def test():
setup_logging()
logger = logging.getLogger(__name__)
logger.info('first log message')
import os
import logging
import functools
import json
from logging_setup import setup_logging
setup_logging()
from pika_client.environment_variables import EnvironmentVariable
from pika_client.base import Connector
from pika_client.consumers import BasePubSubConsumer
LOGGER = logging.getLogger(__name__)
FROM_EMAIL = os.environ.get('FROM_EMAIL', '*****@*****.**')
class EmailConsumer(BasePubSubConsumer):
def __init__(
self,
service,
connector,
app_id='EMAIL_SERVICE',
queue='emails',
durable=False,
exchange='notifications_x',
exchange_type='topic',
routing_key='notifications.email'):
super().__init__(
connector,
app_id=app_id,
queue=queue,
durable=durable,
def test():
setup_logging()
logger = logging.getLogger(__name__)
logger.info('first log message')
beam_tx = alib.e3d_array_beam_stage1_dense_interp(az0=0,
el0=90.0,
I_0=10**4.2)
beam_rx = alib.e3d_array_beam_interp(az0=0, el0=90.0, I_0=10**4.5)
radar.set_beam(beam_tx, 'TX')
radar.set_beam(beam_rx, 'RX')
#plot_scan_for_object(obj, radar, 0.0, 1.5*24.0*3600.0)
#radar.set_scan(rs2)
#plot_scan_for_object(obj, radar, 0.0, 12.0*3600.0)
#exit()
logger = logging_setup.setup_logging(
term_level=logging.DEBUG,
logfile=False,
)
det_times = get_detections(obj,
radar,
0.0,
1.0 * 24.0 * 3600.0,
logger=None)
#print(det_times)
total_dets = len(det_times[0]["snr"])
print('total_dets: {}'.format(total_dets))
if total_dets > 0:
max_snr = n.max(det_times[0]["snr"])
"""
results = {}
for report in reports:
if report in reports_train:
res = 'train'
else:
prediction = predictions[reports_test.index(report)]
res = '{} {}'.format(
'true' if prediction == report.category else 'false',
'positive' if prediction == CATEGORY_MALICIOUS else 'negative'
)
results[report.name] = res
with open(os.path.join(log_dir, 'results.json'), 'w') as f:
json.dump(results, f, indent=4)
joblib.dump(clf, os.path.join(log_dir, 'clf.pkl'))
joblib.dump(ml.vec, os.path.join(log_dir, 'vec.pkl'))
joblib.dump(ml.imp, os.path.join(log_dir, 'imp.pkl'))
#joblib.dump(ml.scaler, os.path.join(log_dir, 'scaler.pkl'))
"""
# Precision = (# correctly predicted pos) / (# predicted pos), recall = (# correctly predicted pos) / (# actual positive)
# logger.info(str(classification_report(y_test, predictions, target_names=['benign', 'malware'])))
if __name__ == '__main__':
from logging_setup import setup_logging
log_dir = setup_logging(from_file=__file__)
main()
def test_log():
setup_logging()
logger = logging.getLogger(__name__)
logger.info('Hello message')