#NEWLINE# def inverse_transform( self , X ) : #NEWLINE# #INDENT# 'Scale back the data to the original representation\n\n        Parameters\n        ----------\n        X : {array-like, sparse matrix}\n            The data that should be transformed back.\n        ' #NEWLINE# check_is_fitted ( self , 'scale_' ) #NEWLINE# X = check_array ( self , accept_sparse = ( 'csr' , 'csc' ) , copy = self . copy , ensure_2d = False , estimator = self , dtype = FLOAT_DTYPES ) #NEWLINE# if ( X . ndim == 1 ) : #NEWLINE# #INDENT# warnings . warn ( DEPRECATION_MSG_1D , DeprecationWarning ) #NEWLINE# #UNINDENT# if sparse . issparse ( X ) : #NEWLINE# #INDENT# inplace_column_scale ( X , self . scale_ ) #NEWLINE# #UNINDENT# else : #NEWLINE# #INDENT# X *= self . scale_ #NEWLINE# #UNINDENT# return X