def test_importing_csv(self):
from pm4py.objects.log.importer.csv import factory as csv_importer
df = csv_importer.import_dataframe_from_path(
os.path.join("input_data", "running-example.csv"))
df = csv_importer.import_dataframe_from_path_wo_timeconversion(
os.path.join("input_data", "running-example.csv"))
stream = csv_importer.apply(
os.path.join("input_data", "running-example.csv"))
stru = "case:concept:name,concept:name,time:timestamp\nA1,A,1970-01-01 01:00:00\n"
df = csv_importer.import_dataframe_from_csv_string(stru)
stream = csv_importer.import_log_from_string(stru)
def test_inductiveminer_stream(self):
stream = csv_importer.apply(
os.path.join("input_data", "running-example.csv"))
net, im, fm = inductive_miner.apply(stream)
aligned_traces_tr = tr_factory.apply(stream, net, im, fm)
aligned_traces_alignments = align_factory.apply(stream, net, im, fm)
evaluation = eval_factory.apply(stream, net, im, fm)
fitness = rp_fit_factory.apply(stream, net, im, fm)
precision = precision_factory.apply(stream, net, im, fm)
generalization = generalization_factory.apply(stream, net, im, fm)
simplicity = simplicity_factory.apply(net)
def test_csvimp_xesexp(self):
log0 = csv_importer.apply(
os.path.join("input_data", "running-example.csv"))
log = log_conv_factory.apply(log0,
variant=log_conv_factory.TO_EVENT_LOG)
stream = log_conv_factory.apply(
log0, variant=log_conv_factory.TO_EVENT_STREAM)
df = log_conv_factory.apply(log0,
variant=log_conv_factory.TO_DATAFRAME)
xes_exporter_factory.apply(log, "ru.xes")
xes_exporter_factory.apply(stream, "ru.xes")
xes_exporter_factory.apply(df, "ru.xes")
os.remove('ru.xes')
def test_ts_stream(self):
stream = csv_importer.apply(
os.path.join("input_data", "running-example.csv"))
ts = ts_disc_factory.apply(stream)
def test_dfg_stream(self):
stream = csv_importer.apply(
os.path.join("input_data", "running-example.csv"))
dfg = dfg_mining_factory.apply(stream)