I am trying to animate a graph whose edges widths and color change over time. My code works, but it is extremely slow. I imagine there are more efficient implementations.

def minimal_graph(datas, pos):
    frames = len(datas[0])
    fig, axes = plt.subplots(1, 2)
    axes = axes.flatten()
    for j, dat in enumerate(datas):
        G = nx.from_numpy_matrix(dat[0])
        nx.draw(G, pos, ax=axes[j])
    def update(it, data, pos, ax):
        print(it)
        for i, dat in enumerate(data):
            # This is the problematic line, because I clear the axis hence
            # everything has to be drawn from scratch every time.
            ax[i].clear()
            G = nx.from_numpy_matrix(dat[it])
            edges, weights = zip(*nx.get_edge_attributes(G, 'weight').items())
            nx.draw(
                G,
                pos,
                node_color='#24FF00',
                edgelist=edges,
                edge_color=weights,
                width=weights,
                edge_vmin=-5,
                edge_vmax=5,
                ax=ax[i])
    ani = animation.FuncAnimation(fig, update, frames=frames, fargs=(
        datas, pos, axes), interval=100)
    ani.save('temp/graphs.mp4')
    plt.close()


dataset1 = []
dataset2 = []
for i in range(100):
    arr1 = np.random.rand(400, 400)
    arr2 = np.random.rand(400, 400)
    dataset1.append(arr1)
    dataset2.append(arr2)

datasets = [dataset1, dataset2]
G = nx.from_numpy_matrix(dataset1[0])
pos = nx.spring_layout(G)

minimal_graph(datasets, pos)

As pointed out in the code, the problem is that at every frame I redraw the graph from "scratch". When using animations in matplotlib, I usually try to create lines and use the function '''line.set_data()''', which I know is a lot faster. It's just that I don't know how to set that for a graph using networkx. I found