code: def inspect_node_neighborhood(nlinks, msinds, node_msindex):
      
      # seed_indexes = np.nonzero(node_seed)
      # selected_inds = msinds[seed_indexes]
      # node_msindex = selected_inds[0]
  
      node_neighbor_edges = get_neighborhood_edes(nlinks, node_msindex)
  
      node_neighbor_seeds = np.zeros_like(msinds, dtype=np.int8)
      for neighboor_ind in np.unique(node_neighbor_edges[:, :2].ravel()):
          node_neighbor_ind = np.where(msinds == neighboor_ind)
          node_neighbor_seeds[node_neighbor_ind] = 2
  
      node_neighbor_seeds[np.where(msinds == node_msindex)] = 1
  
      # node_coordinates = np.unravel_index(selected_voxel_ind, msinds.shape)
      # node_neighbor_coordinates = np.unravel_index(np.unique(node_neighbor_edges[:, :2].ravel()), msinds.shape)
      return node_neighbor_edges, node_neighbor_seeds
docs: Get information about one node in graph
  
      :param nlinks: neighboorhood edges
      :param msinds: indexes in 3d image
      :param node_msindex: int, multiscale index of selected voxel
      :return: node_neighboor_edges_and_weights, node_neighboor_seeds