def predict(self, X, batch_size=1, show_progressbar=False):
        """
        Predict the BMU for each input data.

        Parameters
        ----------
        X : numpy array.
            The input data.
        batch_size : int, optional, default 100
            The batch size to use in prediction. This may affect prediction
            in stateful, i.e. sequential SOMs.
        show_progressbar : bool
            Whether to show a progressbar during prediction.

        Returns
        -------
        predictions : numpy array
            An array containing the BMU for each input data point.

        """
        dist = self.transform(X, batch_size, show_progressbar)
        res = dist.__getattribute__(self.argfunc)(1)

        return res
def predict ( self , X , batch_size = 1 , show_progressbar = False ) : dist = self . transform ( X , batch_size , show_progressbar ) res = dist . __getattribute__ ( self . argfunc ) ( 1 ) return res
Predict the BMU for each input data.

        Parameters
        ----------
        X : numpy array.
            The input data.
        batch_size : int, optional, default 100
            The batch size to use in prediction. This may affect prediction
            in stateful, i.e. sequential SOMs.
        show_progressbar : bool
            Whether to show a progressbar during prediction.

        Returns
        -------
        predictions : numpy array
            An array containing the BMU for each input data point.