[Neuroimaging] Nibabel get_fdata()

[Matthew Brett]

Hi,
On Wed, Oct 17, 2018 at 1:20 PM serafim loukas <seralouk at hotmail.com> wrote:
>
> Hello,
>
>
> The images are on my local HD.
> The file is around 60GB.
>
> Here is my code to demonstrate this:
>
> import nibabel as nib
>
> data = nib.load('wBOLD.nii')
> slices_fast = data.get_data()[:,:,:,0]
> slices_slow = data.get_fdata()[:,:,:,0]
>
> And here you can find the file compressed: https://drive.google.com/open?id=1BkClOxytqUKtv5Zt7fMr2P-kvzJ5OKS0
>
>
> I was thinking to use get_data() instead of get_fdata() and then conduct some analysis.
> In this case, what is the difference between the 2 commands ?

I'm guessing from the above, that you're getting better performance
from `get_data`.  This is because, in your case, you have a 32-bit
float image, that doesn't have any scalefactors, so the optimized path
for you, is to use a memory mapped version of the array.  This is what
happens for `get_data`, but for various reasons, `get_fdata` always
returns 64-bit floats, so inflating memory, and making it impossible
to use memory mapping (because the image data type is not the same).

Cheers,

Matthew