[Numpy-discussion] is __array_ufunc__ ready for prime-time?

[josef.pktd at gmail.com]

On Thu, Nov 2, 2017 at 8:46 AM, <josef.pktd at gmail.com> wrote:

>
>
> On Wed, Nov 1, 2017 at 6:55 PM, Nathan Goldbaum <nathan12343 at gmail.com>
> wrote:
>
>> I think the biggest issues could be resolved if __array_concatenate__
>> were finished. Unfortunately I don't feel like I can take that on right now.
>>
>> See Ryan May's talk at scipy about using an ndarray subclass for units
>> and the issues he's run into:
>>
>> https://www.youtube.com/watch?v=qCo9bkT9sow
>>
>
>
> Interesting talk, but I don't see how general library code should know
> what units the output has.
> for example if units are some flows per unit of time and we average, sum
> or integrate over time, then what are the new units? (e.g. pandas time
> aggregation)
> What are units of covariance or correlation between two variables with the
> same units, and what are they between variables with different units?
>
> How do you concatenate and operate arrays with different units?
>
> interpolation or prediction would work with using the existing units.
>
> partially related:
> statsmodels uses a wrapper for pandas Series and DataFrames and tries to
> preserve the index when possible and make up a new DataFrame or Series if
> the existing index doesn't apply.
> E.g. predicted values and residuals are in terms of the original provided
> index, and could also get original units assigned. That would also be
> possible with prediction confidence intervals. But for the rest, see above.
>

using pint

>>> x
<Quantity([0 1 2 3 4], 'meter')>
>>> x / x
<Quantity([ nan   1.   1.   1.   1.], 'dimensionless')>

>>> x / (1 + x)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\...\python-3.4.4.amd64\lib\site-packages\pint\quantity.py", line
669, in __add__
    raise DimensionalityError(self._units, 'dimensionless')
    return self._add_sub(other, operator.add)
  File "C:\...\python-3.4.4.amd64\lib\site-packages\pint\quantity.py", line
580, in _add_sub
pint.errors.DimensionalityError: Cannot convert from 'meter' to
'dimensionless'

np.exp(x)
raises
pint.errors.DimensionalityError: Cannot convert from 'meter' ([length]) to
'dimensionless' (dimensionless)


Josef



>
> Josef
>
>
>>
>>
>> On Wed, Nov 1, 2017 at 5:50 PM, Marten van Kerkwijk <
>> m.h.vankerkwijk at gmail.com> wrote:
>>
>>> From my experience with Quantity, routines that properly ducktype work
>>> well, those that feel the need to accept list and blatantly do
>>> `asarray` do not - even if in many cases they would have worked if
>>> they used `asanyarray`...  But there are lots of nice surprises, with,
>>> e.g., `np.fft.fftfreq` just working as one would hope.  Anyway, bottom
>>> line, I think you should let this stop you from trying only if you
>>> know something important does not work. -- Marten
>>> _______________________________________________
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion at python.org
>>> https://mail.python.org/mailman/listinfo/numpy-discussion
>>>
>>
>>
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion at python.org
>> https://mail.python.org/mailman/listinfo/numpy-discussion
>>
>>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20171102/83ea71ae/attachment-0001.html>