[Numpy-discussion] 'nansqrt' function?

Charles R Harris charlesr.harris at gmail.com
Wed Feb 13 17:09:46 EST 2019


On Wed, Feb 13, 2019 at 2:14 PM Mauro Cavalcanti <maurobio at gmail.com> wrote:

> Chuck,
>
> Sure, using numpy.sqrt works fine.
>
> Thank you very much.
>
> Best regards,
>
> Em qua, 13 de fev de 2019 às 19:09, Charles R Harris <
> charlesr.harris at gmail.com> escreveu:
>
>>
>>
>> On Wed, Feb 13, 2019 at 1:35 PM Mauro Cavalcanti <maurobio at gmail.com>
>> wrote:
>>
>>> Dear ALL,
>>>
>>> In the process of porting an existing (but abandoned) package to the
>>> latest version of Numpy, I stumbled upon a call to a 'numpy.nansqrt'
>>> function, which seems not to exist.
>>>
>>> Here is the specific code:
>>>
>>> def normTrans(y):
>>>     denom = np.nansqrt(np.nansum(y**2))
>>>     return y/denom
>>>
>>> As far as I could find, there is no such 'nansqrt' function in the
>>> current version of Numpy, so I suspect that the above code has not been
>>> properly tested.
>>>
>>> Am I right, or that function had existed in some past version of Numpy?
>>>
>>> Thanks in advance for any comments or suggestions.
>>>
>>>
>> I don't recall any such function, but  nansum will not result in any
>> nans, so plain old sqrt should work.
>>
>>
Note that there are various nan stat functions:

- `nanmin` -- minimum non-NaN value
- `nanmax` -- maximum non-NaN value
- `nanargmin` -- index of minimum non-NaN value
- `nanargmax` -- index of maximum non-NaN value
- `nansum` -- sum of non-NaN values
- `nanprod` -- product of non-NaN values
- `nancumsum` -- cumulative sum of non-NaN values
- `nancumprod` -- cumulative product of non-NaN values
- `nanmean` -- mean of non-NaN values
- `nanvar` -- variance of non-NaN values
- `nanstd` -- standard deviation of non-NaN values
- `nanmedian` -- median of non-NaN values
- `nanquantile` -- qth quantile of non-NaN values
- `nanpercentile` -- qth percentile of non-NaN values

Chuck
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20190213/f61015dd/attachment-0001.html>


More information about the NumPy-Discussion mailing list