On Thu, Oct 20, 2011 at 10:08 AM, Mathieu Blondel <[email protected]> wrote:
> On Thu, Oct 20, 2011 at 10:41 PM, Virgile Fritsch
> <[email protected]> wrote:
>> In both cases, we would need to write some more lines of code to deal with a
>> np.matrix input (whether it is for converting it or rejecting it, we need to
>> test the object type). The code will be a bit more complex whatever the
>> adopted solution is, therefore I vote for "converting" since at least the
>> end user will appreciate this functionality.
>
> Will converting the matrix imply that the data exists twice in memory
> at some point? Doing things behind the scene is not so nice, so I'd
> prefer to raise an exception to force the user to change his/her
> user-land code.

No, np.asarray is standard if you need an array and it does not copy
for subtypes

>>> a = np.matrix(np.random.randn(3,4))
>>> b = np.asarray(a)
>>> b.flags
OWNDATA : False

Josef

>
> Mathieu
>
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