docs: def histogram(self, bmus=None):
          """\
          Return a 2D histogram of bmus.
  
          :param bmus: the best-match units indexes for underlying data.
          :type bmus: :class:`numpy.ndarray`
          :returns: the computed 2D histogram of bmus.
          :rtype: :class:`numpy.ndarray`
          """
          if bmus is None:
              assert self._bmus is not None, 'not trained'
              bmus = self._bmus
          arr = np.zeros((self._som.nrows, self._som.ncols))
          for i,j in bmus:
              arr[i,j] += 1
          return arr