#NEWLINE# def transform_targets_exp( self ) : #NEWLINE# #INDENT# '\n        Apply exp transformation (inverse of natural log transformation) to all targets (both predictions and true values)\n        ' #NEWLINE# for target in self . targets : #NEWLINE# #INDENT# if ( 'df_true' in dir ( self ) ) : #NEWLINE# #INDENT# self . df_true [ target ] = ( np . exp ( self . df_true [ target ] ) - 1 ) #NEWLINE# #UNINDENT# if ( 'df_true_segment' in dir ( i ) ) : #NEWLINE# #INDENT# self . df_true_segment [ target ] = ( np . exp ( self . df_true_segment [ target ] ) - 1 ) #NEWLINE# #UNINDENT# if ( 'df_ensemble' in dir ( self ) ) : #NEWLINE# #INDENT# self . df_ensemble [ target ] = ( np . exp ( self . df_ensemble [ target ] ) - 1 ) #NEWLINE# #UNINDENT# if ( 'df_ensemble_segment' in dir ( self ) ) : #NEWLINE# #INDENT# self . df_ensemble_segment [ target ] = ( np . exp ( self . df_ensemble_segment [ target ] ) - 1 ) #NEWLINE# #UNINDENT# for i in range ( len ( self . sub_models ) ) : #NEWLINE# #INDENT# self . sub_models [ i ] [ target ] = ( np . exp ( self . sub_models [ i ] [ target ] ) - 1 ) #NEWLINE# #UNINDENT# for i in range ( len ( self . sub_models_segment ) ) : #NEWLINE# #INDENT# self . sub_models_segment [ i ] [ target ] = ( np . exp ( self . sub_models_segment [ i ] [ target ] ) - 1 )