Hello,
Sorry for being insistent, but I recognize that I'm having a bad time
with NumPy data type rational. Is there an explanation for this?:
>>> numpy.dtype('i4').type
>>> numpy.dtype('int32').type
>>> numpy.dtype('i4').type == numpy.dtype('int32').type
True
So far so good, but is the next t
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Francesc Altet wrote:
> So far so good, but is the next the intended behaviour?
>
numpy.typeDict['i4']
>
numpy.typeDict['int32']
>
numpy.typeDict['i4'] == numpy.typeDict['int32']
> False
>
>
By way of comparison, I get (Linux/AMD 64):
In [1]: import numpy
In [2]: numpy.typeDic
El dc 27 de 09 del 2006 a les 10:01 +0100, en/na James Graham va
escriure:
> Francesc Altet wrote:
> > So far so good, but is the next the intended behaviour?
> >
> numpy.typeDict['i4']
> >
> numpy.typeDict['int32']
> >
> numpy.typeDict['i4'] == numpy.typeDict['int32']
> > False
>
Thanks for the hint,
that solved it!
Hanno
Charles R Harris <[EMAIL PROTECTED]> said:
> --=_Part_15501_7322175.1159288578594
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
> Content-Transfer-Encoding: 7bit
> Content-Disposition: inline
>
> On 9/26/06, Hanno Klemm <[EMAIL PR
On Tuesday, September 26, Robert Kern wrote:
> Please run numpy.test(10,10). That will print out the name of the test before
> running it. Thus we will find out which test is segfaulting.
Robert,
The last line is:
Check creation from list of list of tuplesSegmentation fault
This matches what gdb
Francesc Altet wrote:
> Hello,
>
> Sorry for being insistent, but I recognize that I'm having a bad time
> with NumPy data type rational. Is there an explanation for this?:
>
>
numpy.dtype('i4').type
>
>
numpy.dtype('int32').type
>
>
numpy.dtype
Francesc Altet wrote:
> Hello,
>
> Sorry for being insistent, but I recognize that I'm having a bad time
> with NumPy data type rational. Is there an explanation for this?:
>
>
Your actually talking about the array scalar types not the data-type
objects.
But, more to the point
numpy
El dc 27 de 09 del 2006 a les 11:01 -0600, en/na Travis Oliphant va
escriure:
> Francesc Altet wrote:
> > Hello,
> >
> > Sorry for being insistent, but I recognize that I'm having a bad time
> > with NumPy data type rational. Is there an explanation for this?:
> >
> >
> Your actually talking abo
Hi,
This is a vaguely formulated question ...
When I work with memmap'ed files/arrays I have a derived class
that adds special attributes to the array class (referring to the MRC image
file format used in medical / microscopy imaging)
What are the pros and cons for asarray() vs. asanyarray()
On
Sebastian Haase wrote:
> Hi,
> This is a vaguely formulated question ...
> When I work with memmap'ed files/arrays I have a derived class
> that adds special attributes to the array class (referring to the MRC image
> file format used in medical / microscopy imaging)
>
> What are the pros and con
During my NumPy Tutorial at the SciPy conference last month, somebody
asked the question about the memory requirements of index arrays that I
gave the wrong impression about. Here is the context and the correct
response that should alleviate concerns about large cross-product index
arrays.
I
Hi all,
I'd like to release numpy 1.0rc2 on about October 5 of next week.
Then, the release of numpy 1.0 official should happen on Monday, October
17. Please try and get all fixes and improvements in before then.
Backward-incompatible changes are not acceptable at this point (unless
they
Hello,
I just download the newly Python-2.5 and Numpy-1.0rc1 and all work fine
on Linux-x86 32 and 64bit platforms.
Now, I try to compile the both distributions on WindowsXP with
VisualStudio2003. No problem to compile Python-2.5, but i have some
troubles with Numpy-1.0rc1 and I didn't find an
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