def test_static_api():
host = '127.0.0.1'
user = '******'
password = '******'
algorithm = [
'iforest', 'ocsvm', 'lof', 'robustcovariance', 'cblof', 'knn', 'hbos',
'sod', 'pca', 'dagmm', 'autoencoder', 'lstm_ad', 'lstm_ed',
'staticautoencoder'
]
rng = np.random.RandomState(42)
np.random.seed(42)
conn, cursor = connect_server(host, user, password)
ground_truth_whole = insert_demo_data(conn,
cursor,
'db',
't',
ground_truth_flag=True)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time='2019-07-20 00:00:00',
end_time='2019-08-20 00:00:00',
time_serie=False,
ground_truth_flag=True)
for alg in algorithm:
clf = algorithm_selection(alg, random_state=rng, contamination=0.1)
print('Start processing:')
start_time = time.clock()
clf.fit(data)
prediction_result = clf.predict(data)
outlierness = clf.decision_function(data)
output_performance(alg, ground_truth, prediction_result,
time.clock() - start_time, outlierness)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time=None,
end_time=None,
time_serie=False,
ground_truth_flag=True)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time=None,
end_time=None,
time_serie=False,
ground_truth_flag=False)
conn.close()
def test_io_static():
host = '127.0.0.1'
user = '******'
password = '******'
alg = 'iforest'
rng = np.random.RandomState(42)
np.random.seed(42)
conn, cursor = connect_server(host, user, password)
ground_truth_whole = insert_demo_data(conn,
cursor,
'db',
't',
ground_truth_flag=True)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time='2019-07-20 00:00:00',
end_time='2019-08-20 00:00:00',
time_serie=False,
ground_truth_flag=True)
clf = algorithm_selection(alg, random_state=rng, contamination=0.1)
print('Start processing:')
start_time = time.clock()
clf.fit(data)
prediction_result = clf.predict(data)
outlierness = clf.decision_function(data)
output_performance(alg, ground_truth, prediction_result,
time.clock() - start_time, outlierness)
visualize_distribution_static(data, prediction_result, outlierness)
visualize_distribution(data, prediction_result, outlierness)
visualize_outlierscore(outlierness, prediction_result, contamination=0.1)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time=None,
end_time='2019-08-20 00:00:00',
time_serie=False,
ground_truth_flag=True)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time='2019-07-20 00:00:00',
end_time=None,
time_serie=False,
ground_truth_flag=True)
def test_timestamp_api():
host = '127.0.0.1'
user = '******'
password = '******'
algorithm = ['luminol']
rng = np.random.RandomState(42)
np.random.seed(42)
conn, cursor = connect_server(host, user, password)
ground_truth_whole = insert_demo_data(conn,
cursor,
'db',
't',
ground_truth_flag=True)
data, ground_truth = query_data(conn,
cursor,
'db',
't',
time_serie_name='ts',
ground_truth=ground_truth_whole,
start_time='2019-07-20 00:00:00',
end_time='2019-08-20 00:00:00',
time_serie=True,
ground_truth_flag=True)
for alg in algorithm:
clf = algorithm_selection(alg, random_state=rng, contamination=0.1)
print('Start processing:')
start_time = time.clock()
clf.fit(data)
prediction_result = clf.predict(data)
outlierness = clf.decision_function(data)
output_performance(alg, ground_truth, prediction_result,
time.clock() - start_time, outlierness)
conn.close()
#read data
print('Load dataset and table')
start_time = time.clock()
if args.ground_truth:
ground_truth_whole = insert_demo_data(conn, cursor, args.database,
args.table, args.ground_truth)
else:
insert_demo_data(conn, cursor, args.database, args.table,
args.ground_truth)
if args.ground_truth:
data, ground_truth = query_data(conn,
cursor,
args.database,
args.table,
args.start_time,
args.end_time,
args.time_serie_name,
ground_truth_whole,
time_serie=args.time_stamp,
ground_truth_flag=args.ground_truth)
else:
data = query_data(conn,
cursor,
args.database,
args.table,
args.start_time,
args.end_time,
args.time_serie_name,
time_serie=args.time_stamp,
ground_truth_flag=args.ground_truth)
