Is there any reason why the defaults for `allclose` and `assert_allclose` differ? This makes debugging a broken test much more difficult. More importantly, using an absolute tolerance of 0 causes failures for some common cases. For example, if two values are very close to zero, a test will fail: np.testing.assert_allclose(0, 1e-14) Git blame suggests the change was made in the following commit, but I guess that change only reverted to the original behavior. https://github.com/numpy/numpy/commit/f43223479f917e404e724e6a3df27aa701e6d6... It seems like the defaults for `allclose` and `assert_allclose` should match, and an absolute tolerance of 0 is probably not ideal. I guess this is a pretty big behavioral change, but the current default for `assert_allclose` doesn't seem ideal. Thanks, -Tony