human
Solve the following python programming problem given the following code:
@ property 
def metric(self) : 
    'Compute metric distortion of the flatmap.

        Metric distortion is calculated as the difference in squared distance
        from each vertex to its neighbors between the flatmap and the reference.

        Positive values of metric distortion mean that vertices are farther from
        their neighbors in the flatmap than in the reference surface (expansion),
        etc.

        See: Fishl, Sereno, and Dale, 1999.

        Returns
        -------
        vertdists : 1D ndarray, shape (total_verts,)
            Metric distortion at each vertex.
        ' 
    import networkx as nx 
    def iter_surfedges(tris) : 
        for (a, b, c) in tris : 
            (yield (a, b)) 
            (yield (b, c)) 
            (yield (a, c)) 
def make_surface_graph(tris) : 
        graph = nx.Graph () 
        graph.add_edges_from (iter_surfedges (tris)) 
        return graph 
G = make_surface_graph (self.polys) 
    selverts = np.unique (self.polys.ravel ()) 
    ref_dists = [np.sqrt (((self.ref [G.neighbors (ii)] - self.ref [ii]) ** 2).sum (1)) for ii in selverts] 
    flat_dists = [np.sqrt (((self.flat [G.neighbors (ii)] - self.flat [ii]) ** 2).sum (1)) for ii in selverts] 
    msdists = np.array ([(f - r).mean () for (r, f) in zip (ref_dists, flat_dists)]) 
    alldists = np.zeros ((len (G.ref),)) 
    alldists [selverts] = msdists 
    return alldists 

    
    

    Fix the buggy line: alldists = np.zeros ((len (G.ref),))
assistant
#Here is Python program to fix the buggy line: alldists = np.

alldists = np.zeros ((len (self.ref),))