[FIX] Fixes handling of volumetric maps for null models #11
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Always use `nilearn.image.resample_to_img` and just use relevant atlas as reference image
First pass, very bad, super memory intensive
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[FIX] Fixes handling of volumetric maps for null models e356c91
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A first pass towards being able to generate null maps for volumetric images. The primary issue I'm running into here is that this is computationally...I don't wanna say impossible, but basically impossible. If you're working with 1mm isotropic data in MNI152, by default you've got upwards of 1.8 million voxels. The distance matrix ends up being many terabytes 😬
Will consider ways around this... Potentially thresholding the distance matrix based on a KNN regime, where users supply the desired K as a distance (i.e., "10mm")?