On 6 February 2012 21:41, Ralf Gommers wrote:
>
>
> On Mon, Feb 6, 2012 at 8:17 AM, Scott Sinclair
> wrote:
>>
>> On 5 February 2012 13:07, Ralf Gommers
>> wrote:
>> >
>> > Does it need to be a new repo, or would permissions on
>> > https://github.com/numpy/numpy.scipy.org work as well?
>>
>> Ye
irfftn is an optimization for real input and does not take complex
input. You have to use numpy.fft.ifftn instead:
import numpy
a_shape = (63, 4, 98)
a = numpy.complex128(numpy.random.rand(*a_shape)+\
> ... 1j*numpy.random.rand(*a_shape))
axes = [0, 2]
numpy.
Hi,
Sorry for my latest post, hands way too quick ;(
On Mon, Feb 6, 2012 at 9:16 PM, Moroney, Catherine M (388D) <
catherine.m.moro...@jpl.nasa.gov> wrote:
> Hello,
>
> I have to write a code to downsample an array in a specific way, and I am
> hoping that
> somebody can tell me how to do this w
2012/2/6 Stéfan van der Walt
> Hi all,
>
> I noticed the following docstring on ``np.polynomial.polyval``:
>
> In [116]: np.polynomial.polyval?
> File: /home/stefan/src/numpy/numpy/lib/utils.py
> Definition: np.polynomial.polyval(*args, **kwds)
> Docstring:
> `polyval` is deprecated!
> Plea
Hi,
On Mon, Feb 6, 2012 at 9:16 PM, Moroney, Catherine M (388D) <
catherine.m.moro...@jpl.nasa.gov> wrote:
> Hello,
>
> I have to write a code to downsample an array in a specific way, and I am
> hoping that
> somebody can tell me how to do this without the nested do-loops. Here is
> the problem
On Mon, Feb 6, 2012 at 1:17 AM, Wes McKinney wrote:
>
> Whenever I get motivated enough I'm going to make a pull request on
> NumPy with something like khash.h and start fixing all the O(N log N)
> algorithms floating around that ought to be O(N). NumPy should really
> have a "match" function sim
That makes sense.
I figured that ambiguity was the reason it was removed.
Thank you for the explanation. I'm a big fan of your work.
John
On Mon, Feb 6, 2012 at 1:18 PM, Mark Wiebe wrote:
> Hey John,
>
> NumPy doesn't provide this, because it's already provided by the
> datetime.date.strftime
On Sat, Feb 4, 2012 at 3:55 PM, Ralf Gommers
wrote:
>
>
> On Wed, Dec 14, 2011 at 6:50 PM, Ralf Gommers
> wrote:
>>
>>
>>
>> On Wed, Dec 14, 2011 at 3:04 PM, David Cournapeau
>> wrote:
>>>
>>> On Tue, Dec 13, 2011 at 3:43 PM, Ralf Gommers
>>> wrote:
>>> > On Sun, Oct 30, 2011 at 12:18 PM, David
>
> # Make a 4D view of this data, such that b[i,j]
> # is a 2D block with shape (4,4) (e.g. b[0,0] is
> # the same as a[:4, :4]).
> b = as_strided(a, shape=(a.shape[0]/4, a.shape[1]/4, 4, 4),
>strides=(4*a.strides[0], 4*a.strides[1], a.strides[0],
> a.strides[1]))
>
Yes :-) B
Hey John,
NumPy doesn't provide this, because it's already provided by the
datetime.date.strftime function in Python:
http://docs.python.org/library/datetime.html#datetime.date.strftime
One reason this format isn't supported automatically is that parsing
"MM/dd/YY" is inherently ambiguous, and t
The last t1 on each lineis of course t2. Sorry for the typo. Hard to code on an
ipad ;-)
Sturla
Sendt fra min iPad
Den 6. feb. 2012 kl. 22:12 skrev Sturla Molden :
>
> Something like this:
>
> m,n = data.shape
> x = data.reshape((m,n//4,4))
> z = (x[0::4,...] >= t1) & (x[0::4,...] <= t1)
>
Something like this:
m,n = data.shape
x = data.reshape((m,n//4,4))
z = (x[0::4,...] >= t1) & (x[0::4,...] <= t1)
z |= (x[1::4,...] >= t1) & (x[1::4,...] <= t1)
z |= (x[2::4,...] >= t1) & (x[2::4,...] <= t1)
z |= (x[3::4,...] >= t1) & (x[3::4,...] <= t1)
found = np.any(z, axis=2)
Sturla
Sendt f
On Mon, Feb 6, 2012 at 2:57 PM, Sturla Molden wrote:
> Short answer: Create 16 view arrays, each with a stride of 4 in both
> dimensions. Test them against the conditions and combine the tests with an
> |= operator. Thus you replace the nested loop with one that has only 16
> iterations. Or resha
Short answer: Create 16 view arrays, each with a stride of 4 in both
dimensions. Test them against the conditions and combine the tests with an |=
operator. Thus you replace the nested loop with one that has only 16
iterations. Or reshape to 3 dimensions, the last with length 4, and you can do
Hello,
Is there a way to specify a format for the datetime64 constructor? The
constructor doesn't have a doc. I have dates in a file with the format
"MM/dd/YY". datetime64 used to be able to parse these in 1.6.1 but the dev
version throws an error.
Cheers,
John
___
The namespace is different. If you want to use numpy.sin(), for
example, you would use:
import numpy as np
np.sin(angle)
or
from numpy import *
sin(angle)
I generally prefer the first option because then I don't need to worry
about multiple imports writing on top of each other (i.e., having te
On Mon, Feb 6, 2012 at 8:17 AM, Scott Sinclair
wrote:
> On 5 February 2012 13:07, Ralf Gommers
> wrote:
> >
> >> On 20/01/12 08:49, Scott Sinclair wrote:
> >> > On 19 January 2012 21:48, Fernando Perez
> wrote:
> >> >> We've moved to the following setup with ipython, which works very
> well
> >>
David: from 9-10 minutes to about 2-3 seconds, it's amazing!
Thanks,
Naresh
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basic difference between the commands:
import numpy as np
from numpy import *
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Hi all,
I noticed the following docstring on ``np.polynomial.polyval``:
In [116]: np.polynomial.polyval?
File: /home/stefan/src/numpy/numpy/lib/utils.py
Definition: np.polynomial.polyval(*args, **kwds)
Docstring:
`polyval` is deprecated!
Please import polyval from numpy.polynomial.polynomia
Hello,
I have to write a code to downsample an array in a specific way, and I am
hoping that
somebody can tell me how to do this without the nested do-loops. Here is the
problem
statement: Segment a (MXN) array into 4x4 squares and set a flag if any of the
pixels
in that 4x4 square meet a cer
Is the following behaviour expected:
>>> import numpy
>>> a_shape = (63, 4, 98)
>>> a = numpy.complex128(numpy.random.rand(*a_shape)+\
... 1j*numpy.random.rand(*a_shape))
>>>
>>> axes = [0, 2]
>>>
>>> numpy.fft.irfftn(a, axes=axes)
Traceback (most recent call last):
File "", line 1, in
I have two large matrices, say, ABC and DEF, each with a shape of 7000 by
4500. I have another list, say, elem, containing 850 values from ABC. I am
interested in finding out the corresponding values in DEF where ABC has
elem and store them *separately*. The code that I am using is:
for i in range
On Sun, Feb 5, 2012 at 10:41 AM, Paolo wrote:
> I solved using 'rb' instead of 'r' option in the open file task.
>
> that would do it, if it's binary data, but you might as well so it
"right":
> matrix="".join(f.readlines())
>
> readlines is giving you a list of the data, as separated by newlin
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