contributing C/Cython code to the scikit

[Stéfan van der Walt]

Hi Mael

On Tue, Sep 21, 2010 at 11:10 AM, mael <mael.primet at gmail.com> wrote:
> I will try to gradually improve my python code style, have you
> specifics you have seen in my code that were out of the way?

I think mostly spacing issues; but those are well described in the PEP.

> I removed opencv on my laptop because this wouldn't build (I'll try to
> figure out why)

No problem; just make sure that those changes don't get committed to your repo!

> for the data types, the discussion is very interesting,
> most of the algorithms could be adapted for different data-types by
> some preprocessor-like translation,
> however, this might create some problems (floating point comparison
> etc). Plus, our feeling with the previous
> library we were using (Megawave) was that it was better not to provide
> an algorithm for each and every possible datatype,
> as it forced the end-user to ponder whether the algorithm he was
> trying to use was suited to his case etc.
> But I concur that writing float (possibly float and doubles) and
> integer (int and unsigned char?) arrays should be
>  made as easy as possible.

Our thought was that two types may be manageable, but while we could
always generalise to support more types, it's very hard to go back --
so I'm happy that we're taking a conservative approach here.

> btw we're also interested in coding some powerful visualization
> function. I guess we'd rather not clutter the scikit with dependencies
> to pyQt or other libraries.
> How would you go about doing something like this? Use some library
> like chaco? Write from scratch a PyQt viewer?

You'll be glad to discover that we already have a Qt visualisation
plugin!  Different "imshow" implementations are available, depending
on what is available on your system.  Try this:

import scikits.image.io as sio
print sio.plugins()
sio.use_plugin('qt')
imshow(...)

It should pop up a qt viewer.  You may also do

imshow(..., fancy=True)

for a display with tuning widgets (only supported on Qt currently).

> I'm not really that good a coder, so I'd be happy to have you guys
> refactor some of my code and tell me the best way to go about it,
> particularly to avoid
> copying arrays over and over. We want to have simple contiguous arrays
> though, because we don't want to bother with complex array iteration
> in our C code.

You'll probably find that, especially for large images, it is often
quicker to do a single copy (to get contiguous data) and then perform
your operation.  Good coding comes with practise, and we're all still
learning, so you're in good company.

> Is the way I'm doing it (that was given to us by Emmanuelle) the
> proper way of getting our arrays as contiguous C arrays or are there
> some more efficient
> and/or  elegant way to do this?

The clearest way is probably `numpy.ascontiguousarray`.

Regards
Stéfan