Travis E. Oliphant wrote:
> Damian Eads wrote:
>> This is good to know because there have been a few situations when this
>> would have been very useful.
>>
>> Suppose I do something like (in Python):
>>
>>import ctypes
>>mylib = ctypes.CDLL('libmylib.so')
>>y = mylib.get_float_array_f
Damian Eads wrote:
>
> This is good to know because there have been a few situations when this
> would have been very useful.
>
> Suppose I do something like (in Python):
>
>import ctypes
>mylib = ctypes.CDLL('libmylib.so')
>y = mylib.get_float_array_from_c_function()
>
> which returns
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
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.
>
> Can you cl
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 "buff
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 longe
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.
>
> While trying to reverse an array in place and keep it contig
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 t
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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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 c
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