On Wed, Jul 16, 2014 at 1:47 PM, Ralf Gommers
wrote:
>
>
>
> On Wed, Jul 16, 2014 at 6:37 AM, Tony Yu wrote:
>
>> Is there any reason why the defaults for `allclose` and `assert_allclose`
>> differ? This makes debugging a broken test much more difficult. More
>&g
Is there any reason why the defaults for `allclose` and `assert_allclose`
differ? This makes debugging a broken test much more difficult. More
importantly, using an absolute tolerance of 0 causes failures for some
common cases. For example, if two values are very close to zero, a test
will fail:
On Tue, Feb 18, 2014 at 11:11 AM, Jaime Fernández del Río <
jaime.f...@gmail.com> wrote:
>
>
>
> On Tue, Feb 18, 2014 at 9:03 AM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>>
>> On Tue, Feb 18, 2014 at 9:40 AM, Nathaniel Smith wrote:
>>
>>> On 18 Feb 2014 11:05, "Charles R Ha
Announcement: scikits-image 0.7.0
=
We're happy to announce the 7th version of scikits-image!
Scikits-image is an image processing toolbox for SciPy that includes
algorithms
for segmentation, geometric transformations, color space manipulation,
analysis, filtering,
On Fri, Jul 27, 2012 at 11:39 AM, Derek Homeier <
de...@astro.physik.uni-goettingen.de> wrote:
> On 27.07.2012, at 3:27PM, Benjamin Root wrote:
>
> > > I would prefer not to use: from xxx import *,
> > >
> > > because of the name pollution.
> > >
> > > The name convention that I copied above fac
On Mon, Jun 18, 2012 at 11:55 AM, bob tnur wrote:
> Hi,
> how I can convert (by adding zero) of any non-square numpy matrix in to
> square matrix using numpy? then how to find the minimum number in each row
> except the zeros added(for making square matrix)? ;)
>
> ___
On Sun, May 20, 2012 at 3:47 AM, eat wrote:
> Hi,
>
> On Sun, May 20, 2012 at 10:21 AM, Chao YUE wrote:
>
>> Dear all,
>>
>> could anybody give one sentence about this? why in the loop I didn't get
>> zerodivision error by when I explicitly do this, I get a zerodivision
>> error? thanks.
>>
>> I
On Thu, May 3, 2012 at 9:57 AM, Robert Kern wrote:
> On Thu, May 3, 2012 at 2:50 PM, Robert Elsner wrote:
> >
> > Am 03.05.2012 15:45, schrieb Robert Kern:
> >> On Thu, May 3, 2012 at 2:24 PM, Robert Elsner
> wrote:
> >>> Hello Everybody,
> >>>
> >>> is there any news on the status of np.bincou
On Fri, Apr 20, 2012 at 2:15 PM, Andre Martel wrote:
> What would be the best way to remove the maximum from a cube and
> "collapse" the remaining elements along the z-axis ?
> For example, I want to reduce Cube to NewCube:
>
> >>> Cube
> array([[[ 13, 2, 3, 42],
> [ 5, 100, 7,
On Mon, Apr 16, 2012 at 6:01 PM, Skipper Seabold wrote:
> On Mon, Apr 16, 2012 at 5:51 PM, Tony Yu wrote:
> >
> >
> > On Mon, Apr 16, 2012 at 5:27 PM, Skipper Seabold
> > wrote:
> >>
> >> Hi,
> >>
> >> I have a pull request here [1
On Mon, Apr 16, 2012 at 5:27 PM, Skipper Seabold wrote:
> Hi,
>
> I have a pull request here [1] to add a cut function similar to R's
> [2]. It seems there are often requests for similar functionality. It's
> something I'm making use of for my own work and would like to use in
> statstmodels and i
On Mon, Apr 9, 2012 at 12:22 PM, Benjamin Root wrote:
>
>
> On Mon, Apr 9, 2012 at 12:14 PM, Jonathan T. Niehof wrote:
>
>> On 04/06/2012 06:54 AM, Benjamin Root wrote:
>>
>> > Take a peek at how np.gradient() does it. It creates a list of None with
>> > a length equal to the number of dimensions
On Fri, Apr 6, 2012 at 8:54 AM, Benjamin Root wrote:
>
>
> On Friday, April 6, 2012, Val Kalatsky wrote:
>
>>
>> The only slicing short-cut I can think of is the Ellipsis object, but
>> it's not going to help you much here.
>> The alternatives that come to my mind are (1) manipulation of shape
>>
Is there a way to slice an nd-array along a specified axis? It's easy to
slice along a fixed axis, e.g.:
axis = 0:
>>> array[start:end]
axis = 1:
>>> array[:, start:end]
...
But I need to do this inside of a function that accepts arrays of any
dimension, and the user can operate on any axis of t
On Thu, Feb 9, 2012 at 2:47 PM, Eric Firing wrote:
> On 02/09/2012 09:20 AM, Drew Frank wrote:
> > Eric Firing hawaii.edu> writes:
> >
> >>
> >> On 02/08/2012 09:31 PM, teomat wrote:
> >>>
> >>> Hi,
> >>>
> >>> Am I wrong or the numpy.arange() function is not correct 100%?
> >>>
> >>> Try to do
On Wed, Feb 8, 2012 at 11:32 AM, Stephanie Cooke
wrote:
> Hello,
>
> When I try to use the command hstack, I am given the error message
> "TypeError: hstack() takes exactly 1 argument (2 given)". I have a 9X1
> array (called array) that I would like to concatenate to a 9X2 matrix
> (called matrix)
On Fri, Jan 27, 2012 at 9:28 AM, Paul Anton Letnes <
paul.anton.let...@gmail.com> wrote:
>
> On 27. jan. 2012, at 14:52, Chao YUE wrote:
>
> > Dear all,
> >
> > suppose I have a ndarray a:
> >
> > In [66]: a
> > Out[66]: array([0, 1, 2, 3, 4])
> >
> > how can use it as 5X1 array without doing a=a.
On Sun, Jan 15, 2012 at 10:45 AM, wrote:
>
> Counting the Colors of RGB-Image,
> nameit im0 with im0.shape = 2500,3500,3
> with this code:
>
> tab0 = zeros( (256,256,256) , dtype=int)
> tt = im0.view()
> tt.shape = -1,3
> for r,g,b in tt:
> tab0[r,g,b] += 1
>
> Question:
>
> Is there a faster wa
On Tue, Dec 6, 2011 at 2:51 AM, Xavier Barthelemy wrote:
> ok let me be more precise
>
> I have an Z array which is the elevation
> from this I extract a discrete array of Zero Crossing, and another
> discrete array of Crests.
> len(crest) is different than len(Xzeros). I have a threshold method
On Wed, Nov 30, 2011 at 1:49 PM, Neal Becker wrote:
> My suggestion is: don't.
>
> It's easier to script runs if you read parameters from the command line.
> I recommend argparse.
>
>
I think setting parameters in a config file and setting them on the
command line both have their merits. I like
On Sun, Oct 16, 2011 at 12:49 PM, Pauli Virtanen wrote:
> (16.10.2011 18:39), Tony Yu wrote:
> > >>> import numpy as np
> > >>> a = np.arange(10)
> > >>> b = np.ones(10, dtype=np.uint8)
> >
> > # this runs without error
> >
On Sun, Oct 16, 2011 at 12:39 PM, Tony Yu wrote:
> Hi,
>
> I noticed a type-checking inconsistency between assignments using slicing
> and fancy-indexing. The first will happily cast on assignment (regardless of
> type), while the second will throw a type error if there's rea
Hi,
I noticed a type-checking inconsistency between assignments using slicing
and fancy-indexing. The first will happily cast on assignment (regardless of
type), while the second will throw a type error if there's reason to believe
the casting will be unsafe. I'm not sure which would be the "corre
On Thu, Sep 1, 2011 at 5:33 PM, Jonas Wallin wrote:
> Hello,
>
> I implemented the following line of code:
>
> Gami[~index0].shape > (100,)
> sigma.shape > (1,1)
> Gami[~index0] = Gam[~index0] - sigma**2
>
> I get the error message:
> *** ValueError: array is not broadcastable
On Sun, Jul 17, 2011 at 3:35 PM, Ralf Gommers
wrote:
>
> On Sun, Jul 17, 2011 at 7:15 PM, Tony Yu wrote:
>
>>
>> Am I doing something wrong here?
>>
>> You're not, it's a Sphinx bug that Pauli already has a fix for. See
> http://projects.scipy
I'm building documentation using Sphinx, and it seems that numpydoc is
raising
a lot of warnings. Specifically, the warnings look like "failed to import
", "toctree
references unknown document u''", "toctree contains reference
to nonexisting document ''---for each method defined. The
example below
Date: Fri, 17 Jul 2009 13:27:25 -0400
From: Ralf Gommers
Subject: Re: [Numpy-discussion] Using interpolate with zero-rank array
raises error
[snip]
If it works with scalars it should work with 0-D arrays I think. So
you
should probably open a ticket and attach your patch.
Thanks f
Date: Thu, 16 Jul 2009 23:37:58 -0400
From: Ralf Gommers
It seems to me that there are quite a few other functions that will
give
errors with 0-D arrays (apply_along/over_axis are two that come to
mind).
There is nothing to interpolate so I'm not surprised.
Hmm, I don't quite understand
Sorry, I don't know if its proper mailing-list-etiquette to bump my
own post...
Are there any comments on whether this interp error is expected
behavior?
Thanks,
-Tony
> Date: Mon, 13 Jul 2009 13:50:50 -0400
> From: Tony Yu
> Subject: [Numpy-discussion] Using interpolate
(Sorry if this is a duplicate; I think sent this from the wrong email
the first time)
When using interpolate with a zero-rank array, I get "ValueError:
object of too small depth for desired array". The following code
reproduces this issue
>>> import numpy as np
>>> x0 = np.array(0.1)
>>>
>
> Message: 8
> Date: Mon, 22 Sep 2008 19:28:50 -0400
> From: Pierre GM <[EMAIL PROTECTED]>
> Subject: Re: [Numpy-discussion] array with named columns (or record
> arrays with homogenous types)
> To: Discussion of Numerical Python
> Message-ID: <[EMAIL PROTECTED]>
> Content-Type: text/plai
Ok, so you guys shot down my last attempt at finding a bug :). Here's
another attempt.
array + masked_array
outputs a masked array
array += masked_array
outputs an array.
I'm actually not sure if this is a bug (works the same for both the
old and new masked arrays), but I thoug
f an array. Copying
seems inefficient.
-Tony
Matthieu
2008/5/31 Tony Yu <[EMAIL PROTECTED]>:
Great job getting numpy 1.1.0 out and thanks for including the old API
of masked arrays.
I've been playing around with some software using numpy 1.0.4 and took
a crack at upgrading it to n
?
Thanks in advance for your help.
-Tony Yu
Example:
In [1]: import numpy
In [2]: masked = numpy.ma.masked_array([[1, 2, 3, 4, 5]], mask=False)
In [3]: masked[:] = numpy.fliplr(masked.copy())
In [4]: print masked
[[5 4 3 2 1]]
In [5]: masked[:] = numpy.fliplr(masked)
In [6]: prin
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