Good day,
Reversing a 1-dimensional array in numpy is simple,
A = A[:,:,-1] .
However A is a new array referring to the old one and is no longer
contiguous.
While trying to reverse an array in place and keep it contiguous, I
encountered some weird behavior. The reason for keeping it
On Sun, Feb 03, 2008 at 12:25:56PM -0700, Damian Eads wrote:
On similar note, does the assignment
A = A * B
create a new array with a new buffer to hold the result of A * B, and
assign A to refer to the new array?
Yes. Without a JIT, Python cannot know that A is present both on the
Damian Eads wrote:
Good day,
Reversing a 1-dimensional array in numpy is simple,
A = A[:,:,-1] .
Err, I meant A=A[::-1] here. My apologies.
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Damian Eads wrote:
Here's another question: is there any way to construct a numpy array and
specify the buffer address where it should store its values? I ask
because I would like to construct numpy arrays that work on buffers that
come from mmap.
Can you clarify that a little? By buffer
Thanks Anne for your very informative response.
Anne Archibald wrote:
On 03/02/2008, Damian Eads [EMAIL PROTECTED] wrote:
Good day,
Reversing a 1-dimensional array in numpy is simple,
A = A[:,:,-1] .
However A is a new array referring to the old one and is no longer
contiguous.
Damian Eads wrote:
Robert Kern wrote:
Damian Eads wrote:
Here's another question: is there any way to construct a numpy array and
specify the buffer address where it should store its values? I ask
because I would like to construct numpy arrays that work on buffers that
come from mmap.
