On Wed, Jun 9, 2010 at 1:16 PM, Alan G Isaac wrote:
> On 6/9/2010 12:49 PM, greg whittier wrote:
>> Is there a way to do A*A.T without two
>> copies of A?
>
> Does this do what you want?
> Alan Isaac
np.tensordot(a,a,axes=(-1,-1))
This seems to suffer from the same problem. A temporary arra
Alan G Isaac wrote:
> On 6/9/2010 12:49 PM, greg whittier wrote:
>
>> Is there a way to do A*A.T without two
>> copies of A?
>>
>
> Does this do what you want?
> Alan Isaac
>
>
a
> array([[0, 1],
> [2, 3],
> [4, 5],
> [6, 7],
> [8, 9]])
On 6/9/2010 12:49 PM, greg whittier wrote:
> Is there a way to do A*A.T without two
> copies of A?
Does this do what you want?
Alan Isaac
>>> a
array([[0, 1],
[2, 3],
[4, 5],
[6, 7],
[8, 9]])
>>> np.tensordot(a,a,axes=(-1,-1))
array([[ 1, 3, 5, 7, 9],
On Wed, Jun 9, 2010 at 12:57 PM, "V. Armando Solé" wrote:
> greg whittier wrote:
>> a = np.ones((400, 50), dtype=np.float32)
>> c = np.dot(a, a.T)
>>
>>
> In such cases I create a matrix of zeros with the final size and I fill
> it with a loop of dot products of smaller chunks of the original
greg whittier wrote:
> When I run
>
> import numpy as np
>
> a = np.ones((400, 50), dtype=np.float32)
> c = np.dot(a, a.T)
>
> produces a "MemoryError" on the 32-bit Enthought Python Distribution
> on 32-bit Vista. I understand this has to do with the 2GB limit with
> 32-bit python and the fac
When I run
import numpy as np
a = np.ones((400, 50), dtype=np.float32)
c = np.dot(a, a.T)
produces a "MemoryError" on the 32-bit Enthought Python Distribution
on 32-bit Vista. I understand this has to do with the 2GB limit with
32-bit python and the fact numpy wants a contiguous chunk of me
