diff --git a/examples/cpr_sns.py b/examples/cpr_sns.py index 7624062e68aace4a542dddba5bb00e1ca5784d64..4e51eb8d33eabea8c06e289421d6d7fbcee106b1 100644 --- a/examples/cpr_sns.py +++ b/examples/cpr_sns.py @@ -56,7 +56,7 @@ Res = collections.namedtuple("Res", ["x", "y", "J", "Jx", "Jy"]) @vectorize_parallel(returns_object=True, noarray=True) @usadelndsoc.with_log_level(logging.WARNING) -def j(T, h, phi, n=15, eta=0.1, alpha_soc=0.1, L=10, perturbative=False): +def j(T, h, phi, n=15, eta=0.1, alpha_soc=0.1, L=10): sol = get_solver(soc_alpha=alpha_soc, eta=eta, L=L, n=n, phi=phi, h=h) @@ -78,13 +78,11 @@ def j(T, h, phi, n=15, eta=0.1, alpha_soc=0.1, L=10, perturbative=False): def main(): T = 0.1 - alpha_soc = 0.1 + alpha_soc = 0.3 h = np.r_[0.0, 0.25, 0.5, 1.0, 1.5] phi = np.linspace(-pi, pi, 37) - res = j( - T, h[:, None], phi[None, :], alpha_soc=alpha_soc, perturbative=False, mem=mem - ) + res = j(T, h[:, None], phi[None, :], alpha_soc=alpha_soc, L=3, mem=mem) Jx_mean = np.asarray( [Res(*x).Jx[1:-1].sum(axis=1).mean(axis=0) for x in res.flat]