From d844d3ad6d5932107c7fbbfba17bee68489f9d72 Mon Sep 17 00:00:00 2001
From: Matthias Miltenberger <miltenberger@zib.de>
Date: Tue, 11 Sep 2018 12:53:09 +0200
Subject: [PATCH 1/2] compute activity before comparison with lhs/rhs for
 correct dualsols

---
 src/pyscipopt/scip.pyx | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/src/pyscipopt/scip.pyx b/src/pyscipopt/scip.pyx
index ae2a00d05..fb4bc2eef 100644
--- a/src/pyscipopt/scip.pyx
+++ b/src/pyscipopt/scip.pyx
@@ -2056,6 +2056,7 @@ cdef class Model:
         # TODO this should ideally be handled on the SCIP side
         cdef int _nvars
         cdef SCIP_VAR** _vars
+        cdef SCIP_Real* _vals
         cdef SCIP_Bool _success
         dual = 0.0
 
@@ -2072,13 +2073,14 @@ cdef class Model:
             dual = SCIPgetDualsolLinear(self._scip, transcons.cons)
             if dual == 0.0 and _nvars == 1:
                 _vars = SCIPgetVarsLinear(self._scip, transcons.cons)
-                LPsol = SCIPvarGetLPSol(_vars[0])
+                _vals = SCIPgetValsLinear(self._scip, transcons.cons)
+                activity = SCIPvarGetLPSol(_vars[0]) * _vals[0]
                 rhs = SCIPgetRhsLinear(self._scip, transcons.cons)
                 lhs = SCIPgetLhsLinear(self._scip, transcons.cons)
-                if (LPsol == rhs) or (LPsol == lhs):
+                if (activity == rhs) or (activity == lhs):
                     dual = SCIPgetVarRedcost(self._scip, _vars[0])
 
-            if self.getObjectiveSense() == "maximize":
+            if self.getObjectiveSense() == "maximize" and not dual == 0.0:
                 dual = -dual
         except:
             raise Warning("no dual solution available for constraint " + cons.name)

From 1f1569128764f8180bbb9715788b692eca2c9c4d Mon Sep 17 00:00:00 2001
From: Matthias Miltenberger <miltenberger@zib.de>
Date: Tue, 11 Sep 2018 15:40:28 +0200
Subject: [PATCH 2/2] use SCIP internal method for next release

---
 src/pyscipopt/scip.pxd |  1 +
 src/pyscipopt/scip.pyx | 58 +++++++++++++++++++++++-------------------
 2 files changed, 33 insertions(+), 26 deletions(-)

diff --git a/src/pyscipopt/scip.pxd b/src/pyscipopt/scip.pxd
index f1bd897e2..79dca3bf2 100644
--- a/src/pyscipopt/scip.pxd
+++ b/src/pyscipopt/scip.pxd
@@ -670,6 +670,7 @@ cdef extern from "scip/scip.h":
     SCIP_Real SCIPgetDualbound(SCIP* scip)
     SCIP_Real SCIPgetDualboundRoot(SCIP* scip)
     SCIP_Real SCIPgetVarRedcost(SCIP* scip, SCIP_VAR* var)
+    SCIP_RETCODE SCIPgetDualSolVal(SCIP* scip, SCIP_CONS* cons, SCIP_Real* dualsolval, SCIP_Bool* boundconstraint)
 
     # Reader plugin
     SCIP_RETCODE SCIPincludeReader(SCIP* scip,
diff --git a/src/pyscipopt/scip.pyx b/src/pyscipopt/scip.pyx
index fb4bc2eef..503fdfe21 100644
--- a/src/pyscipopt/scip.pyx
+++ b/src/pyscipopt/scip.pyx
@@ -2053,38 +2053,44 @@ cdef class Model:
         :param Constraint cons: linear constraint
 
         """
-        # TODO this should ideally be handled on the SCIP side
+        cdef SCIP_Real dualsolval
+        cdef SCIP_Bool boundconstraint
         cdef int _nvars
         cdef SCIP_VAR** _vars
         cdef SCIP_Real* _vals
         cdef SCIP_Bool _success
-        dual = 0.0
 
-        constype = bytes(SCIPconshdlrGetName(SCIPconsGetHdlr(cons.cons))).decode('UTF-8')
-        if not constype == 'linear':
-            raise Warning("dual solution values not available for constraints of type ", constype)
+        if self.version() > 6.0:
+            PY_SCIP_CALL( SCIPgetDualSolVal(self._scip, cons.cons, &dualsolval, &boundconstraint) )
+            return dualsolval
+        else:
+            dual = 0.0
 
-        try:
-            _nvars = SCIPgetNVarsLinear(self._scip, cons.cons)
-            if cons.isOriginal():
-                transcons = <Constraint>self.getTransformedCons(cons)
-            else:
-                transcons = cons
-            dual = SCIPgetDualsolLinear(self._scip, transcons.cons)
-            if dual == 0.0 and _nvars == 1:
-                _vars = SCIPgetVarsLinear(self._scip, transcons.cons)
-                _vals = SCIPgetValsLinear(self._scip, transcons.cons)
-                activity = SCIPvarGetLPSol(_vars[0]) * _vals[0]
-                rhs = SCIPgetRhsLinear(self._scip, transcons.cons)
-                lhs = SCIPgetLhsLinear(self._scip, transcons.cons)
-                if (activity == rhs) or (activity == lhs):
-                    dual = SCIPgetVarRedcost(self._scip, _vars[0])
-
-            if self.getObjectiveSense() == "maximize" and not dual == 0.0:
-                dual = -dual
-        except:
-            raise Warning("no dual solution available for constraint " + cons.name)
-        return dual
+            constype = bytes(SCIPconshdlrGetName(SCIPconsGetHdlr(cons.cons))).decode('UTF-8')
+            if not constype == 'linear':
+                raise Warning("dual solution values not available for constraints of type ", constype)
+
+            try:
+                _nvars = SCIPgetNVarsLinear(self._scip, cons.cons)
+                if cons.isOriginal():
+                    transcons = <Constraint>self.getTransformedCons(cons)
+                else:
+                    transcons = cons
+                dual = SCIPgetDualsolLinear(self._scip, transcons.cons)
+                if dual == 0.0 and _nvars == 1:
+                    _vars = SCIPgetVarsLinear(self._scip, transcons.cons)
+                    _vals = SCIPgetValsLinear(self._scip, transcons.cons)
+                    activity = SCIPvarGetLPSol(_vars[0]) * _vals[0]
+                    rhs = SCIPgetRhsLinear(self._scip, transcons.cons)
+                    lhs = SCIPgetLhsLinear(self._scip, transcons.cons)
+                    if (activity == rhs) or (activity == lhs):
+                        dual = SCIPgetVarRedcost(self._scip, _vars[0])
+
+                if self.getObjectiveSense() == "maximize" and not dual == 0.0:
+                    dual = -dual
+            except:
+                raise Warning("no dual solution available for constraint " + cons.name)
+            return dual
 
     def getDualfarkasLinear(self, Constraint cons):
         """Retrieve the dual farkas value to a linear constraint.