On 22 Aug 2011, at 14:50, Travis Oliphant wrote:
> This goes into the category of "feature". Structured arrays use
> tuples to indicate a record. So, (only) when using structured
> arrays as a dtype, there is a difference between lists and
> tuples.In this case, array sees the tuple a
On Mon, Aug 22, 2011 at 10:07, Chris Withers wrote:
> On 22/08/2011 00:18, Mark Dickinson wrote:
>> On Sun, Aug 21, 2011 at 1:08 AM, Robert Kern wrote:
>>> You may want to try the cdecimal package:
>>>
>>> http://pypi.python.org/pypi/cdecimal/
>>
>> I'll second this suggestion. cdecimal is an
Hi,
On Sun, Aug 21, 2011 at 1:53 AM, Ben Walsh wrote:
>
> Hi
>
> My bad. Very sorry about that, guys.
>
> There's a patch for this here:
>
> https://github.com/walshb/numpy/tree/fix_np_lookfor_segv
>
> And I submitted a pull request. I'll add something to the tests too when I
> have a little more
On 19 August 2011 16:11, Matthew Brett wrote:
> Hi,
>
> On Fri, Aug 19, 2011 at 1:04 PM, Angus McMorland wrote:
>> Hi all,
>>
>> I'm giving this email a new subject, in case that helps it catch the
>> attention of someone who can fix my problem. I currently cannot
>> upgrade numpy from git to any
On Mon, Aug 22, 2011 at 4:07 PM, Chris Withers wrote:
> On 22/08/2011 00:18, Mark Dickinson wrote:
>>
>> On Sun, Aug 21, 2011 at 1:08 AM, Robert Kern
>> wrote:
>>>
>>> You may want to try the cdecimal package:
>>>
>>> http://pypi.python.org/pypi/cdecimal/
>>
>> I'll second this suggestion. cdec
On 22/08/2011 00:18, Mark Dickinson wrote:
> On Sun, Aug 21, 2011 at 1:08 AM, Robert Kern wrote:
>> You may want to try the cdecimal package:
>>
>> http://pypi.python.org/pypi/cdecimal/
>
> I'll second this suggestion. cdecimal is an extraordinarily carefully
> written and well-tested (almost)
This goes into the category of "feature". Structured arrays use tuples to
indicate a record. So, (only) when using structured arrays as a dtype, there
is a difference between lists and tuples.In this case, array sees the tuple
and expects it to have 2 elements to match the number of field
On Mon, Aug 22, 2011 at 1:30 PM, Stefan Krah wrote:
> Numpy arrays and memoryview currently have different representations
> for shape and strides if ndim = 0:
>
from numpy import *
x = array(9, int32)
x.ndim
> 0
x.shape
> ()
x.strides
> ()
m = memoryview(x)
m.nd
Hello,
Numpy arrays and memoryview currently have different representations
for shape and strides if ndim = 0:
>>> from numpy import *
>>> x = array(9, int32)
>>> x.ndim
0
>>> x.shape
()
>>> x.strides
()
>>> m = memoryview(x)
>>> m.ndim
0L
>>> m.shape is None
True
>>> m.strides is None
True
I t
Hi everyone,
I just stumbled on a behavior in NumPy for which I can't find an
explanation in the documentation. I wonder whether this is a bug or an
undocumented (or badly documented) feature:
--
import numpy
On Sun, Aug 21, 2011 at 1:08 AM, Robert Kern wrote:
> You may want to try the cdecimal package:
>
> http://pypi.python.org/pypi/cdecimal/
I'll second this suggestion. cdecimal is an extraordinarily carefully
written and well-tested (almost) drop-in replacement for the decimal
module, and well w
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