Thanks Anthony and Paul!
OlyDLG
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You can use np.pad for this:
In [1]: import numpy as np
In [2]: x = np.ones((3, 3))
In [3]: np.pad(x, [(0, 0), (0, 1)], mode='constant')
Out[3]:
array([[ 1., 1., 1., 0.],
[ 1., 1., 1., 0.],
[ 1., 1., 1., 0.]])
Each item of the pad_width (second) argument is a tuple of bef
Hi all,
This should be an easy one but I can not come up with a good solution.
Given an ndarray with a shape of (..., X) I wish to zero-pad it to have
a shape of (..., X + K), presumably obtaining a new array in the process.
My best solution this far is to use
np.zeros(curr.shape[:-1] + (curr
Hi,
On Tue, Dec 31, 2013 at 1:29 PM, Julian Taylor
wrote:
>
> On 31.12.2013 14:13, Amira Chekir wrote:
> > Hello together,
> >
> > I try to load a (large) NIfTI file (DMRI from Human Connectome Project,
> > about 1 GB) with NiBabel.
> >
> > import nibabel as nib
> > img = nib.load("dmri.nii.gz")
