code: def __quadratic_forms_matrix_euclidean(h1, h2):
      r
      A = scipy.repeat(h2[:,scipy.newaxis], h1.size, 1) # repeat second array to form a matrix
      A = scipy.absolute(A - h1) # euclidean distances
      return 1 - (A / float(A.max()))
docs: r"""
      Compute the bin-similarity matrix for the quadratic form distance measure.
      The matric :math:`A` for two histograms :math:`H` and :math:`H'` of size :math:`m` and
      :math:`n` respectively is defined as
      
      .. math::
      
          A_{m,n} = 1 - \frac{d_2(H_m, {H'}_n)}{d_{max}}
      
      with
      
      .. math::
      
         d_{max} = \max_{m,n}d_2(H_m, {H'}_n)
      
      See also
      --------
      quadratic_forms