def build_dictionaries(self, parameters):
"""
Builds the dictionaries needed to store the information during the replay
Parameters
---------------
parameters
Parameters:
- Parameters.DICT_VARIANT: type of dictionary to use
- Parameters.CASE_DICT_ID: identifier of the dictionary hosting the markings (0)
- Parameters.MISSING_DICT_ID: identifier of the dictionary hosting the missing tokens (1)
- Parameters.REMAINING_DICT_ID: identifier of the dictionary hosting the remaining tokens (2)
"""
dict_variant = exec_utils.get_param_value(Parameters.DICT_VARIANT, parameters, generator.Variants.THREAD_SAFE)
case_dict_id = exec_utils.get_param_value(Parameters.CASE_DICT_ID, parameters, 0)
missing_dict_id = exec_utils.get_param_value(Parameters.MISSING_DICT_ID, parameters, 1)
remaining_dict_id = exec_utils.get_param_value(Parameters.REMAINING_DICT_ID, parameters, 2)
parameters_case_dict = copy(parameters)
parameters_case_dict[Parameters.DICT_ID] = case_dict_id
parameters_missing = copy(parameters)
parameters_case_dict[Parameters.DICT_ID] = missing_dict_id
parameters_remaining = copy(parameters)
parameters_remaining[Parameters.DICT_ID] = remaining_dict_id
self.case_dict = generator.apply(variant=dict_variant, parameters=parameters_case_dict)
self.missing = generator.apply(variant=dict_variant, parameters=parameters_missing)
self.remaining = generator.apply(variant=dict_variant, parameters=parameters_remaining)
def build_dictionaries(self, parameters):
"""
Builds the dictionaries needed to store the information during the replay
Parameters
---------------
parameters
Parameters:
- Parameters.DICT_VARIANT: type of dictionary to use
- Parameters.CASE_DICT_ID: identifier of the dictionary hosting the last activity of a case (1)
- Parameters.DEV_DICT_ID: identifier of the dictionary hosting the deviations (2)
"""
dict_variant = exec_utils.get_param_value(Parameters.DICT_VARIANT,
parameters,
generator.Variants.CLASSIC)
case_dict_id = exec_utils.get_param_value(Parameters.CASE_DICT_ID,
parameters, 0)
dev_dict_id = exec_utils.get_param_value(Parameters.DEV_DICT_ID,
parameters, 1)
parameters_case_dict = copy(parameters)
parameters_case_dict[Parameters.DICT_ID] = case_dict_id
parameters_dev_dict = copy(parameters)
parameters_dev_dict[Parameters.DICT_ID] = dev_dict_id
self.case_dict = generator.apply(variant=dict_variant,
parameters=parameters_case_dict)
self.dev_dict = generator.apply(variant=dict_variant,
parameters=parameters_dev_dict)
def __init__(self,
temporal_profile: typing.TemporalProfile,
parameters: Optional[Dict[Any, Any]] = None):
"""
Initialize the streaming conformance checking.
Implements the approach described in:
Stertz, Florian, Jürgen Mangler, and Stefanie Rinderle-Ma. "Temporal Conformance Checking at Runtime based on Time-infused Process Models." arXiv preprint arXiv:2008.07262 (2020).
Parameters
---------------
temporal_profile
Temporal profile
parameters
Parameters of the algorithm, including:
- Parameters.ACTIVITY_KEY => the attribute to use as activity
- Parameters.START_TIMESTAMP_KEY => the attribute to use as start timestamp
- Parameters.TIMESTAMP_KEY => the attribute to use as timestamp
- Parameters.ZETA => multiplier for the standard deviation
- Parameters.CASE_ID_KEY => column to use as case identifier
- Parameters.DICT_VARIANT => the variant of dictionary to use
- Parameters.CASE_DICT_ID => the identifier of the case dictionary
- Parameters.DEV_DICT_ID => the identifier of the deviations dictionary
"""
if parameters is None:
parameters = {}
self.temporal_profile = temporal_profile
self.activity_key = exec_utils.get_param_value(
Parameters.ACTIVITY_KEY, parameters,
xes_constants.DEFAULT_NAME_KEY)
self.timestamp_key = exec_utils.get_param_value(
Parameters.TIMESTAMP_KEY, parameters,
xes_constants.DEFAULT_TIMESTAMP_KEY)
self.start_timestamp_key = exec_utils.get_param_value(
Parameters.START_TIMESTAMP_KEY, parameters,
xes_constants.DEFAULT_TIMESTAMP_KEY)
self.case_id_key = exec_utils.get_param_value(
Parameters.CASE_ID_KEY, parameters, constants.CASE_CONCEPT_NAME)
self.zeta = exec_utils.get_param_value(Parameters.ZETA, parameters,
6.0)
parameters_gen = copy(parameters)
dict_variant = exec_utils.get_param_value(
Parameters.DICT_VARIANT, parameters,
generator.Variants.THREAD_SAFE)
case_dict_id = exec_utils.get_param_value(Parameters.CASE_DICT_ID,
parameters, 0)
parameters_gen[Parameters.DICT_ID] = case_dict_id
self.case_dictionary = generator.apply(variant=dict_variant,
parameters=parameters_gen)
parameters_dev = copy(parameters)
dev_dict_id = exec_utils.get_param_value(Parameters.DEV_DICT_ID,
parameters, 1)
parameters_dev[Parameters.DICT_ID] = dev_dict_id
self.deviations_dict = generator.apply(variant=dict_variant,
parameters=parameters_dev)
StreamingAlgorithm.__init__(self)
def build_dictionaries(self, parameters):
"""
Builds the dictionaries that are needed by the
discovery operation
Parameters
---------------
parameters
Parameters:
- Parameters.DICT_VARIANT: type of dictionary to use
- Parameters.CASE_DICT_ID: identifier of the case dictionary (hosting the last activity of a case) (0)
- Parameters.DFG_DICT_ID: identifier of the DFG dictionary (1)
- Parameters.ACT_ID: identifier of the dictionary hosting the count of the activities (2)
- Parameters.START_ACT_DICT_ID: identifier of the dictionary hosting the count of the start activities (3)
"""
dict_variant = exec_utils.get_param_value(
Parameters.DICT_VARIANT, parameters,
generator.Variants.THREAD_SAFE)
case_dict_id = exec_utils.get_param_value(Parameters.CASE_DICT_ID,
parameters, 0)
dfg_dict_id = exec_utils.get_param_value(Parameters.DFG_DICT_ID,
parameters, 1)
act_dict_id = exec_utils.get_param_value(Parameters.ACT_DICT_ID,
parameters, 2)
start_act_dict_id = exec_utils.get_param_value(
Parameters.START_ACT_DICT_ID, parameters, 3)
parameters_case_dict = copy(parameters)
parameters_case_dict[Parameters.DICT_ID] = case_dict_id
parameters_dfg = copy(parameters)
parameters_dfg[Parameters.DICT_ID] = dfg_dict_id
parameters_activities = copy(parameters)
parameters_activities[Parameters.DICT_ID] = act_dict_id
parameters_start_activities = copy(parameters)
parameters_start_activities[Parameters.DICT_ID] = start_act_dict_id
self.case_dict = generator.apply(variant=dict_variant,
parameters=parameters_case_dict)
self.dfg = generator.apply(variant=dict_variant,
parameters=parameters_dfg)
self.activities = generator.apply(variant=dict_variant,
parameters=parameters_activities)
self.start_activities = generator.apply(
variant=dict_variant, parameters=parameters_start_activities)
