Add option for get Rhs, Lhs of nonlinear cons. Remove some mentions of quadratic cons

Author: Joao-Dionisio

CHANGELOG.md

@@ -2,6 +2,7 @@
 
 ## Unreleased
 ### Added
+- Added option to get Lhs, Rhs of nonlinear constraints
 - Added transformed option to getVarDict, updated test
 - Added categorical data example
 - Added printProblem to print problem to stdout

src/pyscipopt/scip.pxi

@@ -4265,7 +4265,7 @@ cdef class Model:
             if len(v) == 1: # linear
                 var = <Variable>v[0]
                 PY_SCIP_CALL(SCIPaddLinearVarNonlinear(self._scip, scip_cons, var.scip_var, c))
-            else: # quadratic
+            else: # nonlinear
                 assert len(v) == 2, 'term length must be 1 or 2 but it is %s' % len(v)
 
                 varexprs = <SCIP_EXPR**> malloc(2 * sizeof(SCIP_EXPR*))
@@ -4624,7 +4624,7 @@ cdef class Model:
                  enforce=True, check=True, propagate=True, local=False,
                  modifiable=False, dynamic=False, removable=False,
                  stickingatnode=False):
-        """Adds multiple linear or quadratic constraints.
+        """Adds multiple constraints.
 
         Each of the constraints is added to the model using Model.addCons().
 
@@ -5578,7 +5578,7 @@ cdef class Model:
         Parameters
         ----------
         cons : Constraint
-            linear or quadratic constraint
+            constraint to change the right-hand side from
         rhs : float or None
             new right-hand side (set to None for +infinity)
 
@@ -5602,7 +5602,7 @@ cdef class Model:
         Parameters
         ----------
         cons : Constraint
-            linear or quadratic constraint
+            constraint to change the left-hand side from
         lhs : float or None
             new left-hand side (set to None for -infinity)
 
@@ -5626,7 +5626,7 @@ cdef class Model:
         Parameters
         ----------
         cons : Constraint
-            linear or quadratic constraint
+            constraint to get the right-hand side from
 
         Returns
         -------
@@ -5636,7 +5636,7 @@ cdef class Model:
         constype = bytes(SCIPconshdlrGetName(SCIPconsGetHdlr(cons.scip_cons))).decode('UTF-8')
         if constype == 'linear':
             return SCIPgetRhsLinear(self._scip, cons.scip_cons)
-        elif constype == 'quadratic':
+        elif constype == 'nonlinear':
             return SCIPgetRhsNonlinear(cons.scip_cons)
         else:
             raise Warning("method cannot be called for constraints of type " + constype)
@@ -5648,7 +5648,7 @@ cdef class Model:
         Parameters
         ----------
         cons : Constraint
-            linear or quadratic constraint
+            linear or nonlinear constraint
 
         Returns
         -------
@@ -5658,7 +5658,7 @@ cdef class Model:
         constype = bytes(SCIPconshdlrGetName(SCIPconsGetHdlr(cons.scip_cons))).decode('UTF-8')
         if constype == 'linear':
             return SCIPgetLhsLinear(self._scip, cons.scip_cons)
-        elif constype == 'quadratic':
+        elif constype == 'nonlinear':
             return SCIPgetLhsNonlinear(cons.scip_cons)
         else:
             raise Warning("method cannot be called for constraints of type " + constype)
@@ -5724,7 +5724,7 @@ cdef class Model:
         Parameters
         ----------
         cons : Constraint
-            linear or quadratic constraint
+            linear constraint
         sol : Solution or None, optional
             solution to compute activity of, None to use current node's solution (Default value = None)
 
@@ -5761,7 +5761,7 @@ cdef class Model:
         Parameters
         ----------
         cons : Constraint
-            linear or quadratic constraint
+            linear constraint
         sol : Solution or None, optional
             solution to compute slack of, None to use current node's solution (Default value = None)
         side : str or None, optional

tests/test_nonlinear.py

@@ -305,3 +305,14 @@ def test_addExprNonLinear():
     assert m.getNSols() > 0
     assert m.isEQ(m.getVal(y), 2)
     assert m.isEQ(m.getVal(z), 27)
+
+def test_nonlinear_lhs_rhs():
+    from helpers.utils import random_nlp_1
+
+    m = random_nlp_1()
+    c = m.getConss()
+
+    m.hideOutput()
+    m.optimize()
+    assert m.isInfinity(-m.getLhs(c[0])) 
+    assert m.isEQ(m.getRhs(c[0]), 5)