[Numpy-discussion] Documentation team meeting - Monday 27 March at 12 PM UTC (noon)

2023-03-26 Thread Mukulika Pahari
Hi all!

Our next Documentation Team meeting will happen on *Monday, March 27* at
***12PM UTC***. We now alternate the meeting times to be a bit more
inclusive. This means that we'll have a meeting at 12pm UTC every 28 days,
and a meeting at 4pm UTC every 28 days.

All are welcome - you don't need to already be a contributor to join. If
you have questions or are curious about what we're doing, we'll be happy to
meet you!

If you wish to join on Zoom, use this (updated) link:

https://numfocus-org.zoom.us/j/85016474448?pwd=TWEvaWJ1SklyVEpwNXUrcHV1YmFJQ...

Here's the permanent hackmd document with the meeting notes (still being
updated):

https://hackmd.io/oB_boakvRqKR-_2jRV-Qjg

Hope to see you around!

* You can also visit https://scientific-python.org/calendars to add the
NumPy community calendar as an .ics file to your preferred calendar
manager. *

Best wishes,
Mukulika
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[Numpy-discussion] Add support for array `atol` and `rtol` in `np.testing.assert_allclose` and `np.allclose`

2023-03-26 Thread Quang Anh
Numpy version 1.24.0.

The current behavior of `np.testing.assert_allclose` and `np.allclose` are 
still inconsistent with the docs, which specifies that `atol` and `rtol` must 
be a scalar. However, the current implementation of `np.allclose` allows 
passing in `atol` and `rtol` as an array, while `np.testing.assert_allclose` 
only raises error because of a string formatting line `header = f'Not equal to 
tolerance rtol={rtol:g}, atol={atol:g}'`. To make things less confusing, for 
BOTH `np.allclose()` and `np.testing.assert_allclose()`, we should either 
perform a check for the correct type of `atol` and `rtol`, or to actually 
support an array as `atol`.

Indeed there are real use-cases for array `atol` and `rtol`. For example for 
`atol`: let's say we want to compare two 3D vectors x and y where the first two 
axis should have absolute tolerance of 0.1 while the third axis should have 
absolute tolerance of 1, because there are more stringent requirements on x and 
y. I believe this is the use case that many of us run into, and it is quite 
natural to write

```python3
import numpy as np
x = [1, 2, 3]
y = [1.1, 2.1, 5]
np.allclose(x, y, atol=[0.1, 0.1, 1])
```

[I have posted this as a comment on an 
issue](https://github.com/numpy/numpy/issues/14320#issuecomment-1482201277)
[And there is already a proposed PR to support this 
change](https://github.com/numpy/numpy/pull/14343)
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[Numpy-discussion] next NumPy community meeting

2023-03-26 Thread Inessa Pawson
The next NumPy community meeting will be held this Wednesday, March 29th at
19:00 (7 pm) UTC.
Join us via Zoom:
https://us06web.zoom.us/j/83278611437?pwd=ekhoLzlHRjdWc0NOY2FQM0NPemdkZz09.
Everyone is welcome and encouraged to attend.
To add to the meeting agenda the topics you’d like to discuss, follow the
link: https://hackmd.io/76o-IxCjQX2mOXO_wwkcpg?both.
For the notes from the previous meeting, visit:
https://github.com/numpy/archive/blob/main/community_meetings/community-2023-03-15.md
.

-- 
Cheers,
Inessa

Inessa Pawson
Contributor Experience Lead | NumPy
https://numpy.org/
GitHub: inessapawson
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[Numpy-discussion] NumPy 2.0 meeting - Monday, April 3rd, 3 - 7pm UTC

2023-03-26 Thread Inessa Pawson
Hi, everyone!
The preparation for NumPy 2.0 release is currently underway. The NumPy
project leadership would like to invite you all to join us on Monday, April
3rd, 3 - 7pm UTC for the meeting where the NumPy maintainers will present
the scope of the planned work for this release and hold in-depth
discussions on every proposed feature.
For details of the meeting agenda, visit:
https://docs.google.com/document/d/1vNDBlnVCJM-Nv7xF02Re4qk_5rR9uAUi0ih6K3b2YAE/edit?usp=sharing.
Please keep in mind that it hasn’t been finalized yet.
Join us via Zoom:
https://numfocus-org.zoom.us/j/87080449579?pwd=dmt5dktCT2l1NG5ZNGFvb3dKdUNIdz09
.

-- 
Cheers,
Inessa

Inessa Pawson
Contributor Experience Lead | NumPy
https://numpy.org/
GitHub: inessapawson
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