On Thu, May 31, 2012 at 7:30 AM, Neal Becker wrote:
> That is, will:
>
> u[a:b] = u[c:d]
>
> always work (assuming the ranges of a:b, d:d are equal, or course)
It works most of the time. This thread shows you how to find an
example where it does not work:
http://mail.scipy.org/pipermail/numpy-d
Will copying slices always work correctly w/r to aliasing?
That is, will:
u[a:b] = u[c:d]
always work (assuming the ranges of a:b, d:d are equal, or course)
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Hi Wolfgang,
I thought maybe there is a trick for your specific operation.
Your array stacking is a simple case of the group-by operation and
normalization is aggregation followed by update.
I believe group-by and aggregation are on the NumPy todo-list.
You may have to write a small extension modu
Hey Val,
Well it doesn't matter what I do, but specifically I do factor =
sum(data_array[start_point:start_point+length_data]) and then
data[array[start_point:start_point+length_data]) /= factor. and that for every
star_point and length data.
How to do this fast?
Cheers
Wolfgang
On 2012-05-
Be sure to file a ticket...
-Travis
On May 30, 2012, at 9:05 PM, chris farrow wrote:
> Hi all,
>
> I encountered an odd bug today that I wanted to bring to everyone's
> attention. First the code:
>
> >>> import numpy as np
> >>> shape = (8, 8)
> >>> dtype = np.dtype(np.uint8)
> >>> image = np
