def __init__(self, mdl, exchange_format=None, **kwargs):
IndexerEngine.__init__(self)
warnings.warn(
'Solve using \'docloud\' agent is deprecated. Consider submitting your model to DOcplexcloud. See https://ibm.biz/BdYhhK',
DeprecationWarning)
docloud_context = kwargs.get('docloud_context')
# --- log output can be overridden at solve time, so use te one from the context, not the model's
actual_log_output = kwargs.get('log_output') or mdl.log_output
self._model = mdl
self._connector = DOcloudConnector(docloud_context,
log_output=actual_log_output)
self._exchange_format = exchange_format or docloud_context.exchange_format or _DEFAULT_EXCHANGE_FORMAT
mangle_names = mdl.ignore_names or mdl.context.solver.docloud.mangle_names
self._printer = ModelPrinterFactory.new_printer(self._exchange_format,
full_obj=True)
if mangle_names:
self._printer.set_mangle_names(True)
# -- results.
self._lpname_to_var_map = {}
self._solve_details = SolveDetails.make_dummy()
self._quality_metrics = {} # latest quality metrics from json
# noinspection PyPep8
self.debug_dump = docloud_context.debug_dump
self.debug_dump_dir = docloud_context.debug_dump_dir
def __init__(self,
prioritizer='all',
verbose=False,
precision=default_precision,
override=False,
**kwargs):
self.output_table_customizer = kwargs.get(
'output_processing') # wml tables, internal
self.output_table_property_name = 'relaxations_output'
self.default_output_table_name = 'relaxations.csv'
self.output_table_using_df = True # if pandas is available of course
self._precision = precision
# ---
if hasattr(prioritizer, 'get_priority'):
self._prioritizer = prioritizer
elif prioritizer == 'match':
self._prioritizer = MatchNamePrioritizer(override=override)
elif isinstance(prioritizer, dict):
self._prioritizer = MappingPrioritizer(
priority_mapping=prioritizer, override=override)
elif prioritizer == 'named':
self._prioritizer = NamedPrioritizer()
elif prioritizer is None or prioritizer == 'all':
self._prioritizer = UniformPrioritizer(override=override)
elif is_function(prioritizer):
self._prioritizer = FunctionalPrioritizer(prioritizer,
override=override)
else:
print(
"Cannot deduce a prioritizer from: {0!r} - expecting \"name\"|\"default\"| dict",
prioritizer)
raise TypeError
self._cumulative = True
self._listeners = []
# result data
self._last_relaxation_status = False
self._last_relaxation_objective = -1e+75
self._last_successful_relaxed_priority = Priority.MANDATORY
self._last_relaxation_details = SolveDetails.make_dummy()
self._relaxations = {}
self._verbose = verbose
self._verbose_listener = VerboseRelaxationListener()
if self._verbose:
self.add_listener(self._verbose_listener)
def __init__(self,
prioritizer='all',
verbose=False,
precision=default_precision,
override=False):
self._precision = precision
# ---
if isinstance(prioritizer, IConstraintPrioritizer):
self._prioritizer = prioritizer
elif prioritizer == 'match':
self._prioritizer = MatchNamePrioritizer(override=override)
elif isinstance(prioritizer, dict):
self._prioritizer = MappingPrioritizer(
priority_mapping=prioritizer, override=override)
elif prioritizer == 'named':
self._prioritizer = NamedPrioritizer()
elif prioritizer is None or prioritizer is 'all':
self._prioritizer = UniformPrioritizer(override=override)
elif is_function(prioritizer):
self._prioritizer = FunctionalPrioritizer(prioritizer,
override=override)
else:
print(
"Cannot deduce a prioritizer from: {0!r} - expecting \"name\"|\"default\"| dict",
prioritizer)
raise TypeError
self._cumulative = True
self._listeners = []
# result data
self._last_relaxation_status = False
self._last_relaxation_objective = -1e+75
self._last_successful_relaxed_priority = Priority.MANDATORY
self._last_relaxation_details = SolveDetails.make_dummy()
self._relaxations = {}
self._verbose = verbose
self._verbose_listener = VerboseRelaxationListener()
if self._verbose:
self.add_listener(self._verbose_listener)
