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Read and write neuroimaging file formats: NIfTI, GIFTI, CIFTI, MGH, Minc, Analyze, SPM. Core I/O for fMRI, diffusion MRI, structural MRI pipelines.
Passed 20 of 22 test cases with the skill, and 20 of 22 without it.
1 fixed19 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
A test case the skill fixed. Same model, same prompt, with and without the skill.
How do you install the standard Python library for NIfTI file I/O using the modern uv package manager?
| Checked | Without skill | With skill |
|---|---|---|
| Executes uv pip install nibabel | Missed | Passed |
The instructions your model reads when the skill loads.
NiBabel is the core Python library for neuroimaging file I/O. Use it to read and write NIfTI, GIFTI, CIFTI, MGH, MINC, and Analyze files, inspect affine metadata, and move data between imaging tools and NumPy.
uv pip install nibabel
import nibabel as nib
img = nib.load('brain_t1.nii.gz')
data = img.get_fdata()
affine = img.affine
header = img.header
print(data.shape)
print(header.get_zooms())
print(affine)
import numpy as np
masked = (data > data.mean()).astype(np.float32)
out = nib.Nifti1Image(masked, affine, header)
nib.save(out, 'brain_mask.nii.gz')
fmri = nib.load('rest_bold.nii.gz')
arr = fmri.get_fdata() # shape like (x, y, z, t)
test cases passed, vs 20 / 22 without
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