human
Solve the following python programming problem given the following code:
def _fit_best_piecewise(self, vectors, n_best, n_clusters) : 
    'Find the ``n_best`` vectors that are best approximated by piecewise
        constant vectors.

        The piecewise vectors are found by k-means.
the best is chosen
        according to Euclidean distance.

        ' 
    def make_piecewise(v) : 
        (centroid, labels) = self._k_means (v.reshape ((- 1), 1), n_clusters) 
        return centroid [labels].ravel () 
piecewise_vectors = np.apply_along_axis (make_piecewise, axis = 1, arr = vectors) 
    dists = np.apply_along_axis (norm, axis = 1, arr = (vectors - result)) 
    result = vectors [np.argsort (dists) [: n_best]] 
    return result 

    
    

    Fix the buggy line: dists = np.apply_along_axis (norm, axis = 1, arr = (vectors - result))
assistant
#Here is Python code to find the ``n_best`` vectors that are best approximated by piecewise
.

dists = np.apply_along_axis (norm, axis = 1, arr = (vectors - piecewise_vectors))