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54 lines
1.3 KiB
Python
54 lines
1.3 KiB
Python
from utils import transport
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from utils.ml import ML, AnomalyDetection
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import unittest
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import json
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import os
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path = os.environ['MONITOR_CONFIG_PATH']
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f = open(path)
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CONFIG = json.loads( f.read())
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f.close()
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factory = transport.DataSourceFactory()
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class TestML(unittest.TestCase):
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def setUp(self):
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ref = CONFIG['store']['class']['read']
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p = CONFIG['store']['args']
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p['qid'] = ['apps']
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self.greader = factory.instance(type=ref,args=p)
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def test_has_date(self):
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r = self.greader.read()
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self.assertTrue(r)
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def test_Filter(self):
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r = self.greader.read()
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r = r['apps']
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x = ML.Filter('label','Google Chrome',r)
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for row in x:
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self.assertTrue(row['label'] == 'Google Chrome')
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def test_Extract(self):
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r = self.greader.read()
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r = r['apps']
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x = ML.Filter('label','Google Chrome',r)
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x_ = ML.Extract(['cpu_usage','memory_usage'], x)
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self.assertTrue (len (x) == len(x_))
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pass
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def test_Learn(self):
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ref = CONFIG['store']['class']['read']
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p = CONFIG['store']['args']
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greader = factory.instance(type=ref,args=p)
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data = greader.read()
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data = data['apps']
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lhandler = AnomalyDetection()
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features = CONFIG['learner']['anomalies']['features']
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label = CONFIG['learner']['anomalies']['label']
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lhandler.learn(data,'label','Google Chrome',features,label)
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if __name__ == '__main__' :
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unittest.main() |