sklearn_utils/noise/noise_preprocessing.py
def transform(self, X):
        '''
        :X: numpy ndarray 
        '''
        noise = self._noise_func(*self._args, size=X.shape)
        results = X + noise
        self.relative_noise_size_ = self.relative_noise_size(X, results)
        return results
def transform(self, X):
        '''
        :X: numpy ndarray 
        '''
        noise = self._noise_func(*self._args, size=X.shape)
        results = X + noise
        self.relative_noise_size_ = self.relative_noise_size(X, results)
        return results
def transform ( self , X ) : noise = self . _noise_func ( * self . _args , size = X . shape ) results = X + noise self . relative_noise_size_ = self . relative_noise_size ( X , results ) return results
:X: numpy ndarray
: X : numpy ndarray