Sparse Fascicle Model

This is a start on an implementation of the model we describe here: 

http://arxiv.org/abs/1411.0721

The main current issue with this is that this will have a local dependency on scikit-learn, because it uses ElasticNet for the fit. How do people feel about that? 
done

On Sat, Dec 13, 2014 at 12:57 PM, Eleftherios Garyfallidis <
notifications@github.com> wrote:
>
> In doc/examples/sfm_tracking.py
> <https://github.com/nipy/dipy/pull/460#discussion-diff-21791192>:
>
> > @@ -0,0 +1,193 @@
> > +"""
> > +==============================================================
> > +Deterministic Tracking with the Sparse Fascicle Model and EuDX
> > +==============================================================
> > +
> > +In this example, we will use the Sparse Fascicle Model [Rokem2014]_, together
> > +with the EuDX [Garyfallidis12]_ deterministic tracking algorithm.
> > +
> > +First, we import the modules we will use in this example:
> > +"""
> > +
> > +import numpy as np
>
> imported but unused
>
> —
> Reply to this email directly or view it on GitHub
> <https://github.com/nipy/dipy/pull/460/files#r21791192>.
>