'''
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 pm4py.statistics.attributes.log import get as attr_get
from pm4py.objects.dfg.utils import dfg_utils
from pm4py.util import xes_constants as xes
from pm4py.util import exec_utils
from pm4py.statistics.service_time.log import get as serv_time_get
from enum import Enum
from pm4py.util import constants
from typing import Optional, Dict, Any, Tuple
import graphviz
from pm4py.objects.log.obj import EventLog
from collections import Counter
from pm4py.visualization.dfg.util import dfg_gviz
[docs]
class Parameters(Enum):
ACTIVITY_KEY = constants.PARAMETER_CONSTANT_ACTIVITY_KEY
FORMAT = "format"
MAX_NO_EDGES_IN_DIAGRAM = "maxNoOfEdgesInDiagram"
START_ACTIVITIES = "start_activities"
END_ACTIVITIES = "end_activities"
TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY
START_TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_START_TIMESTAMP_KEY
FONT_SIZE = "font_size"
RANKDIR = "rankdir"
BGCOLOR = "bgcolor"
STAT_LOCALE = "stat_locale"
[docs]
def apply(dfg: Dict[Tuple[str, str], int], log: EventLog = None, parameters: Optional[Dict[Any, Any]] = None, activities_count : Dict[str, int] = None, serv_time: Dict[str, float] = None) -> graphviz.Digraph:
"""
Visualize a frequency directly-follows graph
Parameters
-----------------
dfg
Frequency Directly-follows graph
log
(if provided) Event log for the calculation of statistics
activities_count
(if provided) Dictionary associating to each activity the number of occurrences in the log.
serv_time
(if provided) Dictionary associating to each activity the average service time
parameters
Variant-specific parameters
Returns
-----------------
gviz
Graphviz digraph
"""
if parameters is None:
parameters = {}
activity_key = exec_utils.get_param_value(Parameters.ACTIVITY_KEY, parameters, xes.DEFAULT_NAME_KEY)
image_format = exec_utils.get_param_value(Parameters.FORMAT, parameters, "png")
max_no_of_edges_in_diagram = exec_utils.get_param_value(Parameters.MAX_NO_EDGES_IN_DIAGRAM, parameters, 100000)
start_activities = exec_utils.get_param_value(Parameters.START_ACTIVITIES, parameters, {})
end_activities = exec_utils.get_param_value(Parameters.END_ACTIVITIES, parameters, {})
font_size = exec_utils.get_param_value(Parameters.FONT_SIZE, parameters, 12)
font_size = str(font_size)
if start_activities is None:
start_activities = dict()
if end_activities is None:
end_activities = dict()
activities = sorted(list(set(dfg_utils.get_activities_from_dfg(dfg)).union(set(start_activities)).union(set(end_activities))))
rankdir = exec_utils.get_param_value(Parameters.RANKDIR, parameters, constants.DEFAULT_RANKDIR_GVIZ)
bgcolor = exec_utils.get_param_value(Parameters.BGCOLOR, parameters, constants.DEFAULT_BGCOLOR)
stat_locale = exec_utils.get_param_value(Parameters.STAT_LOCALE, parameters, {})
if activities_count is None:
if log is not None:
activities_count = attr_get.get_attribute_values(log, activity_key, parameters=parameters)
else:
# the frequency of an activity in the log is at least the number of occurrences of
# incoming arcs in the DFG.
# if the frequency of the start activities nodes is also provided, use also that.
activities_count = Counter({key: 0 for key in activities})
for el in dfg:
activities_count[el[1]] += dfg[el]
if isinstance(start_activities, dict):
for act in start_activities:
activities_count[act] += start_activities[act]
if serv_time is None:
if log is not None:
serv_time = serv_time_get.apply(log, parameters=parameters)
else:
serv_time = {key: 0 for key in activities}
return dfg_gviz.graphviz_visualization(activities_count, dfg, image_format=image_format, measure="frequency",
max_no_of_edges_in_diagram=max_no_of_edges_in_diagram,
start_activities=start_activities, end_activities=end_activities, serv_time=serv_time,
font_size=font_size, bgcolor=bgcolor, rankdir=rankdir)
