[pymvpa] zscore clarification and question

[J.A. Etzel]

I want to make sure I understand how zscore works, so will describe what 
I think the behavior is, then add a question. Please correct any errors. 
:) I'm assuming in all cases that the mean and standard deviation are 
calculated by zscore, not passed.

I think zscore normalizes what I usually call column-wise: by default 
(perchunk=True and pervoxel=True) the voxel time course is normalized (a 
single voxel over the samples (volumes) in that chunk). So after 
normalization each voxel has a mean of zero and standard deviation of 
one within each chunk.

Setting perchunk=False and pervoxel=True normalizes the entire column: 
each voxel has a mean of zero and standard deviation of one over all 
volumes in the dataset.

Setting perchunk=False and pervoxel=False normalizes over all columns: 
all voxels together have a mean of zero and standard deviation of one 
over all volumes in the dataset.

Setting perchunk=True and pervoxel=False normalizes over all columns 
within each chunk: all voxels together have a mean of zero and standard 
deviation of one over all volumes in each chunk.

This gives various options for normalizing column-wise, but is it 
possible to normalize row-wise? In other words, normalize so that the 
voxels in each sample (volume) have a mean of zero and standard 
deviation one? Chunks are irrelevant for this case, since each sample is 
normalized separately. If this is already in pyMVPA, can you point me in 
the right direction?

thanks,
Jo