""" Project: enhanced_cs.RO_2507.22546v1_Explainable_Deep_Anomaly_Detection_with_Sequential Type: computer_vision Description: Enhanced AI project based on cs.RO_2507.22546v1_Explainable-Deep-Anomaly-Detection-with-Sequential with content analysis. """

import logging import os import sys import yaml from typing import Dict, List, Optional from pathlib import Path

Set up logging

logging.basicConfig( level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s", handlers=[ logging.FileHandler("project.log"), logging.StreamHandler(sys.stdout), ], )

Define constants

PROJECT_NAME = "Explainable Deep Anomaly Detection" PROJECT_VERSION = "1.0" PROJECT_AUTHOR = "Your Name"

Define configuration

class Config: def init(self, config_file: str): self.config_file = config_file self.config = self.load_config()

def load_config(self) -> Dict:
    with open(self.config_file, "r") as f:
        config = yaml.safe_load(f)
    return config

def get(self, key: str) -> Optional[str]:
    return self.config.get(key)

def set(self, key: str, value: str):
    self.config[key] = value
    with open(self.config_file, "w") as f:
        yaml.dump(self.config, f)

Define exception classes

class ProjectError(Exception): pass

class ConfigError(ProjectError): pass

Define data structures/models

class Anomaly: def init(self, id: int, timestamp: float, value: float): self.id = id self.timestamp = timestamp self.value = value

class Dataset: def init(self, anomalies: List[Anomaly]): self.anomalies = anomalies

Define validation functions

def validate_config(config: Dict) -> None: required_keys = ["anomaly_threshold", "velocity_threshold"] for key in required_keys: if key not in config: raise ConfigError(f"Missing required key: {key}")

Define utility methods

def load_dataset(config: Config) -> Dataset: anomalies = [] for i in range(100): # Replace with actual dataset loading anomaly = Anomaly(i, 0.0, 0.0) anomalies.append(anomaly) return Dataset(anomalies)

def detect_anomalies(dataset: Dataset, config: Config) -> List[Anomaly]: anomalies = [] for anomaly in dataset.anomalies: if anomaly.value > config.get("anomaly_threshold"): anomalies.append(anomaly) return anomalies

def calculate_velocity(anomalies: List[Anomaly]) -> float: velocity = 0.0 for i in range(1, len(anomalies)): velocity += anomalies[i].value - anomalies[i-1].value return velocity / len(anomalies)

Define main class

class Project: def init(self, config_file: str): self.config_file = config_file self.config = Config(self.config_file) self.dataset = load_dataset(self.config) self.anomalies = detect_anomalies(self.dataset, self.config)

def run(self) -> None:
    logging.info("Running project...")
    velocity = calculate_velocity(self.anomalies)
    logging.info(f"Velocity: {velocity}")
    if velocity > self.config.get("velocity_threshold"):
        logging.warning("Anomaly detected!")
    else:
        logging.info("No anomaly detected.")

Define integration interfaces

class IntegrationInterface: def init(self, project: Project): self.project = project

def run(self) -> None:
    self.project.run()

Define constants and configuration

PROJECT_CONFIG_FILE = "project.yaml"

Define main function

def main() -> None: try: project = Project(PROJECT_CONFIG_FILE) project.run() except ProjectError as e: logging.error(f"Project error: {e}") sys.exit(1) except ConfigError as e: logging.error(f"Config error: {e}") sys.exit(1)

if name == "main": main()