FSaverage Source Space to Non-Uniform Single Subject Grid

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Fieldtrip has functionality to morph a volumetric source space from MNI to a single subject grid: Create MNI-aligned grids in individual head-space - FieldTrip toolbox

What is the best way to morph the FSaverage source grid to single subject space in MNE. The result would be that all single subject src data would have the same number of voxels, but the resulting voxels will have a non-uniform spacing in single subject space. The nice part being that all of the subjects will have a 1 to 1 voxel correspondance in atlas/subject space (so as an example voxel 1200 (?) is always in left primary visual cortex for all subjects).

I have done the following to get a morph from Ave to SingleSubject. The output gives the morph.vol_morph_mat, but I am not sure how to use the compressed sparse matrix to get the source locations in the single subject space. Its also possible that this is the wrong way to do it.

  morph = mne.compute_source_morph(
        src_ave, subject_from='fsaverage', 
        subject_to=subject, src_to=src, 
        subjects_dir=subjects_dir, spacing=None,   verbose=False,
        precompute=True)

Any insight is helpful. Thanks!

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as I understand it, what you’re asking simply isn’t possible in MNE-Python because we always use a regular grid, and interpolate to that (?), rather than preserving the number and sequence of voxels in subject_from

cc @britta-wstnr who explained it to me a couple weeks ago and can hopefully correct whatever my fuzzy memory got wrong.

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Yes, indeed. MNE-Python handles across-subjects source spaces differently from FieldTrip, and the possibility of warping an MNI grid to a single subject source space (as FieldTrip does) is not implemented.
In MNE, you would start with an individual source grid and morph this to fsaverage, as for example explained here (for volumetric grids):
https://mne.tools/stable/auto_examples/inverse/morph_volume_stc.html