Merge branch 'new-pyros-preprocessor-and-subproblems' of github.com:s…

…hermanjasonaf/pyomo into new-pyros-preprocessor-and-subproblems

.github/workflows/test_branches.yml

@@ -519,7 +519,7 @@ jobs:
         $BARON_DIR = "${env:TPL_DIR}/baron"
         echo "$BARON_DIR" | `
             Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-        $URL = "https://www.minlp.com/downloads/xecs/baron/current/"
+        $URL = "https://minlp.com/downloads/xecs/baron/current/"
         if ( "${{matrix.TARGET}}" -eq "win" ) {
             $INSTALLER = "${env:DOWNLOAD_DIR}/baron_install.exe"
             $URL += "baron-win64.exe"

.github/workflows/test_pr_and_main.yml

@@ -562,7 +562,7 @@ jobs:
         $BARON_DIR = "${env:TPL_DIR}/baron"
         echo "$BARON_DIR" | `
             Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
-        $URL = "https://www.minlp.com/downloads/xecs/baron/current/"
+        $URL = "https://minlp.com/downloads/xecs/baron/current/"
         if ( "${{matrix.TARGET}}" -eq "win" ) {
             $INSTALLER = "${env:DOWNLOAD_DIR}/baron_install.exe"
             $URL += "baron-win64.exe"

doc/OnlineDocs/contributed_packages/gdpopt.rst

@@ -93,10 +93,10 @@ An example that includes the modeling approach may be found below.
     Variables:
       x : Size=1, Index=None
           Key  : Lower : Value : Upper : Fixed : Stale : Domain
-          None :  -1.2 :   0.0 :     2 : False : False :  Reals
+          None :  -1.2 :     0 :     2 : False : False :  Reals
       y : Size=1, Index=None
           Key  : Lower : Value : Upper : Fixed : Stale : Domain
-          None :   -10 :   1.0 :    10 : False : False :  Reals
+          None :   -10 :     1 :    10 : False : False :  Reals
   <BLANKLINE>
     Objectives:
       objective : Size=1, Index=None, Active=True
@@ -106,7 +106,7 @@ An example that includes the modeling approach may be found below.
     Constraints:
       c : Size=1
           Key  : Lower : Body : Upper
-          None :   1.0 :  1.0 :   1.0
+          None :   1.0 :    1 :   1.0
 
 .. note:: 
 

pyomo/contrib/appsi/base.py

@@ -1007,7 +1007,7 @@ def add_constraints(self, cons: List[ConstraintData]):
                 raise ValueError(
                     'constraint {name} has already been added'.format(name=con.name)
                 )
-            self._active_constraints[con] = (con.lower, con.body, con.upper)
+            self._active_constraints[con] = con.expr
             if self.use_extensions and cmodel_available:
                 tmp = cmodel.prep_for_repn(con.body, self._expr_types)
             else:
@@ -1363,40 +1363,13 @@ def update(self, timer: HierarchicalTimer = None):
         cons_to_remove_and_add = dict()
         need_to_set_objective = False
         if config.update_constraints:
-            cons_to_update = list()
-            sos_to_update = list()
             for c in current_cons_dict.keys():
-                if c not in new_cons_set:
-                    cons_to_update.append(c)
+                if c not in new_cons_set and c.expr is not self._active_constraints[c]:
+                    cons_to_remove_and_add[c] = None
+            sos_to_update = []
             for c in current_sos_dict.keys():
                 if c not in new_sos_set:
                     sos_to_update.append(c)
-            for c in cons_to_update:
-                lower, body, upper = self._active_constraints[c]
-                new_lower, new_body, new_upper = c.lower, c.body, c.upper
-                if new_body is not body:
-                    cons_to_remove_and_add[c] = None
-                    continue
-                if new_lower is not lower:
-                    if (
-                        type(new_lower) is NumericConstant
-                        and type(lower) is NumericConstant
-                        and new_lower.value == lower.value
-                    ):
-                        pass
-                    else:
-                        cons_to_remove_and_add[c] = None
-                        continue
-                if new_upper is not upper:
-                    if (
-                        type(new_upper) is NumericConstant
-                        and type(upper) is NumericConstant
-                        and new_upper.value == upper.value
-                    ):
-                        pass
-                    else:
-                        cons_to_remove_and_add[c] = None
-                        continue
             self.remove_sos_constraints(sos_to_update)
             self.add_sos_constraints(sos_to_update)
         timer.stop('cons')

pyomo/contrib/appsi/cmodel/src/fbbt_model.cpp

@@ -205,7 +205,7 @@ void process_fbbt_constraints(FBBTModel *model, PyomoExprTypes &expr_types,
   py::handle con_body;
 
   for (py::handle c : cons) {
-    lower_body_upper = active_constraints[c];
+    lower_body_upper = c.attr("to_bounded_expression")();
     con_lb = lower_body_upper[0];
     con_body = lower_body_upper[1];
     con_ub = lower_body_upper[2];

pyomo/contrib/appsi/cmodel/src/lp_writer.cpp

@@ -289,7 +289,7 @@ void process_lp_constraints(py::list cons, py::object writer) {
   py::object nonlinear_expr;
   PyomoExprTypes expr_types = PyomoExprTypes();
   for (py::handle c : cons) {
-    lower_body_upper = active_constraints[c];
+    lower_body_upper = c.attr("to_bounded_expression")();
     cname = getSymbol(c, labeler);
     repn = generate_standard_repn(
         lower_body_upper[1], "compute_values"_a = false, "quadratic"_a = true);

pyomo/contrib/appsi/cmodel/src/nl_writer.cpp

@@ -527,7 +527,7 @@ void process_nl_constraints(NLWriter *nl_writer, PyomoExprTypes &expr_types,
   py::handle repn_nonlinear_expr;
 
   for (py::handle c : cons) {
-    lower_body_upper = active_constraints[c];
+    lower_body_upper = c.attr("to_bounded_expression")();
     repn = generate_standard_repn(
         lower_body_upper[1], "compute_values"_a = false, "quadratic"_a = false);
     _const = appsi_expr_from_pyomo_expr(repn.attr("constant"), var_map,

pyomo/contrib/appsi/solvers/maingo.py

@@ -57,33 +57,13 @@
 from pyomo.repn.util import valid_expr_ctypes_minlp
 
 
-def _import_SolverModel():
-    try:
-        from . import maingo_solvermodel
-    except ImportError:
-        raise
-    return maingo_solvermodel
-
-
-maingo_solvermodel, solvermodel_available = attempt_import(
-    "maingo_solvermodel", importer=_import_SolverModel
-)
-
-MaingoVar = namedtuple("MaingoVar", "type name lb ub init")
-
 logger = logging.getLogger(__name__)
-
-
-def _import_maingopy():
-    try:
-        import maingopy
-    except ImportError:
-        MAiNGO._available = MAiNGO.Availability.NotFound
-        raise
-    return maingopy
-
-
-maingopy, maingopy_available = attempt_import("maingopy", importer=_import_maingopy)
+MaingoVar = namedtuple("MaingoVar", "type name lb ub init")
+maingopy, maingopy_available = attempt_import("maingopy")
+# Note that importing maingo_solvermodel will trigger the import of
+# maingopy, so we defer that import using attempt_import (which will
+# always succeed, even if maingopy is not available)
+maingo_solvermodel = attempt_import("pyomo.contrib.appsi.solvers.maingo_solvermodel")[0]
 
 
 class MAiNGOConfig(MIPSolverConfig):
@@ -185,9 +165,11 @@ def __init__(self, only_child_vars=False):
         self._last_results_object: Optional[MAiNGOResults] = None
 
     def available(self):
-        if not maingopy_available:
-            return self.Availability.NotFound
-        self._available = True
+        if self._available is None:
+            if maingopy_available:
+                MAiNGO._available = True
+            else:
+                MAiNGO._available = MAiNGO.Availability.NotFound
         return self._available
 
     def version(self):

pyomo/contrib/appsi/solvers/maingo_solvermodel.py

@@ -28,15 +28,7 @@
 from pyomo.repn.util import valid_expr_ctypes_minlp
 
 
-def _import_maingopy():
-    try:
-        import maingopy
-    except ImportError:
-        raise
-    return maingopy
-
-
-maingopy, maingopy_available = attempt_import("maingopy", importer=_import_maingopy)
+maingopy, maingopy_available = attempt_import("maingopy")
 
 _plusMinusOne = {1, -1}
 
@@ -219,7 +211,7 @@ def _linear_to_maingo(self, node):
         return sum(values)
 
 
-class SolverModel(maingopy.MAiNGOmodel):
+class SolverModel(maingopy.MAiNGOmodel if maingopy_available else object):
     def __init__(self, var_list, objective, con_list, idmap, logger):
         maingopy.MAiNGOmodel.__init__(self)
         self._var_list = var_list

pyomo/contrib/community_detection/community_graph.py

@@ -123,7 +123,7 @@ def generate_model_graph(
         # Create a list of the variable numbers that occur in the given constraint equation
         numbered_variables_in_constraint_equation = [
             component_number_map[constraint_variable]
-            for constraint_variable in identify_variables(model_constraint.body)
+            for constraint_variable in identify_variables(model_constraint.expr)
         ]
 
         # Update constraint_variable_map

pyomo/contrib/cp/tests/test_logical_to_disjunctive.py

@@ -200,6 +200,41 @@ def test_equivalence(self):
 
         assertExpressionsEqual(self, m.cons[10].expr, m.z[5] >= 1)
 
+    def test_equivalent_to_True(self):
+        m = self.make_model()
+        e = m.a.equivalent_to(True)
+
+        visitor = LogicalToDisjunctiveVisitor()
+        m.cons = visitor.constraints
+        m.z = visitor.z_vars
+
+        visitor.walk_expression(e)
+
+        self.assertIs(m.a.get_associated_binary(), m.z[1])
+        self.assertEqual(len(m.z), 4)
+        self.assertEqual(len(m.cons), 10)
+
+        # z[2] == !a v True
+        assertExpressionsEqual(
+            self, m.cons[1].expr, (1 - m.z[2]) + (1 - m.z[1]) + 1 >= 1
+        )
+        assertExpressionsEqual(self, m.cons[2].expr, 1 - (1 - m.z[1]) + m.z[2] >= 1)
+        assertExpressionsEqual(self, m.cons[3].expr, m.z[2] + (1 - 1) >= 1)
+
+        # z[3] == a v ! c
+        assertExpressionsEqual(self, m.cons[4].expr, (1 - m.z[3]) + m.z[1] >= 1)
+        assertExpressionsEqual(self, m.cons[5].expr, m.z[3] + (1 - m.z[1]) >= 1)
+        assertExpressionsEqual(self, m.cons[6].expr, m.z[3] + 1 >= 1)
+
+        # z[4] == z[2] ^ z[3]
+        assertExpressionsEqual(self, m.cons[7].expr, m.z[4] <= m.z[2])
+        assertExpressionsEqual(self, m.cons[8].expr, m.z[4] <= m.z[3])
+        assertExpressionsEqual(
+            self, m.cons[9].expr, 1 - m.z[4] <= 2 - (m.z[2] + m.z[3])
+        )
+
+        assertExpressionsEqual(self, m.cons[10].expr, m.z[4] >= 1)
+
     def test_xor(self):
         m = self.make_model()
         e = m.a.xor(m.b)
@@ -263,8 +298,6 @@ def test_at_most(self):
         # z3 = a ^ b
         assertExpressionsEqual(self, m.cons[1].expr, m.z[3] <= a)
         assertExpressionsEqual(self, m.cons[2].expr, m.z[3] <= b)
-        m.cons.pprint()
-        print(m.cons[3].expr)
         assertExpressionsEqual(self, m.cons[3].expr, 1 - m.z[3] <= 2 - sum([a, b]))
 
         # atmost in disjunctive form

pyomo/contrib/cp/transform/logical_to_disjunctive_walker.py

@@ -51,14 +51,7 @@ def _dispatch_var(visitor, node):
 
 
 def _dispatch_param(visitor, node):
-    if int(value(node)) == value(node):
-        return False, node
-    else:
-        raise ValueError(
-            "Found non-integer valued Param '%s' in a logical "
-            "expression. This cannot be written to a disjunctive "
-            "form." % node.name
-        )
+    return False, node
 
 
 def _dispatch_expression(visitor, node):
@@ -244,6 +237,12 @@ def initializeWalker(self, expr):
 
     def beforeChild(self, node, child, child_idx):
         if child.__class__ in EXPR.native_types:
+            if child.__class__ is bool:
+                # If we encounter a bool, we are going to need to treat it as
+                # binary explicitly because we are finally pedantic enough in the
+                # expression system to not allow some of the mixing we will need
+                # (like summing a LinearExpression with a bool)
+                return False, int(child)
             return False, child
 
         if child.is_numeric_type():

pyomo/contrib/fbbt/expression_bounds_walker.py

@@ -232,15 +232,15 @@ def _handle_unknowable_bounds(visitor, node, arg):
 
 
 def _handle_equality(visitor, node, arg1, arg2):
-    return eq(*arg1, *arg2)
+    return eq(*arg1, *arg2, feasibility_tol=visitor.feasibility_tol)
 
 
 def _handle_inequality(visitor, node, arg1, arg2):
-    return ineq(*arg1, *arg2)
+    return ineq(*arg1, *arg2, feasibility_tol=visitor.feasibility_tol)
 
 
 def _handle_ranged(visitor, node, arg1, arg2, arg3):
-    return ranged(*arg1, *arg2, *arg3)
+    return ranged(*arg1, *arg2, *arg3, feasibility_tol=visitor.feasibility_tol)
 
 
 def _handle_expr_if(visitor, node, arg1, arg2, arg3):