human
I wrote the below code

    (n_name, nodes) = n
    G = nx.Graph()
    G.add_nodes_from(nodes)
    if (weight is None):
        weight = {v: random.expovariate(1) for v in G}
    if (pos is None):
        pos = {v: [random.random() for i in range(dim)] for v in nodes}
    if (metric is None):
        metric = euclidean
    nx.set_node_attributes(G, weight, 'weight')
    nx.set_node_attributes(G, pos, 'pos')
    def should_join(pair):
        (u, v) = pair
        (u_pos, v_pos) = (pos[u], pos[v])
        (u_weight, v_weight) = (weight[u], weight[v])
        return ((theta * (metric(u_pos, v_pos) ** alpha)) <= (u_weight + v_weight))
    G.add_edges_from(filter(should_join, combinations(G, 2)))
    return G

What's a good function header?
assistant
#Here's a good function header.

@nodes_or_number(0)
def geographical_threshold_graph(n, theta, alpha=2, dim=2, pos=None, weight=None, metric=None):