45 lines
1.5 KiB
Python
45 lines
1.5 KiB
Python
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import json
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import os
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import re
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from pydantic import BaseModel, Field
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from typing import List, Dict
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import requests
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import numpy as np
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from loguru import logger
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from .base_tool import BaseToolModel
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class KSigmaDetector(BaseToolModel):
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"""
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Tips:
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default control Required, e.g. key1 is not Required/key2 is Required
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"""
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name: str = "KSigmaDetector"
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description: str = "Anomaly detection using K-Sigma method"
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class ToolInputArgs(BaseModel):
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"""Input for KSigmaDetector."""
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data: List[float] = Field(..., description="List of data points")
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detect_window: int = Field(default=5, description="The size of the detect window for detecting anomalies")
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abnormal_window: int = Field(default=3, description="The threshold for the number of abnormal points required to classify the data as abnormal")
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k: float = Field(default=3.0, description="the coef of k-sigma")
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class ToolOutputArgs(BaseModel):
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"""Output for KSigmaDetector."""
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is_abnormal: bool = Field(..., description="Indicates whether the input data is abnormal or not")
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@staticmethod
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def run(data, detect_window=5, abnormal_window=3, k=3.0):
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refer_data = np.array(data[-detect_window:])
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detect_data = np.array(data[:-detect_window])
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mean = np.mean(refer_data)
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std = np.std(refer_data)
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is_abnormal = np.sum(np.abs(detect_data - mean) > k * std) >= abnormal_window
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return {"is_abnormal": is_abnormal}
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