The people at STScI put me in touch with Peter Verveer, the author of
nd_image. Unfortunately Peter is currently unable to maintain the code
(either in numarray or scipy), but he did send me some comments on the
problem discussed in this thread. Here's what he said:
James.
-
Hi James,
Yes,
Example.
In [18]:a = array([1,2,3])
In [19]:a.flags
Out[19]:
C_CONTIGUOUS : True
F_CONTIGUOUS : True
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
In [20]:a.shape = (1,3)
In [21]:a.flags
Out[21]:
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE
Charles R Harris wrote:
All three shapes are both C_CONTIGUOUS and F_CONTIGUOUS. I think
ignoring all 1's in the shape would give the right results for
otherwise contiguous arrays because in those positions the index can
only take the value 0.
I've thought about this before too. But,
On Thu, Mar 22, 2007 at 02:41:52PM -0400, Anne Archibald wrote:
On 22/03/07, James Turner [EMAIL PROTECTED] wrote:
So, its not really a bug, its a undesired feature...
It is curable, though painful - you can pad the image out, given an
estimate of the size of the window. Yes, this sucks.
Stefan van der Walt wrote:
On Thu, Mar 22, 2007 at 02:41:52PM -0400, Anne Archibald wrote:
On 22/03/07, James Turner [EMAIL PROTECTED] wrote:
So, its not really a bug, its a undesired feature...
It is curable, though painful - you can pad the image out, given an
estimate of the
Hello,
I'd like to concatenate a couple of 1D arrays to make it a 2D array, with two
columns
(one for each of the original 1D arrays). I thought this would work:
In [47]:a=arange(0,10,1)
In [48]:a
Out[48]:array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
In [49]:b=arange(-10,0,1)
In [51]:b
On Thu, Mar 22, 2007 at 08:13:22PM -0400, Brian Blais wrote:
Hello,
I'd like to concatenate a couple of 1D arrays to make it a 2D array, with two
columns
(one for each of the original 1D arrays). I thought this would work:
In [47]:a=arange(0,10,1)
In [48]:a
Out[48]:array([0, 1, 2,
Hi Zachary,
OK - I sent Peter the URL for your post...
Cheers,
James.
___
Numpy-discussion mailing list
Numpy-discussion@scipy.org
http://projects.scipy.org/mailman/listinfo/numpy-discussion
On Thu, Mar 22, 2007 at 04:33:53PM -0700, Travis Oliphant wrote:
I would rather opt for changing the spline fitting algorithm than for
padding with zeros.
From what I understand, the splines used in ndimage have the implicit
mirror-symmetric boundary condition which also allows them to
By the way, ringing at sharp edges is an intrinsic feature of higher-
order spline interpolation, right? I believe this kind of interpolant
is really intended for smooth (band-limited) data. I'm not sure why
the pre-filtering makes a difference though; I don't yet understand
well enough what the
Hi,
Gnosis Utils (http://www.gnosis.cx/download/Gnosis_Utils.More/) contains
several modules for XML processing, one of which (xml.pickle) serializes
objects to and from XML and has an API compatible with Python's pickle
[http://freshmeat.net/projects/gnosisxml/].
The xml.pickle module needs
On 3/22/07, Stefan van der Walt [EMAIL PROTECTED] wrote:
On Thu, Mar 22, 2007 at 08:13:22PM -0400, Brian Blais wrote:
Hello,
I'd like to concatenate a couple of 1D arrays to make it a 2D array, with
two columns
(one for each of the original 1D arrays). I thought this would work:
Hello all,
By the way, ringing at sharp edges is an intrinsic feature of higher-
order spline interpolation, right? I believe this kind of interpolant
is really intended for smooth (band-limited) data. I'm not sure why
the pre-filtering makes a difference though; I don't yet understand
well
Hi list,
maybe this is a really stupid idea, and I don't want to advertise this, but
what actually happens when I reassign the dtype of an object?
Does it return the same as array.view?
say I have the following code
In [64]: b
Out[64]:
array([[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8],
Sebastian Haase wrote:
On 3/22/07, Stefan van der Walt [EMAIL PROTECTED] wrote:
On Thu, Mar 22, 2007 at 08:13:22PM -0400, Brian Blais wrote:
Hello,
I'd like to concatenate a couple of 1D arrays to make it a 2D array, with
two columns
(one for each of the original 1D arrays). I thought
15 matches
Mail list logo
