Thank you for pointing this out. This is the code block which includes the
first appearance of the keyword `logical_not`.
BTW, why can't the ~ operator be tested equal to 'np.invert', as shown below:
```
In [1]: import numpy as np
In [3]: np.invert is np.bitwise_not
Out[3]: True
In [4]:
On Mon, Oct 4, 2021 at 12:09 AM wrote:
> > (the bool implementation uses the `logical_not` loop).
>
> Do you the following code snippet:
>
>
> https://github.com/numpy/numpy/blob/3c1e9b4717b2eb33a2bf2d495006bc300f5b8765/numpy/core/src/umath/loops.c.src#L1627-L1633
This is the one that gets
> (the bool implementation uses the `logical_not` loop).
Do you the following code snippet:
https://github.com/numpy/numpy/blob/3c1e9b4717b2eb33a2bf2d495006bc300f5b8765/numpy/core/src/umath/loops.c.src#L1627-L1633
___
NumPy-Discussion mailing list --
On Sun, Oct 3, 2021 at 9:27 PM wrote:
>
> So, C/Python operator `~` has been overridden by the corresponding user
> function in numpy, but where is the corresponding source code
> implementation?
>
ufuncs are implemented in C. We provide so-called loop functions that
iterate over contiguous
I noticed the following documentation on `numpy.invert`: [1]
numpy.invert
[...]
Compute bit-wise inversion, or bit-wise NOT, element-wise.
Computes the bit-wise NOT of the underlying binary representation of the
integers in the input arrays. This ufunc implements the C/Python operator
Hi All,
Dropping 32 manylinux wheels was discussed in a triage meeting some time
ago and the general consensus was to do so. However, it has never been run
past the larger community on the discussion list, so this is that. Note
that we have already dropped 32 bit manylinux wheels for the upcoming
On Sun, Oct 3, 2021 at 4:15 PM Mark Bakker wrote:
> Dear List,
>
> I just found out that there is a numpy.math subpackage with a bunch of
> extra mathematical functions (I needed the factorial function). I have been
> googling for 10 minutes, but can not find any documentation on the
>
Dear List,
I just found out that there is a numpy.math subpackage with a bunch of
extra mathematical functions (I needed the factorial function). I have been
googling for 10 minutes, but can not find any documentation on the
numpy.math subpackage (my poor google skills, I am sure). Can anybody
