code: def fit_predict(self, data, labels, unkown=None):
          
          self.fit(data, labels)
          return self._predict_from_bmus(self._bmus, unkown)
docs: \
          Fit and classify data efficiently.
  
          :param data: sparse input matrix (ideal dtype is `numpy.float32`)
          :type data: :class:`scipy.sparse.csr_matrix`
          :param labels: the labels associated with data
          :type labels: iterable
          :param unkown: the label to attribute if no label is known
          :returns: the labels guessed for data
          :rtype: `numpy.array`