def test_importExportCSVtoCSV(self): eventLog = csv_importer.import_from_path(os.path.join(INPUT_DATA_DIR,"running-example.csv")) eventLog.sort() eventLog.sample() eventLog.insert_event_index_as_event_attribute() traceLog = log_transform.transform_event_log_to_trace_log(eventLog) traceLog.sort() traceLog.sample() traceLog.insert_trace_index_as_event_attribute() eventLogTransformed = log_transform.transform_trace_log_to_event_log(traceLog) csv_exporter.export_log(eventLogTransformed, os.path.join(OUTPUT_DATA_DIR,"running-example-exported.csv")) eventLogImportedAfterExport = csv_importer.import_from_path(os.path.join(OUTPUT_DATA_DIR,"running-example-exported.csv")) traceLogImportedAfterExport = log_transform.transform_event_log_to_trace_log(eventLogImportedAfterExport) self.assertEqual(len(traceLog), len(traceLogImportedAfterExport)) os.remove(os.path.join(OUTPUT_DATA_DIR,"running-example-exported.csv"))
def obtainPetriNetThroughAlphaMiner(self, logName):
if ".xes" in logName:
traceLog = xes_importer.import_from_file_xes(logName)
else:
eventLog = csv_importer.import_from_path(logName)
traceLog = log_transform.transform_event_log_to_trace_log(eventLog)
net, marking, fmarking = alpha_factory.apply(traceLog)
return traceLog, net, marking, fmarking
def test_importExportXEStoCSV(self): traceLog = xes_importer.import_from_file_xes(os.path.join(INPUT_DATA_DIR, "running-example.xes")) eventLog = log_transform.transform_trace_log_to_event_log(traceLog) csv_exporter.export_log(eventLog, os.path.join(OUTPUT_DATA_DIR,"running-example-exported.csv")) eventLogImportedAfterExport = csv_importer.import_from_path(os.path.join(OUTPUT_DATA_DIR,"running-example-exported.csv")) traceLogImportedAfterExport = log_transform.transform_event_log_to_trace_log(eventLogImportedAfterExport) self.assertEqual(len(traceLog), len(traceLogImportedAfterExport)) os.remove(os.path.join(OUTPUT_DATA_DIR,"running-example-exported.csv"))
def obtainPetriNetThroughImdf(self, logName):
if ".xes" in logName:
traceLog = xes_importer.import_from_file_xes(logName)
else:
eventLog = csv_importer.import_from_path(logName)
traceLog = log_transform.transform_event_log_to_trace_log(eventLog)
imdf = InductMinDirFollows()
net, marking, final_marking = imdf.apply(traceLog, None)
return traceLog, net, marking, final_marking
def load_logs():
"""
If enabled, load logs in the folder
"""
if shared.config["logFolder"]["loadLogsAutomatically"]:
shared.sem.acquire()
# loading logs
logsFolderPath = shared.config["logFolder"]["logFolderPath"]
folderContent = os.listdir(logsFolderPath)
for file in folderContent:
fullPath = os.path.join(logsFolderPath, file)
try:
if os.path.isfile(fullPath):
logName = file.split(".")[0]
logExtension = file.split(".")[-1]
if not logName in shared.trace_logs:
if logExtension == "xes":
# load XES files
shared.trace_logs[
logName] = xes_importer.import_from_file_xes(
fullPath)
shared.trace_logs[logName].sort()
shared.trace_logs[
logName].insert_trace_index_as_event_attribute(
)
elif logExtension == "csv":
# load CSV files
event_log = csv_importer.import_from_path(fullPath)
shared.trace_logs[
logName] = transform.transform_event_log_to_trace_log(
event_log)
shared.trace_logs[logName].sort()
shared.trace_logs[
logName].insert_trace_index_as_event_attribute(
)
except Exception as e:
# manage exception
logging.error("exception loading log: " + str(file) + ": " +
str(e))
logging.error("traceback: " + traceback.format_exc())
shared.sem.release()
def test_csv1documentation(self):
import os
from pm4py.log.importer import csv as csv_importer
event_log = csv_importer.import_from_path(
"inputData\\running-example.csv", sep=",")
event_log_length = len(event_log)
# print(event_log_length)
for event in event_log:
# print(event)
pass
from pm4py.log import transform
trace_log = transform.transform_event_log_to_trace_log(
event_log, case_glue="case:concept:name")
from pm4py.log.importer import csv as csv_importer
from pm4py.log import transform
dataframe = csv_importer.import_dataframe_from_path(
"inputData\\running-example.csv", sep=",")
event_log = csv_importer.convert_dataframe_to_event_log(dataframe)
trace_log = transform.transform_event_log_to_trace_log(
event_log, case_glue="case:concept:name")
from pm4py.log.exporter import csv as csv_exporter
csv_exporter.export_log(event_log, "outputFile1.csv")
os.remove("outputFile1.csv")
from pm4py.log.exporter import csv as csv_exporter
csv_exporter.export_log(trace_log, "outputFile2.csv")
os.remove("outputFile2.csv")
from pm4py.log.importer import xes as xes_importer
from pm4py.algo.dfg.versions import native as dfg_instance
from pm4py.algo.causal import factory as causal_instance
from pm4py.algo.alpha.versions import classic as alpha_classic
from pm4py.log.importer import csv as csv_importer
from pm4py.models.petri import visualize as pn_viz
from pm4py.log import transform as transformer
from tests.constants import INPUT_DATA_DIR
event = log_instance.Event({'concept:name': 'a'})
event['test'] = 'test'
# csv
start = time.time()
print(os.path.join(INPUT_DATA_DIR, "running-example.csv"))
log = csv_importer.import_from_path(
os.path.join(INPUT_DATA_DIR, "running-example.csv"), ";")
print(time.time() - start)
print(len(log))
print(log)
trace_log = transformer.transform_event_log_to_trace_log(log,
case_glue='Case ID')
'''
start = time.time()
log2 = log_instance.EventLog(log.attributes, filter(lambda e: e['amount'] > 50.0, log))
print(time.time() - start)
print(len(log2))
'''
def compare_time_of_first_event(t1, t2):
return (t1[0]['time:timestamp'] - t2[0]['time:timestamp']).microseconds
