更新python igraph中的容量

Question

I'm currently reviewing a working system to identify areas that can be optimised. I've found that the loop below increases the run time by around 70%

for t in G.get_edgelist():
    eid = G.get_eid(*t)
    origin = G.vs[t[0]]['name']
    destin = G.vs[t[1]]['name']

    if fc.cpdict[origin]['node_type'] == 'dependency':
        cp_func[nodes.index(destin)] *= cp_func[nodes.index(origin)]

    cap = cp_func[nodes.index(origin)]
    G.es[eid]["capacity"] = cap

The system needs to update the capacity of the edges that have changed since the last iteration of the model time. In why-is-add-edge-function-so-slow-ompared-to-add-edges an answer states

The reason is that igraph uses an indexed edge list as its data structure in the C layer. The index makes it possible to query the neighbors of a specific vertex in constant time. This is good if your graph rarely changes, but it becomes a burden when the modification operations are far more frequent than the queries, since whenever you add or remove an edge, you have to update the index.

Is there a better way to do this update.

Answer 1

In case someone else is looking for help, or has a better solution. After reviewing the documentation I went with the following changes:

    def update_capacity(self, components, comp_sample_func):
      for comp_index, (comp_id, component) in enumerate(components.iteritems()):
        for dest_index, dest_comp_id in enumerate(component.destination_components.iterkeys()):
            if component.node_type == 'dependency':
                comp_sample_func[dest_index] *= comp_sample_func[comp_index]

            edge_id = self.comp_graph.get_eid(comp_id, dest_comp_id)
            self.comp_graph.es[edge_id]['capacity'] = comp_sample_func[comp_index]

I created the nodes to with the same order as my ordered dictionary and then retrieved the vertice with the indices. This gave a 10-20% improvement.