gaitsetpy.dataset.arduous

  1'''
  2Arduous Dataset Loader.
  3Maintainer: @aharshit123456
  4
  5This file contains the Arduous dataset loader class that inherits from BaseDatasetLoader.
  6'''
  7
  8import os
  9import pandas as pd
 10import numpy as np
 11from typing import List, Dict, Tuple
 12from ..core.base_classes import BaseDatasetLoader
 13from .utils import download_dataset, extract_dataset, sliding_window
 14
 15
 16class ArduousLoader(BaseDatasetLoader):
 17    """
 18    Arduous dataset loader class.
 19    
 20    This class handles loading and processing of the Arduous dataset for gait analysis.
 21    """
 22    
 23    def __init__(self):
 24        super().__init__(
 25            name="arduous",
 26            description="Arduous Dataset - Contains multi-sensor wearable data for daily activity recognition"
 27        )
 28        self.metadata = {
 29            'sensors': ['accelerometer', 'gyroscope', 'magnetometer'],
 30            'components': ['x', 'y', 'z'],
 31            'sampling_frequency': 50,  # Typical for Arduous
 32            'activities': ['walking', 'running', 'sitting', 'standing', 'lying']
 33        }
 34    
 35    def load_data(self, data_dir: str, **kwargs) -> Tuple[List[pd.DataFrame], List[str]]:
 36        """
 37        Load Arduous dataset from the specified directory.
 38        
 39        Args:
 40            data_dir: Directory to store/find the dataset
 41            **kwargs: Additional arguments (unused for Arduous)
 42            
 43        Returns:
 44            Tuple of (data_list, names_list)
 45        """
 46        # TODO: Implement Arduous data loading
 47        # This is a placeholder implementation
 48        print("Arduous data loading is not yet implemented")
 49        return [], []
 50    
 51    def create_sliding_windows(self, data: List[pd.DataFrame], names: List[str], 
 52                             window_size: int = 192, step_size: int = 32) -> List[Dict]:
 53        """
 54        Create sliding windows from the Arduous dataset.
 55        
 56        Args:
 57            data: List of DataFrames containing Arduous data
 58            names: List of names corresponding to the data
 59            window_size: Size of the sliding window (default: 192)
 60            step_size: Step size for the sliding window (default: 32)
 61            
 62        Returns:
 63            List of dictionaries containing sliding windows for each DataFrame
 64        """
 65        # TODO: Implement Arduous sliding window creation
 66        # This is a placeholder implementation
 67        print("Arduous sliding window creation is not yet implemented")
 68        return []
 69    
 70    def get_supported_formats(self) -> List[str]:
 71        """
 72        Get list of supported file formats for Arduous dataset.
 73        
 74        Returns:
 75            List of supported file extensions
 76        """
 77        return ['.csv', '.txt']
 78    
 79    def get_sensor_info(self) -> Dict[str, List[str]]:
 80        """
 81        Get information about sensors in the dataset.
 82        
 83        Returns:
 84            Dictionary containing sensor information
 85        """
 86        return {
 87            'sensors': self.metadata['sensors'],
 88            'components': self.metadata['components'],
 89            'sampling_frequency': self.metadata['sampling_frequency']
 90        }
 91    
 92    def get_activity_info(self) -> List[str]:
 93        """
 94        Get information about activities in the dataset.
 95        
 96        Returns:
 97            List of activity types
 98        """
 99        return self.metadata['activities']
100
101
102# Legacy function wrapper for backward compatibility
103def load_arduous_data():
104    """
105    Legacy function for loading Arduous data.
106    
107    Returns:
108        Tuple of (data_list, names_list)
109    """
110    loader = ArduousLoader()
111    return loader.load_data("")