On Wed, May 31, 2023 at 5:01 PM David Menéndez Hurtado <
davidmen...@gmail.com> wrote:
> On Wed, 31 May 2023, 22:41 Robert Kern, wrote:
>
>> Not sure anyone really uses tanh for serious work.
>>
>
> At the risk of derailing the discussion, the case I can think of
rticularly
special values at places in between adjacent representable floating point
numbers.
> I'm ambivalent about reverting. I know I would love speed improvements
> because transformation calculations in GIS is slow using numpy, but also
> some coordinate transformations might break
]
|21> x = np.arange(2*3).reshape((2, 3))
[~]
|22> x
array([[0, 1, 2],
[3, 4, 5]])
[~]
|23> x.flat[[0, 1, 2, 3]]
array([0, 1, 2, 3])
```
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Robert Kern
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otion scheme.
`np.dot()` is kind of an oddball already, and "half-precision inputs ->
full-precision outputs" might be a worthwhile use case given hardware
accelerators. Given that this largely affects non-numpy implementations of
the Array API, you probably want to raise it with that group.
iding such an `out=`) will fall down
to the `ff->f` loop and cause upcasting of the operands, which is not what
they want. But notionally one could add an `ee->f` loop between those two
that would catch this case when `dtype=np.float32` is requested.
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Robert Kern
g
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>
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ot for RC releases):
http://pypi.python.org/pypi/numexpr
Documentation is hosted at:
http://numexpr.readthedocs.io/en/latest/
Share your experience
-
Let us know of any bugs, suggestions, gripes, kudos, etc. you may
have.
Enjoy data!
21])
> ```
> which matches your example in the cumsum0() documentation. Did something
> change in a recent release?
>
That's not what's in his example.
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them up a little bit and opensource
it shortly.
-Robert
On Sun, Nov 26, 2017 at 1:58 PM, Stephan Hoyer wrote:
> On Sat, Nov 25, 2017 at 3:34 PM Matthew Rocklin
> wrote:
>
>> Thoughts on basing this on a more generic Array type rather than the
>> np.ndarray? I can imagine o
by no means ready for real users, but I hope this is a useful place to
build from. Any feedback or contributions would be appreciated.
-Robert
On Tue, Nov 28, 2017 at 2:04 PM, Stephan Hoyer wrote:
> On Tue, Nov 28, 2017 at 5:11 PM Robert T. McGibbon
> wrote:
>
>> I'm strongl
of
numpy, that would be fine.
I'm interested in creating something similar to
https://github.com/pypa/auditwheel that could statically check for
compatibility between wheel files and python installations, in situations
where the metadata about how they were compiled is missing.
--
-R
Matti,
That doesn't quite cover my use case. I'm interested in querying a .whl
file containing .so files that were compiled against numpy (not my
currently installed version of numpy) to determine the conditions under
which those `.so` files were compiled.
-Robert
On Mon, Oct 8, 2018
program code. NEP 19 doesn't need an update for us to endorse SPEC
7 (whether it needs one, separately, to clarify its intent is another
question).
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turn dict(bg_state=bg_state, seed_seq=ss_dict)
def rng_fromdict(d):
bg_state = d['bg_state']
ss = np.random.SeedSequence(**d['seed_seq'])
bg = getattr(np.random, bg_state['bit_generator'])(ss)
bg.state = bg_state
rng = np.random.Generator(bg)
se and leave the 0-length-axis case
alone.
3. Fix the 0-length-axis case to use the following `# shape=...` comment
too.
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is suggesting that behavior should change. The issue is whether or
not an unnecessary, _additional_ copy gets made when converting a
not-exactly-an-`ndarray` object to an `ndarray` object before doing the
assignment (which always copies values over to the destination array).
--
Robert
py/pull/5749/files
>>> original_oindex = OrthogonalIndexer(original)
>>> original_oindex[i, j, k]
array([[1237, 1241, 1243],
[1267, 1271, 1273],
[1297, 1301, 1303],
[1327, 1331, 1333],
[1357, 1361, 1363]])
Note that some other array implementations li
ich is primarily for 2D arrays (and presumably
following a convention from another language like MATLAB). In order to get
the (2, 3, 4) arrays that you want, use `indexing='ij'`
# Note the flipped order of inputs and outputs since you want the `zt`
values across the fi
ort into it, but I think the
first step would be to walk through what the stride tricks actually would
be to get this operation to work. Then we can talk about whether or not
it's desirable to plug it in.
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Robert Kern
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ike an ad hoc algorithm rather than a well-known, well-studied
random process. I'm happy to be corrected with references to the
literature, but even if there are references, I'm happy to leave this for
users to implement on their own.
--
Robert Kern
_
ing polygons onto images, I might follow
scikit-image's convention instead.
By and large, you can usually safely follow whatever is your personal
preference without fearing that you are missing out on something vital.
What makes these convention
one of the arrangements than others (e.g. the ravelled
will likely be the least convenient), but it has more to do with other code
and file formats that you are interacting with that will be the largest
factors in breaking the symmetry.
--
Robert Kern
__
g
any that do implement these functions (the exception being the cotangent in
degrees, which Cephes implements, and we already expose in scipy.special).
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To unsubscr
s(c, a) / (a**2).sum()
> Out[135]: array([-0.93244529, 0.74775365, 1.09117371])
>
Delightful!
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https
print(res)
...
[-2.22044605e-16 0.e+00 -1.66533454e-16]
[7.56339436e-16 8.88178420e-16 2.77555756e-16]
[-5.55111512e-17 -2.77555756e-16 -2.22044605e-16]
[-1.66533454e-16 -5.55111512e-17 0.e+00]
[0.e+00 6.66133815e-16 3.33066907e-16]
[-1.11022302e-16 0.0
On Sat, Jun 28, 2025 at 8:42 AM Kwaku Oppong via NumPy-Discussion <
numpy-discussion@python.org> wrote:
> can someone helps me. Whenever i ytried to launch Jupyter from Navigator,
> this is the message I gets
>
Sorry, this isn't the place for Jupyter questio
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