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60 lines
1.5 KiB
60 lines
1.5 KiB
from analytic_types import ModelCache, TimeSeries |
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from analytic_types.segment import Segment |
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from typing import List, Optional, Tuple |
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import utils.meta |
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class DetectionResult: |
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def __init__( |
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self, |
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cache: Optional[ModelCache] = None, |
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segments: Optional[List[Segment]] = None, |
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last_detection_time: int = None, |
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time_step: int = None |
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): |
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if cache is None: |
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cache = {} |
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if segments is None: |
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segments = [] |
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self.cache = cache |
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self.segments = segments |
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self.last_detection_time = last_detection_time |
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self.time_step = time_step |
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# TODO: use @utils.meta.JSONClass (now it can't serialize list of objects) |
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def to_json(self): |
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return { |
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'cache': self.cache, |
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'segments': list(map(lambda segment: segment.to_json(), self.segments)), |
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'lastDetectionTime': self.last_detection_time, |
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'timeStep': self.time_step |
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} |
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@utils.meta.JSONClass |
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class ProcessingResult(): |
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def __init__( |
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self, |
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data: Optional[TimeSeries] = None |
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): |
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if data is None: |
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data = [] |
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self.data = data |
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@utils.meta.JSONClass |
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class AnomalyProcessingResult(): |
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def __init__( |
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self, |
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lower_bound: Optional[TimeSeries] = None, |
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upper_bound: Optional[TimeSeries] = None, |
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): |
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if lower_bound is None: |
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lower_bound = [] |
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self.lower_bound = lower_bound |
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if upper_bound is None: |
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upper_bound = [] |
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self.upper_bound = upper_bound
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