On Fri, Feb 27, 2009 at 19:06, Brian Gerke wrote:
>
> On Feb 27, 2009, at 4:30 PM, Robert Kern wrote:
>>>
>> r[where(r.field1 == 1.)] make a copy. There is no way for us to
>> construct a view onto the original memory for this circumstance given
>> numpy's memory model.
>
> Many thanks for the qui
On 27-Feb-09, at 3:35 PM, David Warde-Farley wrote:
>
> a[[2,3,6],:,:][:,:,[3,2]] should do what you want.
Slightly more elegantly (I always forget about this syntax):
a[[2,3,6], ...][..., [3,2]]
David
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On Feb 27, 2009, at 4:30 PM, Robert Kern wrote:
>>
> r[where(r.field1 == 1.)] make a copy. There is no way for us to
> construct a view onto the original memory for this circumstance given
> numpy's memory model.
Many thanks for the quick reply. I assume that this is true only for
record array
As a follow-up to Robert's answer:
>>> r[r.field1 == 1].field2 = 1
doesn't work, but
>>>r.field2[r.field1==1] = 1
does.
> So far, so good.
> Now I want to change the value of field2 for those same elements:
>
> In [128]: r[where(r.field1 == 1.)].field2 = 1
>
> Ok, so now the value
On Fri, Feb 27, 2009 at 18:26, Brian Gerke wrote:
>
> Hi-
>
> I'm quite new to numpy and to python in general, so I apologize if I'm
> missing something obvious, but I've come across some seemingly nasty
> behavior when trying to assign values to the fields of an indexed
> subarray of a numpy reco
Hi-
I'm quite new to numpy and to python in general, so I apologize if I'm
missing something obvious, but I've come across some seemingly nasty
behavior when trying to assign values to the fields of an indexed
subarray of a numpy record array. Perhaps an example would explain
it best.
Nathan Bell wrote:
> On Fri, Feb 27, 2009 at 2:33 PM, David Cournapeau wrote:
>
>> Great, thanks. Do you have VS installed ? Did you install python for
>> all users (I would guess so, but I am not yet clear on all the details
>> on that matter).
>>
>>
>
> I do not have VS installed. I jus
On Fri, Feb 27, 2009 at 4:08 PM, Nathan Bell wrote:
> On Fri, Feb 27, 2009 at 2:33 PM, David Cournapeau
> wrote:
> >
> > Great, thanks. Do you have VS installed ? Did you install python for
> > all users (I would guess so, but I am not yet clear on all the details
> > on that matter).
> >
>
> I
On Fri, Feb 27, 2009 at 2:33 PM, David Cournapeau wrote:
>
> Great, thanks. Do you have VS installed ? Did you install python for
> all users (I would guess so, but I am not yet clear on all the details
> on that matter).
>
I do not have VS installed. I just downloaded the official Python
2.6.1
> Message: 2
> Date: Thu, 26 Feb 2009 23:32:35 -0600
> From: Robert Kern
> Subject: Re: [Numpy-discussion] Speedup creation of a 3-color array
> from a 2-d color-index array a color lut
> To: Discussion of Numerical Python
> Message-ID:
> <3d375d730902262132k5a011d14t84317458f9b6c.
On Fri, Feb 27, 2009 at 14:41, Delbert Franz wrote:
>
>> Message: 2
>> Date: Thu, 26 Feb 2009 23:32:35 -0600
>> From: Robert Kern
>> Subject: Re: [Numpy-discussion] Speedup creation of a 3-color array
>> from a 2-d color-index array a color lut
>> To: Discussion of Numerical Python
>> Mes
On Thu, Feb 26, 2009 at 21:00, Jonathan Taylor
wrote:
> Am I right to assume that there is no way elegant way to interact with
> slices. i.e. Is there anyway to get
>
> a[ix_([2,3,6],:,[3,2])]
>
> to work? So that the dimension is completely specified? Or perhaps
> the only way to do this is vi
Hey Jon,
On 26-Feb-09, at 10:00 PM, Jonathan Taylor wrote:
> Am I right to assume that there is no way elegant way to interact with
> slices. i.e. Is there anyway to get
>
> a[ix_([2,3,6],:,[3,2])]
>
> to work? So that the dimension is completely specified? Or perhaps
> the only way to do thi
Hi all,
I just grabbed the latest bilateral filter from Stéfan's repository,
but I can't get it to work! I'm using a recent numpy SVN and the
latest release of cython...
In [10]: bl = bilateral.bilateral(image, 2, 150)
--
Well,
I came up with a slightly different approach.
Get the first row on the image.
It would be something like this:
[1,1,1,0,0,0,1,1,0,0,1]
1 = white, 0 = black.
Run the floodfill on [0],[6] and [10] pixel
if floodfill area is smaller then given area then paint that area black
if floodfill area
On Sat, Feb 28, 2009 at 4:15 AM, Nathan Bell wrote:
> On Fri, Feb 27, 2009 at 12:31 PM, David Cournapeau
> wrote:
>> Hi,
>>
>> That's a call for testing for 64 bits windows users out there:
>> please try the following binary with the test suite:
>>
>> http://www.ar.media.kyoto-u.ac.jp/members/
On Fri, Feb 27, 2009 at 12:31 PM, David Cournapeau
wrote:
> Hi,
>
> That's a call for testing for 64 bits windows users out there:
> please try the following binary with the test suite:
>
> http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy/numpy-1.3.0.dev6517.win-amd64-py2.6.exe
>
Hello,
>> This a little wiered problem. I am having a black and white image.
>> (black
>> background)
>> Entire image is filled with noisy white patterns of different size
>> and
>> shape. I need to fill the
>> white patches if there area is more then given one. Logically this
>> could
>> po
Hi,
That's a call for testing for 64 bits windows users out there:
please try the following binary with the test suite:
http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy/numpy-1.3.0.dev6517.win-amd64-py2.6.exe
python -c "import numpy; numpy.test()"
Report any crash. I am partic
Hi Prashant
2009/2/27 Prashant Saxena :
> This a little wiered problem. I am having a black and white image. (black
> background)
> Entire image is filled with noisy white patterns of different size and
> shape. I need to fill the
> white patches if there area is more then given one. Logically thi
Hi,
This a little wiered problem. I am having a black and white image. (black
background)
Entire image is filled with noisy white patterns of different size and shape. I
need to fill the
white patches if there area is more then given one. Logically this could
possible to use a quickfill algorit
On Fri, Feb 27, 2009 at 8:20 AM, Nils Wagner
wrote:
> Hi all,
>
> Is it possible to modify the behaviour of float wrt
> the following situation
>
>
> >>> permas_M[0,2]
> '1.569809265137D+01'
> >>> float(permas_M[0,2])
> Traceback (most recent call last):
> File "", line 1, in
> ValueError:
Hi all,
Is it possible to modify the behaviour of float wrt
the following situation
>>> permas_M[0,2]
'1.569809265137D+01'
>>> float(permas_M[0,2])
Traceback (most recent call last):
File "", line 1, in
ValueError: invalid literal for float():
1.569809265137D+01
The following wor
Zachary Pincus wrote:
> Hi,
>
>> intersect1d and setmember1d doesn't give expected results in case
>> there are duplicate values in either array becuase it works by
>> sorting data and substracting previous value. Is there an
>> alternative in numpy to get indices of intersected values.
>
> Fr
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