Or implement the other option. I kinda like that. Will help with the Travis
issue as well...


On Tue, Feb 18, 2014 at 12:54 PM, Demian Wassermann <
notifications@github.com> wrote:

> In dipy/reconst/shore.py:
>
> >
> > -        for n in range(int(self.radial_order / 2) + 1):
> > -            signal_0 += coef[n] * genlaguerre(n, 0.5)(0) * \
> > -                ((factorial(n)) / (2 * np.pi * (self.zeta ** 1.5) * gamma(n + 1.5))) ** 0.5
> > +            for n in range(int(self.radial_order / 2) + 1):
> > +                signal_0 += (
> > +                    coef[n] * (genlaguerre(n, 0.5)(0) * (
> > +                        (factorial(n)) / (2 * np.pi * (self.zeta ** 1.5) * gamma(n + 1.5))
> > +                    ) ** 0.5)
> > +                )
> > +
> > +            coef = coef / signal_0
> > +        else:
> > +            data = data / data[self.gtab.b0s_mask].mean()
> > +
> > +            if cvxopt is not None:  # If cvxopt is not available use scipy (~100 times slower)
>
> Ups, left forgotten from a previous approach. Should delete the comment.
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/nipy/dipy/pull/324/files#r9841202>
> .
>