Merge branch 'pyros-vars-as-params' of github.com:shermanjasonaf/pyom…

…o into pyros-vars-as-params

examples/gdp/circles/circles.py

@@ -10,8 +10,8 @@
 #  ___________________________________________________________________________
 
 """
-The "circles" GDP example problem originating in Lee and Grossman (2000). The 
-goal is to choose a point to minimize a convex quadratic function over a set of 
+The "circles" GDP example problem originating in Lee and Grossman (2000). The
+goal is to choose a point to minimize a convex quadratic function over a set of
 disjoint hyperspheres.
 """
 

examples/gdp/farm_layout/farm_layout.py

@@ -11,10 +11,10 @@
 
 """
 Farm layout example from Sawaya (2006). The goal is to determine optimal placements and dimensions for farm
-plots of specified areas to minimize the perimeter of a minimal enclosing fence. This is a GDP problem with 
-some hyperbolic constraints to establish consistency of areas with length and width. The FLay05 and FLay06 
-instances may take some time to solve; the others should be fast. Note that the Sawaya paper contains a 
-little bit of nonclarity: it references "height" variables which do not exist - we use "length" for the x-axis 
+plots of specified areas to minimize the perimeter of a minimal enclosing fence. This is a GDP problem with
+some hyperbolic constraints to establish consistency of areas with length and width. The FLay05 and FLay06
+instances may take some time to solve; the others should be fast. Note that the Sawaya paper contains a
+little bit of nonclarity: it references "height" variables which do not exist - we use "length" for the x-axis
 and "width" on the y-axis, and it also is unclear on the way the coordinates define the rectangles; we have
 decided that they are on the bottom-left and adapted the disjunction constraints to match.
 """

examples/gdp/nine_process/small_process.py

@@ -9,9 +9,7 @@
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
 
-"""Small process synthesis-inspired toy GDP example.
-
-"""
+"""Small process synthesis-inspired toy GDP example."""
 
 from pyomo.core import ConcreteModel, RangeSet, Var, Constraint, Objective
 from pyomo.core.expr.current import exp, log, sqrt

examples/gdp/small_lit/basic_step.py

@@ -9,10 +9,10 @@
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
 
-""" Example from Section 3.2 in paper of Pseudo Basic Steps
+"""Example from Section 3.2 in paper of Pseudo Basic Steps
 
 Ref:
-    Pseudo basic steps: bound improvement guarantees from Lagrangian 
+    Pseudo basic steps: bound improvement guarantees from Lagrangian
     decomposition in convex disjunctive programming
     Papageorgiou and Trespalacios, 2017
 

examples/pyomo/columngeneration/cutting_stock.py

@@ -16,7 +16,7 @@
 Bradley, S.P., A.C. Hax, and T.L. Magnanti. 1977. Applied Mathematical Programming,
 Addison-Wesley, Reading, MA. Available: http://web.mit.edu/15.053/www/AMP.htm.
 
-Data from https://en.wikipedia.org/wiki/Cutting_stock_problem 
+Data from https://en.wikipedia.org/wiki/Cutting_stock_problem
 '''
 
 import pyomo.environ as pyo

examples/pyomo/sos/sos2_piecewise.py

@@ -10,11 +10,11 @@
 #  ___________________________________________________________________________
 
 """
-This example shows how to represent a piecewise function using 
+This example shows how to represent a piecewise function using
 Pyomo's built SOSConstraint component. The function is defined as:
 
        / 3x-2 , 1 <= x <= 2
-f(x) = | 
+f(x) = |
        \ 5x-6 , 2 <= x <= 3
 """
 

pyomo/common/tests/test_config.py

@@ -88,6 +88,7 @@ def _display(obj, *args):
 
 class GlobalClass(object):
     "test class for test_known_types"
+
     pass
 
 

pyomo/contrib/community_detection/event_log.py

@@ -9,7 +9,7 @@
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
 
-""" Logger function for community_graph.py """
+"""Logger function for community_graph.py"""
 
 from logging import getLogger
 from pyomo.core import Constraint, Objective, Var

pyomo/contrib/incidence_analysis/config.py

@@ -8,8 +8,7 @@
 #  rights in this software.
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
-"""Configuration options for incidence graph generation
-"""
+"""Configuration options for incidence graph generation"""
 
 import enum
 from pyomo.common.config import ConfigDict, ConfigValue, InEnum

pyomo/contrib/incidence_analysis/incidence.py

@@ -8,8 +8,7 @@
 #  rights in this software.
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
-"""Functionality for identifying variables that participate in expressions
-"""
+"""Functionality for identifying variables that participate in expressions"""
 
 from contextlib import nullcontext
 

pyomo/contrib/incidence_analysis/visualize.py

@@ -8,9 +8,7 @@
 #  rights in this software.
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
-"""Module for visualizing results of incidence graph or matrix analysis
-
-"""
+"""Module for visualizing results of incidence graph or matrix analysis"""
 from pyomo.contrib.incidence_analysis.config import IncidenceOrder
 from pyomo.contrib.incidence_analysis.interface import (
     IncidenceGraphInterface,

pyomo/contrib/mindtpy/tests/MINLP4_simple.py

@@ -10,7 +10,7 @@
 #  ___________________________________________________________________________
 
 # -*- coding: utf-8 -*-
-""" Example 1 in Paper 'Using regularization and second order information in outer approximation for convex MINLP'
+"""Example 1 in Paper 'Using regularization and second order information in outer approximation for convex MINLP'
 
 The expected optimal solution value is -56.981.
 

pyomo/contrib/mindtpy/tests/constraint_qualification_example.py

@@ -10,7 +10,7 @@
 #  ___________________________________________________________________________
 
 # -*- coding: utf-8 -*-
-""" Example of constraint qualification.
+"""Example of constraint qualification.
 
 The expected optimal solution value is 3.
 

pyomo/contrib/mindtpy/tests/online_doc_example.py

@@ -9,7 +9,7 @@
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
 
-""" Example in the online doc.
+"""Example in the online doc.
 
 The expected optimal solution value is 2.438447187191098.
 

pyomo/contrib/parmest/examples/reaction_kinetics/simple_reaction_parmest_example.py

@@ -8,7 +8,7 @@
 #  rights in this software.
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
-''' 
+'''
 Example from Y. Bard, "Nonlinear Parameter Estimation", (pg. 124)
 
 This example shows:

pyomo/contrib/parmest/examples/rooney_biegler/rooney_biegler.py

@@ -10,8 +10,8 @@
 #  ___________________________________________________________________________
 
 """
-Rooney Biegler model, based on Rooney, W. C. and Biegler, L. T. (2001). Design for 
-model parameter uncertainty using nonlinear confidence regions. AIChE Journal, 
+Rooney Biegler model, based on Rooney, W. C. and Biegler, L. T. (2001). Design for
+model parameter uncertainty using nonlinear confidence regions. AIChE Journal,
 47(8), 1794-1804.
 """
 

pyomo/contrib/parmest/examples/semibatch/parallel_example.py

@@ -10,7 +10,7 @@
 #  ___________________________________________________________________________
 
 """
-The following script can be used to run semibatch parameter estimation in 
+The following script can be used to run semibatch parameter estimation in
 parallel and save results to files for later analysis and graphics.
 Example command: mpiexec -n 4 python parallel_example.py
 """

pyomo/contrib/parmest/examples/semibatch/semibatch.py

@@ -9,9 +9,9 @@
 #  This software is distributed under the 3-clause BSD License.
 #  ___________________________________________________________________________
 """
-Semibatch model, based on Nicholson et al. (2018). pyomo.dae: A modeling and 
+Semibatch model, based on Nicholson et al. (2018). pyomo.dae: A modeling and
 automatic discretization framework for optimization with di
-erential and 
+erential and
 algebraic equations. Mathematical Programming Computation, 10(2), 187-223.
 """
 import json

pyomo/contrib/sensitivity_toolbox/examples/rooney_biegler.py

@@ -22,8 +22,8 @@
 # at the URL "https://github.com/IDAES/idaes-pse".
 ##############################################################################
 """
-Rooney Biegler model, based on Rooney, W. C. and Biegler, L. T. (2001). Design for 
-model parameter uncertainty using nonlinear confidence regions. AIChE Journal, 
+Rooney Biegler model, based on Rooney, W. C. and Biegler, L. T. (2001). Design for
+model parameter uncertainty using nonlinear confidence regions. AIChE Journal,
 47(8), 1794-1804.
 """
 from pyomo.common.dependencies import pandas as pd

pyomo/contrib/sensitivity_toolbox/tests/test_k_aug_interface.py

@@ -20,8 +20,6 @@
 # This software is distributed under the 3-clause BSD License.
 # ____________________________________________________________________________
 
-"""
-"""
 import os
 import pyomo.common.unittest as unittest
 from io import StringIO

pyomo/contrib/viewer/qt.py

@@ -21,7 +21,7 @@
 #  ___________________________________________________________________________
 
 """
-Try to import PySide6, which is the current official Qt 6 Python interface. Then, 
+Try to import PySide6, which is the current official Qt 6 Python interface. Then,
 try PyQt5 if that doesn't work. If no compatible Qt Python interface is found,
 use some dummy classes to allow some testing.
 """

pyomo/contrib/viewer/tests/test_qt.py

@@ -23,6 +23,13 @@
 """
 UI Tests
 """
+# The pytest-qt plugin can generate exceptions / core dumps when it is
+# run in a terminal (without an active X11 screen).  Setting the
+# QT_QPA_PLATFORM environment variable *before* initializing Qt can work
+# around this error (see https://stackoverflow.com/a/74719383):
+import os
+
+os.environ['QT_QPA_PLATFORM'] = 'offscreen'
 
 from pyomo.environ import (
     ConcreteModel,

pyomo/solvers/plugins/solvers/SAS.py

@@ -195,7 +195,9 @@ def _presolve(self, *args, **kwds):
 
     def available(self, exception_flag=False):
         """True if the solver is available"""
-        return self._python_api_exists
+        if not self._python_api_exists:
+            return False
+        return self.start_sas_session() is not None
 
     def _has_integer_variables(self):
         """True if the problem has integer variables."""
@@ -285,12 +287,7 @@ def __init__(self, **kwds):
 
         # Store other options for the SAS session
         self._session_options = kwds
-
-        # Create the session
-        try:
-            self._sas_session = self._sas.SASsession(**self._session_options)
-        except:
-            self._sas_session = None
+        self._sas_session = None
 
     def __del__(self):
         # Close the session, if we created one
@@ -314,6 +311,15 @@ def _create_statement_str(self, statement):
     def sas_version(self):
         return self._sasver
 
+    def start_sas_session(self):
+        if self._sas_session is None:
+            # Create (and cache) the session
+            try:
+                self._sas_session = self._sas.SASsession(**self._session_options)
+            except:
+                pass
+        return self._sas_session
+
     def _apply_solver(self):
         """ "Prepare the options and run the solver. Then store the data to be returned."""
         logger.debug("Running SAS")
@@ -374,10 +380,7 @@ def _apply_solver(self):
         sas_options = "option notes nonumber nodate nosource pagesize=max;"
 
         # Get the current SAS session, submit the code and return the results
-        if not self._sas_session:
-            sas = self._sas_session = self._sas.SASsession(**self._session_options)
-        else:
-            sas = self._sas_session
+        sas = self.start_sas_session()
 
         # Find the version of 9.4 we are using
         self._sasver = sas.sasver
@@ -585,19 +588,23 @@ def __init__(self, **kwds):
             self._python_api_exists = True
 
         self._session_options = kwds
-
-        # Create the session
-        try:
-            self._sas_session = self._sas.CAS(**self._session_options)
-        except:
-            self._sas_session = None
+        self._sas_session = None
 
     def __del__(self):
         # Close the session, if we created one
         if self._sas_session:
             self._sas_session.close()
             del self._sas_session
 
+    def start_sas_session(self):
+        if self._sas_session is None:
+            # Create (and cache) the session
+            try:
+                self._sas_session = self._sas.CAS(**self._session_options)
+            except:
+                pass
+        return self._sas_session
+
     def _uploadMpsFile(self, s, unique):
         # Declare a unique table name for the mps table
         mpsdata_table_name = "mps" + unique

pyomo/solvers/plugins/solvers/mosek_direct.py

@@ -1068,7 +1068,7 @@ def _warm_start(self):
         for pyomo_var, mosek_var in self._pyomo_var_to_solver_var_map.items():
             if pyomo_var.value is not None:
                 self._solver_model.putxxslice(
-                    self._whichsol, mosek_var, mosek_var + 1, [(pyomo_var.value)]
+                    self._whichsol, mosek_var, mosek_var + 1, [pyomo_var.value]
                 )
 
         if (self._version[0] > 9) & (self._whichsol == mosek.soltype.itg):

pyomo/solvers/tests/checks/test_SAS.py

@@ -26,7 +26,7 @@
     Suffix,
 )
 from pyomo.opt.results import SolverStatus, TerminationCondition, ProblemSense
-from pyomo.opt import SolverFactory, check_available_solvers
+from pyomo.opt import SolverFactory
 import warnings
 
 CFGFILE = os.environ.get("SAS_CFG_FILE_PATH", None)
@@ -38,7 +38,10 @@
 }
 
 
-sas_available = check_available_solvers("sas")
+try:
+    sas94_available = SolverFactory('_sas94').available()
+except:
+    sas94_available = False
 
 
 class SASTestAbc:
@@ -292,7 +295,7 @@ def test_solver_with_milp(self):
         )
 
 
-@unittest.skipIf(not sas_available, "The SAS solver is not available")
+@unittest.skipIf(not sas94_available, "The SAS94 solver interface is not available")
 class SASTestLP94(SASTestLP, unittest.TestCase):
     @mock.patch(
         "pyomo.solvers.plugins.solvers.SAS.SAS94.sas_version",
@@ -325,7 +328,7 @@ def test_solver_error(self, submit_mock, symget_mock):
         self.assertEqual(results.solver.status, SolverStatus.error)
 
 
-# @unittest.skipIf(not sas_available, "The SAS solver is not available")
+# @unittest.skipIf(not sascas_available, "The SAS solver is not available")
 @unittest.skip("Tests not yet configured for SAS Viya interface.")
 class SASTestLPCAS(SASTestLP, unittest.TestCase):
     solver_io = "_sascas"
@@ -526,13 +529,13 @@ def test_solver_warmstart_capable(self):
         self.assertTrue(self.opt_sas.warm_start_capable())
 
 
-# @unittest.skipIf(not sas_available, "The SAS solver is not available")
+# @unittest.skipIf(not sas94_available, "The SAS solver is not available")
 @unittest.skip("MILP94 tests disabled.")
 class SASTestMILP94(SASTestMILP, unittest.TestCase):
     pass
 
 
-# @unittest.skipIf(not sas_available, "The SAS solver is not available")
+# @unittest.skipIf(not sascas_available, "The SAS solver is not available")
 @unittest.skip("Tests not yet configured for SAS Viya interface.")
 class SASTestMILPCAS(SASTestMILP, unittest.TestCase):
     solver_io = "_sascas"

pyomo/solvers/tests/piecewise_linear/problems/concave_multi_vararray1.py

@@ -14,7 +14,7 @@
        | 7x+12 , -4 <= x <= -3
        | 5x+6  , -3 <= x <= -2
        | 3x+2  , -2 <= x <= -1
-f(x) = | 1     , -1 <= x <=  1 
+f(x) = | 1     , -1 <= x <=  1
        | -3x+2 ,  1 <= x <=  2
        | -5x+6 ,  2 <= x <=  3
        \ -7x+12,  3 <= x <=  4

pyomo/solvers/tests/piecewise_linear/problems/concave_multi_vararray2.py

@@ -14,7 +14,7 @@
        | 7x+12 , -4 <= x <= -3
        | 5x+6  , -3 <= x <= -2
        | 3x+2  , -2 <= x <= -1
-f(x) = | 1     , -1 <= x <=  1 
+f(x) = | 1     , -1 <= x <=  1
        | -3x+2 ,  1 <= x <=  2
        | -5x+6 ,  2 <= x <=  3
        \ -7x+12,  3 <= x <=  4