'''
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.conversion.log import converter as log_conversion
from pm4py.visualization.common import gview
from pm4py.visualization.common import save as gsave
from pm4py.visualization.petri_net.variants import wo_decoration, alignments, greedy_decoration_performance, \
greedy_decoration_frequency, token_decoration_performance, token_decoration_frequency
from pm4py.util import exec_utils
from enum import Enum
import pkgutil
from pm4py.visualization.common.gview import serialize, serialize_dot
from pm4py.objects.petri_net.obj import PetriNet, Marking
from typing import Optional, Dict, Any, Union, Tuple
from pm4py.objects.log.obj import EventLog, EventStream
import pandas as pd
import graphviz
[docs]class Variants(Enum):
WO_DECORATION = wo_decoration
FREQUENCY = token_decoration_frequency
PERFORMANCE = token_decoration_performance
FREQUENCY_GREEDY = greedy_decoration_frequency
PERFORMANCE_GREEDY = greedy_decoration_performance
ALIGNMENTS = alignments
WO_DECORATION = Variants.WO_DECORATION
FREQUENCY_DECORATION = Variants.FREQUENCY
PERFORMANCE_DECORATION = Variants.PERFORMANCE
FREQUENCY_GREEDY = Variants.FREQUENCY_GREEDY
PERFORMANCE_GREEDY = Variants.PERFORMANCE_GREEDY
ALIGNMENTS = Variants.ALIGNMENTS
[docs]def apply(net: PetriNet, initial_marking: Marking = None, final_marking: Marking = None, log: Union[EventLog, EventStream, pd.DataFrame] = None, aggregated_statistics=None, parameters: Optional[Dict[Any, Any]] = None,
variant=Variants.WO_DECORATION) -> graphviz.Digraph:
if parameters is None:
parameters = {}
if log is not None:
if pkgutil.find_loader("pandas"):
import pandas
from pm4py.objects.log.util import dataframe_utils
if isinstance(log, pandas.core.frame.DataFrame):
log = dataframe_utils.convert_timestamp_columns_in_df(log)
log = log_conversion.apply(log, parameters, log_conversion.TO_EVENT_LOG)
return exec_utils.get_variant(variant).apply(net, initial_marking, final_marking, log=log,
aggregated_statistics=aggregated_statistics,
parameters=parameters)
[docs]def save(gviz: graphviz.Digraph, output_file_path: str):
"""
Save the diagram
Parameters
-----------
gviz
GraphViz diagram
output_file_path
Path where the GraphViz output should be saved
"""
gsave.save(gviz, output_file_path)
[docs]def view(gviz: graphviz.Digraph):
"""
View the diagram
Parameters
-----------
gviz
GraphViz diagram
"""
return gview.view(gviz)
[docs]def matplotlib_view(gviz: graphviz.Digraph):
"""
Views the diagram using Matplotlib
Parameters
---------------
gviz
Graphviz
"""
return gview.matplotlib_view(gviz)