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https://github.com/blakeblackshear/frigate.git
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9e825811f2
* initial event search api implementation * fix lint * fix tests * move chromadb imports and pysqlite hotswap to fix tests * remove unused import * switch default limit to 50 * fix events accidently pulling inside chroma results loop
48 lines
1.1 KiB
Python
48 lines
1.1 KiB
Python
"""Z-score normalization for search distance."""
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import math
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class ZScoreNormalization:
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"""Running Z-score normalization for search distance."""
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def __init__(self):
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self.n = 0
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self.mean = 0
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self.m2 = 0
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@property
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def variance(self):
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return self.m2 / (self.n - 1) if self.n > 1 else 0.0
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@property
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def stddev(self):
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return math.sqrt(self.variance)
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def normalize(self, distances: list[float]):
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self._update(distances)
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if self.stddev == 0:
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return distances
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return [(x - self.mean) / self.stddev for x in distances]
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def _update(self, distances: list[float]):
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for x in distances:
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self.n += 1
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delta = x - self.mean
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self.mean += delta / self.n
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delta2 = x - self.mean
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self.m2 += delta * delta2
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def to_dict(self):
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return {
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"n": self.n,
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"mean": self.mean,
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"m2": self.m2,
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}
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def from_dict(self, data: dict):
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self.n = data["n"]
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self.mean = data["mean"]
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self.m2 = data["m2"]
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return self
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