1.1.3

fix: make sure that sloppy arg is being passed to super (#83)
Netlib tests test also cloned models (#79)
Add a Gitter chat badge to README.rst (#86) (#88)

README.rst

@@ -3,7 +3,7 @@ optlang
 
 *Sympy based mathematical programming language*
 
-|PyPI| |License| |Travis| |Appveyor| |Coverage Status| |Documentation Status| |JOSS| |DOI|
+|PyPI| |License| |Travis| |Appveyor| |Coverage Status| |Documentation Status| |Gitter| |JOSS| |DOI|
 
 Optlang is a Python package for solving mathematical optimization
 problems, i.e. maximizing or minimizing an objective function over a set
@@ -153,4 +153,7 @@ also provides a good overview of the project's roadmap.
    :target: https://zenodo.org/badge/latestdoi/5031/biosustain/optlang
 .. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/443yp8hf25c6748h/branch/master?svg=true
    :target: https://ci.appveyor.com/project/phantomas1234/optlang/branch/master
+.. |Gitter| image:: https://badges.gitter.im/biosustain/optlang.svg
+   :alt: Join the chat at https://gitter.im/biosustain/optlang
+   :target: https://gitter.im/biosustain/optlang?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge
 

optlang/cplex_interface.py

@@ -201,7 +201,7 @@ class Constraint(interface.Constraint):
     _INDICATOR_CONSTRAINT_SUPPORT = True
 
     def __init__(self, expression, sloppy=False, *args, **kwargs):
-        super(Constraint, self).__init__(expression, *args, **kwargs)
+        super(Constraint, self).__init__(expression, *args, sloppy=sloppy, **kwargs)
 
     def set_linear_coefficients(self, coefficients):
         if self.problem is not None:
@@ -314,7 +314,7 @@ def __iadd__(self, other):
 @six.add_metaclass(inheritdocstring)
 class Objective(interface.Objective):
     def __init__(self, expression, sloppy=False, **kwargs):
-        super(Objective, self).__init__(expression, **kwargs)
+        super(Objective, self).__init__(expression, sloppy=sloppy, **kwargs)
         self._expression_expired = False
         if not (sloppy or self.is_Linear or self.is_Quadratic):
             raise ValueError("Cplex only supports linear and quadratic objectives.")
@@ -577,7 +577,7 @@ def __init__(self, problem=None, *args, **kwargs):
                 elif sense == 'L':
                     constr = Constraint(lhs, ub=rhs, name=name, problem=self)
                 elif sense == 'R':
-                    range_val = self.problem.linear_constraints.get_rhs(name)
+                    range_val = self.problem.linear_constraints.get_range_values(name)
                     if range_val > 0:
                         constr = Constraint(lhs, lb=rhs, ub=rhs + range_val, name=name, problem=self)
                     else:

optlang/glpk_interface.py

@@ -284,7 +284,7 @@ def get_linear_coefficients(self, variables):
 @six.add_metaclass(inheritdocstring)
 class Objective(interface.Objective):
     def __init__(self, expression, sloppy=False, **kwargs):
-        super(Objective, self).__init__(expression, **kwargs)
+        super(Objective, self).__init__(expression, sloppy=sloppy, **kwargs)
         self._expression_expired = False
         if not (sloppy or self.is_Linear):
             raise ValueError(

optlang/gurobi_interface.py

@@ -323,7 +323,7 @@ def __iadd__(self, other):
 @six.add_metaclass(inheritdocstring)
 class Objective(interface.Objective):
     def __init__(self, expression, sloppy=False, *args, **kwargs):
-        super(Objective, self).__init__(expression, *args, **kwargs)
+        super(Objective, self).__init__(expression, *args, sloppy=sloppy, **kwargs)
         self._expression_expired = False
         if not (sloppy or self.is_Linear):  # or self.is_Quadratic: # QP is not yet supported
             raise ValueError("The given objective is invalid. Must be linear or quadratic (not yet supported")

optlang/interface.py

@@ -738,17 +738,21 @@ def _canonicalize(self, expression):
             return expression
         assert len(lonely_coeffs) == 1
         coeff = lonely_coeffs[0]
-        if self.lb is None and self.ub is None:
+        expression = expression - coeff
+        if self.lb is not None and self.ub is not None:
+            oldub = self.ub
+            self.ub = None
+            self.lb = self.lb - float(coeff)
+            self.ub = oldub - float(coeff)
+        elif self.lb is not None:
+            self.lb = self.lb - float(coeff)
+        elif self.ub is not None:
+            self.ub = self.ub - float(coeff)
+        else:
             raise ValueError(
                 "%s cannot be shaped into canonical form if neither lower or upper constraint bounds are set."
                 % expression
             )
-        else:
-            expression = expression - coeff
-            if self.lb is not None:
-                self.lb = self.lb - float(coeff)
-            if self.ub is not None:
-                self.ub = self.ub - float(coeff)
         return expression
 
     @property

optlang/scipy_interface.py

@@ -445,7 +445,7 @@ def get_linear_coefficients(self, variables):
 @six.add_metaclass(inheritdocstring)
 class Objective(interface.Objective):
     def __init__(self, expression, sloppy=False, **kwargs):
-        super(Objective, self).__init__(expression, sloppy, **kwargs)
+        super(Objective, self).__init__(expression, sloppy=sloppy, **kwargs)
         if not (sloppy or self.is_Linear):
             raise ValueError(
                 "Scipy only supports linear objectives. %s is not linear." % self)

optlang/tests/abstract_test_cases.py

@@ -274,6 +274,34 @@ def test_constraint_get_linear_coefficients_raises(self):
     def test_constraint_set_linear_coefficients_raises(self):
         self.assertRaises(Exception, self.constraint.set_linear_coefficients, {})
 
+    def test_move_constant_to_rhs(self):
+        x = self.interface.Variable("x")
+        c1 = self.interface.Constraint(x + 3, lb=0, ub=0)
+        self.assertEqual(c1.expression - x, 0)
+        self.assertEqual(c1.lb, -3)
+        self.assertEqual(c1.ub, -3)
+
+        c2 = self.interface.Constraint(x - 3, lb=0, ub=0)
+        self.assertEqual(c2.expression - x, 0)
+        self.assertEqual(c2.lb, 3)
+        self.assertEqual(c2.ub, 3)
+
+        c3 = self.interface.Constraint(x - 3, lb=0)
+        self.assertEqual(c3.expression - x, 0)
+        self.assertEqual(c3.lb, 3)
+
+        c4 = self.interface.Constraint(x - 3, ub=0)
+        self.assertEqual(c4.expression - x, 0)
+        self.assertEqual(c4.ub, 3)
+
+        c5 = self.interface.Constraint(x + 3, lb=0)
+        self.assertEqual(c5.expression - x, 0)
+        self.assertEqual(c5.lb, -3)
+
+        c6 = self.interface.Constraint(x + 3, ub=0)
+        self.assertEqual(c6.expression - x, 0)
+        self.assertEqual(c6.ub, -3)
+
 
 @six.add_metaclass(abc.ABCMeta)
 class AbstractObjectiveTestCase(unittest.TestCase):

optlang/tests/test_netlib_cplex_interface.py

@@ -123,6 +123,20 @@ def test_netlib(netlib_tar_path=os.path.join(os.path.dirname(__file__), 'data/ne
                         netlib_id, os.path.basename(str(__file__)))
                     yield func
 
+                    if not os.getenv('TRAVIS', False):
+                        # check that a cloned model also gives the correct result
+                        model = Model.clone(model, use_json=False, use_lp=False)
+                        model.optimize()
+                        if model.status == 'optimal':
+                            model_objval = model.objective.value
+                        else:
+                            raise Exception('No optimal solution found for netlib model %s' % netlib_id)
+
+                        func = partial(check_objval_against_the_final_netlib_results, netlib_id, model_objval)
+                        func.description = "test_netlib_check_objective_value__against_the_final_netlib_results_after_cloning_%s (%s)" % (
+                            netlib_id, os.path.basename(str(__file__)))
+                        yield func
+
     except ImportError as e:
 
         if str(e).find('cplex') >= 0:
@@ -136,29 +150,17 @@ def test_fail(self):
 
 if __name__ == '__main__':
     # tar = tarfile.open('data/netlib_lp_problems.tar.gz')
-    # model_paths_in_tar = glob.fnmatch.filter(tar.getnames(), '*.SIF')
-    # for model_path_in_tar in model_paths_in_tar:
-    # try:
-    #
-    # fhandle = tar.extractfile(model_path_in_tar)
+    # fhandle = tar.extractfile('./netlib/SEBA.SIF')
     # problem = read_netlib_sif_cplex(fhandle)
-    #
-    # except cplex.exceptions.CplexSolverError, e:
-    # print model_path_in_tar
-    # print problem
-    # print problem.get_problem_name()
-    # print e
-    # fhandle = tar.extractfile('./netlib/ADLITTLE.SIF')
-    # glpk_problem = read_netlib_sif_glpk(fhandle)
-    # glp_simplex(glpk_problem, None)
-    # print glp_get_obj_val(glpk_problem)
-    # print glpk_problem
-    # fhandle = tar.extractfile('./netlib/ADLITTLE.SIF')
-    # glpk_problem = read_netlib_sif_glpk(fhandle)
-    # model = Model(problem=glpk_problem)
-    # glp_simplex(glpk_problem, None)
-    # model.optimize()
-    # print model.objective.value
-    # print model
-    # test_netlib().next()
+    # model = Model(problem=problem)
+    # status = model.optimize()
+    # print(status)
+    # print(model.objective.value)
+    # print(model.constraints['VILLKOR7'])
+    # # print(model)
+    # model = Model.clone(model, use_lp=False, use_json=False)
+    # status = model.optimize()
+    # print(status)
+    # print(model.constraints['VILLKOR7'])
+    # print(model.objective.value)
     nose.runmodule()

optlang/tests/test_netlib_glpk_interface.py

@@ -111,6 +111,21 @@ def check_objval_against_the_final_netlib_results(netlib_id, model_objval):
                     netlib_id, os.path.basename(str(__file__)))
                 yield func
 
+                if not os.getenv('TRAVIS', False):
+                    # check that a cloned model also gives the correct result
+                    model = Model.clone(model, use_json=False, use_lp=False)
+                    model.optimize()
+                    if model.status == 'optimal':
+                        model_objval = model.objective.value
+                    else:
+                        raise Exception('No optimal solution found for netlib model %s' % netlib_id)
+
+                    if not os.getenv('TRAVIS', False):
+                        func = partial(check_objval_against_the_final_netlib_results, netlib_id, model_objval)
+                        func.description = "test_netlib_check_objective_value__against_the_final_netlib_results_after_cloning_%s (%s)" % (
+                            netlib_id, os.path.basename(str(__file__)))
+                        yield func
+
 
 if __name__ == '__main__':
     # tar = tarfile.open('data/netlib_lp_problems.tar.gz')

optlang/tests/test_netlib_gurobi_interface.py

@@ -126,6 +126,20 @@ def test_netlib(netlib_tar_path=os.path.join(os.path.dirname(__file__), 'data/ne
                         netlib_id, os.path.basename(str(__file__)))
                     yield func
 
+                    if not os.getenv('TRAVIS', False):
+                        # check that a cloned model also gives the correct result
+                        model = Model.clone(model, use_json=False, use_lp=False)
+                        model.optimize()
+                        if model.status == 'optimal':
+                            model_objval = model.objective.value
+                        else:
+                            raise Exception('No optimal solution found for netlib model %s' % netlib_id)
+
+                        func = partial(check_objval_against_the_final_netlib_results, netlib_id, model_objval)
+                        func.description = "test_netlib_check_objective_value__against_the_final_netlib_results_after_cloning_%s (%s)" % (
+                            netlib_id, os.path.basename(str(__file__)))
+                        yield func
+
     except ImportError as e:
 
         if str(e).find('gurobipy') >= 0: