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

[j***@gmail.com]

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

[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

Post by j***@gmail.com
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)
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
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NumPy-Discussion mailing list
https://mail.scipy.org/mailman/listinfo/numpy-discussion

[j***@gmail.com]

Post by CJ Carey
The short answer is: "kind of".
https://github.com/scipy/scipy/issues/3995
https://github.com/scipy/scipy/issues/4239

Thanks, I didn't pay attention to those issues, or only very superficially.

+1 for doing anything else than converting to object arrays.

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

The default should be overwritten for warnings that are always relevant.
I usually don't use sparse arrays, and don't know if this should always
warn.

Josef

Post by CJ Carey
-CJ

Post by j***@gmail.com
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)
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
https://mail.scipy.org/mailman/listinfo/numpy-discussion

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