Hi all, We just merged the PR to add `np.finfo.smallest_normal` and `np.finfo.smallest_subnormal` to `np.finfo` (the floating point DType information object):
* smallest_normal:
- An alias for `np.finfo.tiny`
- The smallest "normal". I.e. the smallest number larger than
zero that has full precision.
* smallest_subnormal:
- Equivalent to `np.nextafter(0., 1.)`
- The smallest subnormal/denormal number. I.e. the smallest
representable number larger than zero.
Please don't hesitate to comment if you have any thoughts on the API
addition.
Cheers,
Sebastian
On Wed, 2021-04-21 at 17:44 -0500, Stephannie Jiménez Gacha wrote:
> Good afternoon,
>
> Given the discussions happened in the Data API consortium when
> looking into
> the attributes of `finfo` used in the wild, we found that `tiny` is
> used
> regularly but in a good amount of cases not for its intended purpose
> but
> rather as "just give me a small number". Following this we are
> proposing
> the addition of `smallest_normal` and `smallest_subnormal`
> attributes.
> Personally, I think that the `tiny` name is a little bit odd and
> misleading, so it will be great to leave that as an alias but have a
> clear
> name in this class.
>
> Right now the PR: https://github.com/numpy/numpy/pull/18536 has all
> the
> changes and all the values added were checked against IEEE-754
> standard.
> One of the main concerns is the support of subnormal numbers in
> certain
> architectures, where the values can't be calculated accurately. Given
> the
> state of the discussion, we don't know if the best alternative is to
> not
> add the `smallest_subnormal` attribute and just add the
> `smallest_number`
> attribute as an alias to `tiny`.
>
> We open this to discussion to see what way we can go in order to get
> this
> PR merged.
>
> *Stephannie Jimenez Gacha*Software developer
>
> *Quansight* | Your Data Experts
>
> w: www.quansight.com e: [email protected]
> <https://www.linkedin.com/company/quansight>
> <https://twitter.com/quansightai>
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