Ipopt-v2

watertap/conftest.py

@@ -51,7 +51,7 @@ def _handle_requires_idaes_solver(
 
     solver = solver or get_solver()
     idaes_bin_dir = Path(bin_directory).resolve()
-    solver_bin_path = Path(solver.executable()).resolve()
+    solver_bin_path = Path(solver.config.executable.path()).resolve()
 
     if not idaes_bin_dir in solver_bin_path.parents:
         action(f"This test is known to be failing with {solver_bin_path}")

watertap/core/plugins/solvers.py

@@ -14,7 +14,8 @@
 
 import pyomo.environ as pyo
 from pyomo.common.collections import Bunch
-from pyomo.solvers.plugins.solvers.IPOPT import IPOPT
+from pyomo.contrib.solver.base import LegacySolverWrapper
+from pyomo.contrib.solver.ipopt import Ipopt
 
 import idaes.core.util.scaling as iscale
 from idaes.core.util.scaling import (
@@ -36,14 +37,18 @@ def _pyomo_nl_writer_logger_filter(record):
     return True
 
 
+class LegacyWrapperIpopt(LegacySolverWrapper, Ipopt):
+    pass
+
+
 @pyo.SolverFactory.register(
     "ipopt-watertap",
     doc="The Ipopt NLP solver, with user-based variable and automatic Jacobian constraint scaling",
 )
 class IpoptWaterTAP:
 
     name = "ipopt-watertap"
-    _base_solver = IPOPT
+    _base_solver = LegacyWrapperIpopt
 
     def __init__(self, **kwds):
         kwds["name"] = self.name
@@ -60,7 +65,7 @@ def __getattr__(self, attr):
 
     def solve(self, blk, *args, **kwds):
 
-        solver = self._base_solver()
+        solver = self._base_solver(options={})
         self._tee = kwds.get("tee", False)
 
         self._original_options = self.options
@@ -81,6 +86,14 @@ def solve(self, blk, *args, **kwds):
         if "honor_original_bounds" not in self.options:
             self.options["honor_original_bounds"] = "no"
 
+        # Setup writer_config
+        if "writer_config" not in kwds:
+            kwds["writer_config"] = {}
+        if "linear_presolve" not in kwds["writer_config"]:
+            kwds["writer_config"]["linear_presolve"] = True
+        if "scale_model" not in kwds["writer_config"]:
+            kwds["writer_config"]["scale_model"] = False
+
         if not self._is_user_scaling():
             for k, v in self.options.items():
                 solver.options[k] = v

watertap/core/plugins/tests/test_solvers.py

@@ -143,8 +143,8 @@ def test_passthrough_positive(self, m, s):
     def test_passthrough_negative(self, m, s):
         s.options["nlp_scaling_method"] = "gradient-based"
         s.options["ignore_variable_scaling"] = True
-        with pytest.raises(ApplicationError):
-            pyo.assert_optimal_termination(s.solve(m, tee=True))
+        with pytest.raises(RuntimeError):
+            s.solve(m, tee=True)
         del s.options["nlp_scaling_method"]
         del s.options["ignore_variable_scaling"]
         self._test_bounds(m)