/dports/math/py-luminol/luminol-0.3.1/src/luminol/tests/ |
H A D | test_anomaly_detector.py | 57 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 D | test_anomaly_detector.py | 39 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__.py | 23 def __init__(self, class_name, time_series, baseline_time_series=None): argument 33 self.baseline_time_series = baseline_time_series
|
H A D | default_detector.py | 25 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 D | diff_percent_threshold.py | 26 …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 D | absolute_threshold.py | 25 baseline_time_series=None): argument 35 …super(AbsoluteThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
|
H A D | sign_test.py | 40 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 D | derivative_detector.py | 27 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 D | exp_avg_detector.py | 27 …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 D | bitmap_detector.py | 31 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__.py | 23 def __init__(self, class_name, time_series, baseline_time_series=None): argument 33 self.baseline_time_series = baseline_time_series
|
H A D | default_detector.py | 25 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 D | diff_percent_threshold.py | 26 …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 D | absolute_threshold.py | 25 baseline_time_series=None): argument 35 …super(AbsoluteThreshold, self).__init__(self.__class__.__name__, time_series, baseline_time_series)
|
H A D | derivative_detector.py | 27 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 D | exp_avg_detector.py | 27 …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 D | bitmap_detector.py | 31 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 D | anomaly_detector.py | 27 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 D | anomaly_detector.py | 27 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 D | README.md | 97 __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 D | README.md | 97 __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.
|