brainconn.generative.evaluate_generative_model

evaluate_generative_model(A, Atgt, D, eta, gamma=None, model_type='matching', model_var='powerlaw', epsilon=1e-06)

Generates synthetic networks with parameters provided and evaluates their energy function. The energy function is defined as in Betzel et al. 2016. Basically it takes the Kolmogorov-Smirnov statistics of 4 network measures; comparing the degree distributions, clustering coefficients, betweenness centrality, and Euclidean distances between connected regions.

The energy is globally low if the synthetic network matches the target. Energy is defined as the maximum difference across the four statistics.