def ba_lasso(r = 20): fps = np.zeros(r) fns = np.zeros(r) norms = np.zeros(r) for i in range(r): samples, cov = network.ba_network() t = 1e-1 fpr, fnr, fnorm = estimate_data(samples, cov, t) fps[i] = fpr fns[i] = fnr norms[i] = fnorm return fps.mean(), fns.mean(), norms.mean()
def test_ba(): samples, cov = network.ba_network(p=10)