On 15/08/07, Glen W. Mabey <[EMAIL PROTECTED]> wrote:
> On Tue, Aug 14, 2007 at 12:23:26AM -0400, Anne Archibald wrote:
> > On 13/08/07, Glen W. Mabey <[EMAIL PROTECTED]> wrote:
> >
> > > As I have tried to think through what should be the appropriate
> > > behavior for the returned value of __geti
Hi,
Thanks for looking into this because we (neuroimaging.scipy.org) use
mmaps a lot. I am very away from my desk at the moment but please do
keep us all informed, and we'll try and pitch in if we can...
Matthew
On 8/15/07, Glen W. Mabey <[EMAIL PROTECTED]> wrote:
> On Tue, Aug 14, 2007 at 12:2
On Tue, Aug 14, 2007 at 12:23:26AM -0400, Anne Archibald wrote:
> On 13/08/07, Glen W. Mabey <[EMAIL PROTECTED]> wrote:
>
> > As I have tried to think through what should be the appropriate
> > behavior for the returned value of __getitem__, I have not been able to
> > see an appropriate solution
Hello,
I am hoping to release NumPy 1.0.3.1 and SciPy 0.5.2.1 this weekend.
These releases will work with each other and get rid of the annoying
deprecation warning about SciPyTest.
They are both basically ready to release. If you have some time,
please build and install the stable branches and
Maybe this is not the intended use of where, but it seems to work:
>>> from numpy import * # No complaining now
>>> a = arange(12)
>>> a.shape = (4,3)
>>> a
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
[ 9, 10, 11]])
>>> b = array([6,7,8])
>>> row = all( equal(a,b), 1 )
>>>
Hi list,
When I do large array manipulations, I get out-of-memory errors.
If the array size is 5000 by 6000, the following codes use nearly 1G.
Then my PC displays a Python error box. The try/except won't catch it
if the memory error happens in "astype" instead of "array1* array2"
try:
On Wed, Aug 15, 2007 at 03:11:59AM -0700, mark wrote:
> Yeah, I can see the copying is essential.
> I just think the syntax
> a = delete(a,1)
> confusing, as I would expect the deleted value back, rather than the
> updated array.
> As in the 'pop' function for lists.
> No 'pop' in numpy? (I presume
The where function ?
Matthieu
2007/8/15, mark <[EMAIL PROTECTED]>:
>
> Oops, 'find' is in pylab (matplotlib).
> I guess in numpy you have to use 'where', which does almost the same,
> but it returns a Tuple.
> Is there a function that is more like the find in matplotlib?
> Mark
>
>
> On Aug 15, 1
Oops, 'find' is in pylab (matplotlib).
I guess in numpy you have to use 'where', which does almost the same,
but it returns a Tuple.
Is there a function that is more like the find in matplotlib?
Mark
On Aug 15, 12:26 pm, Andy Cheesman <[EMAIL PROTECTED]>
wrote:
> Thanks for the speedy response bu
Thanks for the speedy response but where can I locate the find function
as it isn't in numpy.
Andy
mark wrote:
> I think you can create an array with a true value in the right spot as
> folows:
>
> row = all( equal(a,b), 1 )
>
> Then you can either find the row (but you already knew that one, a
Yeah, I can see the copying is essential.
I just think the syntax
a = delete(a,1)
confusing, as I would expect the deleted value back, rather than the
updated array.
As in the 'pop' function for lists.
No 'pop' in numpy? (I presume this may have been debated extensively
in the past).
I find the syn
I think you can create an array with a true value in the right spot as
folows:
row = all( equal(a,b), 1 )
Then you can either find the row (but you already knew that one, as it
is b)
a[row]
or the row index
find(row==True)
Mark
On Aug 15, 11:53 am, Andy Cheesman <[EMAIL PROTECTED]>
wrote:
>
Dear nice people
I'm trying to match a row (b) within a large numpy array (a). My most
successful attempt is below
hit = equal(b, a)
total_hits = add.reduce(hit, 1)
max_hit = argmax(total_hits, 0)
answer = a[max_hit]
where ...
a = array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
>
> I now get the feeling the delete command needs to copy the entire
> array with exception of the deleted item. I guess this is a hard thing
> to do efficiently?
>
Well, if you don't copy the array, the value will always remain present.
Matthieu
___
N
I am trying to delete a value from an array
This seems to work as follows
>>> a = array([1,2,3,4])
>>> a = delete( a, 1 )
>>> a
array([1, 3, 4])
But wouldn't it make more sense to have a function like
a.delete(1) ?
I now get the feeling the delete command needs to copy the entire
array with exc
15 matches
Mail list logo
