Figure 7.2 
-------------

:download:`Downloadable Source Code <fig7p2.py>` 

.. image:: fig7p2.png

::
    
    import networkx as nx
    import EoN
    from collections import defaultdict
    import matplotlib.pyplot as plt
    import scipy
    import random
    
    tau = 1.
    gamma = 1.
    N=10**5
    colors = ['#5AB3E6','#FF2000','#009A80','#E69A00', '#CD9AB3', '#0073B3','#F0E442']
    
    print('setting up')
    G = nx.configuration_model([4]*N)
    
    chosen = random.sample(range(N),int(0.01*N)) 
                                
    initial_infecteds = set()
    
    for node in chosen:
        for nbr in G.neighbors(node):
            initial_infecteds.add(nbr)
    
    print('simulating')
    t, S, I, R = EoN.fast_SIR(G, tau, gamma, initial_infecteds = initial_infecteds)
    report_times = scipy.linspace(0,10,101)
    
    S, I, R = EoN.subsample(report_times, t, S, I, R)
    
    plt.plot(report_times, S, color =colors[1], label = 'simulation')
    plt.plot(report_times, I, color = colors[1])
    plt.plot(report_times, R, color = colors[1])
    
    print('doing ODE models')
    t, S, I, R = EoN.SIR_effective_degree_from_graph(G, tau, gamma, initial_infecteds=initial_infecteds, tmax = 10, tcount = 51)
    plt.plot(t,S, color = colors[2], dashes = [6,6], label = 'effective degree')
    plt.plot(t,I, color = colors[2], dashes = [6,6])
    plt.plot(t,R, color = colors[2], dashes = [6,6])
    
    t, S, I, R = EoN.SIR_heterogeneous_pairwise_from_graph(G, tau, gamma, initial_infecteds=initial_infecteds, tmax = 10, tcount = 51)
    plt.plot(t, S, color = colors[3],  dashes = [3,2,1,2], linewidth=3, label = 'pairwise')
    plt.plot(t, I, color = colors[3],  dashes = [3,2,1,2], linewidth=3)
    plt.plot(t, R, color = colors[3],  dashes = [3,2,1,2], linewidth=3)  #, dashes = [6,3,2,3]
    
    
    t, S, I, R = EoN.EBCM_from_graph(G, tau, gamma, initial_infecteds=initial_infecteds, tmax = 10, tcount =51)
    plt.plot(t, S, ':', color = colors[4], label = 'EBCM')
    plt.plot(t, I, ':', color = colors[4])
    plt.plot(t, R, ':', color = colors[4])
    
    plt.axis(xmax=10, xmin=0)
    plt.xlabel('$t$')
    plt.legend(loc = 'center right')
    plt.savefig('fig7p2.png')