On Fri, Aug 27, 2010 at 2:47 PM, Robert Kern wrote:
> On Fri, Aug 27, 2010 at 15:32, David Huard wrote:
> > Nils and Joseph,
> > Thanks for the bug report, this is now fixed in SVN (r8672).
>
> While we're at it, can we change the name of the argument? "normed"
> has caused so much confusion ove
On 2010-08-27, at 5:15 PM, Robert Kern wrote:
>> How would people feel about an optional argument to support this behaviour?
>> I'd be happy with either a "minlength" or an "exactly this length" with
>> values above this range being ignored, but it seems like the latter might be
>> useful in mo
On Fri, Aug 27, 2010 at 1:35 PM, Robert Kern wrote:
> [~]
> |8> %timeit kern_in(ar, valid)
> 10 loops, best of 3: 115 ms per loop
>
> [~]
> |9> %timeit np.in1d(ar, valid)
> 1 loops, best of 3: 279 ms per loop
>
> As valid gets larger, in1d() will catch up but for smallish sizes of
> valid, which I
On Fri, Aug 27, 2010 at 16:13, David Warde-Farley wrote:
> I've been using bincount() in situations where I always want the count vector
> to be a certain fixed length, even if the upper bins are 0. e.g. I want the
> counts of 0 through 9, and if there are no 9's in the vector I'm counting,
> I
I've been using bincount() in situations where I always want the count vector
to be a certain fixed length, even if the upper bins are 0. e.g. I want the
counts of 0 through 9, and if there are no 9's in the vector I'm counting, I'd
still like it to be at least length 10. It's kind of a pain to
On Fri, Aug 27, 2010 at 15:32, David Huard wrote:
> Nils and Joseph,
> Thanks for the bug report, this is now fixed in SVN (r8672).
While we're at it, can we change the name of the argument? "normed"
has caused so much confusion over the years. We could deprecate
normed=True in favor of pdf=True
On Fri, Aug 27, 2010 at 15:21, Nathaniel Smith wrote:
> On Fri, Aug 27, 2010 at 1:17 PM, Robert Kern wrote:
>> But in any case, that would be very slow for large arrays since it
>> would invoke a Python function call for every value in ar. Instead,
>> iterate over the valid array, which is much s
Nils and Joseph,
Thanks for the bug report, this is now fixed in SVN (r8672).
Ralph. is this something that you want to see backported in 1.5 ?
Regards,
David
On Fri, Aug 6, 2010 at 7:49 PM, wrote:
> On Fri, Aug 6, 2010 at 4:53 PM, Nils Becker wrote:
> > Hi again,
> >
> > first a correctio
On Fri, Aug 27, 2010 at 4:17 PM, Robert Kern wrote:
> On Fri, Aug 27, 2010 at 15:10, Ken Watford wrote:
>> On Fri, Aug 27, 2010 at 3:58 PM, Brett Olsen wrote:
>>> Hello,
>>>
>>> I have an array of non-numeric data, and I want to create a boolean
>>> array denoting whether each element in this ar
On 27 August 2010 16:17, Robert Kern wrote:
> On Fri, Aug 27, 2010 at 15:10, Ken Watford wrote:
>> On Fri, Aug 27, 2010 at 3:58 PM, Brett Olsen wrote:
>>> Hello,
>>>
>>> I have an array of non-numeric data, and I want to create a boolean
>>> array denoting whether each element in this array is a
On Fri, Aug 27, 2010 at 1:17 PM, Robert Kern wrote:
> But in any case, that would be very slow for large arrays since it
> would invoke a Python function call for every value in ar. Instead,
> iterate over the valid array, which is much shorter:
>
> mask = np.zeros(ar.shape, dtype=bool)
> for good
On Fri, Aug 27, 2010 at 15:10, Ken Watford wrote:
> On Fri, Aug 27, 2010 at 3:58 PM, Brett Olsen wrote:
>> Hello,
>>
>> I have an array of non-numeric data, and I want to create a boolean
>> array denoting whether each element in this array is a "valid" value
>> or not. This is straightforward i
On Fri, Aug 27, 2010 at 3:58 PM, Brett Olsen wrote:
> Hello,
>
> I have an array of non-numeric data, and I want to create a boolean
> array denoting whether each element in this array is a "valid" value
> or not. This is straightforward if there's only one possible valid
> value:
import num
Hello,
I have an array of non-numeric data, and I want to create a boolean
array denoting whether each element in this array is a "valid" value
or not. This is straightforward if there's only one possible valid
value:
>>> import numpy as N
>>> ar = N.array(("a", "b", "c", "b", "b", "a", "d", "c",
=
Announcing carray 0.2
=
What it is
==
carray is a container for numerical data that can be compressed
in-memory. The compresion process is carried out internally by Blosc,
a high-performance compressor that is optimized for binary data.
Having d
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