp, activity) );
   }
   else
   {
      SCIP_CALL( SCIPnlrowGetPseudoActivity(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp, activity) );
   }
 
   return SCIP_OKAY;
}
 
/** gives the feasibility of a nonlinear row for the given primal solution
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowSolFeasibility(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP nonlinear row */
   SCIP_SOL*             sol,                /**< primal CIP solution */
   SCIP_Real*            feasibility         /**< pointer to store feasibility value */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowSolFeasibility", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   if( sol != NULL )
   {
      SCIP_CALL( SCIPnlrowGetSolFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, sol, feasibility) );
   }
   else if( scip->nlp != NULL && SCIPnlpHasCurrentNodeNLP(scip->nlp) && SCIPnlpHasSolution(scip->nlp) )
   {
      SCIP_CALL( SCIPnlrowGetNLPFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->primal, scip->tree, scip->nlp, feasibility) );
   }
   else
   {
      SCIP_CALL( SCIPnlrowGetPseudoFeasibility(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->transprob, scip->primal, scip->tree, scip->lp, feasibility) );
   }
 
   return SCIP_OKAY;
}
 
/** gives the minimal and maximal activity of a nonlinear row w.r.t. the variable's bounds
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPgetNlRowActivityBounds(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   SCIP_Real*            minactivity,        /**< buffer to store minimal activity, or NULL */
   SCIP_Real*            maxactivity         /**< buffer to store maximal activity, or NULL */
   )
{
   SCIP_CALL( SCIPcheckStage(scip, "SCIPgetNlRowActivityBounds", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowGetActivityBounds(nlrow, scip->mem->probmem, scip->set, scip->stat, minactivity, maxactivity) );
 
   return SCIP_OKAY;
}
 
/** prints a nonlinear row to file stream
 *
 *  @return \ref SCIP_OKAY is returned if everything worked. Otherwise a suitable error code is passed. See \ref
 *          SCIP_Retcode "SCIP_RETCODE" for a complete list of error codes.
 *
 *  @pre This method can be called if SCIP is in one of the following stages:
 *       - \ref SCIP_STAGE_PRESOLVED
 *       - \ref SCIP_STAGE_INITSOLVE
 *       - \ref SCIP_STAGE_SOLVING
 */
SCIP_RETCODE SCIPprintNlRow(
   SCIP*                 scip,               /**< SCIP data structure */
   SCIP_NLROW*           nlrow,              /**< NLP row */
   FILE*                 file                /**< output file (or NULL for standard output) */
   )
{
   assert(nlrow != NULL);
 
   SCIP_CALL( SCIPcheckStage(scip, "SCIPprintNlRow", FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE) );
 
   SCIP_CALL( SCIPnlrowPrint(nlrow, scip->mem->probmem, scip->set, scip->stat, scip->messagehdlr, file) );
 
   return SCIP_OKAY;
}
 
/** @} */