def test_boolean_encoding_parsing(self):
encoding = create_test_encoding(value_encoding=ValueEncodings.BOOLEAN.value, prefix_length=2, padding=True)
parser = self._get_parser(encoding=ValueEncodings.BOOLEAN.value)
train_df = boolean(self.train_log, self.train_event_names, self.labelling, encoding)
test_df = boolean(self.test_log, self.test_event_names, self.labelling, encoding)
train_df, targets_df = self._drop_columns_and_split(train_df)
test_df, _ = self._drop_columns_and_split(test_df)
parser.parse_training_dataset(train_df)
parser.parse_targets(targets_df)
parser.parse_testing_dataset(test_df)
def _eventlog_to_dataframe(log: EventLog,
encoding: Encoding,
labelling: Labelling,
additional_columns=None,
cols=None):
if encoding.prefix_length < 1:
raise ValueError("Prefix length must be greater than 1")
if encoding.value_encoding == ValueEncodings.SIMPLE_INDEX.value:
run_df = simple_index(log, labelling, encoding)
elif encoding.value_encoding == ValueEncodings.BOOLEAN.value:
if cols is None:
cols = unique_events(log)
run_df = boolean(log, cols, labelling, encoding)
elif encoding.value_encoding == ValueEncodings.FREQUENCY.value:
if cols is None:
cols = unique_events(log)
run_df = frequency(log, cols, labelling, encoding)
elif encoding.value_encoding == ValueEncodings.COMPLEX.value:
run_df = complex(log, labelling, encoding, additional_columns)
elif encoding.value_encoding == ValueEncodings.LAST_PAYLOAD.value:
run_df = last_payload(log, labelling, encoding, additional_columns)
# elif encoding.value_encoding == ValueEncodings.SEQUENCES.value: #TODO JONAS
# run_df = sequences(log, labelling, encoding, additional_columns)
elif encoding.value_encoding == ValueEncodings.DECLARE.value:
run_df = declare_encoding(log,
labelling,
encoding,
additional_columns,
cols=cols)
if cols is None:
cols = list(run_df.columns)
else:
raise ValueError("Unknown value encoding method {}".format(
encoding.value_encoding))
return run_df, cols
def test_header(self):
df = boolean(self.log, self.event_names, self.labelling, self.encoding)
names = ['register request', 'examine casually', 'check ticket', 'decide',
'reinitiate request', 'examine thoroughly',
'reject request', 'trace_id', 'label', 'elapsed_time']
for name in names:
self.assertIn(name, df.columns.values.tolist())
def test_prefix1_no_elapsed_time(self):
encoding = create_test_encoding(
value_encoding=ValueEncodings.BOOLEAN.value,
task_generation_type=TaskGenerationTypes.ONLY_THIS.value,
prefix_length=1)
df = boolean(self.log, self.event_names, self.labelling, encoding)
self.assertEqual(df.shape, (2, 9))
self.assertNotIn('elapsed_time', df.columns.values.tolist())
def test_prefix1(self):
df = boolean(self.log, self.event_names, self.labelling, self.encoding)
self.assertEqual(df.shape, (2, 10))
row1 = df[df.trace_id == '5'].iloc[0]
self.assertTrue(row1['register request'])
self.assertFalse(row1['examine casually'])
self.assertEqual(1576440.0, row1.label)
row2 = df[df.trace_id == '4'].iloc[0]
self.assertTrue(row2['register request'])
self.assertFalse(row2['examine casually'])
self.assertEqual(520920.0, row2.label)
def test_prefix10_padding_all_in_one(self):
encoding = create_test_encoding(value_encoding=ValueEncodings.BOOLEAN.value,
prefix_length=10,
add_elapsed_time=True,
padding=True,
task_generation_type=ALL_IN_ONE)
df = boolean(self.log, self.event_names, self.labelling, encoding)
self.assertEqual(df.shape, (15, 10))
row1 = df[df.trace_id == '4'].iloc[4]
self.assertListEqual(['4', True, False, True, True, False, True, True, 520920.0, 0.0], row1.values.tolist())
self.assertFalse(df.isnull().values.any())
def test_prefix10_padding(self):
encoding = create_test_encoding(
value_encoding=ValueEncodings.BOOLEAN.value,
add_elapsed_time=True,
task_generation_type=TaskGenerationTypes.ONLY_THIS.value,
prefix_length=10,
padding=True)
df = boolean(self.log, self.event_names, self.labelling, encoding)
self.assertEqual(df.shape, (2, 10))
row1 = df[df.trace_id == '4'].iloc[0]
self.assertListEqual(['4', True, False, True, True, False, True, True, 520920.0, 0.0], row1.values.tolist())
def test_prefix2(self):
encoding = create_test_encoding(
value_encoding=ValueEncodings.BOOLEAN.value,
add_elapsed_time=True,
task_generation_type=TaskGenerationTypes.ONLY_THIS.value,
prefix_length=2)
df = boolean(self.log, self.event_names, self.labelling, encoding)
self.assertEqual(df.shape, (2, 10))
row1 = df[df.trace_id == '5'].iloc[0]
self.assertTrue(row1['register request'])
self.assertTrue(row1['examine casually'])
self.assertEqual(1485600.0, row1.label)
row2 = df[df.trace_id == '4'].iloc[0]
self.assertTrue(row2['register request'])
self.assertFalse(row2['examine casually'])
self.assertTrue(row2['check ticket'])
self.assertEqual(445080.0, row2.label)
def test_prefix1_no_label(self):
labelling = create_test_labelling(label_type=LabelTypes.NO_LABEL.value)
df = boolean(self.log, self.event_names, labelling, self.encoding)
self.assertEqual(df.shape, (2, 8))
self.assertNotIn('label', df.columns.values.tolist())
