data_processing.py

# nbca/data_processing.py

import logging
import numpy as np

class DataProcessing:
    def __init__(self):
        """Initialize the Data Processing module."""
        logging.info("Data Processing module initialized.")

    def analyze_event(self, event):
        """
        Analyze a detected neutrino event.
        :param event: The neutrino event data to analyze.
        :return: Analysis results.
        """
        logging.info(f"Analyzing event: {event['event_id']}")
        energy = event['energy']
        direction = event['direction']
        
        # Perform analysis (e.g., classify event based on energy)
        classification = self.classify_event(energy)
        logging.info(f"Event classified as: {classification}")

        # Extract features
        features = self.extract_features(event)
        logging.info(f"Extracted features: {features}")

        return {
            "event_id": event['event_id'],
            "classification": classification,
            "features": features
        }

    def classify_event(self, energy):
        """
        Classify the neutrino event based on its energy.
        :param energy: The energy of the neutrino event.
        :return: Classification label.
        """
        if energy < 1e-4:
            return "Low Energy"
        elif energy < 1e-2:
            return "Medium Energy"
        else:
            return "High Energy"

    def extract_features(self, event):
        """
        Extract features from the neutrino event for further analysis.
        :param event: The neutrino event data.
        :return: Feature vector.
        """
        # Example feature extraction
        features = np.array([
            event['energy'],  # Energy of the event
            event['direction']['theta'],  # Polar angle
            event['direction']['phi']  # Azimuthal angle
        ])
        return features

    def format_data(self, processed_data):
        """
        Format the processed data for transmission or storage.
        :param processed_data: The processed data to format.
        :return: Formatted data as a dictionary.
        """
        formatted_data = {
            "event_id": processed_data['event_id'],
            "classification": processed_data['classification'],
            "features": processed_data['features'].tolist()  # Convert numpy array to list
        }
        logging.info(f"Formatted data for transmission: {formatted_data}")
        return formatted_data

    def save_to_database(self, formatted_data):
        """
        Save the formatted data to a database (simulated).
        :param formatted_data: The data to save.
        """
        # Simulate saving to a database
        logging.info(f"Saving data to database: {formatted_data}")
        # In a real implementation, this would involve database operations

    def process_event(self, event):
        """
        Process a neutrino event from detection to storage.
        :param event: The neutrino event data to process.
        """
        analyzed_data = self.analyze_event(event)
        formatted_data = self.format_data(analyzed_data)
        self.save_to_database(formatted_data)