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src/s/t/StochasticBlockmodel-HEAD/test_minimal.py   StochasticBlockmodel(Download)
        return abs(x_node[i_1] - x_node[i_2]) < 0.3
    net.new_edge_covariate(covariate).from_binary_function_ind(f_x)
net.generate(data_model)
net.show()
print 'True beta_1: %.2f' % data_model.beta['x_1']

src/s/t/StochasticBlockmodel-HEAD/test_laplace.py   StochasticBlockmodel(Download)
        return abs(x_node[i_1] - x_node[i_2]) < 0.3
    net.new_edge_covariate(covariate).from_binary_function_ind(f_x)
net.generate(data_model)
print 'True beta_1: %.2f' % data_model.beta['x_1']