Hello!

I am a graduate student who studies the ionosphere. This summer, I have been asked to develop a code base using python/scipy for ionospheric tomography. I have so far used the *radon* and *iradon* functions that are part of the scikit-image library.

I will soon finish my preliminary research/paper-reading/algorithm-testing phase, and am starting to plan the code phase. I wonder if the code I develop may be of value to the scikit-image library. For instance, I want/need to implement a more generalized Radon transform function that allows for specifying specific angle/offset pairs, and can work with sparse matrices. Also, perhaps a function for generating projection matrices. If it it may be of value, I would obviously want to design the code from the outset to conform to the scikit testing/style/code standards and best practices (this is probably a good idea regardless).

My sentiment is really similar to Emmanuelle Gouillart's: https://groups.google.com/forum/#!searchin/scikit-image/tomography/scikit-image/RrMX_mIE5_s/H_IcGh1vuF8J
Although, I am surely less experienced.

Here are four questions:

1) Is scikit-image the correct library for such functionality (like generalized Radon transform and projection matrix creation)?

2) Is there a reason (limitation) why the current radon/iradon functions are not more generalized?

3) If you think this functionality may be of use--any advice for development etc?

4) Where do you think the scikit-image project is in its lifecycle?

Thank you so much!

- Brian