[Numpy-discussion] Problem migrating PDL's index() into NumPy

josef.pktd@gmai... josef.pktd@gmai...
Wed Mar 17 06:30:27 CDT 2010


On Wed, Mar 17, 2010 at 7:12 AM, Miroslav Sedivy
<miroslav.sedivy@weather-consult.com> wrote:
> Hello,
>
> being quite new to NumPy and having used previously PDL in Perl, I am
> currently migrating one of my PDL projects into NumPy.
>
> Most of the functions can be migrated without problems and there are
> functions in NumPy that allow me to do things in much clearer way than
> in PDL. However, I have a problem with the following operation:
>
> There are two 2D arrays with dimensions: A[10000,1000] and B[10000,100].
> The first dimension of both arrays corresponds to a list of 10000 objects.
>
> The array A contains for each of 10000 objects 1000 integer values
> between 0 and 99, so that for each of 10000 objects a corresponding
> value can be found in the array B.
>
> I need a new array C[10000,1000] with values from B the following way:
>
> for x in range(10000):
>    for y in range(1000):
>       C[x,y] = B[x,A[x,y]]
>
> In Perl's PDL, this can be done with $C = $B->index($A)
>
> If in NumPy I do C = B[A], then I do not get a [10000,1000] 2D array,
> but rather a [10000,1000,1000] 3D array, in which I can find the correct
> values on the following positions:
>
> for x in range(10000):
>    for y in range(1000):
>       C[x,y,y]
>
> which may seem nice, but it needs 1000 times more memory and very
> probably 1000 times more time to calculate... Impossible with such large
> arrays... :-(
>
> Could anyone help me, please?

try
C = B[:,A]
or
C = B[np.arange(1000)[:,None], A]

I think, one of the two (or both) should work (but no time for trying it myself)

Josef

>
> Regards,
> Miroslav Sedivy
>
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