本文整理汇总了Python中Network.Network.show方法的典型用法代码示例。如果您正苦于以下问题：Python Network.show方法的具体用法？Python Network.show怎么用？Python Network.show使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Network.Network的用法示例。
在下文中一共展示了Network.show方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: alpha_unif
# 需要导入模块: from Network import Network [as 别名]
# 或者: from Network.Network import show [as 别名]
alpha_unif(net, 0.5)
# Initialize the data model; generate covariates and associated coefficients
data_model = NonstationaryLogistic()
data_model.kappa = -7.0
covariates = ['x_%d' % i for i in range(5)]
for covariate in covariates:
data_model.beta[covariate] = normal(0, 1.0)
x_node = normal(0, 1.0, N)
def f_x(i_1, i_2):
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.offset_extremes()
net.show()
print 'True theta_0: %.2f' % data_model.beta['x_0']
# Initialize the fit model; specify which covariates it should have terms for
fit_model = NonstationaryLogistic()
for covariate in covariates:
fit_model.beta[covariate] = None
# Set up random subnetwork generator, and run fitting experiments
gen = RandomSubnetworks(net, (200, 200))
for rep in range(5):
subnet = gen.sample()
fit_model.fit(subnet)
print 'Estimated theta_0: %.2f' % fit_model.beta['x_0']