def featRand( dData, b_human=False ):
    '''
    @summary: Random feature - used for robustness testing
    @param dData: Dictionary of data to use
    @param b_human: if true return dataframe to plot
    @return: DataFrame array containing values
    '''
    
    dfPrice = dData['close']
    
    #''' Feature DataFrame will be 1:1, we can use the price as a template '''
    dfRet = pand.DataFrame( index=dfPrice.index, columns=dfPrice.columns, 
                            data=np.random.randn(*dfPrice.shape) )
    
    if b_human:
        for sym in dData['close']:
            x=1000/dData['close'][sym][0]
            dData['close'][sym]=dData['close'][sym]*x
        return dData['close']
    return dfRet
dataset/ETHPy150Open QuantSoftware/QuantSoftwareToolkit/QSTK/qstkfeat/features.py/featRand/original