Hi all, these are just a couple of small fixes to the string support in
Numexpr, and a test case for the string copy operation.
For the base patches:
1.http://www.mail-archive.com/numpy-discussion@lists.sourceforge.net/msg01551.html
2.http://www.mail-archive.com/numpy-discussion@lists.sourceforge
Hi,
Change set 3213 changed the data type printing with an array from
something like dtype=int64 to dtype='int64'. Although this is a small
cosmetic change it has broken all of the doctests I have written for
numpy code. I expect that I am not the only person this change has
caught. Please
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Hi,
I am sorry if I have missed anything obvious here, but is there a fast
simple way to downcast an array to the smallest storage that hold
array data within a specified precision - e.g.
a = array([1.0])
small_a = fantasy_function(a, rtol=1.0001e-05, atol=1e-08 )
b = array([1.2])
sm
Hi,
I have been bitten by a subtlety in numpy scalar divisions. The next
exposes the issue:
>>> -1/20
-1
>>> Numeric.array([-1])[0] / Numeric.array([20])[0]
-1
>>> numarray.array([-1])[0] / numarray.array([20])[0]
-1
>>> numpy.array([-1])[0] / numpy.array([20])[0]
0
After some digging, I've foun
Christopher Hanley wrote:
> Hi,
>
> Change set 3213 changed the data type printing with an array from
> something like dtype=int64 to dtype='int64'. Although this is a small
> cosmetic change it has broken all of the doctests I have written for
> numpy code.
I was changing the way dtypes print
Hi,
Anybody know if there is a map between NumPy types and Numeric
typecodes? Something like 'typecodes' for numarray:
>>> numarray.typecode
{'UInt64': 'U', 'Int32': 'i', 'Int16': 's', 'Float64': 'd', 'Object':
'O', 'UInt8': 'b', 'UInt32': 'u', 'Complex64': 'D', 'UInt16': 'w',
'Bool': 'B', 'Compl
Francesc Altet wrote:
>Hi,
>
>Anybody know if there is a map between NumPy types and Numeric
>typecodes? Something like 'typecodes' for numarray:
>
>
How about
dtype(obj).char?
-Travis
-
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El dl 25 de 09 del 2006 a les 11:08 -0600, en/na Travis Oliphant va
escriure:
> Francesc Altet wrote:
>
> >Hi,
> >
> >Anybody know if there is a map between NumPy types and Numeric
> >typecodes? Something like 'typecodes' for numarray:
> >
> >
> How about
>
> dtype(obj).char?
This doesn't work
Francesc Altet wrote:
>El dl 25 de 09 del 2006 a les 11:08 -0600, en/na Travis Oliphant va
>escriure:
>
>
>>Francesc Altet wrote:
>>
>>
>>
>>>Hi,
>>>
>>>Anybody know if there is a map between NumPy types and Numeric
>>>typecodes? Something like 'typecodes' for numarray:
>>>
>>>
Oh, yo
I've just tried building RC1 on OSX 10.4 (Intel), and it fails almost
immediately. This did not fail in the past with beta5 or from SVN:
Osoyoos:~/Development/numpy-1.0rc1 chris$ python setup.py build
Running from numpy source directory.
F2PY Version 2_3198
blas_opt_info:
FOUND:
extra_li
[EMAIL PROTECTED] wrote:
> I've just tried building RC1 on OSX 10.4 (Intel), and it fails almost
> immediately. This did not fail in the past with beta5 or from SVN:
It looks like a problem on your end:
> gcc: installation problem, cannot exec `cc1': No such file or directory
Can you build any
Ignore this query -- silly mistake on my part. Sorry.
On Sep 25, 2006, at 2:30 PM, [EMAIL PROTECTED] wrote:
> I've just tried building RC1 on OSX 10.4 (Intel), and it fails
> almost immediately. This did not fail in the past with beta5 or
> from SVN:
>
> Osoyoos:~/Development/numpy-1.0rc1 chr
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