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Searched refs:baseline_time_series (Results 1 – 21 of 21) sorted by relevance

/dports/math/py-luminol/luminol-0.3.1/src/luminol/tests/
H A Dtest_anomaly_detector.py57 lambda: AnomalyDetector(self.s1, baseline_time_series=self.s2,
70 lambda: AnomalyDetector(self.s1, baseline_time_series=self.s2,
79 lambda: AnomalyDetector(self.s1, baseline_time_series=self.s2,
86 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
95 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
118 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
135 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
162 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
184 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
194 detector = AnomalyDetector(ts, baseline_time_series=bs, algorithm_name='sign_test',
[all …]
/dports/benchmarks/py-naarad/naarad-1.0.15/lib/luminol/src/luminol/tests/
H A Dtest_anomaly_detector.py39 detector = AnomalyDetector(self.s1, baseline_time_series=self.s2, algorithm_class=CustomAlgo,
49 …detector = AnomalyDetector(self.s1, baseline_time_series=self.s2, algorithm_name='diff_percent_thr…
55 lambda: AnomalyDetector(self.s1, baseline_time_series=self.s2,
140 …def __init__(self, time_series, baseline_time_series, percent_threshold_upper=None, percent_thresh… argument
149 super(CustomAlgo, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
162 baseline_value = self.baseline_time_series[i]
/dports/math/py-luminol/luminol-0.3.1/src/luminol/algorithms/anomaly_detector_algorithms/
H A D__init__.py23 def __init__(self, class_name, time_series, baseline_time_series=None): argument
33 self.baseline_time_series = baseline_time_series
H A Ddefault_detector.py25 def __init__(self, time_series, baseline_time_series=None): argument
31 self.exp_avg_detector = ExpAvgDetector(time_series, baseline_time_series)
32 self.derivative_detector = DerivativeDetector(time_series, baseline_time_series)
H A Ddiff_percent_threshold.py26 …def __init__(self, time_series, baseline_time_series, percent_threshold_upper=None, percent_thresh… argument
35 …er(DiffPercentThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
50 baseline_value = self.baseline_time_series[i]
H A Dabsolute_threshold.py25 baseline_time_series=None): argument
35 …super(AbsoluteThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
H A Dsign_test.py40 def __init__(self, time_series, baseline_time_series, argument
61 super(SignTest, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
96 self.scale * np.array(self.baseline_time_series.values),
H A Dderivative_detector.py27 def __init__(self, time_series, baseline_time_series=None, smoothing_factor=None): argument
34 …uper(DerivativeDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
H A Dexp_avg_detector.py27 …def __init__(self, time_series, baseline_time_series=None, smoothing_factor=None, use_lag_window=F… argument
35 super(ExpAvgDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
H A Dbitmap_detector.py31 def __init__(self, time_series, baseline_time_series=None, precision=None, lag_window_size=None, argument
42 super(BitmapDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
/dports/benchmarks/py-naarad/naarad-1.0.15/lib/luminol/src/luminol/algorithms/anomaly_detector_algorithms/
H A D__init__.py23 def __init__(self, class_name, time_series, baseline_time_series=None): argument
33 self.baseline_time_series = baseline_time_series
H A Ddefault_detector.py25 def __init__(self, time_series, baseline_time_series=None): argument
31 self.exp_avg_detector = ExpAvgDetector(time_series, baseline_time_series)
32 self.derivative_detector = DerivativeDetector(time_series, baseline_time_series)
H A Ddiff_percent_threshold.py26 …def __init__(self, time_series, baseline_time_series, percent_threshold_upper=None, percent_thresh… argument
35 …er(DiffPercentThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
50 baseline_value = self.baseline_time_series[i]
H A Dabsolute_threshold.py25 baseline_time_series=None): argument
35 …super(AbsoluteThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
H A Dderivative_detector.py27 def __init__(self, time_series, baseline_time_series=None, smoothing_factor=None): argument
34 …uper(DerivativeDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
H A Dexp_avg_detector.py27 …def __init__(self, time_series, baseline_time_series=None, smoothing_factor=None, use_lag_window=F… argument
35 super(ExpAvgDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
H A Dbitmap_detector.py31 def __init__(self, time_series, baseline_time_series=None, precision=None, lag_window_size=None, argument
42 super(BitmapDetector, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
/dports/math/py-luminol/luminol-0.3.1/src/luminol/
H A Danomaly_detector.py27 def __init__(self, time_series, baseline_time_series=None, score_only=False, score_threshold=None, argument
45 self.baseline_time_series = self._load(baseline_time_series)
55 …rithm_params = {'time_series': self.time_series, 'baseline_time_series': self.baseline_time_series}
/dports/benchmarks/py-naarad/naarad-1.0.15/lib/luminol/src/luminol/
H A Danomaly_detector.py27 def __init__(self, time_series, baseline_time_series=None, score_only=False, score_threshold=None, argument
45 self.baseline_time_series = self._load(baseline_time_series)
55 …rithm_params = {'time_series': self.time_series, 'baseline_time_series': self.baseline_time_series}
/dports/math/py-luminol/luminol-0.3.1/
H A DREADME.md97 __init__(self, time_series, baseline_time_series=None, score_only=False, score_threshold=None,
108 * `baseline_time_series`: an optional baseline time series of one the types mentioned above.
/dports/benchmarks/py-naarad/naarad-1.0.15/lib/luminol/
H A DREADME.md97 __init__(self, time_series, baseline_time_series=None, score_only=False, score_threshold=None,
108 * `baseline_time_series`: an optional baseline time series of one the types mentioned above.