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"""
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(c) 2019 Data Maker, hiplab.mc.vanderbilt.edu
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version 1.0.0
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This package serves as a proxy to the overall usage of the framework.
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This package is designed to generate synthetic data from a dataset from an original dataset using deep learning techniques
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@TODO:
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- Make configurable GPU, EPOCHS
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"""
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import pandas as pd
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import numpy as np
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BOUNDS = ContinuousToDiscrete.bounds(X,BIN_SIZE)
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values = []
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_BINARY= ContinuousToDiscrete.binary(X,BIN_SIZE)
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# # print (BOUNDS)
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# values = []
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for row in _BINARY :
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# ubound = BOUNDS[row.index(1)]
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index = np.where(row == 1)[0][0]
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ubound = BOUNDS[ index ].right
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lbound = BOUNDS[ index ].left
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args['context'] = col
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BIN_SIZE = 4 if 'bin_size' not in args else int(args['bin_size'])
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