def test_intersection(self):
a = OrderedSet([1, 2, 3, 'a', 'b', 'c'])
b = OrderedSet([3, 4, 'c', 'd'])
c = a.intersection(b)
self.assertEqual(list(c), [3, 'c'])
self.assertEqual(list(a), [1, 2, 3, 'a', 'b', 'c'])
self.assertEqual(list(b), [3, 4, 'c', 'd'])
def _set_pyomo_amplfunc_env(self):
if self._external_functions:
external_Libs = OrderedSet()
for con, ext_funcs in self._external_functions.items():
external_Libs.update([i._fcn._library for i in ext_funcs])
set_pyomo_amplfunc_env(external_Libs)
elif "PYOMO_AMPLFUNC" in os.environ:
del os.environ["PYOMO_AMPLFUNC"]
def test_constructor(self):
a = OrderedSet()
self.assertEqual(len(a), 0)
self.assertEqual(list(a), [])
self.assertEqual(str(a), 'OrderedSet()')
ref = [1, 9, 'a', 4, 2, None]
a = OrderedSet(ref)
self.assertEqual(len(a), 6)
self.assertEqual(list(a), ref)
self.assertEqual(str(a), "OrderedSet(1, 9, 'a', 4, 2, None)")
def test_pickle(self):
ref = [1, 9, 'a', 4, 2, None]
a = OrderedSet(ref)
b = pickle.loads(pickle.dumps(a))
self.assertEqual(a, b)
self.assertIsNot(a, b)
self.assertIsNot(a._dict, b._dict)
def test_in_add(self):
a = OrderedSet()
self.assertNotIn(1, a)
self.assertNotIn(None, a)
a.add(None)
self.assertNotIn(1, a)
self.assertIn(None, a)
a.add(1)
self.assertIn(1, a)
self.assertIn(None, a)
a.add(0)
self.assertEqual(list(a), [None, 1, 0])
# Adding a member alrady in the set does not change the ordering
a.add(1)
self.assertEqual(list(a), [None, 1, 0])
def test_discard_remove_clear(self):
a = OrderedSet([1, 3, 2, 4])
a.discard(3)
self.assertEqual(list(a), [1, 2, 4])
a.discard(3)
self.assertEqual(list(a), [1, 2, 4])
a.remove(2)
self.assertEqual(list(a), [1, 4])
with self.assertRaisesRegex(KeyError, '2'):
a.remove(2)
a.clear()
self.assertEqual(list(a), [])
def _write_equations_section(self, model, output_file, all_blocks_list,
active_components_data_var, symbol_map,
c_labeler, output_fixed_variable_bounds,
skip_trivial_constraints, sorter):
referenced_variable_ids = OrderedSet()
def _skip_trivial(constraint_data):
if skip_trivial_constraints:
if constraint_data._linear_canonical_form:
repn = constraint_data.canonical_form()
if (repn.variables is None) or \
(len(repn.variables) == 0):
return True
elif constraint_data.body.polynomial_degree() == 0:
return True
return False
#
# Check for active suffixes to export
#
if isinstance(model, IBlock):
suffix_gen = lambda b: ((suf.storage_key, suf) \
for suf in pyomo.core.kernel.suffix.\
export_suffix_generator(b,
active=True,
descend_into=False))
else:
suffix_gen = lambda b: pyomo.core.base.suffix.\
active_export_suffix_generator(b)
r_o_eqns = []
c_eqns = []
l_eqns = []
branching_priorities_suffixes = []
for block in all_blocks_list:
for name, suffix in suffix_gen(block):
if name == 'branching_priorities':
branching_priorities_suffixes.append(suffix)
elif name == 'constraint_types':
for constraint_data, constraint_type in iteritems(suffix):
if not _skip_trivial(constraint_data):
if constraint_type.lower() == 'relaxationonly':
r_o_eqns.append(constraint_data)
elif constraint_type.lower() == 'convex':
c_eqns.append(constraint_data)
elif constraint_type.lower() == 'local':
l_eqns.append(constraint_data)
else:
raise ValueError(
"A suffix '%s' contained an invalid value: %s\n"
"Choices are: [relaxationonly, convex, local]"
% (suffix.name, constraint_type))
else:
raise ValueError(
"The BARON writer can not export suffix with name '%s'. "
"Either remove it from block '%s' or deactivate it." %
(block.name, name))
non_standard_eqns = r_o_eqns + c_eqns + l_eqns
#
# EQUATIONS
#
#Equation Declaration
n_roeqns = len(r_o_eqns)
n_ceqns = len(c_eqns)
n_leqns = len(l_eqns)
eqns = []
# Alias the constraints by declaration order since Baron does not
# include the constraint names in the solution file. It is important
# that this alias not clash with any real constraint labels, hence
# the use of the ".c<integer>" template. It is not possible to declare
# a component having this type of name when using standard syntax.
# There are ways to do it, but it is unlikely someone will.
order_counter = 0
alias_template = ".c%d"
output_file.write('EQUATIONS ')
output_file.write("c_e_FIX_ONE_VAR_CONST__")
order_counter += 1
for block in all_blocks_list:
for constraint_data in block.component_data_objects(
Constraint, active=True, sort=sorter, descend_into=False):
if (not constraint_data.has_lb()) and \
(not constraint_data.has_ub()):
assert not constraint_data.equality
continue # non-binding, so skip
if (not _skip_trivial(constraint_data)) and \
(constraint_data not in non_standard_eqns):
eqns.append(constraint_data)
con_symbol = symbol_map.createSymbol(
constraint_data, c_labeler)
assert not con_symbol.startswith('.')
assert con_symbol != "c_e_FIX_ONE_VAR_CONST__"
symbol_map.alias(constraint_data,
alias_template % order_counter)
output_file.write(", " + str(con_symbol))
order_counter += 1
output_file.write(";\n\n")
if n_roeqns > 0:
output_file.write('RELAXATION_ONLY_EQUATIONS ')
for i, constraint_data in enumerate(r_o_eqns):
con_symbol = symbol_map.createSymbol(constraint_data,
c_labeler)
assert not con_symbol.startswith('.')
assert con_symbol != "c_e_FIX_ONE_VAR_CONST__"
symbol_map.alias(constraint_data,
alias_template % order_counter)
if i == n_roeqns - 1:
output_file.write(str(con_symbol) + ';\n\n')
else:
output_file.write(str(con_symbol) + ', ')
order_counter += 1
if n_ceqns > 0:
output_file.write('CONVEX_EQUATIONS ')
for i, constraint_data in enumerate(c_eqns):
con_symbol = symbol_map.createSymbol(constraint_data,
c_labeler)
assert not con_symbol.startswith('.')
assert con_symbol != "c_e_FIX_ONE_VAR_CONST__"
symbol_map.alias(constraint_data,
alias_template % order_counter)
if i == n_ceqns - 1:
output_file.write(str(con_symbol) + ';\n\n')
else:
output_file.write(str(con_symbol) + ', ')
order_counter += 1
if n_leqns > 0:
output_file.write('LOCAL_EQUATIONS ')
for i, constraint_data in enumerate(l_eqns):
con_symbol = symbol_map.createSymbol(constraint_data,
c_labeler)
assert not con_symbol.startswith('.')
assert con_symbol != "c_e_FIX_ONE_VAR_CONST__"
symbol_map.alias(constraint_data,
alias_template % order_counter)
if i == n_leqns - 1:
output_file.write(str(con_symbol) + ';\n\n')
else:
output_file.write(str(con_symbol) + ', ')
order_counter += 1
# Create a dictionary of baron variable names to match to the
# strings that constraint.to_string() prints. An important
# note is that the variable strings are padded by spaces so
# that whole variable names are recognized, and simple
# variable names are not identified inside longer names.
# Example: ' x[1] ' -> ' x3 '
#FIXME: 7/18/14 CLH: This may cause mistakes if spaces in
# variable names are allowed
if isinstance(model, IBlock):
mutable_param_gen = lambda b: \
b.components(ctype=Param,
descend_into=False)
else:
def mutable_param_gen(b):
for param in block.component_objects(Param):
if param.mutable and param.is_indexed():
param_data_iter = \
(param_data for index, param_data
in iteritems(param))
elif not param.is_indexed():
param_data_iter = iter([param])
else:
param_data_iter = iter([])
for param_data in param_data_iter:
yield param_data
if False:
#
# This was part of a merge from master that caused
# test failures. But commenting this out didn't cause additional failures!?!
#
vstring_to_var_dict = {}
vstring_to_bar_dict = {}
pstring_to_bar_dict = {}
for block in all_blocks_list:
for var_data in active_components_data_var[id(block)]:
variable_stream = StringIO()
var_data.to_string(ostream=variable_stream, verbose=False)
variable_string = variable_stream.getvalue()
variable_string = ' ' + variable_string + ' '
vstring_to_var_dict[variable_string] = var_data
if output_fixed_variable_bounds or (not var_data.fixed):
vstring_to_bar_dict[variable_string] = \
' '+object_symbol_dictionary[id(var_data)]+' '
else:
assert var_data.value is not None
vstring_to_bar_dict[variable_string] = \
ftoa(var_data.value)
for param_data in mutable_param_gen(block):
param_stream = StringIO()
param_data.to_string(ostream=param_stream, verbose=False)
param_string = param_stream.getvalue()
param_string = ' ' + param_string + ' '
pstring_to_bar_dict[param_string] = ftoa(param_data())
# Equation Definition
output_file.write('c_e_FIX_ONE_VAR_CONST__: ONE_VAR_CONST__ == 1;\n')
for constraint_data in itertools.chain(eqns, r_o_eqns, c_eqns, l_eqns):
variables = OrderedSet()
#print(symbol_map.byObject.keys())
eqn_body = expression_to_string(constraint_data.body,
variables,
smap=symbol_map)
#print(symbol_map.byObject.keys())
referenced_variable_ids.update(variables)
if len(variables) == 0:
assert not skip_trivial_constraints
eqn_body += " + 0 * ONE_VAR_CONST__ "
# 7/29/14 CLH:
#FIXME: Baron doesn't handle many of the
# intrinsic_functions available in pyomo. The
# error message given by baron is also very
# weak. Either a function here to re-write
# unallowed expressions or a way to track solver
# capability by intrinsic_expression would be
# useful.
##########################
con_symbol = symbol_map.byObject[id(constraint_data)]
output_file.write(str(con_symbol) + ': ')
# Fill in the left and right hand side (constants) of
# the equations
# Equality constraint
if constraint_data.equality:
eqn_lhs = ''
eqn_rhs = ' == ' + ftoa(constraint_data.upper)
# Greater than constraint
elif not constraint_data.has_ub():
eqn_rhs = ' >= ' + ftoa(constraint_data.lower)
eqn_lhs = ''
# Less than constraint
elif not constraint_data.has_lb():
eqn_rhs = ' <= ' + ftoa(constraint_data.upper)
eqn_lhs = ''
# Double-sided constraint
elif constraint_data.has_lb() and \
constraint_data.has_ub():
eqn_lhs = ftoa(constraint_data.lower) + \
' <= '
eqn_rhs = ' <= ' + ftoa(constraint_data.upper)
eqn_string = eqn_lhs + eqn_body + eqn_rhs + ';\n'
output_file.write(eqn_string)
#
# OBJECTIVE
#
output_file.write("\nOBJ: ")
n_objs = 0
for block in all_blocks_list:
for objective_data in block.component_data_objects(
Objective, active=True, sort=sorter, descend_into=False):
n_objs += 1
if n_objs > 1:
raise ValueError(
"The BARON writer has detected multiple active "
"objective functions on model %s, but "
"currently only handles a single objective." %
(model.name))
# create symbol
symbol_map.createSymbol(objective_data, c_labeler)
symbol_map.alias(objective_data, "__default_objective__")
if objective_data.is_minimizing():
output_file.write("minimize ")
else:
output_file.write("maximize ")
variables = OrderedSet()
#print(symbol_map.byObject.keys())
obj_string = expression_to_string(objective_data.expr,
variables,
smap=symbol_map)
#print(symbol_map.byObject.keys())
referenced_variable_ids.update(variables)
output_file.write(obj_string + ";\n\n")
#referenced_variable_ids.update(symbol_map.byObject.keys())
return referenced_variable_ids, branching_priorities_suffixes