[Neuroimaging] Nibabel: Slowdown in traversing object using dataobj

[paul mccarthy]

Howdy,

If you need to stick with ``.nii.gz``, you could use my indexed_gzip
library:

https://github.com/pauldmccarthy/indexed_gzip

The first access will be slow, but subsequent accesses much faster.

Cheers,

Paul

On 30 November 2016 at 00:57, Matthew Brett <matthew.brett at gmail.com> wrote:

> Hi,
>
> On Tue, Nov 29, 2016 at 4:52 PM, Sam Zorowitz <szorowi1 at gmail.com> wrote:
> > Hi all,
> >
> > Hopefully a quick question: Assuming a 4d volume image, can someone
> explain
> > why it takes longer to load from memory the 100th acquisition the 1st
> > acquisition?
> >
> > For example, I have an image that is (110, 110, 63, 977). When I perform:
> >
> >>> %timeit obj.dataobj[..., 0]
> >
> > I get: 10 loops, best of 3: 37.8 ms per loop
> >
> >>> %timeit obj.dataobj[..., 100]
> >
> > I get: 1 loop, best of 3: 5.99 s per loop
> >
> > Why is this? Can someone recommend an alternative?
>
> I'm guessing this is a ``.nii.gz`` file?   If so, then the difference
> is just because nibabel has to gunzip 100 volumes worth of data in the
> latter case.
>
> If you can get away with an uncompressed file, my prediction is that
> you'll find the difference will go away.
>
> Cheers,
>
> Matthew
> _______________________________________________
> Neuroimaging mailing list
> Neuroimaging at python.org
> https://mail.python.org/mailman/listinfo/neuroimaging
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/neuroimaging/attachments/20161130/341e2445/attachment.html>