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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.objects.log.util import sorting
from pm4py.objects.log.util import basic_filter
from pm4py.util import points_subset
from pm4py.util import xes_constants as xes
from pm4py.util import exec_utils
from enum import Enum
from pm4py.util import constants
from typing import Optional, Dict, Any, Union, List
from pm4py.objects.log.obj import EventLog
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"
SORT_LOG_REQUIRED = "sort_log_required"
def apply(log: EventLog, list_activities: List[str], sample_size: int, parameters: Optional[Dict[Union[str, Parameters], Any]] = None) -> Dict[str, Any]:
"""
Finds the performance spectrum provided a log
and a list of activities
Parameters
-------------
log
Log
list_activities
List of activities interesting for the performance spectrum (at least two)
sample_size
Size of the sample
parameters
Parameters of the algorithm, including:
- Parameters.ACTIVITY_KEY
- Parameters.TIMESTAMP_KEY
Returns
-------------
points
Points of the performance spectrum
"""
if parameters is None:
parameters = {}
activity_key = exec_utils.get_param_value(Parameters.ACTIVITY_KEY, parameters, xes.DEFAULT_NAME_KEY)
timestamp_key = exec_utils.get_param_value(Parameters.TIMESTAMP_KEY, parameters, xes.DEFAULT_TIMESTAMP_KEY)
sort_log_required = exec_utils.get_param_value(Parameters.SORT_LOG_REQUIRED, parameters, True)
parameters[Parameters.ATTRIBUTE_KEY] = activity_key
log = basic_filter.filter_log_events_attr(log, list_activities, parameters=parameters)
if sort_log_required:
log = sorting.sort_timestamp_log(log, timestamp_key=timestamp_key)
points = []
for trace in log:
for i in range(len(trace)-len(list_activities)+1):
acti_comb = [event[activity_key] for event in trace[i:i+len(list_activities)]]
if acti_comb == list_activities:
timest_comb = [event[timestamp_key].timestamp() for event in trace[i:i+len(list_activities)]]
points.append(timest_comb)
points = sorted(points, key=lambda x: x[0])
if len(points) > sample_size:
points = points_subset.pick_chosen_points_list(sample_size, points)
return points
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