Hello, I am really liking Numpy a lot. It is wonderful to be able to do
the things that it does in a language as friendly as Python, and with
the performance Numpy delivers over standard Python. Thanks.
I am having a problem with creation of Numpy arrays with my generated
dtypes. I am creating
On May 14, 2010, at 16:03 , josef.p...@gmail.com wrote:
> On Fri, May 14, 2010 at 3:26 PM, wrote:
>> On Fri, May 14, 2010 at 2:43 PM, Brian Blais
>> wrote:
>>> Hello,
>>>
>>> I have the following code, where I noticed a memory leak with +=,
>>> but
>>> not with + alone.
>>> import numpy
>>>
Chris Barker wrote:
> I can't find it right now, but I'm pretty sure there is a function that
> will re-shape an array to remove the length-1 dimensions -- maybe that's
> what the OP needs.
it's np.squeeze()
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOA
>> Second, treating a
>> unit dimension differently from a non-unit dimension *is* making it a
>> special case, and often--usually--one does not want that. It is
>> perfectly reasonable to have an algorithm that uses values sorted along
>> the last axis, even if that dimension sometimes turns out
On Fri, May 14, 2010 at 17:29, Eric Firing wrote:
> On 05/14/2010 11:03 AM, Dr. Phillip M. Feldman wrote:
>>
>> Robert Kern-2 wrote:
>>>
>>> On Wed, May 12, 2010 at 20:19, Dr. Phillip M. Feldman
>>> wrote:
When operating on an array whose last dimension is unity, the default
behav
The setup:
>>> Adata
array([(1, 24, 'Male', '', 212, 193, 'High Pass'),
(2, 26, 'Male', 'Caucasian', 234, 221, 'Honors'),
(3, 31, 'Female', 'Caucasian', 182, 189, ''),
(4, 27, 'Female', 'Hispanic', 214, 211, 'High Pass'),
(5, 27, 'Female', 'Asian', 213, 204, 'Pass'),
On 05/14/2010 11:03 AM, Dr. Phillip M. Feldman wrote:
>
>
>
> Robert Kern-2 wrote:
>>
>> On Wed, May 12, 2010 at 20:19, Dr. Phillip M. Feldman
>> wrote:
>>>
>>> When operating on an array whose last dimension is unity, the default
>>> behavior of argsort is not very useful:
>>>
>>> |6> x=random.
Robert Kern-2 wrote:
>
> On Wed, May 12, 2010 at 20:19, Dr. Phillip M. Feldman
> wrote:
>>
>> When operating on an array whose last dimension is unity, the default
>> behavior of argsort is not very useful:
>>
>> |6> x=random.random((4,1))
>> |7> shape(x)
>> <7> (4, 1)
>>
On Fri, May 14, 2010 at 3:26 PM, wrote:
> On Fri, May 14, 2010 at 2:43 PM, Brian Blais wrote:
>> Hello,
>>
>> I have the following code, where I noticed a memory leak with +=, but
>> not with + alone.
>> import numpy
>>
>> m=numpy.matrix(numpy.ones((23,23)))
>>
>> for i in range(1000):
>>
On Fri, May 14, 2010 at 2:43 PM, Brian Blais wrote:
> Hello,
>
> I have the following code, where I noticed a memory leak with +=, but
> not with + alone.
> import numpy
>
> m=numpy.matrix(numpy.ones((23,23)))
>
> for i in range(1000):
> m+=0.0 # keeps growing in memory
> # m=m+0.0
Hello,
I have the following code, where I noticed a memory leak with +=, but
not with + alone.
import numpy
m=numpy.matrix(numpy.ones((23,23)))
for i in range(1000):
m+=0.0 # keeps growing in memory
#m=m+0.0 # is stable in memory
My version of python is 2.5, numpy 1.3.0,
On May 13, 2010, at 11:51 PM, Vincent Davis wrote:
>> Because the use of `missing` is deprecated (try to use anything but '' for
>> missing, and you'll get a deprecation warning).
>> Use `missing_values` instead.
>
> I wasn't using 'missing' but was wondering what it did.
>
> @Pierre, Stéfan van
On Wed, May 12, 2010 at 20:19, Dr. Phillip M. Feldman
wrote:
>
> When operating on an array whose last dimension is unity, the default
> behavior of argsort is not very useful:
>
> |6> x=random.random((4,1))
> |7> shape(x)
> <7> (4, 1)
> |8> argsort(x)
> <
We are glad to announce release 2.6 of the Modular toolkit for Data
Processing (MDP).
MDP is a Python library of widely used data processing algorithms
that can be combined according to a pipeline analogy to build more
complex data processing software. The base of available algorithms
includes, to
14 matches
Mail list logo
