Hi all,

I'm also experiencing this issue (212 subjects, 4mm voxels, HO 25% GM mask, group average parcellation).

It looks like the actual parcel data (in the .npy files) contains the right number of parcels. You can check this on your own results with the following python code:



This will return two arrays of equal length. The first array shows every unique value in the data, so if your k=100, it should have *around* 100 entries (as Cameron mentions in the paper, NCUT can sometimes produce clustering with empty clusters, so your actual k might end up somewhat smaller than your desired k). The second array is the number of voxels with each value at the same array index in the first array.

I think the issue is with the scripts that convert the NumPy parcellation data into a NIfTI volume. Working on a fix now, will report back if/when I'm successful.

Dan