def test_workflow_working_with_child(self):
m = Mock()
m.side_effect = [[{
"log": 25,
"weigth": 10
}, {
"log": 15,
"weigth": 10
}], [{
"log": 25,
"weigth": 10
}, {
"log": 15,
"weigth": 10
}], [{
"log": 25,
"weigth": 10
}, {
"log": 15,
"weigth": 10
}], [{
"log": 25,
"weigth": 10
}, {
"log": 15,
"weigth": 10
}], [{
"log": 25,
"weigth": 10
}, {
"log": 15,
"weigth": 10
}]]
logflow.treebuilding.Inference.Inference.test = m
default_pattern1 = Pattern(0, [], [])
default_pattern1.id = 1
default_pattern2 = Pattern(0, [], [])
default_pattern2.id = 2
default_pattern3 = Pattern(0, [], [])
default_pattern3.id = 3
m_pattern = Mock()
m_pattern.side_effect = [
default_pattern1, default_pattern2, default_pattern3
] * 3000
logflow.logsparser.Journal.Journal.find_pattern = m_pattern
workflow = Workflow(self.dataset)
workflow.detect_workflow(25)
def test_workflow_wrong_first_log(self):
read_data = pickle.dumps({
'word2vec': {
"1": np.asarray([1] * 20),
"2": np.asarray([2] * 20),
"3": np.asarray([3] * 20),
"4": [4] * 20,
"5": [5] * 20,
"6": [6] * 20,
"7": [7] * 20
},
'counter_patterns': {
1: 100,
2: 100,
3: 100,
4: 100,
6: 1000,
5: 1000
},
"LSTM": {
3: self.model.state_dict()
},
"dict_patterns": {}
})
mockOpen = mock_open(read_data=read_data)
with patch('builtins.open', mockOpen):
dataset_local = Dataset(path_model="/",
path_data="/",
name_model="/")
dataset_local.load_files()
dataset_local.LSTM = self.list_model
dataset_local.list_logs = []
default_pattern_local = Pattern(0, [], [])
default_pattern_local.id = -1
m = Mock()
m.side_effect = [default_pattern_local] * 30
logflow.logsparser.Journal.Journal.find_pattern = m
for i in range(30):
log = Log("-1", index_line=i)
log.pattern = default_pattern_local
dataset_local.list_logs.append(log)
workflow = Workflow(dataset_local)
#with self.assertRaises(Exception):
tree = workflow.detect_workflow(10)
self.assertEqual(tree, "-1")
path_model="model/").start()
# Learn the correlations
size = 100000000
list_cardinalities = Dataset_learning(path_model="model/",
path_data="data/",
name_dataset="Test",
size=size).run()
worker = Worker(cardinalities_choosen=[4, 5, 6, 7],
list_cardinalities=list_cardinalities,
path_model="model/",
name_dataset="Test")
worker.train()
# Show the results
results = Results(path_model="model/", name_model="Test")
results.load_files()
results.compute_results(condition="Test")
results.print_results()
# Get the tree
dataset = Dataset_building(path_model="model/",
name_model="Test",
path_data="data/Windows/Windows.log",
index_line_max=30000,
parser_function=parser_function)
dataset.load_files()
dataset.load_logs()
workflow = Workflow(dataset)
workflow.get_tree(index_line=24712)
def test_workflow_working(self):
workflow = Workflow(self.dataset)
workflow.detect_workflow(25)
workflow.get_tree(25)
def test_create(self):
workflow = Workflow(self.dataset)
def test_workflow_after_last_line(self):
workflow = Workflow(self.dataset)
with self.assertRaises(Exception):
workflow.get_tree(40)