catching 0 weight cases where interpolation and nn weighting correctly differ from each other
@@ -291,6 +291,8 @@ class TestConsistency(unittest.TestCase):
model_weighted, rdms, method=i_method)
eval_m_i = np.mean(compare(model_interpolate.predict_rdm(
theta_m_i), rdms, method=i_method))
+ # catch cases where a 0 rdm is the best fit
+ eval_m_i = max(eval_m_i, 0)
eval_m_w = np.mean(compare(model_weighted.predict_rdm(
theta_m_w), rdms, method=i_method))
eval_m_w_pos = np.mean(compare(model_weighted.predict_rdm(
