On 7/23/06, Eric Firing <[EMAIL PROTECTED]> wrote:
> Sebastian Haase wrote:
> > Hi,
> > I have a (medical) image file.
> > I wrote a nice interface based on memmap using numarray.
> > The class design I used was essentially to return a numarray array
> > object with a new "custom" attribute giving
Hi,
I have posted this mail from my google account a while ago, but
it obviously was blocked by sourceforge. What about that proposal of
moving numpy-discussion to scipy host?
Anyway, I have been recently working with arrays of objects and noticed
some problems. Here are the tickets:
Array impr
Hi,
I have been recently working with arrays of objects and noticed some
problems. Here are the tickets:
Array improperly created from numpy.poly1d object:
http://projects.scipy.org/scipy/numpy/ticket/185
Can't create matrix of dtype=object directly from list (problem of
ndarray.__new__):
http:/
Hi,
the way of accessing data with __array_interface__, as shown by Travis
in [1], also works nicely when used with builtin array.array (if someone
here is still using it;).
Time to convert array.array to ndarray is O(N) but can be made O(1) just
by simple subclassing.
[1] http://aspn.activestat
Hi Travis,
this is a great example of the __array_interface__ usage.
I have spotted some problems after patching the Image.py module and
trying to display an array created from Image in matplotlib.
First issue is a minor one. There is a difference in axis order between
ndarray and PIL:
def _co
Jens wrote:
> Dennis V. Perepelitsa wrote:
>>Hi, all.
>>
>>I've run some benchmarks comparing the performance of scipy, numpy,
>>Numeric and numarray vs. MATLAB. There's also the beginnings of a
>>benchmark framework included. The results are online at:
>>
>> http://web.mit.edu/jonas/www/be
Hi,
> I'm just starting with numpy (via scipy) and I'm wanting to perform
> adaptive thresholding
> (http://www.cee.hw.ac.uk/hipr/html/adpthrsh.html) on an image.
> Basically that means that I need to get a threshold for each pixel by
> examining the pixels around it. In numpy this translates to f
Hi,
It seems that in Numeric the matrixmultiply is alias for dot function,
which "uses the BLAS optimized routines where possible", as the help()
says.
In NumPy (0.9.6, not upgraded yet to 0.9.8), the matrixmultiply is a
function of numpy.core.multiarray, while dot refers to
numpy.core._dotblas.
