Merge pull request #1 from bknueven/pynumero-remove-fixed-variables-c…

…heck

Removing redundant check and adding test

doc/OnlineDocs/library_reference/solvers/index.rst

@@ -7,3 +7,4 @@ Solver Interfaces
    gams.rst
    cplex_persistent.rst
    gurobi_persistent.rst
+   xpress_persistent.rst

doc/OnlineDocs/library_reference/solvers/xpress_persistent.rst

@@ -0,0 +1,7 @@
+XpressPersistent
+================
+
+.. autoclass:: pyomo.solvers.plugins.solvers.xpress_persistent.XpressPersistent
+   :members:
+   :inherited-members:
+   :show-inheritance:

doc/OnlineDocs/modeling_extensions/gdp/modeling.rst

@@ -254,7 +254,7 @@ Here, we demonstrate this capability with a toy example:
 
     >>> # Before solve, Boolean vars have no value
     >>> Reference(m.d[:].indicator_var).display()
-    IndexedBooleanVar : Size=4, Index=s
+    IndexedBooleanVar : Size=4, Index=s, ReferenceTo=d[:].indicator_var
         Key : Value : Fixed : Stale
           1 :  None : False :  True
           2 :  None : False :  True
@@ -265,7 +265,7 @@ Here, we demonstrate this capability with a toy example:
     >>> # based on the algebraic model results
     >>> run_data = SolverFactory('glpk').solve(m)
     >>> Reference(m.d[:].indicator_var).display()
-    IndexedBooleanVar : Size=4, Index=s
+    IndexedBooleanVar : Size=4, Index=s, ReferenceTo=d[:].indicator_var
         Key : Value : Fixed : Stale
           1 :  True : False : False
           2 : False : False : False

doc/OnlineDocs/related_packages.rst

@@ -44,14 +44,14 @@ Domain-Specific Applications
 +==========================+=========================================================+=============================================+
 |  Chama                   | https://github.com/sandialabs/chama                     |  Sensor placement optimization              |
 +--------------------------+---------------------------------------------------------+---------------------------------------------+
-|  Egret                   | https://github.com/grid-parity-exchange/egret           |  Formulation and solution of Unit Commitment|
+|  Egret                   | https://github.com/grid-parity-exchange/egret           |  Formulation and solution of unit commitment|
 |                          |                                                         |  and optimal power flow problems            |
 +--------------------------+---------------------------------------------------------+---------------------------------------------+
 |  IDAES                   | https://github.com/idaes/idaes-pse                      |  Institute for the Design of Advanced       |
 |                          |                                                         |  Energy Systems                             |
 +--------------------------+---------------------------------------------------------+---------------------------------------------+
-|  Prescient               | https://github.com/grid-parity-exchange/prescient       |  Parallel solution of structured            |
-|                          |                                                         |  NLPs.                                      |
+|  Prescient               | https://github.com/grid-parity-exchange/prescient       |  Production Cost Model for power systems    |
+|                          |                                                         |  simulation and analysis                    |
 +--------------------------+---------------------------------------------------------+---------------------------------------------+
 |  PyPSA                   | https://github.com/pypsa/pypsa                          |  Python for Power system Analysis           |
 +--------------------------+---------------------------------------------------------+---------------------------------------------+

examples/pyomobook/test_book_examples.py

@@ -58,6 +58,7 @@
     'test_dae_ch_run_path_constraint_tester': ['ipopt'],
 
     # gdp_ch
+    'test_gdp_ch_pyomo_gdp_uc_sh': ['glpk'],
     'test_gdp_ch_pyomo_scont': ['glpk'],
     'test_gdp_ch_pyomo_scont2': ['glpk'],
     'test_gdp_ch_scont_script': ['glpk'],
@@ -386,6 +387,8 @@ def compare_files(out_file, base_file, abstol, reltol,
             else:
                 extra = out_filtered
                 n = index_of_base_i_in_out
+            if n == float('inf'):
+                n = None
             extra_terms = extra[i:n]
             try:
                 assert len(extra_terms) % 3 == 0

pyomo/contrib/gdpopt/GDPopt.py

@@ -57,7 +57,8 @@
     doc='The GDPopt decomposition-based '
     'Generalized Disjunctive Programming (GDP) solver')
 class GDPoptSolver(object):
-    """Decomposition solver for Generalized Disjunctive Programming (GDP) problems.
+    """Decomposition solver for Generalized Disjunctive Programming (GDP)
+    problems.
 
     The GDPopt (Generalized Disjunctive Programming optimizer) solver applies a
     variety of decomposition-based approaches to solve Generalized Disjunctive
@@ -71,8 +72,8 @@ class GDPoptSolver(object):
     - Partial surrogate cuts [pending]
     - Generalized Bender decomposition [pending]
 
-    This solver implementation was developed by Carnegie Mellon University in the
-    research group of Ignacio Grossmann.
+    This solver implementation was developed by Carnegie Mellon University in
+    the research group of Ignacio Grossmann.
 
     For nonconvex problems, LOA may not report rigorous lower/upper bounds.
 
@@ -179,14 +180,22 @@ def _log_solver_intro_message(self, config):
         config.nlp_solver_args.display(ostream=nlp_args_output)
         config.minlp_solver_args.display(ostream=minlp_args_output)
         config.local_minlp_solver_args.display(ostream=lminlp_args_output)
-        mip_args_text = indent(mip_args_output.getvalue().rstrip(), prefix=" " * 2 + " - ")
-        nlp_args_text = indent(nlp_args_output.getvalue().rstrip(), prefix=" " * 2 + " - ")
-        minlp_args_text = indent(minlp_args_output.getvalue().rstrip(), prefix=" " * 2 + " - ")
-        lminlp_args_text = indent(lminlp_args_output.getvalue().rstrip(), prefix=" " * 2 + " - ")
-        mip_args_text = "" if len(mip_args_text.strip()) == 0 else "\n" + mip_args_text
-        nlp_args_text = "" if len(nlp_args_text.strip()) == 0 else "\n" + nlp_args_text
-        minlp_args_text = "" if len(minlp_args_text.strip()) == 0 else "\n" + minlp_args_text
-        lminlp_args_text = "" if len(lminlp_args_text.strip()) == 0 else "\n" + lminlp_args_text
+        mip_args_text = indent(mip_args_output.getvalue().rstrip(), prefix=" " *
+                               2 + " - ")
+        nlp_args_text = indent(nlp_args_output.getvalue().rstrip(), prefix=" " *
+                               2 + " - ")
+        minlp_args_text = indent(minlp_args_output.getvalue().rstrip(),
+                                 prefix=" " * 2 + " - ")
+        lminlp_args_text = indent(lminlp_args_output.getvalue().rstrip(),
+                                  prefix=" " * 2 + " - ")
+        mip_args_text = "" if len(mip_args_text.strip()) == 0 else \
+                        "\n" + mip_args_text
+        nlp_args_text = "" if len(nlp_args_text.strip()) == 0 else \
+                        "\n" + nlp_args_text
+        minlp_args_text = "" if len(minlp_args_text.strip()) == 0 else \
+                          "\n" + minlp_args_text
+        lminlp_args_text = "" if len(lminlp_args_text.strip()) == 0 else \
+                           "\n" + lminlp_args_text
         config.logger.info(
             """
 Subsolvers:
@@ -209,7 +218,7 @@ def _log_solver_intro_message(self, config):
 If you use this software, you may cite the following:
 - Implementation:
 Chen, Q; Johnson, ES; Siirola, JD; Grossmann, IE.
-Pyomo.GDP: Disjunctive Models in Python. 
+Pyomo.GDP: Disjunctive Models in Python.
 Proc. of the 13th Intl. Symposium on Process Systems Eng.
 San Diego, 2018.
         """.strip()
@@ -227,7 +236,8 @@ def _log_solver_intro_message(self, config):
             to_cite_text += """
 - GLOA algorithm:
 Lee, S; Grossmann, IE.
-A Global Optimization Algorithm for Nonconvex Generalized Disjunctive Programming and Applications to Process Systems.
+A Global Optimization Algorithm for Nonconvex Generalized Disjunctive
+Programming and Applications to Process Systems.
 Comp. and Chem. Eng. 2001, 25, 1675-1697.
 DOI: 10.1016/S0098-1354(01)00732-3.
             """.strip()