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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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@staticmethod
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def continuous(X,BIN_SIZE=4) :
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"""
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This function will approximate a binary vector given boundary information
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:X binary matrix
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:BIN_SIZE
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"""
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BOUNDS = ContinuousToDiscrete.bounds(X,BIN_SIZE)
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values = []
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"""
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# df.to_csv('tmp-'+args['logs'].replace('/','_')+'-'+col+'.csv',index=False)
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def get(**args):
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# # We should create the bins for the values we are observing here
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