Merge remote-tracking branch 'origin/master' into realtime-trace-jsonl

Author: MySweetEden

CHANGELOG.md

@@ -8,6 +8,7 @@
 - Wrapped isObjIntegral() and test
 - Added structured_optimization_trace recipe for structured optimization progress tracking
 - Added methods: getPrimalDualIntegral()
+- getSolVal() supports MatrixExpr now
 - Added realtime_trace_jsonl recipe for real-time optimization progress tracking with JSONL streaming output
 ### Fixed
 - getBestSol() now returns None for infeasible problems instead of a Solution with NULL pointer

src/pyscipopt/scip.pxi

@@ -1098,7 +1098,16 @@ cdef class Solution:
         sol.scip = scip
         return sol
 
-    def __getitem__(self, expr: Union[Expr, MatrixExpr]):
+    def __getitem__(
+        self,
+        expr: Union[Expr, GenExpr, MatrixExpr],
+    ) -> Union[float, np.ndarray]:
+        if not isinstance(expr, (Expr, GenExpr, MatrixExpr)):
+            raise TypeError(
+                "Argument 'expr' has incorrect type, expected 'Expr', 'GenExpr', or "
+                f"'MatrixExpr', got {type(expr).__name__!r}"
+            )
+
         self._checkStage("SCIPgetSolVal")
         return expr._evaluate(self)
 
@@ -10968,75 +10977,63 @@ cdef class Model:
     def getSolVal(
         self,
         Solution sol,
-        expr: Union[Expr, GenExpr],
+        expr: Union[Expr, GenExpr, MatrixExpr],
     ) -> Union[float, np.ndarray]:
         """
-        Retrieve value of given variable or expression in the given solution or in
-        the LP/pseudo solution if sol == None
+        Retrieve value of given variable or expression in the given solution.
 
         Parameters
         ----------
         sol : Solution
-        expr : Expr
-            polynomial expression to query the value of
+            Solution to query the value from. If None, the current LP/pseudo solution is
+            used.
+
+        expr : Expr, GenExpr, MatrixExpr
+            Expression to query the value of.
 
         Returns
         -------
-        float
+        float or np.ndarray
 
         Notes
         -----
         A variable is also an expression.
 
         """
-        if not isinstance(expr, (Expr, GenExpr)):
-            raise TypeError(
-                "Argument 'expr' has incorrect type (expected 'Expr' or 'GenExpr', "
-                f"got {type(expr)})"
-            )
         # no need to create a NULL solution wrapper in case we have a variable
         return (sol or Solution.create(self._scip, NULL))[expr]
 
-    def getVal(self, expr: Union[Expr, GenExpr, MatrixExpr] ):
+    def getVal(self, expr: Union[Expr, GenExpr, MatrixExpr]) -> Union[float, np.ndarray]:
         """
         Retrieve the value of the given variable or expression in the best known solution.
         Can only be called after solving is completed.
 
         Parameters
         ----------
         expr : Expr, GenExpr or MatrixExpr
+            Expression to query the value of.
 
         Returns
         -------
-        float
+        float or np.ndarray
 
         Notes
         -----
         A variable is also an expression.
 
         """
-        cdef SCIP_SOL* current_best_sol
-
-        stage_check = SCIPgetStage(self._scip) not in [SCIP_STAGE_INIT, SCIP_STAGE_FREE]
-        if not stage_check:
+        if SCIPgetStage(self._scip) in {SCIP_STAGE_INIT, SCIP_STAGE_FREE}:
             raise Warning("Method cannot be called in stage ", self.getStage())
 
         # Ensure _bestSol is up-to-date (cheap pointer comparison)
-        current_best_sol = SCIPgetBestSol(self._scip)
+        cdef SCIP_SOL* current_best_sol = SCIPgetBestSol(self._scip)
         if self._bestSol is None or self._bestSol.sol != current_best_sol:
             self._bestSol = Solution.create(self._scip, current_best_sol)
 
         if self._bestSol.sol == NULL and SCIPgetStage(self._scip) != SCIP_STAGE_SOLVING:
             raise Warning("No solution available")
 
-        if isinstance(expr, MatrixExpr):
-            result = np.empty(expr.shape, dtype=float)
-            for idx in np.ndindex(result.shape):
-                result[idx] = self.getSolVal(self._bestSol, expr[idx])
-        else:
-            result = self.getSolVal(self._bestSol, expr)
-
-        return result
+        return self._bestSol[expr]
 
     def hasPrimalRay(self):
         """

src/pyscipopt/scip.pyi

@@ -1,6 +1,6 @@
-from typing import ClassVar
+from typing import ClassVar, Union, overload
 
-import numpy
+import numpy as np
 from _typeshed import Incomplete
 from typing_extensions import disjoint_base
 
@@ -496,7 +496,7 @@ class LP:
     def solve(self, dual: Incomplete = ...) -> Incomplete: ...
     def writeLP(self, filename: Incomplete) -> Incomplete: ...
 
-class MatrixConstraint(numpy.ndarray):
+class MatrixConstraint(np.ndarray):
     def getConshdlrName(self) -> Incomplete: ...
     def isActive(self) -> Incomplete: ...
     def isChecked(self) -> Incomplete: ...
@@ -512,7 +512,7 @@ class MatrixConstraint(numpy.ndarray):
     def isSeparated(self) -> Incomplete: ...
     def isStickingAtNode(self) -> Incomplete: ...
 
-class MatrixExpr(numpy.ndarray):
+class MatrixExpr(np.ndarray):
     def _evaluate(self, sol: Incomplete) -> Incomplete: ...
     def __array_ufunc__(
         self,
@@ -522,7 +522,7 @@ class MatrixExpr(numpy.ndarray):
         **kwargs: Incomplete,
     ) -> Incomplete: ...
 
-class MatrixExprCons(numpy.ndarray):
+class MatrixExprCons(np.ndarray):
     def __array_ufunc__(
         self,
         ufunc: Incomplete,
@@ -1215,7 +1215,10 @@ class Model:
         self, sol: Incomplete, original: Incomplete = ...
     ) -> Incomplete: ...
     def getSolTime(self, sol: Incomplete) -> Incomplete: ...
-    def getSolVal(self, sol: Incomplete, expr: Incomplete) -> Incomplete: ...
+    @overload
+    def getSolVal(self, sol: Solution, expr: Union[Expr, GenExpr]) -> float: ...
+    @overload
+    def getSolVal(self, sol: Solution, expr: MatrixExpr) -> np.ndarray: ...
     def getSols(self) -> Incomplete: ...
     def getSolvingTime(self) -> Incomplete: ...
     def getStage(self) -> Incomplete: ...
@@ -1227,7 +1230,10 @@ class Model:
     def getTransformedCons(self, cons: Incomplete) -> Incomplete: ...
     def getTransformedVar(self, var: Incomplete) -> Incomplete: ...
     def getTreesizeEstimation(self) -> Incomplete: ...
-    def getVal(self, expr: Incomplete) -> Incomplete: ...
+    @overload
+    def getVal(self, expr: Union[Expr, GenExpr]) -> float: ...
+    @overload
+    def getVal(self, expr: MatrixExpr) -> np.ndarray: ...
     def getValsLinear(self, cons: Incomplete) -> Incomplete: ...
     def getVarDict(self, transformed: Incomplete = ...) -> Incomplete: ...
     def getVarLbDive(self, var: Incomplete) -> Incomplete: ...

tests/test_model.py

@@ -1,10 +1,13 @@
-import pytest
-import os
 import itertools
+import os
+
+import numpy as np
+import pytest
 
-from pyscipopt import Model, SCIP_STAGE, SCIP_PARAMSETTING, SCIP_BRANCHDIR, quicksum
+from pyscipopt import SCIP_BRANCHDIR, SCIP_PARAMSETTING, SCIP_STAGE, Model, quicksum
 from helpers.utils import random_mip_1
 
+
 def test_model():
     # create solver instance
     s = Model()
@@ -616,3 +619,26 @@ def create_model_and_get_objects():
 
     assert repr(x) == ""
     assert repr(c) == ""
+
+
+def test_getSolVal():
+    # fix #1136
+
+    m = Model()
+    x = m.addVar(vtype="B")
+    y = m.addMatrixVar(2, vtype="B")
+
+    m.setObjective(x + y.sum())
+    m.optimize()
+    sol = m.getBestSol()
+
+    assert m.getSolVal(sol, x) == m.getVal(x)
+    assert m.getVal(x) == 0
+
+    assert np.array_equal(m.getSolVal(sol, y), m.getVal(y))
+    assert np.array_equal(m.getVal(y), np.array([0, 0]))
+
+    with pytest.raises(TypeError):
+        m.getVal("not_a_var")
+    with pytest.raises(TypeError):
+        m.getSolVal(sol, "not_a_var")