Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Charles R Harris]

On Wed, Feb 17, 2016 at 9:12 AM, Andreas Mueller  wrote:

>
>
> On 02/12/2016 04:19 PM, Nathan Goldbaum wrote:
>
>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>>
>> Thanks.
> That doesn't cover the backward incompatible change to assert_almost_equal
> and assert_array_almost_equal,
> right?


What changes? AFAICT, there have only been some PEP8 changes in those
functions since 1.9.

Chuck
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Andreas Mueller]

On 02/12/2016 04:19 PM, Nathan Goldbaum wrote:

https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst


Thanks.
That doesn't cover the backward incompatible change to 
assert_almost_equal and assert_array_almost_equal,

right?
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Sebastian Berg]

On Di, 2016-02-16 at 00:13 -0500, josef.p...@gmail.com wrote:
> 
> 
> On Tue, Feb 16, 2016 at 12:09 AM,  wrote:
> > 
> > 

> > 
> > 
> > Or, it forces everyone to watch out for the color of the ducks :)
> > 
> > It's just a number, whether it's python scalar, numpy scalar, 1D or
> > 2D.
> > And once we squeeze, we cannot iterate over it anymore. 
> > 
> > 
> > This looks like the last problem with have in statsmodels master.
> > Part of the reason that 0.10 hurt quite a bit is that we are using
> > in statsmodels some of the grey zones so we don't have to commit to
> > a specific usage. Even if a user or developer tries a "weird" case,
> > it works for most of the results, but breaks in some unknown
> > places. 
> > 
> > 
> I meant 1.11 here.
>  

The reason for this part is that `arr[np.array([1])]` is very different
from `arr[np.array(1)]`. For `list[np.array([1])]` if you allow
`operator.index(np.array([1]))` you will not get equivalent results for
lists and arrays.

The normal array result cannot work for lists. We had open bug reports
about it. Of course I dislike it in any case ;), but that is the
reasoning behind being a bit more restrictive for `__index__`.

- Sebastian


> > (In the current case a cryptic exception would be raised if the
> > user has two constant columns in the regression. Which is fine for
> > some usecases but not for every result.)
> > 
> > Josef
> >  
> > > 
> > > Chuck
> > > 
> > > ___
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> > > https://mail.scipy.org/mailman/listinfo/numpy-discussion
> > > 
> > 
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[josef.pktd]

On Tue, Feb 16, 2016 at 12:09 AM,  wrote:

>
>
> On Mon, Feb 15, 2016 at 11:31 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Mon, Feb 15, 2016 at 9:15 PM,  wrote:
>>
>>>
>>>
>>> On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris <
>>> charlesr.har...@gmail.com> wrote:
>>>


 On Mon, Feb 15, 2016 at 8:50 PM,  wrote:

>
>
> On Mon, Feb 15, 2016 at 10:46 PM,  wrote:
>
>
>>
>> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum <
>> nathan12...@gmail.com> wrote:
>>
>>>
>>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>>>
>>> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller 
>>> wrote:
>>>
 Hi.
 Where can I find the changelog?
 It would be good for us to know which changes are done one purpos
 without hunting through the issue tracker.

 Thanks,
 Andy


 On 02/09/2016 09:09 PM, Charles R Harris wrote:

 Hi All,

 I'm pleased to announce the release of NumPy 1.11.0b3. This beta
 contains additional bug fixes as well as limiting the number of
 FutureWarnings raised by assignment to masked array slices. One issue 
 that
 remains to be decided is whether or not to postpone raising an error 
 for
 floats used as indexes. Sources may be found on Sourceforge
  and
 both sources and OS X wheels are availble on pypi. Please test, 
 hopefully
 this will be that last beta needed.

 As a note on problems encountered, twine uploads continue to fail
 for me, but there are still variations to try. The wheeluploader 
 downloaded
 wheels as it should, but could not upload them, giving the error 
 message
 "HTTPError: 413 Client Error: Request Entity Too Large for url:
 https://www.python.org/pypi";. Firefox
 also complains that http://wheels.scipy.org is incorrectly
 configured with an invalid certificate.

 Enjoy,

 Chuck


 ___
 NumPy-Discussion mailing 
 listNumPy-Discussion@scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion



 ___
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 NumPy-Discussion@scipy.org
 https://mail.scipy.org/mailman/listinfo/numpy-discussion


>>>
>>> ___
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion@scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>
> (try to send again)
>
>
>>
>> another indexing question:  (not covered by unit test but showed up
>> in examples in statsmodels)
>>
>>
>> This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and
>> python 3.4)
>>
>> >>> list(range(5))[np.array([0])]
>> 0
>>
>>
>>
>> on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)
>>
>> I get the same exception as here but even if there is just one element
>>
>>
>> >>> list(range(5))[np.array([0, 1])]
>> Traceback (most recent call last):
>>   File "", line 1, in 
>> list(range(5))[np.array([0, 1])]
>> TypeError: only integer arrays with one element can be converted to
>> an index
>>
>
 Looks like a misleading error message. Apparently it requires scalar
 arrays (ndim == 0)

 In [3]: list(range(5))[np.array(0)]
 Out[3]: 0

>>>
>>>
>>> We have a newer version of essentially same function a second time that
>>> uses squeeze and that seems to work fine.
>>>
>>> Just to understand
>>>
>>> Why does this depend on the numpy version?  I would have understood that
>>> this always failed, but this code worked for several years.
>>> https://github.com/statsmodels/statsmodels/issues/2817
>>>
>>
>> It's part of the indexing cleanup.
>>
>> In [2]: list(range(5))[np.array([0])]
>> /home/charris/.local/bin/ipython:1: VisibleDeprecationWarning: converting
>> an array with ndim > 0 to an index will result in an error in the future
>>   #!/usr/bin/python
>> Out[2]: 0
>>
>> The use of multidimensional arrays as indexes is likely a coding error.
>> Or so we hope...
>>
>
> Thanks for the explanation
>
>
> Or, it forces everyone to watch out for the color of the ducks :)
>
> It's just a number, whether it's python scalar, numpy scalar, 1D or 2D.
> And once we squeeze, we cannot iterate over it anymore.
>
>
> This looks like the last problem with have in statsmodels master.
> Part of the reason that 0.10 hurt quite a bit is that we are using in
> statsmodels some of the

Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[josef.pktd]

On Mon, Feb 15, 2016 at 11:31 PM, Charles R Harris <
charlesr.har...@gmail.com> wrote:

>
>
> On Mon, Feb 15, 2016 at 9:15 PM,  wrote:
>
>>
>>
>> On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris <
>> charlesr.har...@gmail.com> wrote:
>>
>>>
>>>
>>> On Mon, Feb 15, 2016 at 8:50 PM,  wrote:
>>>


 On Mon, Feb 15, 2016 at 10:46 PM,  wrote:


>
> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum <
> nathan12...@gmail.com> wrote:
>
>>
>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>>
>> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller 
>> wrote:
>>
>>> Hi.
>>> Where can I find the changelog?
>>> It would be good for us to know which changes are done one purpos
>>> without hunting through the issue tracker.
>>>
>>> Thanks,
>>> Andy
>>>
>>>
>>> On 02/09/2016 09:09 PM, Charles R Harris wrote:
>>>
>>> Hi All,
>>>
>>> I'm pleased to announce the release of NumPy 1.11.0b3. This beta
>>> contains additional bug fixes as well as limiting the number of
>>> FutureWarnings raised by assignment to masked array slices. One issue 
>>> that
>>> remains to be decided is whether or not to postpone raising an error for
>>> floats used as indexes. Sources may be found on Sourceforge
>>>  and
>>> both sources and OS X wheels are availble on pypi. Please test, 
>>> hopefully
>>> this will be that last beta needed.
>>>
>>> As a note on problems encountered, twine uploads continue to fail
>>> for me, but there are still variations to try. The wheeluploader 
>>> downloaded
>>> wheels as it should, but could not upload them, giving the error message
>>> "HTTPError: 413 Client Error: Request Entity Too Large for url:
>>> https://www.python.org/pypi";. Firefox
>>> also complains that http://wheels.scipy.org is incorrectly
>>> configured with an invalid certificate.
>>>
>>> Enjoy,
>>>
>>> Chuck
>>>
>>>
>>> ___
>>> NumPy-Discussion mailing 
>>> listNumPy-Discussion@scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>>
>>> ___
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion@scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>
>> ___
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>
 (try to send again)


>
> another indexing question:  (not covered by unit test but showed up in
> examples in statsmodels)
>
>
> This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and python
> 3.4)
>
> >>> list(range(5))[np.array([0])]
> 0
>
>
>
> on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)
>
> I get the same exception as here but even if there is just one element
>
>
> >>> list(range(5))[np.array([0, 1])]
> Traceback (most recent call last):
>   File "", line 1, in 
> list(range(5))[np.array([0, 1])]
> TypeError: only integer arrays with one element can be converted to an
> index
>

>>> Looks like a misleading error message. Apparently it requires scalar
>>> arrays (ndim == 0)
>>>
>>> In [3]: list(range(5))[np.array(0)]
>>> Out[3]: 0
>>>
>>
>>
>> We have a newer version of essentially same function a second time that
>> uses squeeze and that seems to work fine.
>>
>> Just to understand
>>
>> Why does this depend on the numpy version?  I would have understood that
>> this always failed, but this code worked for several years.
>> https://github.com/statsmodels/statsmodels/issues/2817
>>
>
> It's part of the indexing cleanup.
>
> In [2]: list(range(5))[np.array([0])]
> /home/charris/.local/bin/ipython:1: VisibleDeprecationWarning: converting
> an array with ndim > 0 to an index will result in an error in the future
>   #!/usr/bin/python
> Out[2]: 0
>
> The use of multidimensional arrays as indexes is likely a coding error. Or
> so we hope...
>

Thanks for the explanation


Or, it forces everyone to watch out for the color of the ducks :)

It's just a number, whether it's python scalar, numpy scalar, 1D or 2D.
And once we squeeze, we cannot iterate over it anymore.


This looks like the last problem with have in statsmodels master.
Part of the reason that 0.10 hurt quite a bit is that we are using in
statsmodels some of the grey zones so we don't have to commit to a specific
usage. Even if a user or developer tries a "weird" case, it works for most
of the results, but breaks in some unknown places.

(In the current case a cryptic exception would be raised

Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Charles R Harris]

On Mon, Feb 15, 2016 at 9:15 PM,  wrote:

>
>
> On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Mon, Feb 15, 2016 at 8:50 PM,  wrote:
>>
>>>
>>>
>>> On Mon, Feb 15, 2016 at 10:46 PM,  wrote:
>>>
>>>

 On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum >>> > wrote:

> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>
> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller 
> wrote:
>
>> Hi.
>> Where can I find the changelog?
>> It would be good for us to know which changes are done one purpos
>> without hunting through the issue tracker.
>>
>> Thanks,
>> Andy
>>
>>
>> On 02/09/2016 09:09 PM, Charles R Harris wrote:
>>
>> Hi All,
>>
>> I'm pleased to announce the release of NumPy 1.11.0b3. This beta
>> contains additional bug fixes as well as limiting the number of
>> FutureWarnings raised by assignment to masked array slices. One issue 
>> that
>> remains to be decided is whether or not to postpone raising an error for
>> floats used as indexes. Sources may be found on Sourceforge
>>  and
>> both sources and OS X wheels are availble on pypi. Please test, hopefully
>> this will be that last beta needed.
>>
>> As a note on problems encountered, twine uploads continue to fail for
>> me, but there are still variations to try. The wheeluploader downloaded
>> wheels as it should, but could not upload them, giving the error message
>> "HTTPError: 413 Client Error: Request Entity Too Large for url:
>> https://www.python.org/pypi";. Firefox
>> also complains that http://wheels.scipy.org is incorrectly
>> configured with an invalid certificate.
>>
>> Enjoy,
>>
>> Chuck
>>
>>
>> ___
>> NumPy-Discussion mailing 
>> listNumPy-Discussion@scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>>
>> ___
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>
> ___
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>

>>> (try to send again)
>>>
>>>

 another indexing question:  (not covered by unit test but showed up in
 examples in statsmodels)


 This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and python
 3.4)

 >>> list(range(5))[np.array([0])]
 0



 on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)

 I get the same exception as here but even if there is just one element


 >>> list(range(5))[np.array([0, 1])]
 Traceback (most recent call last):
   File "", line 1, in 
 list(range(5))[np.array([0, 1])]
 TypeError: only integer arrays with one element can be converted to an
 index

>>>
>> Looks like a misleading error message. Apparently it requires scalar
>> arrays (ndim == 0)
>>
>> In [3]: list(range(5))[np.array(0)]
>> Out[3]: 0
>>
>
>
> We have a newer version of essentially same function a second time that
> uses squeeze and that seems to work fine.
>
> Just to understand
>
> Why does this depend on the numpy version?  I would have understood that
> this always failed, but this code worked for several years.
> https://github.com/statsmodels/statsmodels/issues/2817
>

It's part of the indexing cleanup.

In [2]: list(range(5))[np.array([0])]
/home/charris/.local/bin/ipython:1: VisibleDeprecationWarning: converting
an array with ndim > 0 to an index will result in an error in the future
  #!/usr/bin/python
Out[2]: 0

The use of multidimensional arrays as indexes is likely a coding error. Or
so we hope...

Chuck
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[josef.pktd]

On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris <
charlesr.har...@gmail.com> wrote:

>
>
> On Mon, Feb 15, 2016 at 8:50 PM,  wrote:
>
>>
>>
>> On Mon, Feb 15, 2016 at 10:46 PM,  wrote:
>>
>>
>>>
>>> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum 
>>> wrote:
>>>
 https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst

 On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller 
 wrote:

> Hi.
> Where can I find the changelog?
> It would be good for us to know which changes are done one purpos
> without hunting through the issue tracker.
>
> Thanks,
> Andy
>
>
> On 02/09/2016 09:09 PM, Charles R Harris wrote:
>
> Hi All,
>
> I'm pleased to announce the release of NumPy 1.11.0b3. This beta
> contains additional bug fixes as well as limiting the number of
> FutureWarnings raised by assignment to masked array slices. One issue that
> remains to be decided is whether or not to postpone raising an error for
> floats used as indexes. Sources may be found on Sourceforge
>  and
> both sources and OS X wheels are availble on pypi. Please test, hopefully
> this will be that last beta needed.
>
> As a note on problems encountered, twine uploads continue to fail for
> me, but there are still variations to try. The wheeluploader downloaded
> wheels as it should, but could not upload them, giving the error message
> "HTTPError: 413 Client Error: Request Entity Too Large for url:
> https://www.python.org/pypi";. Firefox
> also complains that http://wheels.scipy.org is incorrectly configured
> with an invalid certificate.
>
> Enjoy,
>
> Chuck
>
>
> ___
> NumPy-Discussion mailing 
> listNumPy-Discussion@scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
>
> ___
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> NumPy-Discussion@scipy.org
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>
>

 ___
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 NumPy-Discussion@scipy.org
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>>>
>> (try to send again)
>>
>>
>>>
>>> another indexing question:  (not covered by unit test but showed up in
>>> examples in statsmodels)
>>>
>>>
>>> This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and python
>>> 3.4)
>>>
>>> >>> list(range(5))[np.array([0])]
>>> 0
>>>
>>>
>>>
>>> on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)
>>>
>>> I get the same exception as here but even if there is just one element
>>>
>>>
>>> >>> list(range(5))[np.array([0, 1])]
>>> Traceback (most recent call last):
>>>   File "", line 1, in 
>>> list(range(5))[np.array([0, 1])]
>>> TypeError: only integer arrays with one element can be converted to an
>>> index
>>>
>>
> Looks like a misleading error message. Apparently it requires scalar
> arrays (ndim == 0)
>
> In [3]: list(range(5))[np.array(0)]
> Out[3]: 0
>


We have a newer version of essentially same function a second time that
uses squeeze and that seems to work fine.

Just to understand

Why does this depend on the numpy version?  I would have understood that
this always failed, but this code worked for several years.
https://github.com/statsmodels/statsmodels/issues/2817

Josef




>
> Chuck
>
> ___
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>
>
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Charles R Harris]

On Mon, Feb 15, 2016 at 8:50 PM,  wrote:

>
>
> On Mon, Feb 15, 2016 at 10:46 PM,  wrote:
>
>
>>
>> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum 
>> wrote:
>>
>>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>>>
>>> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller 
>>> wrote:
>>>
 Hi.
 Where can I find the changelog?
 It would be good for us to know which changes are done one purpos
 without hunting through the issue tracker.

 Thanks,
 Andy


 On 02/09/2016 09:09 PM, Charles R Harris wrote:

 Hi All,

 I'm pleased to announce the release of NumPy 1.11.0b3. This beta
 contains additional bug fixes as well as limiting the number of
 FutureWarnings raised by assignment to masked array slices. One issue that
 remains to be decided is whether or not to postpone raising an error for
 floats used as indexes. Sources may be found on Sourceforge
  and
 both sources and OS X wheels are availble on pypi. Please test, hopefully
 this will be that last beta needed.

 As a note on problems encountered, twine uploads continue to fail for
 me, but there are still variations to try. The wheeluploader downloaded
 wheels as it should, but could not upload them, giving the error message
 "HTTPError: 413 Client Error: Request Entity Too Large for url:
 https://www.python.org/pypi";. Firefox
 also complains that http://wheels.scipy.org is incorrectly configured
 with an invalid certificate.

 Enjoy,

 Chuck


 ___
 NumPy-Discussion mailing 
 listNumPy-Discussion@scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion



 ___
 NumPy-Discussion mailing list
 NumPy-Discussion@scipy.org
 https://mail.scipy.org/mailman/listinfo/numpy-discussion


>>>
>>> ___
>>> NumPy-Discussion mailing list
>>> NumPy-Discussion@scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>
> (try to send again)
>
>
>>
>> another indexing question:  (not covered by unit test but showed up in
>> examples in statsmodels)
>>
>>
>> This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and python
>> 3.4)
>>
>> >>> list(range(5))[np.array([0])]
>> 0
>>
>>
>>
>> on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)
>>
>> I get the same exception as here but even if there is just one element
>>
>>
>> >>> list(range(5))[np.array([0, 1])]
>> Traceback (most recent call last):
>>   File "", line 1, in 
>> list(range(5))[np.array([0, 1])]
>> TypeError: only integer arrays with one element can be converted to an
>> index
>>
>
Looks like a misleading error message. Apparently it requires scalar arrays
(ndim == 0)

In [3]: list(range(5))[np.array(0)]
Out[3]: 0

Chuck
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[josef.pktd]

On Mon, Feb 15, 2016 at 10:46 PM,  wrote:

>
>
> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum 
> wrote:
>
>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst
>>
>> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller 
>> wrote:
>>
>>> Hi.
>>> Where can I find the changelog?
>>> It would be good for us to know which changes are done one purpos
>>> without hunting through the issue tracker.
>>>
>>> Thanks,
>>> Andy
>>>
>>>
>>> On 02/09/2016 09:09 PM, Charles R Harris wrote:
>>>
>>> Hi All,
>>>
>>> I'm pleased to announce the release of NumPy 1.11.0b3. This beta
>>> contains additional bug fixes as well as limiting the number of
>>> FutureWarnings raised by assignment to masked array slices. One issue that
>>> remains to be decided is whether or not to postpone raising an error for
>>> floats used as indexes. Sources may be found on Sourceforge
>>>  and both
>>> sources and OS X wheels are availble on pypi. Please test, hopefully this
>>> will be that last beta needed.
>>>
>>> As a note on problems encountered, twine uploads continue to fail for
>>> me, but there are still variations to try. The wheeluploader downloaded
>>> wheels as it should, but could not upload them, giving the error message
>>> "HTTPError: 413 Client Error: Request Entity Too Large for url:
>>> https://www.python.org/pypi";. Firefox also
>>> complains that http://wheels.scipy.org is incorrectly configured with
>>> an invalid certificate.
>>>
>>> Enjoy,
>>>
>>> Chuck
>>>
>>>
>>> ___
>>> NumPy-Discussion mailing 
>>> listNumPy-Discussion@scipy.orghttps://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>>
>>> ___
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>>> NumPy-Discussion@scipy.org
>>> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>
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>
(try to send again)


>
> another indexing question:  (not covered by unit test but showed up in
> examples in statsmodels)
>
>
> This works in numpy at least 1.9.2 and 1.6.1   (python 2.7, and python 3.4)
>
> >>> list(range(5))[np.array([0])]
> 0
>
>
>
> on numpy 0.11.0b2   (I'm not yet at b3)   (python 3.4)
>
> I get the same exception as here but even if there is just one element
>
>
> >>> list(range(5))[np.array([0, 1])]
> Traceback (most recent call last):
>   File "", line 1, in 
> list(range(5))[np.array([0, 1])]
> TypeError: only integer arrays with one element can be converted to an
> index
>
>
> the actual code uses pop on a python list with a return from
> np.where(...)[0]   that returns a one element int64 array
>
> Josef
>
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Nathan Goldbaum]

https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst

On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller  wrote:

> Hi.
> Where can I find the changelog?
> It would be good for us to know which changes are done one purpos without
> hunting through the issue tracker.
>
> Thanks,
> Andy
>
>
> On 02/09/2016 09:09 PM, Charles R Harris wrote:
>
> Hi All,
>
> I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
> additional bug fixes as well as limiting the number of FutureWarnings
> raised by assignment to masked array slices. One issue that remains to be
> decided is whether or not to postpone raising an error for floats used as
> indexes. Sources may be found on Sourceforge
>  and both
> sources and OS X wheels are availble on pypi. Please test, hopefully this
> will be that last beta needed.
>
> As a note on problems encountered, twine uploads continue to fail for me,
> but there are still variations to try. The wheeluploader downloaded wheels
> as it should, but could not upload them, giving the error message
> "HTTPError: 413 Client Error: Request Entity Too Large for url:
> https://www.python.org/pypi";. Firefox also
> complains that http://wheels.scipy.org is incorrectly configured with an
> invalid certificate.
>
> Enjoy,
>
> Chuck
>
>
> ___
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Andreas Mueller]

Hi.
Where can I find the changelog?
It would be good for us to know which changes are done one purpos 
without hunting through the issue tracker.


Thanks,
Andy

On 02/09/2016 09:09 PM, Charles R Harris wrote:

Hi All,

I'm pleased to announce the release of NumPy 1.11.0b3. This beta 
contains additional bug fixes as well as limiting the number of 
FutureWarnings raised by assignment to masked array slices. One issue 
that remains to be decided is whether or not to postpone raising an 
error for floats used as indexes. Sources may be found on Sourceforge 
 and 
both sources and OS X wheels are availble on pypi. Please test, 
hopefully this will be that last beta needed.


As a note on problems encountered, twine uploads continue to fail for 
me, but there are still variations to try. The wheeluploader 
downloaded wheels as it should, but could not upload them, giving the 
error message "HTTPError: 413 Client Error: Request Entity Too Large 
for url: https://www.python.org/pypi";. Firefox also complains that 
http://wheels.scipy.org is incorrectly configured with an invalid 
certificate.


Enjoy,

Chuck


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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[josef.pktd]

On Wed, Feb 10, 2016 at 5:36 PM, Charles R Harris  wrote:

>
>
> On Wed, Feb 10, 2016 at 2:58 PM, Pauli Virtanen  wrote:
>
>> 10.02.2016, 04:09, Charles R Harris kirjoitti:
>> > I'm pleased to announce the release of NumPy 1.11.0b3. This beta
>> contains
>> [clip]
>> > Please test, hopefully this will be that last beta needed.
>>
>> FWIW, https://travis-ci.org/pv/testrig/builds/108384173
>
>
> Thanks Pauli, very interesting.
>


Thanks Pauli, me too

is this intended?:

return np.r_[[np.nan] * head, x, [np.nan] * tail]
TypeError: 'numpy.float64' object cannot be interpreted as an index


In the old times of Python 2.x, statsmodels avoided integers so we don't
get accidental integer division.
Python wanted float() everywhere. Looks like numpy wants int() everywhere.
(fixed in statsmodels master)


Josef






>
> Chuck
>
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Charles R Harris]

On Wed, Feb 10, 2016 at 2:58 PM, Pauli Virtanen  wrote:

> 10.02.2016, 04:09, Charles R Harris kirjoitti:
> > I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
> [clip]
> > Please test, hopefully this will be that last beta needed.
>
> FWIW, https://travis-ci.org/pv/testrig/builds/108384173


Thanks Pauli, very interesting.

Chuck
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Re: [Numpy-discussion] NumPy 1.11.0b3 released.

[Pauli Virtanen]

10.02.2016, 04:09, Charles R Harris kirjoitti:
> I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
[clip]
> Please test, hopefully this will be that last beta needed.

FWIW, https://travis-ci.org/pv/testrig/builds/108384173


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[Numpy-discussion] NumPy 1.11.0b3 released.

[Charles R Harris]

Hi All,

I'm pleased to announce the release of NumPy 1.11.0b3. This beta contains
additional bug fixes as well as limiting the number of FutureWarnings
raised by assignment to masked array slices. One issue that remains to be
decided is whether or not to postpone raising an error for floats used as
indexes. Sources may be found on Sourceforge
 and both
sources and OS X wheels are availble on pypi. Please test, hopefully this
will be that last beta needed.

As a note on problems encountered, twine uploads continue to fail for me,
but there are still variations to try. The wheeluploader downloaded wheels
as it should, but could not upload them, giving the error message
"HTTPError: 413 Client Error: Request Entity Too Large for url:
https://www.python.org/pypi";. Firefox also complains that
http://wheels.scipy.org is incorrectly configured with an invalid
certificate.

Enjoy,

Chuck
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