I'll go for the second idea, since the data is jammed in a big zip file 
full of stuff.
Le 2014-03-12 18:21, Ariel Rokem a écrit :
>
> In dipy/denoise/tests/__init__.py:
>
> > @@ -0,0 +1,4 @@
> > +from os.path import join as pjoin, dirname
> > +import nibabel as nib
> > +
> > +test_piesno = nib.load(pjoin(dirname(__file__), 'test_piesno.nii.gz')).get_data()
> OK - one of two options, I think: either grab their data from their 
> website using a fetcher, or run their code on one of the data sets 
> that we already ship and benchmark to that. On Wed, Mar 12, 2014 at 
> 3:19 PM, Samuel St-Jean <notifications@github.com>wrote:
> … <#>
> In dipy/denoise/tests/__init__.py: > @@ -0,0 +1,4 @@ > +from os.path 
> import join as pjoin, dirname > +import nibabel as nib > + > 
> +test_piesno = nib.load(pjoin(dirname(__file__), 
> 'test_piesno.nii.gz')).get_data() This one is given by the authors and 
> they also give the value they get with their code, meaning we can 
> check if this implementation gives exactly the same result. I could 
> also run their version on any existing dataset, should both do the 
> same thing. — Reply to this email directly or view it on 
> GitHub<https://github.com/nipy/dipy/pull/337/files#r10544335> .
>
> —
> Reply to this email directly or view it on GitHub 
> <https://github.com/nipy/dipy/pull/337/files#r10544432>.
>