Add feastol numerics checks

CHANGELOG.md

@@ -3,6 +3,7 @@
 ## Unreleased
 ### Added
 - Added support for knapsack constraints
+- Added isFeasLE, isFeasLT, isFeasGE, isFeasGT, and tests
 ### Fixed
 ### Changed
 ### Removed

src/pyscipopt/scip.pxd

@@ -1341,6 +1341,10 @@ cdef extern from "scip/scip.h":
     SCIP_Bool SCIPisGT(SCIP* scip, SCIP_Real val1, SCIP_Real val2)
     SCIP_Bool SCIPisEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
     SCIP_Bool SCIPisFeasEQ(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
+    SCIP_Bool SCIPisFeasLT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
+    SCIP_Bool SCIPisFeasGT(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
+    SCIP_Bool SCIPisFeasLE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
+    SCIP_Bool SCIPisFeasGE(SCIP *scip, SCIP_Real val1, SCIP_Real val2)
     SCIP_Bool SCIPisHugeValue(SCIP *scip, SCIP_Real val)
     SCIP_Bool SCIPisPositive(SCIP *scip, SCIP_Real val)
     SCIP_Bool SCIPisNegative(SCIP *scip, SCIP_Real val)

src/pyscipopt/scip.pxi

@@ -298,7 +298,7 @@
     if rc == SCIP_OKAY:
         pass
     elif rc == SCIP_ERROR:
         raise Exception('SCIP: unspecified error!')
     elif rc == SCIP_NOMEMORY:
         raise MemoryError('SCIP: insufficient memory error!')
     elif rc == SCIP_READERROR:
@@ -3070,7 +3070,7 @@
 
     def isFeasEQ(self, val1, val2):
         """
-        Checks, if relative difference of values is in range of feasibility tolerance.
+        Returns if relative difference of values is below feasibility tolerance.
 
         Parameters
         ----------
@@ -3083,6 +3083,70 @@
 
         """
         return SCIPisFeasEQ(self._scip, val1, val2)
+
+    def isFeasLT(self, val1, val2):
+        """
+        Returns if relative difference between val1 and val2 is less than feasibility tolerance.
+
+        Parameters
+        ----------
+        val1 : float
+        val2 : float
+
+        Returns
+        -------
+        bool
+
+        """
+        return SCIPisFeasLT(self._scip, val1, val2)
+
+    def isFeasLE(self, val1, val2):
+        """
+        Returns if relative difference between val1 and val2 is less than or equal to feasibility tolerance.
+
+        Parameters
+        ----------
+        val1 : float
+        val2 : float
+
+        Returns
+        -------
+        bool
+
+        """
+        return SCIPisFeasLE(self._scip, val1, val2)
+
+    def isFeasGT(self, val1, val2):
+        """
+        Returns if relative difference between val1 and val2 is greater than feasibility tolerance.
+
+        Parameters
+        ----------
+        val1 : float
+        val2 : float
+
+        Returns
+        -------
+        bool
+
+        """
+        return SCIPisFeasGT(self._scip, val1, val2)
+
+    def isFeasGE(self, val1, val2):
+        """
+        Returns if relative difference between val1 and val2 is greater than or equal to feasibility tolerance.
+
+        Parameters
+        ----------
+        val1 : float
+        val2 : float
+
+        Returns
+        -------
+        bool
+
+        """
+        return SCIPisFeasGE(self._scip, val1, val2)
 
     def isLE(self, val1, val2):
         """

tests/helpers/utils.py

@@ -51,17 +51,18 @@ def random_mip_1(disable_sepa=True, disable_heur=True, disable_presolve=True, no
 
 
 def random_lp_1():
-    return random_mip_1().relax()
+    random_mip_1().relax()
+    return random_mip_1()
 
 
 def random_nlp_1():
     model = Model()
 
-    v = model.addVar()
-    w = model.addVar()
-    x = model.addVar()
-    y = model.addVar()
-    z = model.addVar()
+    v = model.addVar(name="v", ub=2)
+    w = model.addVar(name="w", ub=3)
+    x = model.addVar(name="x", ub=4)
+    y = model.addVar(name="y", ub=1.4)
+    z = model.addVar(name="z", ub=4)
 
     model.addCons(exp(v) + log(w) + sqrt(x) + sin(y) + z ** 3 * y <= 5)
     model.setObjective(v + w + x + y + z, sense='maximize')
@@ -87,7 +88,7 @@ def knapsack_model(weights=[4, 2, 6, 3, 7, 5], costs=[7, 2, 5, 4, 3, 4], knapsac
         knapsackVars.append(s.addVar(varNames[i], vtype='I', obj=costs[i], ub=1.0))
 
     # adding a linear constraint for the knapsack constraint
-    s.addCons(quicksum(w * v for (w, v) in zip(weights, knapsackVars)) <= knapsackSize)
+    s.addCons(quicksum(w * v for (w, v) in zip(weights, knapsackVars)) <= knapsack_size)
 
     return s
 
@@ -249,4 +250,5 @@ def bin_packing_lp(sizes, capacity):
 
 
 def gastrans_lp():
-    return gastrans_model().relax()
+    gastrans_model().relax()
+    return gastrans_model()

tests/test_numerics.py

@@ -0,0 +1,20 @@
+from pyscipopt import Model
+import pytest
+
+def test_numerical_checks():
+    m = Model()
+
+    m.setParam("numerics/epsilon", 1e-10)
+    m.setParam("numerics/feastol", 1e-3)
+
+    assert m.isFeasEQ(1, 1.00001)
+    assert not m.isEQ(1, 1.00001)
+
+    assert m.isFeasLE(1, 0.99999) 
+    assert not m.isLE(1, 0.99999) 
+
+    assert m.isFeasGE(1, 1.00001)
+    assert not m.isGE(1, 1.00001)
+
+    assert not m.isFeasGT(1, 0.9999)
+    assert m.isGT(1, 0.9999)