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<p>Hello,</p>
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<p> Regarding the Boolean 'pca' option to tf_mixed_norm.py, I'm having trouble figuring what this is doing. In either the T or F case, I get a message saying "Not doing PCA for MEG", but then in the T case another message "Reducing data rank to X" is output,
and the number of sensors represented in the input evoked data is reduced to this number. Disregarding the first message, this option appears to control doing temporal PCA on the sensor data? This is very tempting since the sensors likely represent an oversampling
in space, but doesn't this require (temporal) stationarity of the data?</p>
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<p> Thanks again,</p>
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<p>Per Lysne, University of New Mexico</p>
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