[Numpy-discussion] `allclose` vs `assert_allclose`

[Nathaniel Smith]

On 16 Jul 2014 10:26, "Tony Yu" <tsyu80 at gmail.com> wrote:
>
> 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/f43223479f917e404e724e6a3df27aa701e6d6bf
>
> 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.

What you say makes sense to me, and loosening the default tolerances won't
break any existing tests. (And I'm not too worried about people who were
counting on getting 1e-7 instead of 1e-5 or whatever... if it matters that
much to you exactly what tolerance you test, you should be setting the
tolerance explicitly!) I vote that unless someone comes up with some
terrible objection in the next few days then you should submit a PR :-)

-n
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