'''
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
'''
import collections
from pm4py.util import exec_utils
from pm4py.objects.log import util as log_util
from pm4py.util.xes_constants import DEFAULT_NAME_KEY
from pm4py.objects.transition_system import (
obj as ts,
constants as ts_constants,
)
from enum import Enum
from pm4py.util import constants, pandas_utils
from pm4py.objects.transition_system.obj import TransitionSystem
from typing import Optional, Dict, Any, Union
from pm4py.objects.log.obj import EventLog, EventStream
from pm4py.objects.conversion.log import converter as log_conversion
import pandas as pd
[docs]
class Parameters(Enum):
VIEW_MULTI_SET = "multiset"
VIEW_SET = "set"
VIEW_SEQUENCE = "sequence"
VIEWS = {VIEW_MULTI_SET, VIEW_SET, VIEW_SEQUENCE}
DIRECTION_FORWARD = "forward"
DIRECTION_BACKWARD = "backward"
DIRECTIONS = {DIRECTION_FORWARD, DIRECTION_BACKWARD}
PARAM_KEY_VIEW = "view"
PARAM_KEY_WINDOW = "window"
PARAM_KEY_DIRECTION = "direction"
ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
CASE_ID_KEY = constants.PARAMETER_CONSTANT_CASEID_KEY
INCLUDE_DATA = "include_data"
[docs]
def apply(
log: Union[EventLog, EventStream, pd.DataFrame],
parameters: Optional[Dict[Union[str, Parameters], Any]] = None,
) -> TransitionSystem:
if parameters is None:
parameters = {}
activity_key = exec_utils.get_param_value(
Parameters.ACTIVITY_KEY, parameters, DEFAULT_NAME_KEY
)
include_data = exec_utils.get_param_value(
Parameters.INCLUDE_DATA, parameters, False
)
if pandas_utils.check_is_pandas_dataframe(log):
case_id_key = exec_utils.get_param_value(
Parameters.CASE_ID_KEY, parameters, constants.CASE_CONCEPT_NAME
)
control_flow_log = [
tuple(x)
for x in log.groupby(case_id_key)[activity_key]
.agg(list)
.to_dict()
.values()
]
else:
log = log_conversion.apply(
log, parameters, log_conversion.TO_EVENT_LOG
)
control_flow_log = log_util.log.project_traces(log, activity_key)
transition_system = ts.TransitionSystem()
view_sequence = []
for i in range(len(control_flow_log)):
provided_case = log[i] if type(log) is EventLog else None
view_sequence.append(
__compute_view_sequence(
control_flow_log[i], provided_case, parameters=parameters
)
)
for vs in view_sequence:
__construct_state_path(
vs, transition_system, include_data=include_data
)
return transition_system
def __construct_state_path(
view_sequence, transition_system, include_data=False
):
for i in range(0, len(view_sequence) - 1):
sf = {
"state": s
for s in transition_system.states
if s.name == view_sequence[i][0]
}
sf = (
sf["state"]
if len(sf) > 0
else ts.TransitionSystem.State(view_sequence[i][0])
)
st = {
"state": s
for s in transition_system.states
if s.name == view_sequence[i + 1][0]
}
st = (
st["state"]
if len(st) > 0
else ts.TransitionSystem.State(view_sequence[i + 1][0])
)
t = {
"t": t
for t in sf.outgoing
if t.name == view_sequence[i][1]
and t.from_state == sf
and t.to_state == st
}
if len(t) == 0:
t = ts.TransitionSystem.Transition(view_sequence[i][1], sf, st)
sf.outgoing.add(t)
st.incoming.add(t)
else:
t = t["t"]
if include_data:
# add the event to the data in both the source state,
# the sink state and the transition
sf.data[ts_constants.OUTGOING_EVENTS].append(view_sequence[i][2])
st.data[ts_constants.INGOING_EVENTS].append(view_sequence[i][2])
t.data[ts_constants.EVENTS].append(view_sequence[i][2])
transition_system.states.add(sf)
transition_system.states.add(st)
transition_system.transitions.add(t)
def __compute_view_sequence(trace, full_case, parameters):
view_sequences = list()
direction = exec_utils.get_param_value(
Parameters.PARAM_KEY_DIRECTION,
parameters,
Parameters.DIRECTION_FORWARD.value,
)
window = exec_utils.get_param_value(
Parameters.PARAM_KEY_WINDOW, parameters, 2
)
for i in range(0, len(trace) + 1):
if direction == Parameters.DIRECTION_FORWARD.value:
view_sequences.append(
(
__apply_abstr(trace[i: i + window], parameters),
trace[i] if i < len(trace) else None,
(
(full_case, i)
if full_case is not None and i < len(full_case)
else None
),
)
)
else:
view_sequences.append(
(
__apply_abstr(trace[max(0, i - window): i], parameters),
trace[i] if i < len(trace) else None,
(
(full_case, i)
if full_case is not None and i < len(full_case)
else None
),
)
)
return view_sequences
def __apply_abstr(seq, parameters):
key_view = exec_utils.get_param_value(
Parameters.PARAM_KEY_VIEW, parameters, Parameters.VIEW_SEQUENCE.value
)
if key_view == Parameters.VIEW_SEQUENCE.value:
return list(seq)
elif key_view == Parameters.VIEW_MULTI_SET.value:
return collections.Counter(seq)
elif key_view == Parameters.VIEW_SET.value:
return set(seq)
