maPCA in tedana does not currently z-score data before performing PCA

[eurunuela]

As discussed in tedana #636, the maPCA in tedana currently does not normalize data before performing PCA.

@tsalo already added the normalize option when he restructured the toolbox to be sklearn compatible. However, as I mentioned in the PR, I think we should add an if statement that checks the data is already z-scored and normalizes the data when it isn't. I'd remove the normalize option and do the normalization by default.

[tsalo]

Running z-scoring along the same axis twice shouldn't cause any problems, right? Can we just do it no matter what?

[eurunuela]

You're right, we could just do it anyway. In the end, it'd be (y - 0)/1 if the data was already z-scored.

[eurunuela]

This was closed by #636 in tedana