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
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 fact numpy
On Wed, Jun 9, 2010 at 12:57 PM, V. Armando Solé s...@esrf.fr 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
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],
[
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 Wed, Jun 9, 2010 at 1:16 PM, Alan G Isaac ais...@american.edu 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
