[Numpy-discussion] asarray(sparse) -> object

[CJ Carey]

The short answer is: "kind of".

These two Github issues explain what's going on more in-depth:
https://github.com/scipy/scipy/issues/3995
https://github.com/scipy/scipy/issues/4239

As for the warning only showing once, that's Python's default behavior for
warnings: http://stackoverflow.com/q/22661745/10601

-CJ

On Fri, Nov 20, 2015 at 2:40 PM, <josef.pktd at gmail.com> wrote:

> Is this intentional?
>
>
> >>> exog
> <50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>
>
> >>> np.asarray(exog)
> array(<50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>, dtype=object)
>
>
> I'm just a newbie who thought to use the usual pattern.
>
>
> ....
>
> >>> np.asarray(exog).dot(beta)
> array([ <50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>,
>        <50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>,
>        <50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>,
>        <50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>,
>        <50x5 sparse matrix of type '<class 'numpy.float64'>'
> with 50 stored elements in Compressed Sparse Column format>], dtype=object)
> C:\programs\WinPython-64bit-3.4.3.1\python-3.4.3.amd64\lib\site-packages\scipy\sparse\compressed.py:306:
> SparseEfficiencyWarning: Comparing sparse matrices using >= and <= is
> inefficient, using <, >, or !=, instead.
>   "using <, >, or !=, instead.", SparseEfficiencyWarning)
>
> seems to warn only once
>
> >>> y = np.asarray(exog).dot(beta)
> >>> y.shape
> (5,)
>
>
> >>> np.__version__
> '1.9.2rc1'
>
> >>> scipy.__version__
> '0.15.1'
>
>
>
> Josef
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion at scipy.org
> https://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/numpy-discussion/attachments/20151120/1fd76aee/attachment.html>