On Jan 22, 2014, at 1:13 PM, Oscar Benjamin wrote:
>
> It's not safe to stop removing the null bytes. This is how numpy determines
> the length of the strings in a dtype='S' array. The strings are not
> "fixed-width" but rather have a maximum width.
Exactly--but folks have told us on this list t
On Tue, Jan 21, 2014 at 5:46 PM, Charles R Harris wrote:
>
>
>
> On Tue, Jan 21, 2014 at 9:26 AM, jennifer stone
> wrote:
>
>>
>> >What are your interests and experience? If you use numpy, are there
>>> things
>>> >you would like to fix, or enhancements you would like to see?
>>>
>>> Chuck
>>>
>
On Wed, Jan 22, 2014 at 12:07:28PM -0800, Chris Barker wrote:
> On Wed, Jan 22, 2014 at 2:46 AM, Oscar Benjamin
> wrote:
>
> > BTW, as much as the fixed-width 'S' dtype doesn't really work for str in
> > Python 3 it's also a poor fit for bytes since it strips trailing nulls:
> >
> > >>> a = np.ar
On Wed, Jan 22, 2014 at 2:46 AM, Oscar Benjamin
wrote:
> BTW, as much as the fixed-width 'S' dtype doesn't really work for str in
> Python 3 it's also a poor fit for bytes since it strips trailing nulls:
>
> >>> a = np.array(['a\0s\0', 'qwert'], dtype='S')
> >>> a
> array([b'a\x00s', b'qwert'],
>
Hi Oscar,
> Is it fair to say that people should really be using vlen utf-8 strings for
> text? Is it problematic because of the need to interface with non-Python
> libraries using the same hdf5 file?
The general recommendation has been to use fixed-width strings for
exactly that reason; FORTRAN
On 22.01.2014 18:23, Ralf Juengling wrote:
> Executing the following code,
>
>
>
import numpy as np
>
a = np.zeros((3,))
>
w = np.array([0, 1, 0, 1, 2])
>
v = np.array([10.0, 1, 10.0, 2, 9])
>
a[w] += v
>
>
>
> I was expecting ‘a’ to be array([20., 3., 9.]. Inst
On Wed, 2014-01-22 at 17:23 +, Ralf Juengling wrote:
> Executing the following code,
>
>
>
> >>> import numpy as np
>
> >>> a = np.zeros((3,))
>
> >>> w = np.array([0, 1, 0, 1, 2])
>
> >>> v = np.array([10.0, 1, 10.0, 2, 9])
>
> >>> a[w] += v
>
>
>
> I was expecting ‘a’ to be array(
Executing the following code,
>>> import numpy as np
>>> a = np.zeros((3,))
>>> w = np.array([0, 1, 0, 1, 2])
>>> v = np.array([10.0, 1, 10.0, 2, 9])
>>> a[w] += v
I was expecting 'a' to be array([20., 3., 9.]. Instead I get
>>> a
array([ 10., 2., 9.])
This with numpy version 1.6.1.
Is ther
On Wed, 2014-01-22 at 07:58 +0100, Dr. Leo wrote:
> Hi,
>
> thanks. Both recarray and itertools.chain work just fine in the example
> case.
>
> However, the real purpose of this is to read strings from a large xml
> file into a pandas DataFrame. But fromiter cannot create arrays of dtype
> 'objec
On Tue, Jan 21, 2014 at 06:54:33PM -0700, Andrew Collette wrote:
> Hi Chris,
>
> > it looks from here:
> > http://www.hdfgroup.org/HDF5/doc/ADGuide/WhatsNew180.html
> >
> > that HDF uses utf-8 for unicode strings -- so you _could_ roundtrip with a
> > lot of calls to encode/decode -- which could b
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