m-guggenmos / megmvpa Goto Github PK

Hello, thanks for making this code available! I'm working to replicate your distance notebook with some of our own data and in looking through the definition for the cross validated correlation I see that the denominator is sometimes the square root of covariances, which is not guaranteed to be positive (ie if train and test set have negative covariance, that calculation would fail). If regularize_var is set to true (which you have) this won't be an issue because of the max function, but I'm wondering if you have suggestions for the case when there is negative covariance between data splits? Thank you!