Not meaning that you should do it on your own, of course. I am happy to
help with this.


On Tue, Feb 18, 2014 at 12:55 PM, Ariel Rokem <arokem@gmail.com> wrote:

> 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>
>> .
>>
>
>