[pymvpa] z-score before or after removal of junk data

[mhampel at uni-osnabrueck.de]

Dear all,

I wondered if there is a good reason to keep not needed data for
z-scoring? In the searchlight and sensitivity measures examples the order
is like this:

1. zscore(dataset, dtype='float32', chunks_attr='chunks')
2. dataset = datatset[dataset.sa.targets != '0']

But if I reverse the order, my accuracy values are much higher (10-20%)
when classifying on whole brain. For searchlights the accuracies are also
higher. On a searchlight group level I therefore need a much higher
threshold for the p-values, with a higher threshold I get similar results.

Is it okay to do the z-score after removing the junk data?

Thanks for your help,
Matthias