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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 collections import Counter
from pm4py.objects.log.obj import EventLog, Event, Trace
from pm4py.util import xes_constants as xes_util
import heapq
from pm4py.objects.petri_net.utils.petri_utils import decorate_places_preset_trans, decorate_transitions_prepostset
from pm4py.objects.petri_net.utils import align_utils as utils
from pm4py.objects.petri_net.utils.incidence_matrix import construct
from pm4py.util import constants, pandas_utils
import pandas as pd
def __search(sync_net, ini, fin, stop, cost_function, skip):
decorate_transitions_prepostset(sync_net)
decorate_places_preset_trans(sync_net)
incidence_matrix = construct(sync_net)
ini_vec, fin_vec, cost_vec = utils.__vectorize_initial_final_cost(incidence_matrix, ini, fin, cost_function)
closed = set()
ini_state = utils.SearchTuple(0, 0, 0, ini, None, None, None, True)
open_set = [ini_state]
heapq.heapify(open_set)
visited = 0
queued = 0
traversed = 0
# return all the prefix markings of the optimal alignments as set
ret_markings = None
# keep track of the optimal cost of an alignment (to trim search when needed)
optimal_cost = None
while not len(open_set) == 0:
curr = heapq.heappop(open_set)
current_marking = curr.m
# trim alignments when we already reached an optimal alignment and the
# current cost is greater than the optimal cost
if optimal_cost is not None and curr.f > optimal_cost:
break
already_closed = current_marking in closed
if already_closed:
continue
if stop <= current_marking:
# add the current marking to the set
# of returned markings
if ret_markings is None:
ret_markings = set()
ret_markings.add(current_marking)
# close the marking
closed.add(current_marking)
# set the optimal cost
optimal_cost = curr.f
continue
closed.add(current_marking)
visited += 1
enabled_trans = set()
for p in current_marking:
for t in p.ass_trans:
if t.sub_marking <= current_marking:
enabled_trans.add(t)
trans_to_visit_with_cost = [(t, cost_function[t]) for t in enabled_trans if
not (t is None or utils.__is_log_move(t, skip) or (
utils.__is_model_move(t, skip) and not t.label[1] is None))]
for t, cost in trans_to_visit_with_cost:
traversed += 1
new_marking = utils.add_markings(current_marking, t.add_marking)
if new_marking in closed:
continue
g = curr.g + cost
queued += 1
new_f = g
tp = utils.SearchTuple(new_f, g, 0, new_marking, curr, t, None, True)
heapq.heappush(open_set, tp)
return ret_markings
def get_log_prefixes(log, activity_key=xes_util.DEFAULT_NAME_KEY, case_id_key=constants.CASE_CONCEPT_NAME):
"""
Get log prefixes
Parameters
----------
log
Trace log
activity_key
Activity key (must be provided if different from concept:name)
"""
prefixes = {}
prefix_count = Counter()
if pandas_utils.check_is_pandas_dataframe(log):
traces = [tuple(x) for x in log.groupby(case_id_key)[activity_key].agg(list).to_dict().values()]
else:
traces = [tuple(x[activity_key] for x in trace) for trace in log]
for trace in traces:
for i in range(1, len(trace)):
prefix = constants.DEFAULT_VARIANT_SEP.join(trace[0:i])
next_activity = trace[i]
if prefix not in prefixes:
prefixes[prefix] = set()
prefixes[prefix].add(next_activity)
prefix_count[prefix] += 1
return prefixes, prefix_count
def form_fake_log(prefixes_keys, activity_key=xes_util.DEFAULT_NAME_KEY):
"""
Form fake log for replay (putting each prefix as separate trace to align)
Parameters
----------
prefixes_keys
Keys of the prefixes (to form a log with a given order)
activity_key
Activity key (must be provided if different from concept:name)
"""
fake_log = EventLog()
for prefix in prefixes_keys:
trace = Trace()
prefix_activities = prefix.split(constants.DEFAULT_VARIANT_SEP)
for activity in prefix_activities:
event = Event()
event[activity_key] = activity
trace.append(event)
fake_log.append(trace)
return fake_log
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