Source code for cosinorage.datahandlers.datahandler

###########################################################################
# Copyright (C) 2025 ETH Zurich
# CosinorAge: Prediction of biological age based on accelerometer data
# using the CosinorAge method proposed by Shim, Fleisch and Barata
# (https://www.nature.com/articles/s41746-024-01111-x)
#
# Authors: Jacob Leo Oskar Hunecke
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#         http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
##########################################################################


import time


def clock(func):
    """
    A decorator that prints the execution time of the decorated function.
    Only prints when verbose=True is passed to the decorated function.

    Parameters
    ----------
    func : function
        The function to be decorated.

    Returns
    -------
    function
        The decorated function.
    """

    def inner(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        
        # Check if verbose=True was passed to the function
        verbose = kwargs.get('verbose', False)
        if verbose:
            print(f"{func.__name__} executed in {end - start:.2f} seconds")
        
        return result

    return inner


################################## !!!! ##################################
# whenever you implement a new datahandler for a new datasource, check
# the documentation of the source, e.g., the smartwatch, to make sure
# what units the data is in and scale accordingly.
################################## !!!! ##################################


[docs] class DataHandler: """ A base class for data handlers that process and store ENMO data at the minute level. This class provides a common interface for data handlers with methods to load data, retrieve processed ENMO values, and save data. The `load_data` and `save_data` methods are intended to be overridden by subclasses. Attributes ---------- raw_data : pd.DataFrame or None Raw accelerometer data loaded from the source. sf_data : pd.DataFrame or None Filtered and processed accelerometer data. ml_data : pd.DataFrame or None Minute-level ENMO data calculated from processed data. meta_dict : dict Dictionary storing metadata about the data processing. """
[docs] def __init__(self): """ Initializes an empty DataHandler instance with an empty DataFrame for storing minute-level ENMO values. Notes ----- This is a base class constructor. Subclasses should override this method to accept specific parameters for their data sources. """ self.raw_data = None self.sf_data = None self.ml_data = None self.meta_dict = {}
def __load_data(self, verbose: bool = False): raise NotImplementedError( "The load_data method should be implemented by subclasses" )
[docs] def save_data(self, output_path: str): """ Save minute-level ENMO data to a specified output path. This method is intended to be implemented by subclasses, specifying the format and structure for saving data. Parameters ---------- output_path : str The file path where the minute-level ENMO data will be saved. """ if self.ml_data is None: raise ValueError( "Data has not been loaded. Please call `load_data()` first." ) self.ml_data.to_csv(output_path, index=False)
[docs] def get_raw_data(self): """ Retrieve the raw data. Returns ------- pd.DataFrame A DataFrame containing the raw data. """ return self.raw_data
[docs] def get_sf_data(self): """ Retrieve the filtered data. Returns ------- pd.DataFrame A DataFrame containing the filtered data. """ try: return self.sf_data except: raise ValueError( "No sf_data available." )
[docs] def get_ml_data(self): """ Retrieve the minute-level ENMO values. Returns ------- pd.DataFrame A DataFrame containing the minute-level ENMO values. """ if self.ml_data is None: raise ValueError( "Data has not been loaded. Please call `load_data()` first." ) return self.ml_data
[docs] def get_meta_data(self): """ Retrieve the metadata. Returns ------- dict A dictionary containing the metadata. """ return self.meta_dict