ndarray subclasses

[Almar Klein]

>
> On Thu, Sep 19, 2013 at 12:03 PM, Almar Klein <almar.klein at gmail.com>
> wrote:
> > I suppose that the most important bit is that functions that support
> > anisotropy should look whether a "sampling" attribute is present in the
> > given array.
>
> I don't think we currently have any of these, but for now we can
> probably include a `sampling` argument to functions that support it.
>

Mmm, you seem to be right, but you're *going* to :)  The new marching cubes
algorithm has a sampling argument, and I think Josh spoke about adding it
so some morphological operators. I hope to do a PR on the MCP algorithm
soon, which will add support for anisotropy as well.


 > I do not necessarily mean that a PointSet represents an image (although
> it
> > could), but more generally to for instance store the locations of
> detected
> > feature points.
>
> How do you think this would fit into the scope of image processing?
> (Asked out of curiosity, not at all to put the idea down.)
>

That's a good point. I think a PointSet class fits image processing because
many image processing algorithms either accept or produce some form of
locations or vectors. I would still call it "image processing" when you
process the resulting locations/vectors. However, such algorithms probably
fall out the scope of scikit-image.

So probably a better place for a PointSet class would be Scipy, but I have
a feeling they would not be interested in including it.


I am not related to the development of scikit-image but I guess its goal is
> to work on images in general and not get too specialised, for instance in
> Medical images.
>

I agree with that. I think that the only parameter of interest to scikit
image is the "sampling" to deal with anisotropic arrays. So in that sense,
it should be sufficient that sciki-image provides an Image class to which
arbitrary attributes can be attached. Functions in scikit-image can the
check if the array has a "sampling" attribute, and use it. If it returns an
array with the same shape, it would be nice to also set the sampling on
that.


May I ask: if you were to add sampling information and spatial coordinates,
> such as an origin for the top-left pixel, how would you input that
> information into scikit-image, could you read it directly from the input
> files or would you need some user input?
>

I am not sure I understand. In most cases the attributes are added to the
image (i.e. numpy array) when it is read.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-image/attachments/20130920/9493d192/attachment.html>