data-maker/data/maker/__init__.py

"""
(c) 2019 Data Maker, hiplab.mc.vanderbilt.edu
version 1.0.0

This package serves as a proxy to the overall usage of the framework.
This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques

@TODO:
    - Make configurable GPU, EPOCHS
"""
import pandas as pd
import numpy as np
from multiprocessing import Queue
        self.logger = None
            # logger = 
            _args = dict({'ndx':self.ndx,'module':self.name,'table':self.info['from'],'context':_context,'info':_label,**_args})
        # At this point we apply pre-processing of the data if there were ever a need for it
            _index = np.random.choice(np.arange(self._df[name].shape[0]),5,False)
        else:
        if _args['year'] in ['',None,np.nan] :
            return None
        year = int(_args['year'])
            #
        _xdf = pd.DataFrame()