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| ''' | |
| This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de). | |
| PM4Py is free software: you can redistribute it and/or modify | |
| it under the terms of the GNU General Public License as published by | |
| the Free Software Foundation, either version 3 of the License, or | |
| (at your option) any later version. | |
| PM4Py is distributed in the hope that it will be useful, | |
| but WITHOUT ANY WARRANTY; without even the implied warranty of | |
| MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the | |
| GNU General Public License for more details. | |
| You should have received a copy of the GNU General Public License | |
| along with PM4Py. If not, see <https://www.gnu.org/licenses/>. | |
| ''' | |
| from pm4py.algo.discovery.performance_spectrum.variants import dataframe, log, dataframe_disconnected, log_disconnected | |
| from pm4py.util import exec_utils | |
| from enum import Enum | |
| from pm4py.util import constants, pandas_utils | |
| from typing import Optional, Dict, Any, Union, List | |
| from pm4py.objects.log.obj import EventLog, EventStream | |
| import pandas as pd | |
| class Parameters(Enum): | |
| ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY | |
| TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY | |
| CASE_ID_KEY = constants.PARAMETER_CONSTANT_CASEID_KEY | |
| ATTRIBUTE_KEY = constants.PARAMETER_CONSTANT_ATTRIBUTE_KEY | |
| PARAMETER_SAMPLE_SIZE = "sample_size" | |
| class Outputs(Enum): | |
| LIST_ACTIVITIES = "list_activities" | |
| POINTS = "points" | |
| class Variants(Enum): | |
| DATAFRAME = dataframe | |
| LOG = log | |
| DATAFRAME_DISCONNECTED = dataframe_disconnected | |
| LOG_DISCONNECTED = log_disconnected | |
| def apply(log: Union[EventLog, EventStream, pd.DataFrame], list_activities: List[str], variant=None, parameters: Optional[Dict[Any, Any]] = None) -> Dict[str, Any]: | |
| """ | |
| Finds the performance spectrum provided a log/dataframe | |
| and a list of activities | |
| Parameters | |
| ------------- | |
| log | |
| Event log/Dataframe | |
| list_activities | |
| List of activities interesting for the performance spectrum (at least two) | |
| variant | |
| Variant to be used (see Variants Enum) | |
| parameters | |
| Parameters of the algorithm, including: | |
| - Parameters.ACTIVITY_KEY | |
| - Parameters.TIMESTAMP_KEY | |
| Returns | |
| ------------- | |
| ps | |
| Performance spectrum object (dictionary) | |
| """ | |
| from pm4py.objects.conversion.log import converter as log_conversion | |
| if parameters is None: | |
| parameters = {} | |
| sample_size = exec_utils.get_param_value(Parameters.PARAMETER_SAMPLE_SIZE, parameters, 10000) | |
| if len(list_activities) < 2: | |
| raise Exception("performance spectrum can be applied providing at least two activities!") | |
| points = None | |
| if pandas_utils.check_is_pandas_dataframe(log): | |
| if variant is None: | |
| variant = Variants.DATAFRAME | |
| points = exec_utils.get_variant(variant).apply(log, list_activities, sample_size, parameters) | |
| if points is None: | |
| if variant is None: | |
| variant = Variants.LOG | |
| points = exec_utils.get_variant(variant).apply(log_conversion.apply(log, variant=log_conversion.Variants.TO_EVENT_LOG, parameters=parameters), list_activities, sample_size, | |
| parameters) | |
| ps = {Outputs.LIST_ACTIVITIES.value: list_activities, Outputs.POINTS.value: points} | |
| return ps | |