[Neuroimaging] Nibabel API change - always read as float

Ben Cipollini bcipolli at ucsd.edu
Mon Jul 6 18:56:35 CEST 2015

How about accepting a dtype parameter, with None meaning using the type
determined from load (i.e. current behavior)? This makes it easy to
document the 'arbitrary' behavior for the user (in explaining the
parameter), to convert to whatever datatype you want (if you know your data
or have particular needs like Alex). I also believe this is closer to a
numpy semantic, to_float is a new semantic (even if relatively simple).

As for what the default should be (None or float32 or float64)... I would
not touch that conversation quite yet :)

On Mon, Jul 6, 2015 at 9:37 AM, Matthew Brett <matthew.brett at gmail.com>

> On Mon, Jul 6, 2015 at 5:32 PM, Bertrand Thirion
> <bertrand.thirion at inria.fr> wrote:
> > +1 we (and more importantly, our students)  should rely as much as
> possible
> > on the standard behavior of numpy arrays and make adequate decisions,
> rather
> > than having to figure out the details of the API of neuroimaging
> libraries.
> > So the defaut should be unchanged.
> Your reasoning implies the opposite.   Numpy tries very hard not to
> return arrays of unknown or unpredictable data types, and that is the
> situation we have here.   The returned datatype from a nibabel image
> is essentially arbitrary, in that very few sources of nifti files
> place any weight on whether there are non-default scalefactors or not.
> At the moment, we do, depend on this, silently, and that is extremely
> confusing, and quite contrary to the standard numpy way,
> Cheers,
> Matthew
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