code: def _embedding_spectral(matrix, dimensions=3, unit_length=True,
                          affinity_matrix=None, sigma=1):
      
      if affinity_matrix is None:
          aff = rbf(matrix, sigma=sigma)
      else:
          aff = affinity_matrix
      coords = sklearn.manifold.spectral_embedding(aff, dimensions)
      return normalise_rows(coords) if unit_length else coords
docs: Private method to calculate Spectral embedding
      :param dimensions: (int)
      :return: coordinate matrix (np.array)