Source code for pm4py.statistics.concurrent_activities.log.get
'''
PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.
This program 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 Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.
Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
from enum import Enum
from pm4py.objects.conversion.log import converter
from pm4py.objects.log.util import sorting
from pm4py.util import exec_utils, constants, xes_constants
from typing import Optional, Dict, Any, Union, Tuple
from pm4py.objects.log.obj import EventLog
[docs]
class Parameters(Enum):
ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY
START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY
STRICT = "strict"
[docs]
def apply(
interval_log: EventLog,
parameters: Optional[Dict[Union[str, Parameters], Any]] = None,
) -> Dict[Tuple[str, str], int]:
"""
Gets the number of times for which two activities have been concurrent in the log
Parameters
--------------
interval_log
Interval event log
parameters
Parameters of the algorithm, including:
- Parameters.ACTIVITY_KEY => activity key
- Parameters.START_TIMESTAMP_KEY => start timestamp
- Parameters.TIMESTAMP_KEY => complete timestamp
- Parameters.STRICT => Determine if only entries that are strictly concurrent
(i.e. the length of the intersection as real interval is > 0) should be obtained. Default: False
Returns
--------------
ret_dict
Dictionaries associating to a couple of activities (tuple) the number of times for which they have been
executed in parallel in the log
"""
if parameters is None:
parameters = {}
interval_log = converter.apply(
interval_log,
variant=converter.Variants.TO_EVENT_LOG,
parameters=parameters,
)
activity_key = exec_utils.get_param_value(
Parameters.ACTIVITY_KEY, parameters, xes_constants.DEFAULT_NAME_KEY
)
timestamp_key = exec_utils.get_param_value(
Parameters.TIMESTAMP_KEY,
parameters,
xes_constants.DEFAULT_TIMESTAMP_KEY,
)
start_timestamp_key = exec_utils.get_param_value(
Parameters.START_TIMESTAMP_KEY,
parameters,
xes_constants.DEFAULT_TIMESTAMP_KEY,
)
strict = exec_utils.get_param_value(Parameters.STRICT, parameters, False)
ret_dict = {}
for trace in interval_log:
sorted_trace = sorting.sort_timestamp_trace(trace, start_timestamp_key)
i = 0
while i < len(sorted_trace):
act1 = sorted_trace[i][activity_key]
ts1 = sorted_trace[i][start_timestamp_key]
tc1 = sorted_trace[i][timestamp_key]
j = i + 1
while j < len(sorted_trace):
ts2 = sorted_trace[j][start_timestamp_key]
tc2 = sorted_trace[j][timestamp_key]
act2 = sorted_trace[j][activity_key]
if max(ts1, ts2) <= min(tc1, tc2):
if not strict or max(ts1, ts2) < min(tc1, tc2):
# avoid getting two entries for the same set of
# concurrent activities
tup = tuple(sorted((act1, act2)))
if tup not in ret_dict:
ret_dict[tup] = 0
ret_dict[tup] = ret_dict[tup] + 1
else:
break
j = j + 1
i = i + 1
return ret_dict